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State governments' performance and effectiveness in reducing solid and hazardous waste under the Resource Conservation and Recovery Act (RCRA)

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State governments' performance and effectiveness in reducing solid and hazardous waste under the Resource Conservation and Recovery Act (RCRA) a study of the chemical industry
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Kuo, Chun-Mai Michael
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English
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xviii, 207 leaves : ; 28 cm

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Resource Conservation and Recovery Act of 1976 (United States) ( fast )
Refuse and refuse disposal -- States -- United States ( lcsh )
Hazardous wastes -- States -- United States ( lcsh )
Hazardous wastes -- U.S. states ( fast )
Refuse and refuse disposal -- U.S. states ( fast )
United States ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Bibliography:
Includes bibliographical references (leaves 189-207).
General Note:
School of Public Affairs
Statement of Responsibility:
by Chun-Mai Michael Kuo.

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|University of Colorado Denver
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Auraria Library
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All applicable rights reserved by the source institution and holding location.
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66899761 ( OCLC )
ocm66899761
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LD1193.P86 2005d K86 ( lcc )

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STATE GOVERNMENTS PERFORMANCE AND EFFECTIVENESS IN
REDUCING SOLID AND HAZARDOUS WASTE UNDER THE RESOURCE
CONSERVATION AND RECOVERY ACT (RCRA): A STUDY OF THE
CHEMICAL INDUSTRY
by
Chun-Mai Michael Kuo
B.A., Tunghai University, Taichung, Taiwan, R.O.C., 1987
M.A., Tunghai University, Taichung, Taiwan, R.O.C., 1990
M.P.A., Syracuse University, 1995
M.P.A. University of Southern California, 1998
A thesis submitted to the
University of Colorado at Denver and Health Sciences Center
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Public Affairs
2005


2005 by Chun-Mai Michael Kuo
All rights reserved.


This thesis for the Doctor of Philosophy
degree by
Chun-Mai Michael Kuo
has been approved
by
5yd Burton


Kuo, Chun-Mai Michael (Ph.D., Public Affairs)
State Governments Performance and Effectiveness in Reducing Solid and Hazardous
Waste under the Resource Conservation and Recovery Act (RCRA): A Study of the
Chemical Industry
Thesis directed by Professor Lloyd Burton
ABSTRACT
The main purpose of the study was to investigate the performance and
effectiveness of the regulatory tools adopted by the states in reducing solid and
hazardous waste. According to the Resource Conservation and Recovery Act
(RCRA), states are allowed to enact and enforce provisions that are more stringent
and/or broader in scope than the federally approved program. Based on this
regulatory background, two research questions were addressed: First, what state level
RCRA implementation strategies seem to be most closely associated with the greatest
reduction of solid and hazardous waste in the chemical industry? Second, what
contextual variables, in addition to the regulations, would affect the reduction of solid
and hazardous waste?
To answer these questions, longitudinal waste-related data (1988 to 2002), the
status of state chemical industry, and the survey results of states regulatory choices
were obtained from various sources. In this research, waste reduction was
operationalized as the rate of reduction to account for possible growth in the chemical
industry in a given state as a confounding variable. The research results suggested
IV


that: First, technology-based standards, waste fees, and permits may not be
considered as effective regulatory tools to reduce solid and hazardous waste.
However, compared to other contextual variables, they still had higher effects on
waste reduction. Second, the RCRA Supplemental Environmental Projects (SEPs)
were the only effective predictor among the variables towards waste reduction.
Suggestions were made according to these findings. First, governments need
to remain using technology-based standards as the foundation of the RCRA. Second,
states need to modify and revise their current fee and permit systems in order to help
reduce waste. Third, the importance of the SEPs needs to be recognized by the states
and be utilized as an effective regulatory tool to further reduce waste. Finally, states
need to adopt a contextual approach that flexibly tackles their certain waste issues.
Together, these suggestions may help address the concerns of public safety, peoples
right-to-know, and national security threat posed by the possibility of industrial
sabotage.
This abstract accurately represents the contest of the candidates thesis. I recommend
its publication.
v


ACKNOWLEDGEMENTS
I would like to offer my deepest appreciations to many people for helping me
and guiding me during the process of my dissertation writing. First of all, I would
like to thank my dissertation chair, Dr. Lloyd Burton, for his generous time, support,
and encouragement. I also want to thank him particularly for many thought
provoking comments relating to the regulatory background and policy applications.
Also, I am very thankful to have an outstanding dissertation committee. I
really appreciate Dr. George Busenberg, Dr. Bruce Kirschner, and Dr. Jae Moon for
their detailed comments and suggestions that stimulated me to enhance the level of
my analytical and research skills.
In addition, I wish to thank Ms. Kendra Morrison for helping me obtain the
research data. Without those detailed data and information, I would not be able to
conduct the analyses. My thanks also go to my cohorts Dr. Chul-yong Roh and Dr.
Seong-Gin Moon for their help and encouragement during the years of my study in
the doctoral program. Further, I would like to thank Dr. Andy Hong and Dr. Marcel
Pidoux for editing and revising my dissertation.
Four people deserve my special thanks: my parents-in-law Mr. Ta-Chung
Wang and Mrs. Chia-Li Wang and my close friends Dr. Rabi Wang and Mrs. Nina


Wang. They have been a great help to my family during the last stage of my
dissertation writing.
Finally, I am highly grateful for the love and assistance from my family
members. My parents Mr. Tung-Huan Kuo and Mrs. I-Chung Kuo have always
encouraged me to aim for the highest academic achievement. They have also
continually provided financial support to me and help me achieve the goals. I want to
thank my brother Dr. Chun-Fang Kuo and my sister Mrs. Hui-Chun Cheng for
guiding me to cope with tension and pressure based on their specialties. Additionally,
my earnest appreciation goes to my dearest wife Ai-Ling and my son Joshua.
Without their continued support, prayers, and sharing, this dissertation would not be
finished. In the end, I submit my highest praise to my Heavenly Father for all the
things and blessings He has given to me.


CONTENTS
Figures.............................................................. xiv
Tables................................................................. xv
Chapter
1. Introduction...................................................... 1
2. Literature Review................................................. 6
2.1 Technology-Based Standards: A Brief History...................... 6
2.1.1 Nineteenth and Early Twentieth Century......................... 6
2.1.2 Mid-Twentieth Century and Later................................ 9
2.2 The Rationale for Technology-Based Standards..................... 13
2.2.1 Maintenance of Fundamental Health Requirements................... 13
2.2.2 Consideration of Differences among Industries.................... 14
2.2.3 Impartiality..................................................... 14
2.2.4 Low Costs........................................................ 15
2.2.5 Technology Innovation............................................ 15
2.2.6 Public Involvement and Normative Considerations.................. 16
2.2.7 The Moral Imperative............................................. 17
2.3 Technology-Based Standards: The Foundation of RCRA................ 18
viii


2.3.1 Defining Technology-Based Standards............................ 18
2.3.2 Types of Technology-Based Standards............................ 20
2.4 State Authorization............................................... 22
2.4.1 States with Different Programs................................. 22
2.4.2 RCRA Supplemental Environmental Projects (SEPs)................ 27
2.5 Alternative Regulatory Tools...................................... 30
2.5.1 Hazardous Waste Fees............................................. 30
2.5.2 Penalties........................................................ 31
2.5.3 Permits.......................................................... 32
2.5.4 Subsidies........................................................ 34
2.5.5 Voluntary and Partnership Programs............................... 34
2.6 Conflicting Research Findings..................................... 35
2.6.1 Pro-Technology/Command and Control Approaches.................... 36
2.6.1.1 Theoretical Arguments.......................................... 36
2.6.1.2 Empirical and Case Studies..................................... 39
2.6.2 Pro-Economic Approaches........................................ 43
2.6.2.1 Theoretical Arguments.......................................... 43
2.6.2.2 Empirical and Case Studies................................... 52
2.6.3 RCRA Related Policy Studies...................................... 55
3. Research Design..................................................... 58
ix


3.1 Hypotheses
58
3.1.1 Technology-Based Standards....................................... 58
3.1.2 Hazardous Waste Fees............................................. 60
3.1.3 Permits.......................................................... 61
3.1.4 Other Contextual Variables....................................... 62
3.2 Research Data...................................................... 63
3.2.1 Industry Selection............................................... 63
3.2.2 Data and Sources................................................. 63
3.2.2.1 Solid and Hazardous Waste...................................... 63
3.2.2.2 Regulatory Tools............................................... 65
3.2.2.3 Contextual Variables........................................... 66
3.2.3 Data Measurements.............................................. 68
3.3 Statistical Analysis............................................. 71
4. Results and Findings................................................ 73
4.1 General Trends and State Solid and Hazardous Waste Status........ 73
4.1.1 General Trends................................................... 74
4.1.1.1 BRS Waste Volumes and Number of Facility from 1989 to 1999 .... 74
4.1.1.2 R&D Funds from 1989 to 2001 ................................... 75
4.1.1.3 Technical Assistance and Third Party Treatment Facilities.... 75
4.1.2 State Solid and Hazardous Waste Capacity and Status............ 76
x


4.2 Hypothesis Testing................................................. 77
4.2.1 Descriptive Statistics and Assumption Tests.................... 77
4.2.1.1 Descriptive Statistics......................................... 77
4.2.1.2 Assumption Tests............................................... 79
4.2.2 Hypothesis 1 .................................................. 82
4.2.3 Hypothesis 2..................................................... 84
4.2.4 Hypothesis 3..................................................... 85
4.2.5 Hypotheses 4 to 6................................................ 86
4.2.6 Summary of Hypothesis Testing Results.......................... 89
4.3 Additional Analysis................................................ 90
4.3.1 State Chemical Industry Capacity and Performance............... 90
4.3.1.1 Correlations between Variables................................. 90
4.3.2 Trends Data...................................................... 92
4.3.2.1 Correlations between Variables................................. 93
4.3.2.2 Regression Analysis............................................ 94
4.3.3 Other Additional Statistical Analyses and Summary.............. 96
5. Discussion, Conclusions and Policy Recommendations.................. 97
5.1 Discussion......................................................... 97
5.1.1 Hypothesis 1: Technology-Based Standards......................... 97
5.1.2 Hypothesis 2: Solid and Hazardous Waste Fees..................... 98
xi


5.1.2.1 Reasons for the Failure to Confirm the Hypothesis
99
5.1.3 Hypothesis 3: Generator and Transporter Permits................ 101
5.1.3.1 Reasons for the Failure to Confirm the Hypothesis............ 102
5.1.4 Hypotheses 4 to 6: Regulatory Tools and Contextual Variables... 103
5.1.4.1 The Relative Magnitude and Direction of the Regulatory Tools. 104
5.1.4.2 The Importance of the RCRA SEPs.............................. 105
5.1.5 National Trends, State Status, and Additional Analysis......... 106
5.2 Conclusions and Recommendations.............................. 108
5.2.1 Recognize the Policy Context................................... 109
5.2.2 Strengthen Technology-Based Standards.......................... 110
5.2.3 Modify and Improve the Solid and Hazardous Waste Fee Systems... Ill
5.2.4 Modify and Improve the Permit Systems.......................... 113
5.2.5 Recognize the Importance of the SEPs and Other Factors......... 114
5.2.6 Towards a Contextual Approach for Solid and Hazardous Waste
Reduction...................................................... 115
5.3 Contributions.................................................... 119
5.3.1 To Academia.................................................... 119
5.3.2 To State Implementing Agencies and the EPA..................... 120
5.3.3 To the National Security....................................... 120
5.4 Limitations and Future Studies................................... 122
xii


Appendix
A. RCRA Definitions.................................................. 123
A. 1 Solid Waste..................................................... 123
A. 2 Hazardous Waste................................................. 124
B. Case Studies of Hazardous Waste Reduction....................... 126
C. Market-Based Environmental Policies............................... 135
D. SIC and NAICS Correspondence Tables............................. 144
E. State Hazardous Waste Fee / Tax Systems......................... 155
F. Variables Description and Data Conversion....................... 174
F.l Data Conversion Procedures........................................ 175
F. 1.1 Data Collection and Data Type................................ 175
F. 1.2 Data Conversion............................................... 175
G. General Trends and State Status................................... 177
References............................................................ 189
xiii


FIGURES
Figure
5.1 The Interactions among Major Groups of Solid and Hazardous Waste.... 110
G.l BRS Waste Volumes (tons) by Year.................................... 177
G.2 BRS Number of Facility by Year...................................... 178
G.3 Federal R&D Funds in Millions of Dollars............................ 178
G.4 Company R&D Funds in Millions of Dollars............................ 179
G.5 Federal and Company R&D Funds Comparison............................ 179
G.6 Federal Pollution Reduction Funds in Millions of Dollars............ 180
G.7 Company Pollution Reduction Funds in Millions of Dollars............ 180
G.8 Federal and Company Pollution Reduction Funds Comparison............ 181
G.9 R&D Performing Company R&D Funds in Millions of Dollars............. 181
G. 10 R&D Contract Out Funds in Millions of Dollars..................... 182
G. 11 Number of R&D Company in Chemical Industry........................ 182
G. 12 Number of Technical Assistance from the EPA....................... 183
G. 13 Number of Third Party Treatment Facilities........................ 183
xiv


TABLES
Table
2.1 Summary of State Hazardous Waste Management Programs............. 23
2.2 State Hazardous Waste Fee and Tax Systems....................... 27
2.3 Procedure, Guidance, or Rules for SEPs.......................... 28
2.4 SEPs are a Higher Priority than Other Pollution Prevention/Waste
Minimization Projects.............................................. 29
2.5 Incentives for Innovation under Various Pollution Control
Arrangements....................................................... 44
2.6 Emissions Levels under Various Pollution Control Arrangements... 45
2.7 Summary of Relative Rankings of the Incentives to Promote
Technological Change in Pollution Control and the Attitude Towards
Optimal Agency Response....................................... 46
3.1 Research Data and Sources........................................... 67
3.2 Variable Type and Description...................................... 70
4.1 Directions of the General Trends.................................... 76
4.2 BRS Raw Data Summary............................................... 78
4.3 Descriptive Statistics for Nominal Variables....................... 78
4.4 Descriptive Statistics for Interval Variables...................... 79
4.5 Heteroscedasticity-Consistent Regression Results, Wagners Fee
System............................................................. 81
4.6 Heteroscedasticity-Consistent Regression Results, HTRWCEs Fee
System............................................................. 81
xv


4.7 Multicollinearity Test Results, Wagners Fee System................ 82
4.8 Multicollinearity Test Results, HTRWCEs Fee System................ 82
4.9 Hypothesis 1 Paired Samples T-Test Results, State Reduction Rate
Differences........................................................ 83
4.10.1 Hypothesis 1 Independent-Samples T-Test Results, Additional
Hazardous Waste Standards......................................... g^
4.10.2 Hypothesis 1 Independent-Samples T-Test Results, Additional
Hazardous Waste Standards......................................... QA
4.11.1 Hypothesis 2 One-Way ANOVA Results, Average Reduction Rates
of States with Different Hazardous Waste Fees, Wagners Fee System g^
4.11.2 Hypothesis 2 One-Way ANOVA Results, Average Reduction Rates
of States with Different Hazardous Waste Fees, HTRWCEs Fee
System......................................................... 85
4.12 Hypothesis 3 One-Way ANOVA Results, Average Reduction Rates of
States with Different Permit Systems............................. g^
4.13.1 Hypothesis 4 to 6 Multiple Regression Results, ANOVA (b), Based
on BRS Data and Wagners Fee System............................ gg
4.13.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a),
Based on BRS Data and Wagners Fee System...................... gg
4.14.1 Hypothesis 4 to 6 Multiple Regression Results, ANOVA (b), Based
on BRS Data and HTRWCEs Fee System............................ gg
4.14.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a),
Based on BRS Data and HTRWCEs Fee System....................... g^
4.15 Summary of Hypothesis Testing Results............................ 89
4.16 Pearson Correlations, BRS Data and State Data.................... 91
4.17 Pearson Correlations, BRS Data and National Data................. 93
4.18 Regression Results, Coefficients (a), BRS Waste Reduction Rate... 95
xvi


4.19 Regression Results, Coefficients (a), BRS Waste Volume......... 95
5.1 State Hazardous Waste Fee Systems Comparison.................... 100
5.2 Standardized and Unstandardized Coefficients from Table 4.13 and 4.14 105
5.3.1 Rankings of Solid and Hazardous Waste Reduction Performance,
Wagners Fee System............................................. 117
5.3.2 Rankings of Solid and Hazardous Waste Reduction Performance,
Wagners Fee System, Recoded.................................. I ^
5.4.1 Rankings of Solid and Hazardous Waste Reduction Performance,
HTRWCEs Fee System............................................... ^
5.4.2 Rankings of Solid and Hazardous Waste Reduction Performance,
HTRWCEs Fee System, Recoded.................................. j jg
5.5.1 Rankings of Solid and Hazardous Waste Reduction Performance,
Permits......................................................... 118
5.5.2 Rankings of Solid and Hazardous Waste Reduction Performance,
Permits, Recoded.................................................. g
5.6 Rankings of Solid and Hazardous Waste Reduction Performance, SEPs
Importance....................................................... 119
B. l Hazardous Waste Reduction Cases................................. 126
C. l Major Federal Tradable Permit Systems........................... 135
C.2 Deposit-Refund Systems............................................ 136
C.3 Federal User Charges.............................................. 138
C.4 Federal Insurance Premium Taxes................................... 139
C.5 Federal Sales Taxes............................................... 140
C.6 Administrative Charges............................................ 140
C.l Federal Tax Differentiation....................................... 141
xvii


C. 8 Federal Information Programs................................... 142
D. l 1987 SIC and 1997 NAICS Correspondence Table.................... 144
D. 2 1987 SIC and 2002 NAICS Correspondence Table.................... 149
E. l State Hazardous Waste Fee / Tax Systems....................... 155
F. l Trends Data..................................................... 174
G. 1 Rankings of State Capacity and Status, BRS Data from 1989 to 1999 ... 184
G.2 Rankings of R&D Funds by State, from 1989 to 2001 .............. 186
G.3 Rankings of the Average Number of the Third Party Treatment
Facilities by State.............................................. 188
xviii


1. Introduction
At the outset of the modem environmental movement in the 1970s, the United
States launched a series of regulatory reforms on environmental laws and regulations.
One of the new regulatory regimes was the Resource Conservation and Recovery Act
(RCRA, 42 U.S.C. §6901-6992(k), 1976). RCRA empowered the Environmental
Protection Agency (EPA) to regulate the disposal of solid and hazardous waste in the
United States. Its purpose was to promote the protection of health and the
environment, and to conserve valuable materials and resources. By taking the same
regulatory approach as the Clean Air Act Amendments (CAA, 42 U.S.C. §7521 et
seq., 1970) and the Clean Water Act (CWA, 33 U.S.C. §1251 et seq., 1972), RCRA
established technology-based standards for the accumulation, transportation, storage,
treatment, and disposal of solid and hazardous waste.
Technology-based standards are one of the primary regulatory tools to control
pollution entering surface waters, the atmosphere, public drinking water supplies,
workplaces, and the land. Their purpose is to regulate the pollution control
technology employed by major emitters of the regulated pollutants (for detailed
definition, please refer to section 2.3.1). Scholars argue that technology-based
standards are an effective regulatory tool to maintain the fundamental health
requirements. The technology-based standards have the advantage of being impartial,
1


less expensive, taking into account the differences among industries, promoting
technology innovation, encouraging public involvement, and allowing for strong
normative and moral considerations (Andrews, 1994; Caimcross, 1992; Davies and
Mazurek, 1996; Heaton and Banks, 1998; Marcus and Weber, 1989; Mitnick, 1981;
Meyer, 1982; Norberg-Bohm, 1999; Shapiro and McGarity, 1991; Shrivastava, 1995;
and Wagner, 2000).
While the rationale for technology-based standards is appreciated by some
scholars, other voices are equally sound, which mainly come from the economic
approach of policy making. The latter argues that technology-based standards are
actually labor- and information-intensive for regulators. The standards setting
procedure not only is costly and time-consuming, the technologies chosen are often
not the most proper ones to address the pollution issues. Moreover, the sizable
compliance costs would hamper a companys R&D efforts. Instead, economic
approaches such as pollution fees, taxes, tradable permits, and subsides can resolve
pollution problems in a less expensive and more effective manner (Allenby, 2000;
Caves, 1982; Eggers, Villani, and Andrews, 2000; Downing and White, 1986;
Guttmann, Sierck, and Friedland, 1992; John and Mlay 1999; Kemp, 1997; Magat,
1978; Milliman and Prince, 1989; Rabe, 1986; Scherer and Ross, 1990; and Wender,
1975).
Fortunately, RCRA seems to take a flexible stance that allows states to design
different programs to meet their needs. In other words, a state with authorization may
2


have a program that is more stringent and/or broader in scope than the federal
program. States therefore have certain discretion in choosing different regulatory
tools such as economic approaches to address their own solid and hazardous waste
issues. More explicitly, in addition to technology-based standards established by the
EPA, states may adopt more stringent standards, regulate additional wastes as RCRA
wastes, utilize regulatory tools such as hazardous waste fees and generator or
transporter permits (40 CFR 271.l(i)); RCRA §3008(a)(2); Wagner, 1999).
Unfortunately, most studies tackling the relationship between regulatory tools
and pollution reduction were done in air and water pollution fields. Not much
research has been done in the field of solid and hazardous waste control. Moreover,
most of those studies were conducted at the firm level. Related research at the state
level is fairly scant. With the unique and flexible regulatory background and the
controversy in terms of the relative capabilities between command-and-control
regulations (technology-based standards) and economic approaches in reducing
pollution, it would be interesting to answer the following questions:
First, what state level RCRA implementation strategies seem to be most
closely associated with the greatest reduction of solid and hazardous waste in the
industry studied? Second, what contextual variables, in addition to the regulations,
would affect the reduction of solid and hazardous waste?
3


Following the first question, three hypotheses are proposed:
1. The governments stringent technology-based standards will promote the
reduction of solid and hazardous waste.
2. There will be significant differences in the performance of solid and
hazardous waste reduction among the states that utilize different
hazardous waste fee systems.
3. There will be significant differences in the performance of solid and
hazardous waste reduction among the states that issue, partially issue, and
no issue permits to generators and transporters.
Also, based on the second question, it is further hypothesized that:
4. Technology-based standards are more likely to have stronger effects on the
reduction of solid and hazardous waste than other contextual variables.
5. Hazardous waste fees are more likely to have higher stronger on the
reduction of solid and hazardous waste than other contextual variables.
6. Permits are more likely to have stronger effects on the reduction of solid
and hazardous waste than other contextual variables.
In this research, I focused on the chemical industry. From a toxic and
hazardous emissions point of view, the chemical industry was regarded as the most
critical industry because it accounted for almost half of the total emissions for all
industries in this country (Dooley and Fryxell, 1999). By testing the stated
hypotheses, this research aimed to obtain a better understanding of the relative
performance of regulatory tools in reducing solid and hazardous waste in the
chemical industry; to identify important contextual variables relating to solid and
hazardous waste reduction; to enrich the research field in solid and hazardous waste
control; to provide constructive suggestions and recommendations for the state
governments to design the programs that best meet their needs in reducing solid and
hazardous waste; and to help address the concerns of public safety, peoples right-to-
4


know, and national security threats posed by the possibility of industrial sabotage.
5


2. Literature Review
Technology-based standards are a unique approach to control environmental
pollution. They aim to provide incentives for polluters to create and invent
innovative technologies and to reduce pollution. In the past three decades,
technology-based standards have been mainly used in the field of water and air
pollution control. However, in more recent years, technology-based standards have
been adopted in the area of solid and hazardous waste control. In the following
sections, I discuss the regulatory background and the rationale and definition of
technology-based standards. I also discuss the major regulatory alternatives adopted
by some of the state governments. As for the theoretical and empirical findings, most
of the findings are borrowed from the fields of air and water pollution control, this is
due to limited research done in the field of solid and hazardous waste,
2.1 Technology-Based Standards: A Brief History
2.1.1 Nineteenth and Early Twentieth Century
Environmental pollution is an age-old problem. When the brilliant
Frenchman, de Tocqueville, traveled to America in the 1830s, he described what he
saw with surprise:
6


The American people see themselves marching through
wildernesses, drying up marshes, diverting rivers, peopling the
wilds, and subduing nature (de Tocqueville, 1988 [1835], p.485).
Ever since, dominant American value and ethic towards the environment,
namely utilitarianism, did not seem to have changed from the era of industrial
revolution in the mid and late 19th century to the period between the two world wars.
Western exploration and industrial development seemed to be the major social and
economic activities of this country. Nevertheless, pollution had become a concern in
this country since the 1840s and 1850s.
Initially, pollution control came about through the courts in the form of
nuisance law. People in states then being industrialized such as New Jersey, New
York, and Pennsylvania had sensed the problems of air pollution such as the smoke
and acrid fumes emitted from neighboring brick factories (Campbell v. Seaman, 63
N.Y. 568, 20 Am. Rep. 567 (1876)).
Moreover, the importance of technology to control pollution had begun to be
noticed by the judges of these states. For example, in New York and New Jersey,
judges ordered the fat-boiling industry to reduce their stench nuisances (Westheimer
v. Schultz, 33 How. Prac. 11 (1866)); a cheese business to stop dumping wastes from
their hog pen, slaughterhouse, and cheese factory into a stream (Davis v. Lambertson,
56 Barb. 480 (1868)); an electric power company to stop overloading a power plant
so as to reduce noise and vibration (Braender v. Harlem Lighting Co., 2 N.Y. Supp.
245 (1888)); and a printing and bookbinding company to move its steam boiler and
7


printing presses to another location in order to stop the noise and vibration that were
disturbing a harness manufacturer next to it (Demarest v. Hardham, 34 N.J.Eq. (7
Stew.) 469 (1881)). In those cases, judges argued that it was well within the power
and financial capability of the defendants to install (new) technology to control
pollution without shutting down their factories (Rosen, 1998).
Technology seemed to be playing an increasingly important role in pollution
control by the beginning of the twentieth century. In Georgia v. Tennessee Copper
Co. (206 US 230 (1907)), at issue was the sulphurous acid gas emitted from the
smelters in Tennessee that drifted into Georgia and caused damage. To resolve this
case, Justice Oliver Wendell Holmes adopted a mixture of an air quality-based
approach and a technology-forcing approach to give the defendants a reasonable
amount of time to install treatment facilities. However, the situation was not being
remedied and the case was again brought to the Supreme Court. In their ruling, the
Court admitted that they set out specific emission limits without regard to the
technological feasibility of said limits (Georgia v. Tennessee Copper Co. (237 US
678 (1915)).
In New York v. New Jersey (256 US 296 (1921)), New York filed suit against
New Jersey and the Passaic Valley Sewerage Commissioners to enjoin the execution
of a project to convey the sewage of the Passaic Valley through a sewer system, and
to discharge it into a part of New York Harbor. The Supreme Court declined to
enjoin New Jersey. However, the Court ordered New Jersey to make more efforts
8


than New York in terms of pollution control. During that time, New York was
planning to use a certain water pollution control technology. The Court adopted a
technological feasibility approach that asked New Jersey not only to base its sewage
treatment obligations on New Yorks technology, but utilize other certain
technologies required by the federal government to minimize the pollutants.
2.1.2 Mid-Twentieth Century and Later
The mid-twentieth century was a turning point for environmental protection.
Beginning in the 1950s, issues such as the loss of wilderness, the nuclear arms race
and the related wastes, and a variety of air and water pollution problems forced
Americans to reconsider the importance of environmental protection (Meine, 1995).
The concerns for environmental quality surfaced dramatically in 1962 when Rachel
Carson published Silent Spring, which gave rise to the modem environmental
movement. During this new wave of environmental protection, again, the importance
of technology on pollution control was apparent.
In Oregon, the owner of an aluminum plant was sued by several neighboring
orchard owners who claimed that their crops had been damaged by fluorine emissions
(Renken v. Harvey Aluminum, (Inc.) (226 F. Supp. 169 (1963)). Finding pollution to
be a continuing trespass and a nuisance, the district court awarded the orchard owners
approximately ten thousand dollars each in damages. Moreover, the court decided on
a technology-based approach to control the source of pollution. Namely, it looked at
9


what technology was available and ordered the plant to install state-of-the-art
emission control equipment.
Boomer v. Atlantic Cement Co. (26 N.Y.2d 219 (1970)) was another nuisance
legal case pertaining to dirt, smoke, and vibration pollution caused by a cement plant.
As opposed to the previous case, the court refused to order the use of specific control
technologies because of economic considerations. The New York Court of Appeals
decided that a technology-based cost-benefit analysis was appropriate and sufficient
to determine what amount of pollution control should be implemented. Meanwhile,
the court ordered the plant to compensate the land owners for the damages caused. In
this case, Judge Jasen agreed with the majority that a reversal was required.
However, he took a technology-forcing approach in his dissent and argued that
pollution must be reduced to a certain level within a certain period of time (18 months
in this case) regardless of the current technological feasibility and costs. In doing so,
it could force the development of technology to resolve the problem.
While common law provides the foundation of modem environmental law and
continues to be an influential and significant part of environmental practice, the
federal and state courts in general are reluctant to delve deeply into the field of
pollution control through judicial decree. They seem to believe that the scientific
complexity of many cases could be better handled by the administrative agency with
expertise in certain areas (Meiners and Yandle, 1998; Percival and Alevizatos, 2000;
Plater, Abrams, and Goldfarb, 1998; The Wildlaw, 2005).
10


However, pollution control legislation seemed to be taking a course of slow
evolution and had little impact on environmental degradation until the modem
scheme was enacted. The first law applicable to water pollution was the Refuse Act
(33 U.S.C.A. §40ff (1899)). Nonetheless, its major concern was with navigation. If
pollution did not interfere with navigation, it was not addressed. Also, this law did
not contain any water quality standards, permit frameworks, or any clear distinctions
between federal and state responsibilities. Actually, this law was not applied to
pollution control until the 1960s. In 1948, the Federal Water Pollution Control Act
(33 U.S.C. §1251-1376) was passed. It granted the federal government authority to
do research and investigate water pollution issues. However, again, it did not address
any means to set and enforce pollution standards. Nevertheless, this law was
amended in 1956, and allowed for states to set pollution standards. By taking a more
stringent stance, the Water Quality Act of 1965 required states to set and enforce
quality standards.
In air pollution control, the 1955 Air Pollution Act was the first federal
legislation that attempted to control air pollution at its source. However, it did very
little to prevent air pollution, but simply provided research and technical assistance to
address the issues at the national level. Taking a step ahead, the Clean Air Act of
1963 started to set up air quality criteria. Yet, it focused only on interstate pollutions.
The legislative effort to set out modem scheme of air quality control was the 1967 Air
Quality Standards Act. Nevertheless, its air quality criteria only adopted some
11


technology-based considerations and did not concern with technological feasibility.
Moreover, its implementation plans were set up by states, and the states could
determine whether the recommended technology was necessary to meet the standards.
Fortunately, the regulatory philosophy started to change in the 1970s. In
1972, the Water Pollution Control Act was amended again and became the foundation
of the Clean Water Act (CWA, 33 U.S.C. §1251 et seq., 1972). It required the federal
government to set technology-based effluent standards along with federal
enforcement provisions. Those standards were set as best practicable control
technology currently available (BPT) initially, and later enforced as best available
technology economically achievable (BAT) (Harrington and Krupnick, 1981; Olson,
2005). More specifically, BPT is the average of the best existing treatment
performance, which considers the total cost of application of technology in relation
to the effluent reduction benefits to be achieved from such application. BAT, on the
other hand, is defined as the best existing technology performance in an industry
category, taking into account the... cost of achieving said performance (CWA, 33
U.S.C. §1311(b), 1989).
A similar approach was adopted in the field of air pollution control. When
Congress enacted the Clean Air Act Amendments (CAA, 42 U.S.C. §7521 et seq.,
1970), it opted for an environmental quality approach and called for the EPA to set air
quality standards for the pollutants. The law required the industries to limit their
discharges to meet the standards regardless of what level of technology was needed.
12


However, in view of the success of the Clean Water Act, Congress substantially
amended the Clean Air Act in 1990 and changed it to a more technology-based
legislation. With the early success of controlling air and water pollution by these two
acts, a series of technology-related regulatory reforms was triggered to further protect
the environment. Two of them were the focus of this research, namely, the Resource
Conservation and Recovery Act (RCRA, 42 U.S.C. §6901-6992(k), 1976) and the
Hazardous and Solid Waste Amendments (HSWA, 1984).
2.2 The Rationale for Technology-Based Standards
While the main tools of policy making in many fields are economic
instruments, scholars have argued that these instruments cannot capture the essence of
environmental pollution problems and should be considered as a secondary approach
of pollution control. On the contrary, technology-based standards offer a better
environmental control mechanism and should serve as the foundation of
environmental regulation (Andrews, 1994; Davies and Mazurek, 1996; Heaton and
Banks, 1998; Shapiro and McGarity 1991; Wagner, 2000). The rationale of this
approach is as follows.
2.2.1 Maintenance of Fundamental Health Requirements
Technology-based standards establish fundamental requirements that guarantee
the basic health of the general public. By setting up specific environmental standards,
polluters are forced to reduce their pollution volumes. In turn, the quality of the
13


environment can be controlled and the risk and harm toward human health can be
reduced to an acceptable level.
2.2.2 Consideration of Differences among Industries
Previous technology-based approaches were severely criticized as wildly
inefficient, because they ignored the enormous difference among facilities and
industries by setting up unified standards (Sunstein, 1991). However, studies indicate
that technology-based systems do not operate in a blind manner. Agencies do not
ignore the types of geographical and intra-industry differences. Rather, they utilize
newly developed mechanisms to account for the industrial and geographical
differences. For example, the EPA constantly checks whether the factors relating to a
waste stream are fundamentally different from the factors originally considered by the
agency when setting the standards. If the variances are recognized, the different
factors are required to be included in the setting of the new standards. Also, many
industries are allowed to choose certain control technologies to meet their needs
(Shapiro and McGarity, 1991). These new tools have obtained major improvements
in regulating the pollutants and controlling pollution.
2.2.3 Impartiality
Closely related to the above, impartiality is also an important virtue of
technology-based standards. Regulatory interventions that alter companies
behaviors may have the potential to cause inequities such as competitiveness or
14


barriers to entry. However, if implemented properly, technology-based standards are
highly impartial in how they affect industry. In general, all members of the same
class of an industry are treated in the same way. Further, distinctions can be built into
the selection of technology-based standards to ensure that smaller businesses are not
put at a competitive disadvantage. For instance, one chemical plant is not required to
purchase substantially more expensive pollution abatement equipment than a
competitor in another state. This situation can also be applied to new entrants of an
industry (Wagner, 2000).
2.2.4 Low Costs
Technology-based standards are less expensive to enforce. Based on the
standards, environmental inspectors are only required to determine whether a firm has
installed and properly operated the required technology. On the contrary, economic
instruments such as emissions trading and pollution taxes require inspectors to
monitor constantly the amount of pollution that a plant emits. As a consequence,
monitoring all of the possible discharge points will be far more expensive and
difficult than simply identifying whether a firm is using a required technology
(Shapiro and McGarity, 1991; Wagner, 2000).
2.2.5 Technology Innovation
Being required to reduce the emissions and meet the specific standards,
industries will be forced to seek out new ways to reduce pollution in the most
15


efficient and effective manner. The most common response from the industries is to
innovate around the existing technologies and/or create brand new technologies and
entirely change the manufacturing process. This rationale not only can be applied to
the existing firms and industries, but also to the new plants and industries. As the
new companies and/or new industries are thinking of entering the market, they have
to devise and design newer technologies and mechanisms in advance to enhance their
competitiveness (Andrews, 1994; Davies and Mazurek, 1996; Heaton and Banks,
1998). In comparison, economic instruments, such as subsidies or taxation, do not
necessarily encourage environmental improvement and may even result in fewer
emission-reducing innovations than command and control mechanisms. Economic
subsidies actions that provide commodities, capital, or services at below market cost
- are especially unlikely to stimulate technological advancement (Zellmer, 2000).
Counter arguments against this rationale can be found in the section of pro-economic
approach below.
2.2.6 Public Involvement and Normative Considerations
Technology-based systems are more effective and enforceable because they
offer opportunities for public involvement. On the contrary, economic initiatives
generally lack this feature. Take the CWA permit program as an example. Before a
permit may be issued, the EPA must allow public comments and determine whether
the discharge will comply with the applicable requirements. Input obtained during
16


the public comment period is included as part of the official record. At the end of the
comment period, the Regional Administrator decides whether to issue or deny the
permit. Also, any interested individual may request a formal hearing within thirty
days of the decision. These involvements during the decision making process allow
the EPA to reach a well-informed and enforceable decision. In contrast, economic
instruments such as subsidies or taxation generally inhibit citizen involvement
(Zellmer, 2000).
Moreover, many social factors such as emotions, feelings, and attitudes are
unlikely to be measured. Despite this difficulty, or improbability, some economists
still try to convert everything, including normative concepts, to the simple metric of
economic efficiency in monetary terms. Consequently, these calculations may be
biased based on the analysts self-interest and the interests of their clients such as
environmental groups and industries. In turn, the final choices of environmental
control often become political decisions according to the political powers of the
groups. The scientific facts of pollution are often neglected (Campbell, 1996;
Grossman and Krueger, 1995; Jacobs, 1991).
2.2.7 The Moral Imperative
From a moral and normative stance, technology-based standards send out a
message that the regulated entities must do their best, or nearly their best, to fulfill
their responsibility of guaranteeing the public health and environmental quality.
17


These standards assume that there is pollution, that it is undesirable, and that a strong
effort to reduce the pollution is needed. These standards can also be designed to
place the burden on the polluters and demonstrate that the pollution control
technology they selected is inappropriate. Oftentimes, these standards are criticized
as cost-blind and will cause damages to the industries (Sunstein, 1991). However,
from the consideration of human health and environmental quality, technology-based
standards should still represent a fundamental regulatory principle (Wagner, 2000).
Critiques on the above rationales are discussed in the section of pro-economic
approaches.
2.3 Technology-Based Standards: The Foundation of
RCRA
The above rationale seems to have a profound impact on the Congressional
enactment of RCRA. In this act, specific and detailed technology-based standards are
utilized to regulate different types of solid and hazardous waste management.
However, Congress also leaves tremendous discretion to the states to administer this
act in a highly flexible manner.
2.3.1 Defining Technology-Based Standards
Technology-based standards are one of the primary regulatory tools to control
pollution entering surface waters, the atmosphere, public drinking water supplies,
workplaces, and the land. Their purpose is to regulate the pollution control
18


technology employed by major emitters of the regulated pollutants. They first
appeared in the Section 111 of the Clean Air Act (42 U.S.C. §7411, §7412(b), 1970)
that required the EPA to set technology-based emission limitations for new major
sources of air pollution. Subsequently, they were adopted in the control of point
source discharges of organic pollutants and toxics in the Clean Water Act (33 U.S.C.
§1251-1385, 1974) and in setting drinking water standards under the Safe Drink
Water Act (SDWA, 33 U.S.C. §3OOg- 1(b)(4), 1974). They were also used to regulate
toxic health risks in the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA,
7 U.S.C. §136 et seq., 1972) and the Toxic Substances Control Act (TSCA, 15 U.S.C.
§2601 et seq., 1976), and to set land-disposal standards under RCRA (42 U.S.C.
§6901-6992(k), 1976).
In these acts, Congress requires the EPA to review currently available or
soon-to-be-available pollution control technologies for the industries to adopt. In
most instances, the EPA uses a three-step strategy in setting the standards. First, the
EPA divides the industries into different categories, which is the SIC code system
mentioned above. Next, the EPA surveys the available technologies in each industrial
category and chooses the technology that best fits congressional goals. Third, the
EPA transfers the pollution reduction capabilities of the chosen technology to
numerical effluent or emission limits for each pollutant (Gaines, 1977; La Pierre,
1977). To do so, the EPA must become familiar with the performance of the selected
technology in reducing pollution and the average volume of pollution for each and
19


every industrial category. Otherwise, it would become controversial if the standards
are set simply according to assumptions.
2.3.2 Types of Technology-Based Standards
The types of technology-based standards are diverse. They can broadly be
divided into two types design standards and performance standards. Design
standards are more onerous. They specify how a certain plant, piece of machinery, or
pollution control apparatus should be designed. The well known examples of this
type are the previously mentioned BAT and BPT, and the best conventional pollutant
control technology (BCT). BCT is required for conventional pollutants, such as total
suspended solids and oil and grease (33 U.S.C. §1311(b)(2)(E)). Performance
standards, on the other hand, allow facilities more flexibility to determine how they
will control their emissions. In other words, these standards set a performance level
for the facilities and allow them to determine how they will achieve it. Owing to this
greater flexibility, performance standards are now more widely used among agencies
than design standards (Gartenstein-Ross, 2003; Percival and Alevizators, 2000).
A typical example of performance standards is the best demonstrated available
technology (BDAT). BDAT refers to the most effective commercially available
means of treating specific types of hazardous waste. The BDAT may change with
advances in treatment technologies. BDAT is the basis for the new source
performance standards (NSPS) in the Clean Air Act, (NSPS 42 U.S.C. §7401-
20


7671(q)) and the Clean Water Act (33 U.S.C. §1316). The NSPS are applied to all
new stationary sources that the EPA determines to cause significant pollution and
endanger public health or welfare. After the EPA designates such sources, it
promulgates regulations to establish performance standards for them. The standards
are set according to the different categories of industrial activity (Gartenstein-Ross,
2003).
In RCRA, standards are also established based on the BDAT pursuant to the
legislative principles of the 1984 RCRA amendments (Plater, Abrams, and Goldfarb,
1998; Wagner, 1999; Hazardous Waste Treatment Council v. EPA, 886 F.2d 355 (D.
C. Cir. 1989)). RCRA regulates twelve hazardous waste activities and units: (1)
container storage units, (2) tank systems, (3) surface impoundments, (4) waste piles,
(5) land treatment areas, (6) landfills, (7) incinerators, (8) thermal treatment units, (9)
chemical, physical, and biological treatment units, (10) miscellaneous units, (11)
containment buildings, (12) underground injection wells. Each of them is assigned
specific technical standards for management.
Take landfills (40 CFR 268) for example, solid and hazardous wastes are
required to be treated in a specified manner or treated to meet specific constituent
levels before land disposal. The treatment standards of the wastes therefore include:
(1) constituent concentrations in milligrams per kilogram (mg/kg) of waste, which
must be met before land disposal, (2) constituent concentrations in an extract of the
waste in milligrams per liter (mg/1), which must be met before land disposal, and (3)
21


treatment standards expressed as specified technologies and represented by a five-
letter code contained in 40 CFR 268.42. These standards are established based on
BDAT as mentioned above.
2.4 State Authorization
2.4.1 States with Different Programs
While the federal government sets the foundation for hazardous waste
management, states play a crucial role in its implementation. RCRA explicitly
intends (§3006) to have the Nations hazardous waste management program
administered by qualified states with only minimal oversight from the federal
government. Any state that seeks authorization for its hazardous waste program must
submit to the EPA an application containing a request letter from the states governor,
all applicable state statutes and regulations, a description of the program, a statement
by the states attorney general, and a memorandum of agreement (40 CFR 271.5).
The EPA has 90 days after receiving the application to make a decision (40 CFR
217.4). Moreover, after approving the states application, the EPA holds the authority
to revise and/or reverse the state program thereafter (40 CFR 271.21).
A state with authorization may have a program that is more stringent or
broader in scope than the federal program (§3008). Being more stringent indicates
that a state can enact stricter regulations than its federal equivalent. For example, a
state may require annual reporting by a generator instead of the biennial reporting
22


required by the federal RCRA program. Being broader in scope means that a state
may increase the size or scope of the regulated community. For instance, a state may
regulate a nonhazardous waste as a RCRA hazardous waste.
The distinction between more stringent and broader in scope is significant: the
EPA may enforce a more stringent state requirement, but not state requirements that
are broader in scope. For example, the EPA may enforce any provision of an
authorized states approved program. However, if the state provisions are broader in
scope and not part of the federal approved RCRA program, the EPA cannot enforce
them (40 CFR 271.1(i). Accordingly, and most importantly, a state may adopt
additional regulatory tools to meet the programs needs. Table 2.1 and Table 2.2 list
the key differences between each states programs (Wagner, 1999; HTRWCE, 2002).
Table 2.1 Summary of State Hazardous Waste Management Programs
State Hazardous Waste Fees Generator or Transporter Permits Additional Hazardous Wastes
Alabama Landfills Transporters No
Alaska No No No
Arizona No Yes No
Arkansas Yes Yes PCBs
California Yes Transporters No
Colorado Yes No No
Connecticut Yes Transporters No
23


Table 2.1 (Cont.)
State Hazardous Waste Fees Generator or Transporter Permits Additional Hazardous Wastes
Delaware No No No
DC No No No
Florida No No Mercury containing lamps
Georgia Yes No Mercury containing lamps
Hawaii No No Oil, gas, and geothermal exploration, development, and production wastes
Idaho Only for disposal No No
Illinois Yes Transporters There are designate special wastes. Fluorescent lamps, if they exhibit a characteristic
Indiana Yes No Mercury containing lamps
Iowa No No No
Kansas Yes No No
Kentucky Yes No Nerve and blistering agents
Louisiana Yes No No
Maine Yes Yes PCBs < 50 ppm
Maryland No TSDFs and transporters PCBs
Massachusetts Yes Transporters Waste oil, PCBs, pain-related wastes
Michigan Yes Transporters No
Minnesota Yes No PCBs
Mississippi Yes No No
24


Table 2.1 (Cont.)
State Hazardous Waste Fees Generator or Transporter Permits Additional Hazardous Wastes
Missouri Yes Transporters PCBs and used oil, not recycled
Montana Yes No No
Nebraska TSDFs No No
Nevada TSDFs No No
New Hampshire Generators and TSDFs No Used oil, strontium sulfide, solid corrosives
New Jersey Generators, TSDFs, and transporters Transporters need a DEP license No
New Mexico Yes No Mercury containing lamps that exhibit a hazardous characteristic
New York Yes No PCBs
North Carolina Yes No No
North Dakota No Transporters No
Ohio Transporters TSDFs No
Oklahoma Yes Transporters Drum cleaning waste
Oregon Yes No Pesticide residues, nerve agents
Pennsylvania Yes Transporters No exclusion for residues from empty containers
Rhode Island Transporters and TSDFs Transporters Solid corrosives, ignitable waste with flash point <200F, PCBs, used oil
South Carolina TSDFs Transporters No
South Dakota No No No
25


Table 2.1 (Cont.)
State Hazardous Waste Fees Generator or Transporter Permits Additional Hazardous Wastes
Tennessee Yes Transporters No
Texas Yes Transporters Some used oil
Utah Commercial TSDFs No No
Vermont No Transporters PCBs, petroleum distillates, pesticides, infections waste, paint- related waste, waste ethylene-glycol- based coolants, metal grinding wastes
Virginia No Transporters Fluorescent lamps that exhibit a characteristic
Washington Yes No No
West Virginia Yes No No
Wisconsin Yes Transporters F500 wastes containing halogenated compounds
Wyoming TSDFs No No
Source: Wagner (1999).
Explanation of Codes
Yes = The state has adopted the federal provision as written.
Hazardous Waste Management Fee = This refers to fees charged by the state for
generators, transporters, or waste management facilities.
Generator or Transporter Permits = This refers to the requirement for generators or
transporters to obtain a permit or license. All hazardous waste management
facilities must have a permit.
Additional Hazardous Wastes = This refers to the classification, identification, or
regulation, of any hazardous waste beyond the federal program.
26


Table 2.2 State Hazardous Waste Fee and Tax Systems
Fee / Tax Systems State Number of States
Hazardous waste management fees and direct treatment disposal fees Arizona, Arkansas, California, Colorado, Delaware, Illinois, Kansas, Kentucky, Maine, Nevada, North Carolina, Ohio, Oklahoma, Oregon, South Dakota, Washington, Wisconsin 17
Hazardous waste management fees but no direct treatment or disposal fees Florida, Indiana, Louisiana, Maryland, Massachusetts, Mississippi, Montana, New Mexico, Rhode Island, Tennessee, Virginia, Wyoming 12
Direct treatment or disposal fees Alabama, Georgia, Idaho, Iowa, Michigan, Minnesota, Missouri, Nebraska, Pennsylvania, South Carolina, Utah, Vermont, West Virginia 13
Direct treatment or disposal fees that also specifically target out-of-state waste Connecticut, New Hampshire, New Jersey, New York, Texas 5
No taxes or fees imposed Alaska, District of Columbia, Hawaii, North Dakota 4
Total 51
Source: HTRWCE (2002)
2.4.2 RCRA Supplemental Environmental Projects
(SEPs)
State RCRA SEPs are projects that incorporate pollution prevention and/or
waste minimization principles into their final enforcement orders. Those projects can
also be used as a settlement tool under RCRA (EPA, 2005). A survey done by the
RCRA Enforcement Task Force of the Association of State and Territorial Solid
Waste Management Officials (ASTSWMO, 1997) showed that among the 34 sates
(out of 56 states/territories) that responded to the survey, 25 states had SEPs and 9
states did not have SEPs. ASTSWMO indicated that although some states did not
have written procedures, the remainder of the survey showed that they still had
some forms of SEPs.
27


The survey also showed that states utilized different programs in their
pollution prevention/waste minimization SEPs. A significant number of states
included training (81%), educational outreach (81%), environmental audits (72%),
household hazardous waste collection/disposal (69%), grants (56%), stream/stream
sediment cleanups (50%), and other specified projects (41%) into their SEPs.
Moreover, when being asked whether the SEPs are a high priority, 16 states reported
yes and 8 states responded no (NC no response). In other words, about 67% of
the respondents alleged that pollution prevention and waste minimization projects
were considered a higher priority in their states. The summary of the survey is listed
in Table 2.3 and Table 2.4.
Table 2.3 Procedure, Guidance, or Rules for SEPs
State Yes No State Yes No State Yes No
AL ME X PA
AK X MD RI X
AZ X* MA SC X
AR X MI SD
CA X MN X TN
CO MS TX X
CT X MO X* UT X
DE X* MT X VT
DC X* NE X VA
FL X NY WA
GA NH X* WV X
HI X NJ X WI X*
ID X NM X WY X
IL X NY X VI
IN X NC X AS
IA X ND X* GU
28


Table 2.3 (Cont.)
State Yes No State Yes No State Yes No
KS OH X PR
KY OK
LA X OR X
Source: ASTSWMO (1997)
X*: Checked no originally, but later counted as yes by ASTSWMO. According to
ASTSWMO, the remainder of the survey indicated that SEPs are utilized in the State.
The question may have been interpreted by the respondent to mean written
procedures, policies, guidance or rules when it was intended just to determine if SEPs
are allowed in settlement negotiations.
Table 2.4 SEPs are a Higher Priority than Other Pollution Prevention/Waste
Minimization Projects
State Yes No State Yes No State Yes No
AL ME X PA
AK X MD RI X
AZ X** MA SC X
AR X MI SD
CA X MN X TN
CO MS TX X
CT X MO X* UT X
DE X* MT X VT
DC X* NE x++ VA
FL X NV WA
GA NH X** WV X
HI X NJ X WI X*
ID X NM X WY X
IL X NY X VI
IN X NC AS
IA ND X* GU
KS OH X PR
KY OK
LA X OR X
Source: ASTSWMO (1997)
NC: No Response.
LA: No Response, but commented: Yes, if we did them.
X*: Checked no in Table 2.3, but responded to the question as no in Table 2.4.
X**: Checked no in Table 2.3, but checked yes in Table 2.4.
29


2.5 Alternative Regulatory Tools
2.5.1 Hazardous Waste Fees
As showed in Table 2.1 and Table 2.2, hazardous waste fees are the major
alternative some states utilize to control hazardous wastes. Hazardous waste fees or
any type of pollution fees apply the principle of market economics. They require
regulated facilities to internalize the costs of the damages they impose on society by
making them pay fixed dollar amount for each unit of pollution they generate
(OLeary, Durant, Fiorino, and Weiland, 1999; Opschoor and Vos, 1989). Different
from the technology-based approach that makes polluters control to the same level of
stringency regardless of the costs, hazardous waste fees recognize that some polluters
can control emissions at lower costs than others can. Polluters with low costs stay
within the pollution limits and pay less in fees. On the other hand, polluters with high
control costs will fall short of the standards but pay high fees. The result should be
the same or less pollution. However, the total cost to society will be less (OLeary,
Durant, Fiorino, and Weiland, 1999; Repetto, 1997).
Scholars also argue that fees provide a constant financial incentive and
demand for innovation and pollution reduction. A fee system depends less than
technology-based standards on the availability of pollution control technology.
Therefore, it can be introduced more quickly at lower costs by reducing demands on
regulatory process to decide complex, detailed engineering and economic questions.
30


Moreover, to further reduce the costs, polluters are forced not only to focus on the
end-of-pipe pollution reduction technologies that have been overwhelmingly applied
in the past, but also innovative ways to integrate the whole manufacturing process
(Stewart, 1981).
2.5.2 Penalties
In addition to the fee systems, RCRA violators are subject to civil and
criminal liability. Nowadays, many courts adopt Superfunds strict liability, joint and
several liability, and retroactive liability standards to RCRA (Stem, 1992).
Intentional violations such as falsification of documents, dumping hazardous waste in
unapproved sites, or any illegal disposure of hazardous wastes may be subject to
criminal liability (42 U.S.C. §6928). Moreover, based on the offense, violators may
be subject to fines from $5,000 per day for failing to follow monitoring and reporting
requirements (42 U.S.C. §6927, §6934) to $25,000 per day for violating a compliance
order (42 U.S.C. §6928, §6929). The exact fines are decided by weighing the
severity of the offence. In extremely grave violations, violators permits may be
suspended or revoked, in addition to civil penalties (42 U.S.C. §6928).
Citizens can also bring suit against any violators or any individual who is
contributing or has contributed to any situation that poses an imminent and substantial
endangerment to health or the environment. However, citizen suits can be barred if
government has initiated a suit against the violators (42 U.S.C. §6972). Also, citizens
31


can bring suit challenging state agencies that breach their duty of enforcing RCRA
provisions (42 U.S.C. §6901-6992k).
2.5.3 Permits
Permitting is the key element in the implementation of hazardous waste
programs under Subtitle C. A RCRA permit establishes the authorized waste
management activities a facility may engage in and under what conditions the
activities must be conducted. It also regulates the administrative requirements such
as record keeping, reporting, waste analyses for the facilities. Its general purpose is
to ensure that hazardous wastes are directed to and maintained by a suitable facility
(Wagner, 1999).
Operators or owners of hazardous waste facilities have to obtain a RCRA
permit to start or to continue the operation, unless they are specifically excluded (40
C.F.R. 270.1 (c)(1)). The RCRA permit application procedure consists of two parts:
Part A and Part B. Part A comprises EPA Form 8700-23, along with maps, drawings,
and photographs of the site. Part B contains no specific form, but need to submit
detailed, site-specific information. For new facilities, operators or owners need to
submit both parts simultaneously. For existing facilities, since the application is time-
consuming, Congress established an interim authorization and allowed certain
facilities to operate legally after submitting Part A. After the facilities submit Part B,
they may obtain a full permit.
32


There is only one type of permit for regular operations, namely, the RCRA or
hazardous waste management permit. However, it is important to note the distinction
between facility and unit. A facility may have one or more units, and a permit is
issued for individual units such as tank, incinerator, or surface impoundment, not for
an entire facility. Therefore, to cover different phases of operations, the permits can
be referred as active permit, final permit, post-closure permit, etc. Although all
hazardous waste management facilities must have a permit, each state may still have
leeway to design its own permit systems for generators or transporters. As showed in
Table 2.1, the decision to issue, not to issue, or issue only to generators or
transporters is made by each state.
In addition to the permits for regular operations, the EPA also issue some
limited special permits like the emergency permits and the research, demonstration,
and development (RD&D) permits. If there is an imminent and substantial
endangerment to human health or the environment, the EPA may issue a temporary
emergency permit (40 C.F.R. 270.61). This permit may require a non-permitted unit
to treat, store, or dispose hazardous wastes, or a permitted unit to treat, store, or
dispose wastes that are not covered by an effective permit. RD&D permits are for
innovative and experimental treatment technologies or processes that have not been
established under 40 C.F.R. 264. The EPA may establish permit terms, conditions,
and technical standards for each RD&D activity to protect human health and the
environment (Wagner, 1999).
33


Again, citizens can challenge the EPAs decisions to issue, deny, modify, or
revoke any permit for the facilities. Citizens can also bring suits challenging state
permit decisions if the state fails to comply with applicable state law, or if state
requirements are less stringent than federal standards (42 U.S.C. §6929, §6976(b)).
2.5.4 Subsidies
This is an additional regulatory tool of RCRA that offers financial assistance
to state, local, and private agencies for their efforts to research, promote, or
demonstrate the reduction of solid waste and unsalvageable waste materials (42
U.S.C. §6981(a)(5)). Due to the financial situation of the RCRA authorities, this
program is currently underfunded and underutilized. Compared to the R&D
investments of the chemical industry, the governments subsidies and funding for
hazardous waste reduction are considerably low (Aboody and Lev, 2001; Zare, 2000;
IRDIS, 1998, 2005).
2.5.5 Voluntary and Partnership Programs
Voluntary and partnership programs are the most recent environmental control
efforts by the governments. They include the EPAs 33/50 programs, the EPAs
Common Sense Initiative, Occupational Safety and Health Administrations (OSHA)
Voluntary Protection Programs, and the EPAs Energy Star Program and Project XL,
and the SEPs mentioned above (Bergeson, 2000; EPA, 1995; EPA, 2005; Franz,
2002; Hogue, 2003). Those regulatory innovations encourage the industries to submit
34


innovative and creative pollution reduction proposals. EPA in turn offers operational
flexibility to allow the industries to put the proposals to test. Voluntary programs are
a moral commitment of the companies. With a set of principles and guidance from
the environmental agencies, pollution problems are addressed through a more
collaborative and less directive manner (Johnson, 1999; Rose, 1991). In recent years,
the number of the facilities that participate in those programs has increased rapidly
(Fiorino and Friedman, 2002). Nevertheless, while a huge number of firms have
signed and joined the programs, the issues of commitment to innovate and honesty to
carry out the programs are still under debate (Berry and Rondinelli, 1998; Kirschner,
1995; Service and Avasthi, 2005).
2.6 Conflicting Research Findings
Based on the above, it seems that in principle, all of the regulatory tools are
effective. However, according to the studies in the field of air and water pollution,
the relative capabilities between command-and-control regulations (technology-based
standards) and economic approaches in reducing pollution are still controversial. In
other words, scholars and analysts differ in their judgment as to which approach
performs better in pollution reduction. In this section, research findings are divided
into pro-technology/command and control approaches and pro-economic approaches.
35


2.6.1 Pro-Technology/Command and Control
Approaches
2.6.1.1 Theoretical Arguments
McHuge (1985) examined the implications of technological indivisibilities, or
lumpiness, for the dynamic efficiency of tax based, economic instruments. In this
study, pollution control and reduction technologies are discrete and identified with
particular control efficiency. McHuge argued that there are two types of innovations
in pollution abatement technology: technology stretching innovation and
inffamarginal cost-reducing innovations. The former innovations are those that lead
to a higher proportion of potential emissions controlled at an acceptable cost. The
later innovations are those which control a lower proportion of emissions than the
currently employed control, however, at a cost low enough to induce firms to switch
to a control technique which controls a power amount of emissions (p. 59).
McHuges analysis focused mainly on the second type of innovation
technology. He argued that given any existing tax rate or permit price, the firm(s) in
the affected sector (in which the inframarginal technological innovations occur) may
find it more attractive to use the new inframarginal technology and reduce the level of
emissions, because the marginal cost of the presently employed technology has
increased above the tax rate.
The policy application of this theory is that the pollution control authorities
may raise the level of the tax to meet the emissions reductions goal. However, total
36


industrys compliance costs may increase, which means that a tax-based
environmental policy may lead to dynamic inefficiencies.
Mendelsohn (1984) tackled the issues of regulation under uncertainty. This
study showed that when the regulator is uncertain about the locus of the linear
marginal cost curve, quantity regulations (standards) are likely to be more efficient
than price regulations. This contradicts the traditional economists argument that
price rules, such as emission taxes in environmental policy, are more efficient than
quantity rules. Mendelsohn found that quantity rules tend to encourage more efficient
levels of technical change. Under price rules, firms tend to overreact and produce
either too much or too little R&D. Mendelsohn therefore concluded that technical
change will induce an additional welfare loss with price rules. Firms in turn will
overreact to the price rule, producing too much or too little abatement output and
stimulating too much or too little R&D. Over the long run, the quantity rule will
induce more efficient levels of technical change and waste reduction.
Nentjes (1988) based his study on the economic theory of bureaucracy. In this
study, government agencies are motivated not by the maximization of social welfare
but by output maximization. In turn, the goal of the control agencies is to maximize
pollution reduction. However, the agencies will not try to achieve emissions
reductions at all costs. The abatement costs may not exceed a certain level. As in
real life, the control agencies are careful not to impose costs too high for the polluting
firms.
37


In this study, higher control efficiency may be achieved through the use of
new pollution control techniques. The range of pollution control technologies runs
from well-known and proven technologies to highly uncertain technologies with high
control efficiencies. However, a risk-averse regulator with a high time preference and
a low cost ceiling will choose a point on the technology choice curve not far from the
best available abatement technology (BAAT). In such a situation, there is little
incentive for the polluting firm to develop innovations with higher control efficiency.
According to Nentjes, this has been the situation in Europe, where cost ceilings have
often been chosen on the basis of well-known and relatively cheap available reduction
technologies.
In addition, scholars argue that the relationship between command-and-
control standards and pollution control innovation is positive from different
perspectives. Porter (1991) maintained that environmental regulations do not
necessarily constrain the innovation related to competitiveness. Rather, regulations
that focus on process change often result in entirely new production technologies.
Also, strict standards and regulations would encourage companies to develop new
products which are less polluting, use resources more efficiently, and carry a higher
perceived value.
In a similar vein, Meyer (1982) and Marcus and Weber (1989) argued that
environmental regulations can be seen as an external jolt that stimulates innovation
within a firm. Without external jolts, firms will continue their old routines. Their
38


members will also resist innovation because they want to maintain the status quo.
Moreover, their organizational practices will stay the same unless an event such as the
imposition of environmental regulations occurs that requires them to change.
Further, Mitnick (1981), Caimcross (1992), and Shrivastava (1995) alleged
that strict regulations can create entrepreneurial opportunities for the firms. In turn,
they will design and develop new procedure and/or equipment to satisfy the
regulatory provisions. In other words, strict mandates can promote innovation and
provide unforeseen opportunities for profit by forcing the firms to upgrade their
technologies, and result in increased efficiency. Firms that manage to innovate and
obtain technological expertise in response to the environmental mandates will hold an
advantage over their competitors. The latter therefore are only compelled to purchase
and learn to use the new technology.
2.6.1.2 Empirical and Case Studies
Empirical and case studies also demonstrate that technology-based standards
have triggered industries to adopt new management styles and manufacturing
procedures that dramatically reduced the pollutants/emission. For example, stringent
standards forced companies to innovate their refineries to improve production and
increase operating efficiencies: Texaco reduced TRI emissions by 80% between 1989
and 1996, while refinery production increased by 12%. Besides, Texaco also reduced
water pollution spills by 12% since the 1990s. Ashland Oil reduced its toxic releases
39


of 17 target chemicals by 33% before the end of 1992 and by 50% by the end of
1995. Baxter International reduced its per unit air toxic and chlorofluorocarbon
emissions by 94%, its nonhazadous waste by 45% (34 million pounds), and its
hazardous waste by more than 48%. In addition, the 3M Corporation cut its air
emissions by 70%, its water releases by 52%, and its solid waste by 32% in its
worldwide operations from 1990 to 1996. Since the late 1980s, PepsiCo also has
reduced the amount of materials in its packages (aluminum cans by 35%,
polyethylene terephthalate in plastic bottles by 28%, and glass in bottles by 25%)
(Rondinelli and Berry, 2000).
Xerox reduced hazardous-waste generation by 50% between 1900 and 1995.
Nortel, the Canadian-based telecommunications, established specific targets for the
year 1993 to 2000: a 50% reduction in pollutant releases, a 50% reduction in solid
wastes, a 30% reduction in paper purchases, and 10% improvement in energy
efficiency (Kerr, 1995). Milliken and Co., a major textile manufacturing company,
reduced its sold waste materials by 21% in 1989, its energy consumption by 9%, from
0.93 to 0.68 EEBL per thousand pounds produced between 1990 and 1994 (DPPEA,
1995). Moreover, Dow Chemical decreased its emissions of compounds by 53%
(more than 51,000 pounds) in its facilities around the globe and made tremendous
profits by using the following strategies: It sold its pollution control technology to
companies and manufacturers that could not to develop it themselves; it sold its
40


expertise and equipment to the government; and it reduced manufacturing waste by
developing new uses for factory by-products (Marcus, 1984).
Likewise, cases in chlorofluorocarbons (CFCs) reduction demonstrate that
although strict regulations and standards are viewed by the firms as a threat, they turn
out to be an opportunity for innovation and emission reduction. At first, Du Pont
openly opposed any laws or treaties to reduce CFCs. However, other companies such
as AT&T, Motorola, and Northern Telecom realized that the future CFC restrictions
would be a big threat to their survival, and the need to innovate alternatives to CFCs
was urgent. Accordingly, they formed the Industry Cooperative for Ozone Layer
Protection (ICOLP) in 1990, which was a coalition that allowed industry competitors
to pool R&D resources for similar research goals. By the end of 1990, A&T& had
met its goal of reducing CFC emissions by 50%. Du Pont eventually realized the
threats from the future restrictions and started radically its new technology initiatives.
As a result, Du Pont reduced its R&D time from the industry norm of more than a
decade to only five years (Piasecki, 1995; Sanchez, 1997; Weber, 1993).
A similar case also shows that by responding to the regulatory requirements, a
cardboard recycling firm, Jackson Paper, established an innovative series of
conservation and reuse projects to obtain considerable positive results in terms of
regulatory compliance. For example, the newly designed on-site pretreatment facility
of the firm can cut effluent discharges from 100,000 gallons per day to 30,000 to
40,000 gallons per day. The new holding tank for the sludge belt press showers can
41


reduce discharge to an average of 22,000 gallons per day. Together, the total effluent
discharge reduction was 78,000 gallons per day, or a 78% reduction of the previous
discharge level. These new facilities helped reduce the annual manufacturing costs
approximately $112,000. The transportation and handling costs have also reduced
around $72,000 pear year (DPPEA, 1998).
The case of the professional garment and textile care industry, however,
displays a more gentle way of technology-based approach. As part of a cooperative
effort between the EPA and the industry, the EPAs Design for the Environment (DfE)
Program recognizes the wet cleaning process, or the water-based cleaning systems, as
an environmentally-preferable technology to clean garments. Currently, most of the
countrys 34,000 commercial drycleaners use perchloroethylene (PCE or perc) as a
solvent to clean garments. In response to the growing health and environmental
concerns about perc, the EPA initiated this program in 1992 and encouraged
professional clothes cleaners to explore those environmentally-preferable
technologies. The new technologies turn out to be a great success. As the study
indicated, the new technologies performed much better in certain types of clothes,
generated no hazardous waste and air pollution, and reduced annual operating costs
from approximately $10,000 to 20,000 among participants (EPA, 1999).
In addition, a series of case studies done by the Division of Pollution
Prevention and Environmental Assistance (DPPEA), North Carolina Department of
42


Environment and Natural Resources (NCDENR, 2005) has demonstrated the
successfulness of technology-based approach. The cases are listed in Appendix B.
2.6.2 Pro-Economic Approaches
In this section, the discussion of the pro-economic approach towards pollution
control is also divided into two parts. The first part depicts the theoretical foundation
and arguments, while the second part illustrates the empirical findings that support
this pollution control approach.
2.6.2.1 Theoretical Arguments
Downing and White (1986) analyzed the effects of four pollution reduction
instruments effluent fees, emission control subsidies, marketable permits, and direct
regulation (standards) in three contexts: (1) the situation where the marginal
conditions are not changed, that is, the reduction in the polluters emissions can be
valued at the existing social value of emissions reduction; (2) the situation where the
innovation changes marginal conditions, but the control authority, fails to adjust; and
(3) the situation where innovation changes marginal conditions and the control
authority adjusts properly, which is referred to as ratcheting.
In all three contexts, Downing and White assumed that the innovating polluter
correctly predicts the reaction of the government authority and bases its innovation
decisions on the prediction. In addition, two properties of the regulatory regimes are
taken into account: the incentives for innovation in pollution control, and the dynamic
43


efficiency of these incentives, which refers to the efficiency of the allocation of
resources after the innovation.
Downing and White summarized their findings in the following two tables.
Table 2.5 demonstrates the incentives for innovation under various pollution control
arrangements. Table 2.6 shows the emissions levels under various pollution control
arrangements. In Table 2.5, optimal indicates the equilibrium between the social
value of emissions reductions and government pollution control arrangements.
Excessive means that the arrangements cause an excessive amount of innovation
and pollution reduction, while deficient is the other way around. Also, as shown in
Table 2.6, when ratcheting happens, the emissions levels can be adjusted to the
optimal status.
Table 2.5 Incentives for Innovation under Various Pollution Control Arrangements
Effluent Fees Subsidies Marketable Permits Direct Control
No change in marginal conditions Optimal Optimal Optimal Deficient
Change in marginal conditions; no ratcheting Excessive Excessive Indeterminate Deficient
Change in marginal conditions; ratcheting Excessive Deficient Deficient Deficient
Source: Downing and White (1986, p.28)
44


Table 2.6 Emissions Levels under Various Pollution Control Arrangements
Effluent Fees Subsidies Marketable Permits Direct Control
No change in marginal conditions Optimal Optimal Optimal Too high
Change in marginal conditions; no ratcheting Too high Too Low Indeterminate Too high
Change in marginal conditions; ratcheting Optimal Optimal Optimal Optimal
Source: Downing and White (1986, p.28)
According to the tables, Downing and White (1986) argued that if the
innovation does not change the social value of emissions reduction, the incentive for
innovation in pollution reduction will be optimal except for direct control. This
situation is similar in the calculation of emissions levels, which suggests that if the
innovative polluter (or polluters) is the only one that innovates among other polluters,
it will be beneficial by the innovation.
On the other hand, when the social value of emissions reduction has changed,
the incentives for innovation will not be optimal no matter whether the government
has made socially appropriate adjustments or not. Consequently, the results will not
be optimal. Nevertheless, if proper ratcheting is applied, the emissions levels will all
be optimal as shown in Table 2.6. This indicates that government should pay
attention to the innovative efforts of the industries and make proper responses for
optimal emission levels.
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Similar to the above, Milliman and Price (1989) examined the linkage
between regulations and pollution reduction through technological change. However,
their study was broader than Downing and Whites in that: (1) they assessed the entire
process of technological change from innovation to diffusion; (2) they analyzed five
regulatory regimes: direct control (standards), emission subsidies, emission taxes, free
marketable permits, and auctioned marketable permits; (3) they assessed incentives
that promoted optimal agency response via political lobbying or information
withholding, for both innovating and non-innovating firms; and (4) they examined
technological change incentives for both non-patented and patented innovations, and
for innovations that occurred outside the polluting industry.
This theory assumes a large number of firms in a competitive industry, each
discharging a homogenous emission into a body of water, air, or land. Also, it
assumes that the regulator holds perfect information on current abatement technology.
However, lags in perceiving a discovery and the political pressures prevent the
regulator from imposing optimal agency response prior to the completion of
diffusion. The relative rankings of the regulatory regimes are listed in Table 2.7.
Table 2.7 Summary of Relative Rankings of the Incentives to Promote Technological
Change in Pollution Control and the Attitude Towards Optimal Agency Response
Direct Control Emission Subsidies Free Permits Auct. Permits Emission Taxes
Innovation 5 1 1 1 1
Diffusion
Inno., N-P 2 2 5 1 2
N-I, N-P 4 2 4 1 2
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Table 2.7 (Cont.)
Direct Control Emission Subsidies Free Permits Auct. Permits Emission Taxes
Inno., P 4 2 5 1 2
N-P, P 4 2 4 1 2
O-F, P 4 2 4 1 2
Optimal Agency Response
Ind., N-P 2-5 2-5 2-5 2-5 1
CAS Oppose Oppose Oppose Oppose Favor
Inno., P 1-4 5 1-4 1-4 1-4
CAS Uncertain Oppose Uncertain Uncertain Uncertain
N-I, P 2-5 2-5 2-5 2-5 1
CAS Oppose Oppose Oppose Oppose Favor
O-F, P 1 4 1 3 4
CAS Favor Oppose Favor Uncertain Oppose
Source: Milliman and Prince (1989, p.257).
Inno.: Innovator; N-P: Non-Patent Innovation; N-I: Non-Innovator; P: Patent Innovation; O-
F: Outside Firm; Ind.: Industry; CAS: Control Adjustment Stance. The firms stance towards
governmental patent protection
In general, as shown in Table 2.7, this study argues that emission taxes and
auctioned permits clearly reward positive gains to an industry innovator from the
entire process of a technological change. Therefore, these two regulatory regimes are
better facilitators of technological changes.
Wender (1975) analyzed the relationships between pollution abatement
technologies and a polluting firms costs of utilizing them under three pollution
reduction approaches: (1) a tax per unit of pollution emitted, where tax is used as
another word for fee or charge; (2) a subsidy per unit of emission reduction; and (3)
emission standards.
47


In this study, innovation in pollution control is firm-specific. The firm tries to
minimize its costs (abatement costs plus tax payments minus any subsides), while the
pollution control agency possesses full information about the marginal cost and
damage functions of the firm. Therein, three situations are considered: (1) the case in
which the pollution control board does not change the emission standard or the tax-
subsidy rate when innovation is available; (2) the case of control adjustment; and (3)
the case where the firm can change the form of the cost abatement function, besides
its position.
Wender concluded that: (1) both taxes and subsidies offer more inducement to
innovation than the emission standard approach. This result is similar to the above
theories; (2) If the pollution control board reacts to the improvement in abatement,
then the inducement to innovation for the firm operating under the corrective tax
becomes greater than the inducement for the firm operating under the subsidy or the
emission standards. This, again, is identical to the results of the theories above; and
(3) If a firm is able to control the direction of its R&D, the firm operating under either
emission controls or a corrective subsidy will prefer innovation which raise the
established level of pollution abatement as little as possible, whereas the firm
operating under a tax will prefer the kind of technological change that raises the
optimal level of abatement as much as possible.
Magat (1978) analyzed the effects of two pollution control policies, namely
effluent taxes and effluent standards, on the path of technological change chosen by a
48


firm that produces an effluent by-product. In this study, the firm may invest
resources to improve its abatement technology, its production technology, or both. In
other words, this firm engages in an R&D program to improve its current technology
of output production and effluent abatement.
In this study, Magat aimed to decipher the interactions between these two
efforts. For each level of R&D spending, this study demonstrated the tradeoffs
available between improving production technology and advancing effluent
abatement technology: a high decrease in the improvement in production technology
is only possible if the increase in the improvement in effluent abatement technology
is low, and vice versa.
Based on the above, Magat (1979) extended his research to analyze five types
of regulatory tools: effluent charges, non-technology-based effluent standards,
marketable permits, technology-based effluent standards, and subsidies for abatement
capital. Margats conclusions in this paper (1979) were somewhat different from the
theories above. He concludes that if standards and marketable permits that induce the
same level of effluent discharge over the entire period of analysis, they will provide
exactly the same incentive for both abatement technology and output technology
innovation. In addition, if the regulator reduces the effluent charge to induce the
same abatement as under the effluent standard, the innovator will still maintain a
transfer gain. Moreover, non-technology-based effluent standards create a stronger
incentive for abatement technology innovation than technology-based effluent
49


standards. Regulatory agencies that adopt technology-based standards may need to
reconsider their approaches.
Lastly, scholars also question technology instruments from the following
aspects: First, research shows that while the water quality has been improved,
technology instruments still have not helped achieve major goals such as fishable-
swimmable waters in the United States.
Second, though surface water has been cleaned, the contamination of ground
water still cannot be resolved by the technology instruments because there are myriad
of non-point pollution sources that are not possible to be controlled (Allenby, 2000;
Plater, Abrams, and Goldfarb, 1998).
Third, the problem of cross-media pollution cannot be resolved under the
technology instruments. Cross-media pollution occurs when pollutants such as toxic
substances and acid deposition transfer and transport through multiple media like
water and air simultaneously. If regulations are designed to tackle pollution problems
separately, such as air program, water program, and land program, etc., cross-media
problems will unlikely be handled in an efficient and effective manner.
Unfortunately, technology instruments are single-source tools, which are limited in
tackling the cross-media problems (John and Mlay 1999; Rabe 1986).
Fourth, while one of the rationales of technology-based approach is that it is
simple to implement, research suggests that technology instruments are actually
labor- and information-intensive for regulators. Those tools require knowledge of the
50


operational processes of polluters; of widely used technologies for controlling
pollutions; and of the costs and feasibility of installing and maintaining these
technologies across a wide range of facilities. Besides, the administrative process for
developing and issuing technology standards is long, cumbersome, and difficult.
Accordingly, technology instruments create huge regulatory lag for the agencies
(National Academy of Public Administration, 1995).
Fifth, it is questionable whether the technologies identified by the government
are actually the most proper ones in controlling the pollution. As government
regulates that certain filtering system is the best available technology to clean the
emissions to the air, industries may complain that those technologies may not be the
most cost efficient and cost effective ones. Furthermore, studies suggest that
technology-based standards are actually freezing in-house technology innovation
because, instead of finding new ways, most industries turn to make minor
improvements on traditional technologies (Eggers, Villani, and Andrews, 2000).
Sixth, scholars state that the relationship between regulation and pollution
reduction innovation is negative because the costs and bureaucracy of environmental
regulation will undermine innovative efforts and restrict firms to pursue advanced
technologies (Breyer, 1982; Carter, 1990). Strict technology instruments add sizable
compliance costs to firms, which forces them to cut back their R&D efforts and limits
their innovative initiatives. Accordingly, the net effect of these constraints is reduced
innovation and put them at a competitive disadvantage status (Caves, 1982;
51


Guttmann, Sierck, and Friedland, 1992; Scherer and Ross, 1990). Firms and facilities
also argue that it is difficult to innovate since regulations often change unexpectedly
and unpredictable. Case studies show that small X-ray companies invest less in new
product inventions over the short term because environmental and other regulations
increase uncertainty in those companies (Bimbaum, 1984). More empirical and case
studies are discussed below.
2.6.2.2 Empirical and Case Studies
The Clariant Corporation in Mount Holly, NC is a major, nationwide
manufacturer of dyes and textile chemicals. During its manufacture procedures, it
produces sulfuric acid, sodium thiosulfate, and ammonium sulfate as co-products.
This company has found that if they can remove some organics from the waste
streams, those co-products can be eliminated from the hazardous waste D-list and
become resalable products. This market approach not only encourages the company
to innovate its technology, but also helps them keep out of the waste streams, meet
regulatory requirements, reduce waste disposal costs, and increase the sales revenue
to 1.1 million dollars per year (DPPEA, 1997).
Similarly, due to market resale incentives, a kitchen and bath plumbing
products manufacturer, Moen Incorporated, developed an environmental plan in 1995
to reduce emissions and wastes. This plan helped reduce the firms aqueous wash
waste by approximately 45% (400,000 lbs.) in 1995, hazardous wastes by 90%
52


(1,000,000 lbs.), process water use by 54% (40,000,000 gal.), and recycling wooden
pallets and cardboard by 42% (1,800,000 lbs.) in 1997. The total annual savings of
this firm was $2,745,000 per year (DPPEA, 1997).
Studies also suggest that taxes can successfully change behavior. A study of
the generation and management of a major group of wastes spent solvents from
cleaning and degreasing metal products has indicated that state taxes can actually
help reduce the amount of wastes generated by the related facilities. Although the
reduction was small (between 5 and 12 percent), compared to the taxes levied (only
$10 to $20 per ton), the reduction of the management costs was huge (more than $100
a ton) (Sigman, 1996).
In addition, state taxes can alter generators behavior as to where to manage
their wastes. Levison (1997) maintained that, first, state taxes have major influence
on the extensive interstate shipment of waste; and, second, high taxes will deter waste
management significantly. Waste management has especially low environmental
costs in states with low population density and arid conditions. If those states choose
low taxes, interstate shipment in response to differentiated taxes would reduce the
environmental costs of waste management. However, if politics is the main force to
decide the pattern of tax rates, the responses to taxes would be costly. Nonetheless,
research findings illustrate that waste generators respond to price signals in ways that
a good tax policy can harness.
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A pilot program in water pollution trading also showed promising results. A
Minnesota-based Rahr Malting Co. planed to increase its production in 1997.
However, the state and federal EPA found that the Minnesota River could not handle
the extra load from the companys new treatment facility. To resolve the problem,
the environmental agencies developed a pilot program and issued the company a
point/nonpoint-polluant-trading permit. This permit allowed the company to reduce
the amount of pollution from nonpoint sources in exchange for the pollution it
discharged from its plant. In response, Rahr created the Minnesota River Corporate
Sponsorship Program to target nonpoint sources such as highly erodible lands and
livestock-damaged riparian zones within the Minnesota River's 16,770 square-mile
(43,400 square-kilometer) drainage area. Through the program, Rahr purchased
easements on sensitive agricultural lands and protected these lands from erosion in
return for the right to discharge into the river. Results showed that this program
reduced not only the pollution in the watershed, but also the companys control and
management costs (Peplin, 1998).
Additional successful cases concerning market-based approaches include: (1)
The U.S. Acid Rain Program (sulfur dioxides (SO2) and nitrogen oxides (NOx)
reduction) proposed by the Congress and the National Acid Precipitation Assessment
Program (NAPAP); (2) the case of the Wisconsin Electric Power Company that
successfully reduced SO2 and NOx under the Acid Rain Program (ETEI, 2005); (3)
the Federal NOx Emission Trading Program by the EPA (EPA, 2003; Zingale, 2002);
54


(4) the Greenhouse Gas Programs (carbon dioxide (CO2) reduction) that utilize
tradable permits and carbon taxes (Pakerr, 2002); (5) the tradable air quality control
permit systems (hydrocarbons discharges) in Portland, Oregon; (6) the air pollutant
discharge fee systems in southern California (Lee and Sexton, 1993); (7) the fuel tax,
parking fee, congestion pricing, third party van subsidies, and carpools in many
metropolitan areas (Giuliano and Washs, 1992); (8) and the market-based
mechanisms/initiatives to control mercury depositions in Minnesota (Hagen, Vincent,
and Welle, 1999), etc. Moreover, a range of marked-based environmental policies at
the federal and state levels are listed in Appendix C.
2.6.3 RCRA Related Policy Studies
Compared to the studies in the field of air and water pollution above, RCRA
related policy studies were fairly scant. With a thorough search of the literature in the
academic and research databases and websites, most studies under RCRA were in the
field of environmental science and/or cases studies at the firm or facility level.
Moreover, the number of RCRA related policy studies found under keyword search
(RCRA and waste reduction) was limited.
For graduate level studies, among the 44 dissertations and theses found under
keyword RCRA in the Digital Dissertations database, 19 were policy and
management related: Four dissertations addressed the issue of RCRA enforcement
and compliance at the state level (Hachey, 1996; Jones, 1994; Okere, 1995; Port,
55


1988). Two dissertations analyzed the economic tools: contracting out hazardous
waste management (Jarvinen, 1995) and commercial insurance under RCRA
(Willingham, 1993). One thesis in the field of environmental science tackled the
issue of hazardous waste minimization of a facility in Ohio (Delay, 1994).
The rest of the studies focused on a variety of topics, such as regulatory
process of environmental laws (Holland, 2003; Keefe, 1993), equity issues in
implementation (Firestone, 2000), regulation of radioactive mixed waste cleanup (St.
Clair, 1993), environmental inspections (Bailey, 1988; Spitzer, 1992), used oil
management (Mueller, 1999), environmental restoration (Dinwiddie, 1997), impact of
presidential administration on environmental regulations (Floyd, 1990), non-regulated
environmentally conscious decisions (Sharp, 1996), environmental justice and
participatory democracy (Gott, 1995), and social regulation and RCRA
implementation (Quinlan, 1993). None of the dissertations and theses analyzed the
relationship between regulatory tools and solid and hazardous waste reduction at the
state level.
An additional search was conducted for related books and research articles.
For example, in Infotracs Expanded Academic database, 1,287 articles could be
found under RCRA. However, when narrowing down to RCRA and waste reduction,
the search engine only found 8 articles. With the same searching procedure in other
databases, the results were: EBSCOs Academic Search Premier from 166 articles
to 1 article; Lexus-Nexus from over 1000 to 190 articles (25 of them were policy
56


related); and Blackwell Synergy from 65 to 30. Again, none of them focused on the
relationships between regulatory tools and chemical industrys waste reduction
performance at the state level. Accordingly, it is believed that this dissertation would
serve the purpose of bridging the research gap between regulatory tools and solid and
hazardous waste reduction under RCRA.
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3. Research Design
3.1 Hypotheses
As the literature above shows, most studies tackling the relationship between
regulatory tools and pollution reduction were done in the fields of air and water
pollution control. Not much research has been done in the field of solid and
hazardous waste control. Also, the relative capabilities between technology-based
standards and economic approaches in reducing pollution were controversial.
Scholars and analysts differed in their judgment as to which approach performed
better in pollution reduction. Moreover, most RCRA related studies were conducted
in the field of environmental science and/or at the firm level. Policy research at the
state level was fairly scant. Accordingly, with the unique and flexible regulatory
background of RCRA, it would be proper to hypothesize based on the findings of
both command-and-control and economic approaches. In doing so, we may obtain a
broader and better understanding of the field of solid and hazardous waste reduction
at the state level. To fulfill this purpose, I listed the following hypotheses.
3.1.1 Technology-Based Standards
Technology-based standards have been regarded as an effective pollution
control mechanism by scholars from different perspectives. As discussed earlier,
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HcHuge (1985) stated that a tax-based environmental policy may cause more (total)
compliance cost to the industry and in turn led to dynamic inefficiencies.
Mendelsohn (1984) argued that when the regulator was uncertain about the locus of
the linear marginal cost curve, quantity regulations (standards) would likely be more
efficient than price regulations. Nentjes (1988) pointed out that the control agencies
were usually careful not to impose too large costs on the polluting firms. Also, higher
control efficiency could be achieved through the use of new pollution control
techniques. Porter (1991) maintained that strict standards and regulations often
triggered the innovation relating to competitiveness. In a similar vein, Meyer (1982)
and Marcus and Weber (1989) argued that environmental regulations could be seen as
an external jolt that stimulated innovation within a firm. Further, Mitnick (1981),
Caimcross (1992), and Shrivastava (1995) alleged that strict regulations could create
entrepreneurial opportunities for the firms. Based on the arguments and the empirical
findings in section 2.6.1.2,1 hypothesized that:
HI: The governments stringent technology-based standards will promote the
reduction of solid and hazardous waste.
In this hypothesis, the independent variable (states) was categorized in two
ways. First, states were divided into two groups according to Wagners (1999)
survey: states that utilized and did not utilize additional standards. Second, states
waste reduction performance was divided and measured before and after the
implementation of the more stringent Hazardous Waste Minimization National Plan
59


of 1995 (EPA, 1996). Detailed description of the variable measurements is presented
in section 3.2.3.
3.1.2 Hazardous Waste Fees
Since technology-based standards are the regulatory foundation of RCRA and
the authorized states have the discretion to enact programs broader in scope than the
federal program, it would be worthwhile to compare the performance of the states that
utilized different types of hazardous waste fees. Scholars in the camp of pro-
economic approaches strongly argued that direct control or strict standards provided
the least or no incentives for innovation and pollution reduction (Downing and White,
1986; Milliman and Prince, 1989; Wender, 1975; and Magat, 1978). Other problems
such as non-point sources (Allenby, 2000), cross-media pollution (John and Mlay
1999; Rabe 1986); administrative costs (National Academy of Public Administration,
1995); in-house technology freeze (Eggers, Villani, and Andrews, 2000); and high
compliance costs and R&D cuts due to strict standards (Caves, 1982; Guttmann,
Sierck, and Friedland, 1992; Scherer and Ross, 1990) all suggested that economic
approaches are a more effective tool. Based on those studies and the empirical
findings in section 2.6.2.2,1 hypothesized that:
H2: There will be significant differences in the performance of solid and
hazardous waste reduction among the states that utilize different
hazardous waste fee systems.
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In this hypothesis, each states fee systems were based on the surveys of
Wagner (1999) and HTRWCE (2002). In Wagners survey, three types of regulatory
adoptions were identified: did not utilize, partially utilized, and fully utilized
hazardous waste fees. In HTRWCEs survey, hazardous waste fees were divided into
five groups: (1) no taxes or fees imposed, (2) hazardous waste management fees and
direct treatment disposal fees, (3) hazardous waste management fees but no direct
treatment or disposal fees, (4) direct treatment or disposal fees, and (5) direct
treatment or disposal fees that also specifically target out-of-state waste.
3.1.3 Permits
Permitting is the key element in the implementation of hazardous waste
programs under Subtitle C. As previously mentioned, all RCRA regulated facilities
have to obtain a RCRA or hazardous waste management permit before operating.
However, based on the state authorization, states may develop and design their own
permit systems for generators and transporters.
As permits are one of the major regulatory tools, it would be meaningful to
compare the performance of the states that issued permits, partially issued permits,
and issued no permits to generators and transporters based on Wagners (1999)
survey. Similar to the above, according to Downing and White (1986), Milliman and
Price (1989), Magat (1978), and the findings of the empirical and case studies
mentioned in section 2.6.2.2,1 hypothesized that:
61


H3: There will be significant differences in the performance of solid and
hazardous waste reduction among the states that issue, partially issue, and
issue no permits to generators and transporters.
3.1.4 Other Contextual Variables
As mentioned in the literature review, in addition to technology-based
standards and other economic approaches, there are other contextual variables that
may also be related to the performance of pollution reduction. Those variables
include state SEPs; the importance of SEPs recognized by the states (ASTSWMO,
1997; EPA, 2005); the R&D funds of the chemical industry (Guttmann, Sierck, and
Friedland, 1992; Scherer and Ross, 1990); the number of third-party treatment
facilities; and the number of technical assistance (U.S. Congress, 1995; OLeary,
Durant, Fiorino, and Weiland, 1999). Detailed description of the (contextual)
variables is also presented in the section of data measurements.
Again, while the relative performance of technology-based standards and
other economic approaches was undecided, it would be worthwhile to compare the
relative performance of those independent variables. Therefore I hypothesized that:
H4: Technology-based standards are more likely to have stronger effects on
the reduction of solid and hazardous waste than other contextual variables.
H5: Hazardous waste fees are more likely to have stronger effects on the
reduction of solid and hazardous waste than other contextual variables.
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H6: Permits are more likely to have stronger effects on the reduction of solid
and hazardous waste than other contextual variables.
3.2 Research Data
3.2.1 Industry Selection
In this study, my focus was on the chemical industry. The chemical industry
has long been recognized as a major source of pollution. From a toxic and hazardous
emissions point of view, the chemical industry can further be regarded as the most
critical industry because it accounts for almost half of the total emissions for all
industries in this country (Dooley and Fryxell, 1999). Among all of the chemical-
related industries, I specifically focused on the chemical manufacturing industries.
These facilities are listed in the category of Chemicals and Allied Products of the
EPAs Standard Industrial Classification (SIC, 1987) Codes, and are coded from 2812
to 2899.
3.2.2 Data and Sources
3.2.2.1 Solid and Hazardous Waste
This research utilized the EPAs solid and hazardous waste databases: the
Resource Conservation and Recovery Act Information System (RCRAInfo or
RCRIS) and the Chemical Industry Biennial Reporting System (BRS). The major
contents of these two databases include: (1) facility identification and certification,
63


which identified the facilities EPA ID number, waste management status, and waste
reduction activity; (2) waste treatment streams, which demonstrate facilities waste
treatment activities such as on-site or off-site treatment; (3) detailed information of
treatment, recycling, and disposal facilities (TRDFs) such as waste form, waste
quantity, and system type; and (4) specific information of the technologies used in
treatment, disposal, or recycling process. Longitudinal data were collected from the
year 1989 to 1999.
As of 2005, EPA has been converting and matching data between SIC and
NACIS coding systems. Therefore, the complete datasets later than 1999 had not
been available from the EPAs RCRAInfo and BRS databases before the finish of this
dissertation. The updated data could be found from the Right to Know Networks
databases. However, first, there was no industry search function (SIC/NACIS) for the
new databases. Second, the new NACIS codes were not matched with the old SIC
codes in those databases. Third, most importantly, more industries were included in
the NACIS system compared to the SIC system, as can be seen in the matching tables
(Appendix D). Since there was no consistency between the datasets of 89-99 and 01 -
03,1 focused on the 89-99 data. Once the matched datasets are released, new analysis
can be conducted.
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3.2.2.2 Regulatory Tools
For technology-based standards, the typology was based on Wagners (1999)
survey. As discussed above, states may adopt standards that are broader in scope
and/or more stringent than the federal requirements. For example, Florida and Georg
regulated mercury as an additional hazardous waste in their RCRA program, while
Colorado and Kansas did not regulate any additional hazardous wastes.
Each states fee systems were based on the surveys of Wagner (1999) and
HTRWCE (2002). For instance, Nevada levied hazardous waste fees from the
treatment, storage, and disposal facilities (TSDFs). However, Ohios fees were
designed for the transporters. As in HTRWCEs system, both Nevada and Ohio were
in the category of states that levied hazardous waste management fees and direct
treatment disposal fees.
As for the permit systems, they were also based on the survey of Wagner
(1999). For example, in Florida, there were no fee systems. In Illinois, transporters
needed to apply permits before operating. In Maryland, both generators and
transporters were required permits.
In addition, more rating systems were utilized, which include: (1) the Green
Index, (2) the levels of fees charged by state governments (Appendix E), and (3) the
sizes of facilities and the production capacities of the chemical industry in the states
(Table G.l, Table G.2, and Table G.3). Based on these rating systems, the variations
within and among the groups such as the state governments eagerness and
65


willingness to enforce the regulations, the relative degree of regulatory assertiveness
of the states, and the size and development of the industry could be revealed and
controlled. Accordingly, detailed and in depth explanations of the relative
performance of the regulatory tools could be offered.
3.2.2.3 Contextual Variables
Contextual variables were gathered from a variety of surveys and databases.
The state RCRA SEPs were based on the survey done by the Association of State and
Territorial Solid Waste Management Officials (ASTSWMO, 1997). Data for the
R&D funds by company, the R&D funds by the governments, the number of R&D
performing companies, and the pollution reduction R&D funds by the governments
and industry were gathered from the datasets provided by the Industrial Research and
Development Information System (IRIS) of the National Science Foundation. The
number of third-party treatment facilities in each state was calculated based on the
RCRAInfo/RCRIS and BRS databases. These databases contain detailed information
about the treatment facilities that import solid and hazardous wastes from other
facilities.
Technical assistance is one of the major environmental policy tools used by
the governments (U.S. Congress, 1995). It is the additional/new technical knowledge
provided by the federal and/or local governments to the facilities to innovate the
existing technologies (U.S. Congress, 1995; OLeary, Durant, Fiorino, and Weiland,
66


1999). According to the EPA, the major technical knowledge and assistance to the
industries come from the publications of its technical support centers. Hence, the
data for the number of technical assistance was obtained by calculating the number of
the hazardous waste related articles published and posted on the centers websites.
Detailed information of the data sources is presented in Table 3.1.
Table 3.1 Research Data and Sources
Data Agency or Author Source or Publishing Data
BRS Data EPA httD://www.ena.eov/eDaoswer/hazwaste/data/#brs

The Right- to-Know Network httD://www.rtknet.org/new/brs/

RCRAInfo / RCRIS Data EPA httn://www.eDa.eov/enviro/html/rcris/rcris query iava.html
The Right- to-Know Network httD://www.rtknet.org/new/rcris/

State Regulations ASTSWMO (1997) Supplemental Environmental Projects (SPEs): Survey of states and territories. Washington DC: ASTSWMO.
Wagner, Travis P. (1999). The Complete Guide to the Hazardous Waste Regulations. New York: John Wiley & Sons, Inc.
HTRWCE (2002) Report on Treatment, Storage & Disposal Facilities (TSDFs) for hazardous, toxic, and radioactive waste. US Army Corps of Engineers, Retrieved April, 2005 from http://www.environmental.usace.armv.mil/librarv/Dubs/tsdf/
tsdf.html
R&D Data National Science Foundation http://www.nsf.eov/sbe/srs/iris/historv data.cfm

67


Table 3.1 (Cont.)
Data Agency or Author Source or Publishing Data
Technical Assistance EPA Hazardous Substance Technical Liaisons http://epa.eov/osD/hstl.htm
National Environmental Publications Information System (NEPIS) http://www.eDa.eov/nepis/
National Service Center for Environmental Publications (NSCEP) http://www.epa.eov/ncepihom/
Pollution Prevention Information Clearinghouse (PPIC) http://www.epa.eov/opptintr/librarv/ppicindex.htm
Pollution Prevention Technical Assistance http://www.epa.eov/p2/assist/index.htm
Publications on the EPA Site http://www.epa.eov/epahome/publications2.htm
Technical Support Projects http ://www.epa. eov/tio/tsp/index .htm

CLU-IN Hazardous Waste Technology Innovations http://www.clu-in.ore/publ .cfm

3.2.3 Data Measurements
For hypotheses 1, there were two sets of independent variables that served two
statistical procedures separately. The first independent variable was a nominal
variable, which indicated before and after the utilization of more stringent
technology-based standards. The dividing point was 1995, the implementation of the
Hazardous Waste Minimization and Combustion Strategy (HWMCS) and the
Hazardous Waste Minimization National Plan (HWMNP) of 1995 (EPA, 1996) that
updated and strengthened the standards under RCRA. The second was also a nominal
68


variable, which included (1) states that did not utilize additional standards and (2)
states that utilized additional standards. The dependent variable was an interval
variable the rate of solid and hazardous waste reduction. It was calculated not by
the actual volume of waste reduction, but by the rate between the reduced waste and
total waste. The higher the rate, the more proactive and effective the states/regulatory
tools were. This was to account for possible growth in the chemical industry in a
given state as a confounding variable. Also, a positive rate indicated waste volume
growth, while a negative rate represented waste volume reduction. The time span for
BRS database was from 1989 to 1999.
For hypotheses 2, the independent variable was a nominal variable, namely,
the types of hazardous fees. Based on Wagners (1999) study, the fees were divided
into three types: (1) states that did not utilize fees, (2) states that partially utilized
fees, and (3) states that fully utilized fees. However, based on the survey of the
Hazardous, Toxic and Radioactive Waste Center of Expertise (HTRWCE, 2002), the
fee systems were divided into five: (1) no taxes or fees imposed; (2) hazardous waste
management fees but no direct treatment or disposal fees; (3) hazardous waste
management fees and direct treatment disposal fees; (4) direct treatment or disposal
fees; and (5) direct treatment or disposal fees that also specifically target out-of-state
waste. Separate statistical analyses were administered based on the two systems. The
dependent variable was an interval variable the rates of solid and hazardous waste
reduction based on the BRS database.
69


For hypotheses 3, again, the independent variable was a nominal variable,
namely, the three types of permit systems: did not issue permits, partially issued
permits, and fully issued permits to generators and transporters. The dependent
variable was an interval variable the rates of solid and hazardous waste reduction
based on the BRS database.
Lastly, the independent variable measurements for hypothesis 4, 5, and 6, as
mentioned above, were: First, nominal variables: technology-based standards,
hazardous waste fees, generator/transporter permits, state SEPs, and SEPs
importance. For state SEPs and SEPs importance, they indicated whether the state
has the projects or not; and whether the state regards SEPs as important or not.
Second, interval variables: the R&D funds of the chemical industry; the number of
third-party treatment facilities, and the number of technical assistance. The
dependent variable, again, was an interval variable the rates of solid and hazardous
waste reduction based on the BRS database. The summary of the data type and
description is showed in Table 3.2 below.
Table 3.2 Variable Type and Description
Independent Variables Data Type Description
State Nominal 50 states and District of Columbia
T echnology-based Standards Nominal States with or without additional standards
Hazardous Waste Fees Wagner Nominal 3 types of fees by Wagner (1999)
Hazardous Waste Fees HTRWCE Nominal 5 types of fees by HTRWCE (2002)
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Table 3.2 (Cont.)
Independent Variables Data Type Description
Generator or Transporter Permits Nominal 3 types of permits by Wagner (1999)
SEPs Nominal State Supplemental Environmental Projects
SEPs Importance Nominal The importance of SEPs recognized by each state
RCRIS Third Party Treatment Facilities Interval The average number of third party treatment facilities in each state
Total R&D Funds Interval The average of total R&D funds (in millions of dollars) to each state (1985-2001), including federal and company
Fed R&D Funds Interval The average of federal R&D funds (in millions of dollars) to each state (1985-2001)
Comp R&D Funds Interval The average of company R&D funds (in millions of dollars) by state (1985-2001)
Cl R&D Funds Interval The average of chemical industry R&D funds (in millions of dollars) by major state (1985- 2001)
Dependent Variables Data Type Description
BRS Reduction Rate Interval The average of reduction rates calculated by the total volume of waste in each state/year (1989- 1999)
BRS Pre Reduction Rate Interval The average of pre reduction rates of each state (1989-1995)
BRS Post Reduction Rate Interval The average of post reduction rates of each state (1995-1999)
3.3 Statistical Analysis
To test the hypotheses, the following statistical procedures were used. First,
for hypotheses 1, two t-test procedures were exercised. The first was a paired-
samples t-test procedure and the second was an independent-samples t-test. The
former computed the mean difference between the reduction rates before and after the
71


implementation of HWMCS and HWMNP of 1995. The latter compared the
reduction rates between states that utilized and did not utilize additional (broader
and/or more stringent) standards.
Second, procedures of one-way ANOVA were utilized for hypotheses 2 and 3.
The purpose of this statistical method was to test whether the means of reduction rates
of different types of fee / permit systems were equal. If the differences existed, post
hoc tests could be used to verify which means were significantly different.
Third, for hypotheses 4, 5, and 6, procedures of multiple regression analysis
were exercised. The regression analyses estimated the coefficients of the linear
equation (one or more independent variables or predictors) that best predict the value
of the dependent variable.
The equation was as follows:
Y= a+PiXi+ P2X2+P3X3+ P4X4+P5X5+ e*
Where:
Y: Solid and hazardous waste reduction rate
a: Intercept
p: Coefficients
Xi: Vector of regulatory tools
X2: Vector of R&D activities
X3: SEPs
X4: Third-party treatment facilities
X5: Technical assistance by the governments
e*: The error or residual term
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4. Results and Findings
Based on the data collected from the sources, hypotheses were tested through
the utilization of computer statistical program SPSS 13.0. Also, research results and
findings were organized into three sections: general trends and state solid and
hazardous waste status, hypothesis testing, and additional analysis. For detailed
descriptions of the variables, data types, and data conversion procedures, please refer
to Table 3.2 and Appendix F.
4.1 General Trends and State Solid and Hazardous
Waste Status
To obtain a big picture of the trends and current status of solid and hazardous
waste, time series data and geographical data were analyzed. Analyzing the national
trends would help realize whether the data had certain patterns and/or directions or
not. The trends analyzed were: (1) BRS waste volumes and reduction rates from
1989 to 1999; (2) R&D funds from 1989 to 2001; (3) the number of technical
assistance from 1988 to 2002; and (4) the number of third party treatment facility
from 1989 to 1999.
For state status, the analysis was to understand and to rank the capacity of the
chemical industry in each state. The rankings included: (1) the rankings of waste
volume, the rankings of the number of facility, and the rankings of waste volume per
73


facility, based on BRS data from 1989 to 1999; (2) the rankings of different R&D
funds from 1989 to 2001; and (3) the rankings of the number of third party treatment
facility based on RCRIS data from 1989 to 1999.
With these rankings, we may obtain a better understanding in terms of the
dirtiness of each and every state. More importantly, additional analyses were
conducted based on these rankings, which are presented in the third section of this
chapter. A summary of the directions of the trends is showed in Table 4.1 below.
The figures of the trends and the tables of state capacity and status can be found in
Appendix G.
4.1.1 General Trends
4.1.1.1 BRS Waste Volumes and Number of Facility
from 1989 to 1999
The trend of BRS waste volumes and number of facility are demonstrated in
Figure G.l and G.2. The trends revealed an interesting situation: by setting different
baseline years, the direction of the trends would be different. In other words, if we
set 1989 as the baseline year, they would show an overall increasing pattern.
However, if we neglected 1989 and set 1991 as the baseline year, the trends would
become decreasing trends. The different direction of the trends may lead to different
policy implications. And a clearer pattern can only be obtained when new data are
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released. In this research, I set the baseline year in 1989 in order to cover the full
spectrum of data released by the EPA.
4.1.1.2 R&D Funds from 1989 to 2001
Chemical industry related R&D data included: federal and company R&D
funds, federal and company pollution reduction funds, R&D performing company
funds, company R&D contract out funds, and the number of R&D company. As
illustrated from Figure G.3 to Figure G.5, we may observe that chemical companies
were the major supporter and source of R&D funds. Compared to the companies, the
federal governments funds were minimal. Similar situation could be found in the
category of pollution reduction funds, which is showed from Figure G.6 to Figure
G.8.
As for the trend direction, data with an increasing trend included: federal
R&D funds, company R&D funds, federal pollution reduction funds, R&D
performing company funds, and company R&D contract out funds. Conversely, data
with a decreasing trend were: company pollution reduction funds and the number of
R&D company.
4.1.1.3 Technical Assistance and Third Party Treatment
Facilities
According to the publications on the EPA websites, the trend of the number of
technical assistance from 1988 to 2002 is presented in Figure G.12. In the figure, we
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may find that the trend was an increasing trend. As for the number of third party
treatment from 1989 to 1999, the data from the RCRAInfo and RCRIS databases is
illustrated in Figure G.13. The trend was a decreasing trend, though the number in
1989 was relatively small.
Table 4.1 Directions of the General Trends
Increasing Trends Decreasing Trends
BRS Waste Volume BRS Number of Facility
Federal R&D Funds Company R&D Funds Federal Pollution Reduction Funds R&D Performing Company Funds Company R&D Contract Out Funds Company Pollution Reduction Funds The Number of R&D Company
The Number of Technical Assistance
The Number of Third Party Treatment Facility
4.1.2 State Solid and Hazardous Waste Capacity and
Status
As previously mentioned, the rankings of status capacity and status included:
(1) the rankings of waste volume, the rankings of the number of facility, and the
rankings of waste volume per facility, based on BRS data from 1989 to 1999; (2) the
rankings of different R&D funds from 1989 to 2001; and (3) the rankings of the
number of third party treatment facility based on RCRIS data from 1989 to 1999. To
improve the readability, the lengthy tables are listed in Appendix G. The numbers in
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the tables are the averages of certain time span of each state. Also, a negative rate in
the tables indicates waste volume reduce, while a positive rate shows waste volume
increase.
4.2 Hypothesis Testing
To answer the research questions, hypotheses were tested based on the
statistical results. Among the six hypotheses, Hypothesis 1 was confirmed and
Hypotheses 2, 3, 4, 5, and 6 were not confirmed. In the original design, technical
assistance was a contextual variable for H4 to H6. However, due to the limitation of
the data type (time series data, and could not be broken down by state), it was not
included in the hypothesis testing and was put into the section of additional analysis.
The summary of the hypotheses, statistical procedures, and testing results are listed in
the end of this section (Table 4.15).
4.2.1 Descriptive Statistics and Assumption Tests
4.2.1.1 Descriptive Statistics
The descriptive statistics are listed from Table 4.2 to 4.4. Table 4.2 presents
the raw data of BRS database. Table 4.3 demonstrates the descriptive statistics for
nominal variables, which include technology-based standards, fees, permits, SEPs,
and SEPs importance. The table contains the case numbers and percentages of each
and every variable. Table 4.4 shows the descriptive statistics for interval variables,
77


which are RCRIS third party treatment facilities, total R&D funds, and BRS reduction
rates.
Table 4.2 BRS Raw Data Summary
Si tates and Washington I >.C.
Valid Miss mg Total
N Percent N Percent N Percent
89 BRS 43 84.3% 8 15.7% 51 100.0%
91 BRS 48 94.1% 3 5.9% 51 100.0%
93 BRS 48 94.1% 3 5.9% 51 100.0%
95 BRS 46 90.2% 5 9.8% 51 100.0%
97 BRS 45 88.2% 6 11.8% 51 100.0%
99 BRS 44 86.3% 7 13.7% 51 100.0%
Table 4.3 Descriptive Statistics for Nominal Variables
Variable Description N Percent
T echnology-Based Standards No Additional Standards 28 54.9
Additional Standards 23 45.1
Total 51 100
Solid and Hazardous Waste Fees, Wagner No Fees 12 23.5
Partial Fees 11 21.6
Full Fees 28 54.9
Total 51 100
Solid and Hazardous Waste Fees, HTRWCE No Fees 4 7.8
Hazardous Waste Management Fees (HWMFs) 12 23.5
HWMFs but no Direct Treatment or Disposal Fees (DTDFs) 17 33.3
DTDFs 13 25.5
DTDFs that also Specifically Target Out-of-State Waste 5 9.8
Total 51 100
Generator and Transporter Permits No Permits 28 54.9
Partial Permits 18 35.3
Full Permits 5 9.8
Total 51 100
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Table 4.3 (Cont.)
Variable Description N Percent
SEPs No SEPs 9 26.5
SEPs 25 73.5
Total 34 100
SEPs Importance Not a High Priority 13 40.6
High Priority 19 59.4
Total 32 100
Table 4.4 Descriptive Statistics for Interval Variables
Variable Description N and Percent Min. Max. Mean SD
Valid Missing Total
RCRIS Third Party Treatment Facilities 44 86.3% 7 13.7% 51 100% 1 46 6.368939 7.4205304
Total R&D Funds 51 100% 0 0% 51 100% 14.29 27178.57 2530.163 4445.205
BRS Reduction Rate 48 94.1% 3 5.9% 51 100% -.7834 183.0471 9.005025 23.1566688
BRS Pre Rate 48 94.1% 3 5.9% 51 100% -.7834 229.8129 13.447841 38.0745760
BRS Post Rate 45 88.2% 6 11.8% 51 100% -.4321 57.1838 1.707168 8.5474093
4.2.1.2 Assumption Tests
Also, to ensure sound statistical results, data must meet certain assumptions.
The major assumption for independent-samples t-tests and one-way ANOVA is
homogeneity of variance the variance within each of the populations is equal. For
regression analysis, the major assumptions are homoscedasticity and
multicollinearity. The former indicates that all observations have constant (equal)
79


variances, while the latter requires no exact linear relation exists between any subset
of explanatory variables.
The results of Levenes test of homogeneity of variance for t-test statistics
(F=12.591, p=.001) suggested that the homogeneity assumption was not met.
Therefore, the statistics in the row labeled Equal variances not assumed should be
used for hypothesis testing (Table 4.10.2). However, as can be seen in the table, the
hypothesis testing results were the same (significant) with or without assuming equal
variances. Consequently, we may safely say that even if the assumption was violated,
it was not drastically affecting the results.
For one-way ANOVA statistics, the results of Welchs tests suggested that the
assumption was not violated. The testing results for the fee systems were: Wagners
system (Welch statistic = 2.282, p=.141) and HTRWCEs system (Welch statistic =
665, p=.637). For Wagners permit system, the results were: Welch statistic = 2.639,
p=.088. Since the null hypothesis of the tests could not be rejected, it indicated that
the assumption of equal variance was met.
As for the assumptions for regression statistics, the results also suggested that
they were not violated. As showed in Table 4.5 and Table 4.6, the p-values of the
variables in the heteroscedasticity test were greater than .05. Therefore, the results
resumed homoscedasticity. The collinearity tests revealed a similar result. As can be
seen from Table 4.7 and Table 4.8, the values of the variance-inflation factor (VIF)
were less than 4 (VIF>=4 is an arbitrary but common cut-of criterion). This indicated
80


that multicolinearity was not a problem. Accordingly, based on the assumption tests
above, we may argue that the statistical results of hypothesis testing in this study were
valid.
Table 4.5 Heteroscedasticity-Consistent Regression Results, Wagners Fee System
Coeff SE(HC) t P>|t|
Constant 34.2867 18.4592 1.8574 .0714
T echnology-Based Standards -9.4302 6.8167 -1.3834 .1751
Fees (Wagner) -7.3205 7.0890 -1.0326 .3087
Permits -9.1226 6.7929 -1.3430 .1877
SEPs 6.3551 9.7830 .6496 .5201
SEPs Importance -21.1494 16.1566 -1.3090 .1988
RCRIS Third Party Treatment Facilities -.2355 1.2682 -.1857 .8537
Total R&D .0004 .0008 .4617 .6471
Table 4.6 Heteroscedasticity-Consistent Regression Results, HTRWCEs Fee System
Coeff SE(HC) t P>|t|
Constant 36.8162 23.3568 1.5763 .1237
T echnology-Based Standards -9.5042 7.2008 -1.3199 .1952
Fees (HTRWCE) -5.2433 6.5172 -.8045 .4264
Permits -7.9100 6.4043 -1.2351 .2248
SEPs 3.3546 10.1038 .3320 .7418
SEPs Importance -19.6392 15.8681 -1.2376 .2239
RCRIS Third Party Treatment Facilities -.3892 1.4461 -.2691 .7894
Total R&D .0004 .0008 .5586 .5799
81


Table 4.7 Multicollinearity Test Results, Wagners Fee System
Predictors Collinearity Statistics
Tolerance VIF
T echnology-Based Standards .923 1.083
Fees .843 1.186
Permits .826 1.210
SEPs .784 1.275
SEPs Importance .863 1.159
RCRIS Third Party Treatment Facilities .848 1.179
Total R&D .756 1.323
Table 4.8 Multicollinearity Test Results, HTRWCEs Fee System
Predictors Collinearity Statistics
Tolerance VIF
Technology-Based Standards .919 1.088
Fees .841 1.190
Permits .818 1.222
SEPs .848 1.179
SEPs Importance .804 1.243
RCRIS Third Party Treatment Facilities .850 1.177
Total R&D .765 1.307
4.2.2 Hypothesis 1
HI: The governments stringent technology-based standards will promote the
reduction of solid and hazardous waste.
82


Full Text

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STATE GOVERNMENTS' PERFORMANCE AND EFFECTIVENESS IN REDUCING SOLID AND HAZARDOUS WASTE UNDER THE RESOURCE CONSERVATION AND RECOVERY ACT (RCRA): A STUDY OF THE CHEMICAL INDUSTRY by Chun-Mai Michael Kuo B.A., Tunghai University, Taichung, Taiwan, R.O.C., 1987 M.A., Tunghai University, Taichung, Taiwan, R.O.C., 1990 M.P .A., Syracuse University, 1995 M.P.A. University of Southern California, 1998 A thesis submitted to the University of Colorado at Denver and Health Sciences Center in partial fulfillment of the requirements for the degree of Doctor of Philosophy Public Affairs 2005

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by Chun-Mai Michael Kuo All rights reserved.

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This thesis for the Doctor of Philosophy degree by Chun-Mai Michael Kuo has been approved by Jae Moon Date

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Kuo, Chun-Mai Michael (Ph.D., Public Affairs) State Governments' Performance and Effectiveness in Reducing Solid and Hazardous Waste under the Resource Conservation and Recovery Act (RCRA): A Study of the Chemical Industry Thesis directed by Professor Lloyd Burton ABSTRACT The main purpose of the study was to investigate the performance and effectiveness of the regulatory tools adopted by the states in reducing solid and hazardous waste. According to the Resource Conservation and Recovery Act (RCRA), states are allowed to enact and enforce provisions that are more stringent and/or broader in scope than the federally approved program. Based on this regulatory background, two research questions were addressed: First, what state level RCRA implementation strategies seem to be most closely associated with the greatest reduction of solid and hazardous waste in the chemical industry? Second, what contextual variables, in addition to the regulations, would affect the reduction of solid and hazardous waste? To answer these questions, longitudinal waste-related data (1988 to 2002), the status of state chemical industry, and the survey results of states' regulatory choices were obtained from various sources. In this research, waste reduction was operationalized as the rate of reduction to account for possible growth in the chemical industry in a given state as a confounding variable. The research results suggested lV

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that: First, technology-based standards, waste fees, and permits may not be considered as effective regulatory tools to reduce solid and hazardous waste. However, compared to other contextual variables, they still had higher effects on waste reduction. Second, the RCRA Supplemental Environmental Projects (SEPs) were the only effective predictor among the variables towards waste reduction. Suggestions were made according to these findings. First, governments need to remain using technology-based standards as the foundation of the RCRA. Second, states need to modify and revise their current fee and permit systems in order to help reduce waste. Third, the importance of the SEPs needs to be recognized by the states and be utilized as an effective regulatory tool to further reduce waste. Finally, states need to adopt a contextual approach that flexibly tackles their certain waste issues. Together, these suggestions may help address the concerns of public safety, people's right-to-know, and national security threat posed by the possibility of industrial sabotage. This abstract accurately represents the contest of the candidate's thesis. I recommend its publication. Signed v

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ACKNOWLEDGEMENTS I would like to offer my deepest appreciations to many people for helping me and guiding me during the process of my dissertation writing. First of all, I would like to thank my dissertation chair, Dr. Lloyd Burton, for his generous time, support, and encouragement. I also want to thank him particularly for many thought provoking comments relating to the regulatory background and policy applications. Also, I am very thankful to have an outstanding dissertation committee. I really appreciate Dr. George Busenberg, Dr. Bruce Kirschner, and Dr. Jae Moon for their detailed comments and suggestions that stimulated me to enhance the level of my analytical and research skills. In addition, I wish to thank Ms. Kendra Morrison for helping me obtain the research data. Without those detailed data and information, I would not be able to conduct the analyses. My thanks also go to my cohorts Dr. Chul-yong Roh and Dr. Seong-Gin Moon for their help and encouragement during the years of my study in the doctoral program. Further, I would like to thank Dr. Andy Hong and Dr. Marcel Pidoux for editing and revising my dissertation. Four people deserve my special thanks: my parents-in-law Mr. Ta-Chung Wang and Mrs. Chia-Li Wang and my close friends Dr. Rabi Wang and Mrs. Nina

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Wang. They have been a great help to my family during the last stage of my dissertation writing. Finally, I am highly grateful for the love and assistance from my family members. My parents Mr. Tung-Huan Kuo and Mrs. I-Chung Kuo have always encouraged me to aim for the highest academic achievement. They have also continually provided financial support to me and help me achieve the goals. I want to thank my brother Dr. Chun-Fang Kuo and my sister Mrs. Hui-Chun Cheng for guiding me to cope with tension and pressure based on their specialties. Additionally, my earnest appreciation goes to my dearest wife Ai-Ling and my son Joshua. Without their continued support, prayers, and sharing, this dissertation would not be finished. In the end, I submit my highest praise to my Heavenly Father for all the things and blessings He has given to me.

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CONTENTS Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..... x1v Tables................................................................................... xv Chapter 1. Introduction ........................................................................ 2. Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1 Technology-Based Standards: A Brief History............................... 6 2.1.1 Nineteenth and Early Twentieth Century.................................... 6 2.1.2 MidTwentieth Century and Later . . . . . . . . . . . . . . . . . . . . . 9 2.2 The Rationale for Technology-Based Standards.............................. 13 2.2.1 Maintenance of Fundamental Health Requirements . . . . . . . . . . . 13 2.2.2 Consideration of Differences among Industries . . . . . . . . . . . . . . 14 2.2.3 Impartiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.4 Low Costs . . . . . . . . . . . . . . . . . . . . . . . . . .......................... 15 2.2.5 Technology Innovation . . . . . . . . . . . . . .. . . . . . . . . . . . . . 15 2.2.6 Public Involvement and Normative Considerations . . . . . . . . . . .. 16 2.2.7 The Moral Imperative......................................................... 17 2.3 Technology-Based Standards: The Foundation of RCRA . . . . . . . . . 18 Vlll

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203 01 Defining Technology-Based Standards 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o ooooooooo 18 203.2 Types of Technology-Based Standards ooo o oooooooooooooooo 20 2.4 State Authorization ... 0 0 0 0. 0 0. 0 0. 0 0. 0 0. 0 0 0 0 0 0. 0 0 0 0 0 0 0 0 0 22 2.401 States with Different Programs 0 0 0 0 0 0 . 0. 0 0. 0 0. 0 0. oooooooooooooo 22 2.4.2 RCRA Supplemental Environmental Projects (SEPs) 0 0. 0 000000000000000000 27 205 Alternative Regulatory Tools 0 0 0. 0 0. 0. 0 0 0 0 0. 0 0 0 0 0. 0 0. 0 0. 0 0 0 0 0 0 0 0 0 0 30 205.1 Hazardous Waste Fees oo ooo o.o o o.o o o. 0 o 0 0 o. o o. o 0 0 0000 30 2.5.2 Penalties o. 0 0. 0 0. 0 0 0 0 0. 0. 0 0 0 0 0 0 0. 0 0 0 0. 0 0. 0 0. 0 0 0 0 0 0 0 0. 0 0. 0 0. 0 0 0 0 0 31 20503 Permits 0 0 0 0 0 0 0 0 0 0 0 0 0 0. 0 0. 0 0 0 0 0 0 0 0 0. 0 0. 0 0. 0 0 0 0 0 0 0 0 0 0 0. 0 0. 0 0 0 0. 0 0 0 0 0 0 32 205.4 Subsidies ... 0 0 0 0 0 0 0 0 0. 0 0. 0 0. 0 0. 0 0 0 0 0 0 0 0 0 0 0 0 0 0. 00 34 205.5 Voluntary and Partnership Programs o o o 0 0 0 o. o 0 o 0. o 34 2.6 Conflicting Research Findings .... 0. 0 0. 0 0 0 0 0 0 ooooooooooooooooo 35 2.601 ProTechnology/Command and Control Approaches ....... 0 0. 0 0. 0. 0. 0. 36 20601.1 Theoretical Arguments 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0. 0. 0 36 2.6.1.2 Empirical and Case Studies 0 0 0 .. 0 0 0 0. 0 0. 0. 0. 39 2.602 Pro-Economic Approaches 0 0 0 0 0. 0 0 0 0 0 0. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 43 206.2.1 Theoretical Arguments 0 . 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 . 0 . 0 . 0 . 0 0 0 0 0 0 0 0 0 0 0. 0 0 0 0 0 0 43 2.6.2.2 Empirical and Case Studies 0 0 0 0 0 0. 0 0. 0 0. 0 0 0 0 0 0 52 2.603 RCRA Related Policy Studies 0. 0 0. 0 0 0 0 0 0. 0 0 0 0. 0. 0 0. 0 0. 0 0. 0 0 0 0. 0 0 ooo... 55 30 Research Design 0 ooo oo ooo ooo ooo o o o o o o.o 58 lX

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3.1 Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 3.1.1 Technology-Based Standards................................................. 58 3.1.2 Hazardous Waste Fees............................................................. 60 3.1.3 Permits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3 .1.4 Other Contextual Variables . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.2 Research Data..................................................................... 63 3.2.1 Industry Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 63 3 .2.2 Data and Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 3.2.2.1 Solid and Hazardous Waste................................................ 63 3.2.2.2 Regulatory Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.2.2.3 Contextual Variables . . . . . . . . . . . . . . . . . . . . . . . . .. . .. 66 3.2.3 Data Measurements............................................................ 68 3.3 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4. Results and Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 73 4.1 General Trends and State Solid and Hazardous Waste Status ... ............ 73 4.1.1 General Trends . . . . . . . . . . . . . . . . . . . . . . . . . .................... 74 4.1.1.1 BRS Waste Volumes and Number of Facility from 1989 to 1999 . .. 74 4.1.1.2 R&D Funds from 1989 to 2001 .................................................. 75 4.1.1.3 Technical Assistance and Third Party Treatment Facilities . . . . . . 75 4.1.2 State Solid and Hazardous Waste Capacity and Status........................ 76 X

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4.2 Hypothesis Testing................................................................ 77 4.2.1 Descriptive Statistics and Assumption Tests . . . . . . . ..................... 77 4.2.1.1 Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 77 4.2.1.2 Assumption Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.2.2 Hypothesis 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . ................... 82 4.2.3 Hypothesis 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 84 4.2.4 Hypothesis 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 85 4.2.5 Hypotheses 4 to 6 . . . . . . . . . . . . . . . . . . . . . . . . ................... 86 4.2.6 Summary of Hypothesis Testing Results.................................... 89 4.3 Additional Analysis . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . .. 90 4.3.1 State Chemical Industry Capacity and Performance . . . . . . . . . . ... 90 4.3 .1.1 Correlations between Variables . . . . . . . . . . . . .......................... 90 4.3.2 Trends Data..................................................................... 92 4.3 .2.1 Correlations between Variables . . . . . . . . . . . . .. .. .. .. .. . .. .. . .. ... 93 4.3.2.2 Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4.3.3 Other Additional Statistical Analyses and Summary..................... 96 5. Discussion, Conclusions and Policy Recommendations..................... 97 5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.1.1 Hypothesis 1: Technology-Based Standards . . . . . . . . . . . . . . . .. 97 5.1.2 Hypothesis 2: Solid and Hazardous Waste Fees........................... 98 XI

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5.1.2.1 Reasons for the Failure to Confirm the Hypothesis . . . . . . . . . . 99 5.1.3 Hypothesis 3: Generator and Transporter Permits......................... 101 5.1.3.1 Reasons for the Failure to Confirm the Hypothesis . . . . . . . . . . 102 5.1.4 Hypotheses 4 to 6: Regulatory Tools and Contextual Variables......... 103 5.1.4.1 The Relative Magnitude and Direction ofthe Regulatory Tools . . . 104 5.1.4.2 The Importance ofthe RCRA SEPs ....................................... 105 5 .1.5 National Trends, State Status, and Additional Analysis . . . . . . . . . 1 06 5.2 Conclusions and Recommendations............................................ 108 5.2.1 Recognize the Policy Context . . . . . . . . . . . . . . . . . . . . . . . . 109 5.2.2 Strengthen Technology-Based Standards................................... 110 5.2.3 Modify and Improve the Solid and Hazardous Waste Fee Systems..... Ill 5.2.4 Modify and Improve the Permit Systems.................................... 113 5.2.5 Recognize the Importance of the SEPs and Other Factors................ 114 5.2.6 Towards a Contextual Approach for Solid and Hazardous Waste Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 5.3 Contributions . . . . . . . . . . . . . . . . . ..... . . . . . . . . . . . . . . . 119 5.3.1 To Academia . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 119 5.3.2 To State Implementing Agencies and the EPA............................. 120 5.3.3 To the National Security...................................................... 120 5.4 Limitations and Future Studies . . . . . . . . . . . . . . . . . . . . . . . . 122 Xll

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Appendix A. RCRA Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 123 A.l Solid Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 A.2 Hazardous Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 124 B. Case Studies of Hazardous Waste Reduction.................................. 126 C. Market-Based Environmental Policies . . . . . . . . . . . . . . . . . . . .. 135 D. SIC and NAICS Correspondence Tables . . . . . . . . . . . . . . . . . . .. 144 E. State Hazardous Waste Fee I Tax Systems..................................... 155 F. Variables Description and Data Conversion..................................... 174 F .1 Data Conversion Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7 5 F .1.1 Data Collection and Data Type . . . . . . . . . . . . . . . . . . . . . . .. 17 5 F.1.2 Data Conversion................................................................ 175 G. General Trends and State Status................................................ 177 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 189 Xlll

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FIGURES Figure 5.1 The Interactions among Major Groups of Solid and Hazardous Waste .. ... 11 0 G.1 BRS Waste Volumes (tons) by Year............................................. 177 G.2 BRS Number of Facility by Year .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 178 G.3 Federal R&D Funds in Millions of Dollars..................................... 178 G.4 Company R&D Funds in Millions of Dollars.................................. 179 G.5 Federal and Company R&D Funds Comparison . . . . . . . . . . . . . . . 179 G.6 Federal Pollution Reduction Funds in Millions of Dollars................... 180 G.7 Company Pollution Reduction Funds in Millions ofDollars ................ 180 G.8 Federal and Company Pollution Reduction Funds Comparison............ 181 G.9 R&D Performing Company R&D Funds in Millions of Dollars............ 181 G .1 0 R&D Contract Out Funds in Millions of Dollars .. .. .. .. .. .. .. .. .. .. .. .. 182 G.11 Number ofR&D Company in Chemical Industry........................... 182 G.12 Number ofTechnical Assistance from the EPA............................... 183 G.l3 Number of Third Party Treatment Facilities . . . . . . . . . . . . . . . . . 183 XIV

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TABLES Table 2.1 Summary of State Hazardous Waste Management Programs . . . . . . ... 23 2.2 State Hazardous Waste Fee and Tax Systems................................ 27 2.3 Procedure, Guidance, or Rules for SEPs . . . . . . . . . . . . . . . . . . .. 28 2.4 SEPs are a Higher Priority than Other Pollution Prevention!W aste Minimization Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . ... 29 2.5 Incentives for Innovation under Various Pollution Control Arrangements . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . ... .. . . 44 2.6 Emissions Levels under Various Pollution Control Arrangements.......... 45 2.7 Summary of Relative Rankings of the Incentives to Promote Technological Change in Pollution Control and the Attitude Towards Optimal Agency Response . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.1 Research Data and Sources . . . . . . . . . . . . . . . . . . . . . . . . . .. 67 3.2 Variable Type and Description................................................. 70 4.1 Directions of the General Trends ... . . . . . . . . . . . . . . . . .. . ....... 76 4.2 BRS Raw Data Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 78 4.3 Descriptive Statistics for Nominal Variables . . . . . . . . . . . . . . . . 78 4.4 Descriptive Statistics for Interval Variables .. .. . . . . . . . . . . . . . .. 79 4.5 Heteroscedasticity-Consistent Regression Results, Wagner's Fee System................................................................................. 81 4.6 Heteroscedasticity-Consistent Regression Results, HTRWCE's Fee System............................................................................. 81 XV

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4.7 Multicollinearity Test Results, Wagner's Fee System . . . . . . . . . . .. 82 4.8 Multicollinearity Test Results, HTRWCE's Fee System.................... 82 4.9 Hypothesis 1 Paired Samples TTest Results, State Reduction Rate Differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. .. ... .. .. 83 4.1 0.1 Hypothesis 1 Independent-Samples TTest Results, Additional Hazardous Waste Standards.................................................. 84 4.1 0.2 Hypothesis 1 Independent-Samples TTest Results, Additional Hazardous Waste Standards ............................................... 84 4.11.1 Hypothesis 2 OneWay ANOV A Results, Average Reduction Rates of States with Different Hazardous Waste Fees, Wagner's Fee System 85 4.11.2 Hypothesis 2 OneWay ANOV A Results, Average Reduction Rates of States with Different Hazardous Waste Fees, HTRWCE's Fee System........................................................................... 85 4.12 Hypothesis 3 OneWay ANOV A Results, Average Reduction Rates of States with Different Permit Systems ....................................... .. 86 4.13.1 Hypothesis 4 to 6 Multiple Regression Results, ANOVA (b), Based on BRS Data and Wagner's Fee System.................................... 88 4.13.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a), Based on BRS Data and Wagner's Fee System ................................ .. 4.14.1 Hypothesis 4 to 6 Multiple Regression Results, ANOVA (b), Based on BRS Data and HTRWCE's Fee System ............................... 4.14.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a), Based on BRS Data and HTRWCE's Fee System ....................... 4.15 Summary ofHypothesis Testing Results ................................... 4.16 Pearson Correlations, BRS Data and State Data ........................... 4.17 Pearson Correlations, BRS Data and National Data ....................... 4.18 Regression Results, Coefficients (a), BRS Waste Reduction Rate ........ XVI 88 88 89 89 91 93 95

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4.19 Regression Results, Coefficients (a), BRS Waste Volume.................. 95 5.1 State Hazardous Waste Fee Systems Comparison ........................... .. 5.2 Standardized and Unstandardized Coefficients from Table 4.13 and 4.14 5.3 .I Rankings of Solid and Hazardous Waste Reduction Performance, Wagner's Fee System ........................................................ 5.3.2 Rankings of Solid and Hazardous Waste Reduction Performance, Wagner's Fee System, Recoded ............................................. .. 5.4.1 Rankings of Solid and Hazardous Waste Reduction Performance, HTRWCE's Fee System .................................................... .. 5.4.2 Rankings of Solid and Hazardous Waste Reduction Performance, HTRWCE's Fee System, Recoded ........................................ .. 5.5.1 Rankings of Solid and Hazardous Waste Reduction Performance, Permits ............................................................................................... 5.5.2 Rankings of Solid and Hazardous Waste Reduction Performance, Permits, Recoded .............................................................. .. 5.6 Rankings of Solid and Hazardous Waste Reduction Performance, SEPs Importance ......................................................................... .. B. I Hazardous Waste Reduction Cases ........................................... C. I Major Federal Tradable Permit Systems .................................... C.2 Deposit-Refund Systems ...................................................... C.3 Federal User Charges ......................................................... .. C.4 Federal Insurance Premium Taxes ........................................... .. C.5 Federal Sales Taxes ............................................................ C.6 Administrative Charges ........................................................ C. 7 Federal Tax Differentiation .................................................... xvn 100 105 117 117 117 118 118 119 119 126 135 136 138 139 140 140 141

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C.8 Federal Information Programs................................................. 142 D.1 1987 SIC and 1997 NAICS Correspondence Table......................... 144 D.2 1987 SIC and 2002 NAICS Correspondence Table......................... 149 E.l State Hazardous Waste Fee I Tax Systems................................... 155 F.1 Trends Data....................................................................... 174 G.1 Rankings of State Capacity and Status, BRS Data from 1989 to 1999 . 184 G.2 Rankings of R&D Funds by State, from 1989 to 2001 ... .. .... ...... .. .. 186 G.3 Rankings of the Average Number of the Third Party Treatment Facilities by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 XVlll

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1. Introduction At the outset of the modem environmental movement in the 1970s, the United States launched a series of regulatory reforms on environmental laws and regulations. One of the new regulatory regimes was the Resource Conservation and Recovery Act (RCRA, 42 U.S.C. -6992(k), 1976). RCRA empowered the Environmental Protection Agency (EPA) to regulate the disposal of solid and hazardous waste in the United States. Its purpose was to promote the protection of health and the environment, and to conserve valuable materials and resources. By taking the same regulatory approach as the Clean Air Act Amendments (CAA, 42 U.S.C. et seq., 1970) and the Clean Water Act (CWA, 33 U.S.C. et seq., 1972), RCRA established technology-based standards for the accumulation, transportation, storage, treatment, and disposal of solid and hazardous waste. Technology-based standards are one of the primary regulatory tools to control pollution entering surface waters, the atmosphere, public drinking water supplies, workplaces, and the land. Their purpose is to regulate the pollution control technology employed by major emitters ofthe regulated pollutants (for detailed definition, please refer to section 2.3 .1 ). Scholars argue that technology-based standards are an effective regulatory tool to maintain the fundamental health requirements. The technology-based standards have the advantage ofbeing impartial, 1

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less expensive, taking into account the differences among industries, promoting technology innovation, encouraging public involvement, and allowing for strong normative and moral considerations (Andrews, 1994; Cairncross, 1992; Davies and Mazurek, 1996; Heaton and Banks, 1998; Marcus and Weber, 1989; Mitnick, 1981; Meyer, 1982; Norberg-Bohm, 1999; Shapiro and McGarity, 1991; Shrivastava, 1995; and Wagner, 2000). While the rationale for technology-based standards is appreciated by some scholars, other voices are equally sound, which mainly come from the economic approach of policy making. The latter argues that technology-based standards are actually laborand information-intensive for regulators. The standards setting procedure not only is costly and time-consuming, the technologies chosen are often not the most proper ones to address the pollution issues. Moreover, the sizable compliance costs would hamper a company's R&D efforts. Instead, economic approaches such as pollution fees, taxes, tradable permits, and subsides can resolve pollution problems in a less expensive and more effective manner (Allenby, 2000; Caves, 1982; Eggers, Villani, and Andrews, 2000; Downing and White, 1986; Guttmann, Sierck, and Friedland, 1992; John and Mlay 1999; Kemp, 1997; Magat, 1978; Milliman and Prince, 1989; Rabe, 1986; Scherer and Ross, 1990; and Wender, 1975). Fortunately, RCRA seems to take a flexible stance that allows states to design different programs to meet their needs. In other words, a state with authorization may 2

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have a program that is more stringent and/or broader in scope than the federal program. States therefore have certain discretion in choosing different regulatory tools such as economic approaches to address their own solid and hazardous waste issues. More explicitly, in addition to technology-based standards established by the EPA, states may adopt more stringent standards, regulate additional wastes as RCRA wastes, utilize regulatory tools such as hazardous waste fees and generator or transporter permits (40 CFR 271.l(i)); RCRA (a)(2); Wagner, 1999). Unfortunately, most studies tackling the relationship between regulatory tools and pollution reduction were done in air and water pollution fields. Not much research has been done in the field of solid and hazardous waste control. Moreover, most of those studies were conducted at the firm level. Related research at the state level is fairly scant. With the unique and flexible regulatory background and the controversy in terms of the relative capabilities between command-and-control regulations (technology-based standards) and economic approaches in reducing pollution, it would be interesting to answer the following questions: First, what state level RCRA implementation strategies seem to be most closely associated with the greatest reduction of solid and hazardous waste in the industry studied? Second, what contextual variables, in addition to the regulations, would affect the reduction of solid and hazardous waste? 3

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Following the first question, three hypotheses are proposed: 1. The government's stringent technology-based standards will promote the reduction of solid and hazardous waste. 2. There will be significant differences in the performance of solid and hazardous waste reduction among the states that utilize different hazardous waste fee systems. 3. There will be significant differences in the performance of solid and hazardous waste reduction among the states that issue, partially issue, and no issue permits to generators and transporters. Also, based on the second question, it is further hypothesized that: 4. Technology-based standards are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. 5. Hazardous waste fees are more likely to have higher stronger on the reduction of solid and hazardous waste than other contextual variables. 6. Permits are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. In this research, I focused on the chemical industry. From a toxic and hazardous emissions point of view, the chemical industry was regarded as the most critical industry because it accounted for almost half of the total emissions for all industries in this country (Dooley and Fryxell, 1999). By testing the stated hypotheses, this research aimed to obtain a better understanding of the relative performance of regulatory tools in reducing solid and hazardous waste in the chemical industry; to identify important contextual variables relating to solid and hazardous waste reduction; to enrich the research field in solid and hazardous waste control; to provide constructive suggestions and recommendations for the state governments to design the programs that best meet their needs in reducing solid and hazardous waste; and to help address the concerns of public safety, people's right-to4

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know, and national security threats posed by the possibility of industrial sabotage. 5

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2. Literature Review Technology-based standards are a unique approach to control environmental pollution. They aim to provide incentives for polluters to create and invent innovative technologies and to reduce pollution. In the past three decades, technology-based standards have been mainly used in the field of water and air pollution control. However, in more recent years, technology-based standards have been adopted in the area of solid and hazardous waste control. In the following sections, I discuss the regulatory background and the rationale and definition of technology-based standards. I also discuss the major regulatory alternatives adopted by some of the state governments. As for the theoretical and empirical findings, most of the findings are borrowed from the fields of air and water pollution control, this is due to limited research done in the field of solid and hazardous waste, 2.1 Technology-Based Standards: A Brief History 2.1.1 Nineteenth and Early Twentieth Century Environmental pollution is an age-old problem. When the brilliant Frenchman, de Tocqueville, traveled to America in the 1830s, he described what he saw with surprise: 6

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The American people see themselves marching through wildernesses, drying up marshes, diverting rivers, peopling the wilds, and subduing nature (de Tocqueville, 1988 [1835], p.485). Ever since, dominant American value and ethic towards the environment, namely utilitarianism, did not seem to have changed from the era of industrial revolution in the mid and late 19th century to the period between the two world wars. Western exploration and industrial development seemed to be the major social and economic activities of this country. Nevertheless, pollution had become a concern in this country since the 1840s and 1850s. Initially, pollution control came about through the courts in the form of nuisance law. People in states then being industrialized such as New Jersey, New York, and Pennsylvania had sensed the problems of air pollution such as the smoke and acrid fumes emitted from neighboring brick factories (Campbell v. Seaman, 63 N.Y. 568,20 Am. Rep. 567 (1876)). Moreover, the importance of technology to control pollution had begun to be noticed by the judges of these states. For example, in New York and New Jersey, judges ordered the fat-boiling industry to reduce their stench nuisances (Westheimer v. Schultz, 33 How. Prac. 11 (1866)); a cheese business to stop dumping wastes from their hog pen, slaughterhouse, and cheese factory into a stream (Davis v. Lambertson, 56 Barb. 480 (1868)); an electric power company to stop overloading a power plant so as to reduce noise and vibration (Braender v. Harlem Lighting Co., 2 N.Y. Supp. 245 (1888)); and a printing and bookbinding company to move its steam boiler and 7

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printing presses to another location in order to stop the noise and vibration that were disturbing a harness manufacturer next to it (Demarest v. Hardham, 34 N.J.Eq. (7 Stew.) 469 (1881 )). In those cases, judges argued that it was well within the power and financial capability of the defendants to install (new) technology to control pollution without shutting down their factories (Rosen, 1998). Technology seemed to be playing an increasingly important role in pollution control by the beginning of the twentieth century. In Georgia v. Tennessee Copper Co. (206 US 230 (1907)), at issue was the sulphurous acid gas emitted from the smelters in Tennessee that drifted into Georgia and caused damage. To resolve this case, Justice Oliver Wendell Holmes adopted a mixture of an air quality-based approach and a technology-forcing approach to give the defendants a reasonable amount of time to install treatment facilities. However, the situation was not being remedied and the case was again brought to the Supreme Court. In their ruling, the Court admitted that they set out specific emission limits without regard to the technological feasibility of said limits (Georgia v. Tennessee Copper Co. (23 7 US 678 (1915)). In New York v. New Jersey (256 US 296 (1921)), New York filed suit against New Jersey and the Passaic Valley Sewerage Conunissioners to enjoin the execution of a project to convey the sewage of the Passaic Valley through a sewer system, and to discharge it into a part ofNew York Harbor. The Supreme Court declined to enjoin New Jersey. However, the Court ordered New Jersey to make more efforts 8

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than New York in terms of pollution control. During that time, New York was planning to use a certain water pollution control technology. The Court adopted a technological feasibility approach that asked New Jersey not only to base its sewage treatment obligations on New York's technology, but utilize other certain technologies required by the federal government to minimize the pollutants. 2.1.2 MidTwentieth Century and Later The mid-twentieth century was a turning point for environmental protection. Beginning in the 1950s, issues such as the loss of wilderness, the nuclear arms race and the related wastes, and a variety of air and water pollution problems forced Americans to reconsider the importance of environmental protection (Meine, 1995). The concerns for environmental quality surfaced dramatically in 1962 when Rachel Carson published Silent Spring, which gave rise to the modem environmental movement. During this new wave of environmental protection, again, the importance of technology on pollution control was apparent. In Oregon, the owner of an aluminum plant was sued by several neighboring orchard owners who claimed that their crops had been damaged by fluorine emissions (Renken v. Harvey Aluminum, (Inc.) (226 F. Supp. 169 (1963)). Finding pollution to be a continuing trespass and a nuisance, the district court awarded the orchard owners approximately ten thousand dollars each in damages. Moreover, the court decided on a technology-based approach to control the source of pollution. Namely, it looked at 9

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what technology was available and ordered the plant to install state-of-the-art emission control equipment. Boomer v. Atlantic Cement Co. (26 N.Y.2d 219 (1970)) was another nuisance legal case pertaining to dirt, smoke, and vibration pollution caused by a cement plant. As opposed to the previous case, the court refused to order the use of specific control technologies because of economic considerations. The New York Court of Appeals decided that a technology-based cost-benefit analysis was appropriate and sufficient to determine what amount of pollution control should be implemented. Meanwhile, the court ordered the plant to compensate the land owners for the damages caused. In this case, Judge Jasen agreed with the majority that a reversal was required. However, he took a technology-forcing approach in his dissent and argued that pollution must be reduced to a certain level within a certain period of time (18 months in this case) regardless of the current technological feasibility and costs. In doing so, it could force the development of technology to resolve the problem. While common law provides the foundation of modem environmental law and continues to be an influential and significant part of environmental practice, the federal and state courts in general are reluctant to delve deeply into the field of pollution control through judicial decree. They seem to believe that the scientific complexity of many cases could be better handled by the administrative agency with expertise in certain areas (Meiners and Yandle, 1998; Percival and Alevizatos, 2000; Plater, Abrams, and Goldfarb, 1998; The Wildlaw, 2005). 10

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However, pollution control legislation seemed to be taking a course of slow evolution and had little impact on environmental degradation until the modern scheme was enacted. The first law applicable to water pollution was the Refuse Act (33 U.S.C.A. ff (1899)). Nonetheless, its major concern was with navigation. If pollution did not interfere with navigation, it was not addressed. Also, this law did not contain any water quality standards, permit frameworks, or any clear distinctions between federal and state responsibilities. Actually, this law was not applied to pollution control until the 1960s. In 1948, the Federal Water Pollution Control Act (33 U.S.C. -1376) was passed. It granted the federal government authority to do research and investigate water pollution issues. However, again, it did not address any means to set and enforce pollution standards. Nevertheless, this law was amended in 1956, and allowed for states to set pollution standards. By taking a more stringent stance, the Water Quality Act of 1965 required states to set and enforce quality standards. In air pollution control, the 1955 Air Pollution Act was the first federal legislation that attempted to control air pollution at its source. However, it did very little to prevent air pollution, but simply provided research and technical assistance to address the issues at the national level. Taking a step ahead, the Clean Air Act of 1963 started to set up air quality criteria. Yet, it focused only on interstate pollutions. The legislative effort to set out modern scheme of air quality control was the 1967 Air Quality Standards Act. Nevertheless, its air quality criteria only adopted some 11

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technology-based considerations and did not concern with technological feasibility. Moreover, its implementation plans were set up by states, and the states could determine whether the recommended technology was necessary to meet the standards. Fortunately, the regulatory philosophy started to change in the 1970s. In 1972, the Water Pollution Control Act was amended again and became the foundation ofthe Clean Water Act (CWA, 33 U.S.C. et seq., 1972). It required the federal government to set technology-based effluent standards along with federal enforcement provisions. Those standards were set as "best practicable control technology currently available" (BPT) initially, and later enforced as "best available technology economically achievable" (BAT) (Harrington and Krupnick, 1981; Olson, 2005). More specifically, BPT is the "average of the best" existing treatment performance, which considers "the total cost of application of technology in relation to the effluent reduction benefits to be achieved from such application." BAT, on the other hand, is defined as the best existing technology performance in an industry category, "taking into account the ... cost of achieving" said performance (CW A, 33 u.s.c. (b), 1989). A similar approach was adopted in the field of air pollution control. When Congress enacted the Clean Air Act Amendments (CAA, 42 U.S.C. et seq., 1970), it opted for an environmental quality approach and called for the EPA to set air quality standards for the pollutants. The law required the industries to limit their discharges to meet the standards regardless of what level of technology was needed. 12

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However, in view of the success of the Clean Water Act, Congress substantially amended the Clean Air Act in 1990 and changed it to a more technology-based legislation. With the early success of controlling air and water pollution by these two acts, a series of technology-related regulatory reforms was triggered to further protect the environment. Two of them were the focus of this research, namely, the Resource Conservation and Recovery Act (RCRA, 42 U .S.C. 1-6992(k), 1976) and the Hazardous and Solid Waste Amendments (HSWA, 1984). 2.2 The Rationale for Technology-Based Standards While the main tools of policy making in many fields are economic instruments, scholars have argued that these instruments cannot capture the essence of environmental pollution problems and should be considered as a secondary approach of pollution control. On the contrary, technology-based standards offer a better environmental control mechanism and should serve as the foundation of environmental regulation (Andrews, 1994; Davies and Mazurek, 1996; Heaton and Banks, 1998; Shapiro and McGarity 1991; Wagner, 2000). The rationale of this approach is as follows. 2.2.1 Maintenance of Fundamental Health Requirements Technology-based standards establish fundamental requirements that guarantee the basic health of the general public. By setting up specific environmental standards, polluters are forced to reduce their pollution volumes. In tum, the quality of the 13

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environment can be controlled and the risk and hann toward human health can be reduced to an acceptable level. 2.2.2 Consideration of Differences among Industries Previous technology-based approaches were severely criticized as "wildly inefficient," because they ignored the enormous difference among facilities and industries by setting up unified standards (Sunstein, 1991 ). However, studies indicate that technology-based systems do not operate in a blind manner. Agencies do not ignore the types of geographical and intra-industry differences. Rather, they utilize newly developed mechanisms to account for the industrial and geographical differences. For example, the EPA constantly checks whether the factors relating to a waste stream are fundamentally different from the factors originally considered by the agency when setting the standards. If the variances are recognized, the different factors are required to be included in the setting of the new standards. Also, many industries are allowed to choose certain control technologies to meet their needs (Shapiro and McGarity, 1991). These new tools have obtained major improvements in regulating the pollutants and controlling pollution. 2.2.3 Impartiality Closely related to the above, impartiality is also an important virtue of technology-based standards. Regulatory interventions that alter companies' behaviors may have the potential to cause inequities such as competitiveness or 14

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barriers to entry. However, if implemented properly, technology-based standards are highly impartial in how they affect industry. In general, all members of the same class of an industry are treated in the same way. Further, distinctions can be built into the selection of technology-based standards to ensure that smaller businesses are not put at a competitive disadvantage. For instance, one chemical plant is not required to purchase substantially more expensive pollution abatement equipment than a competitor in another state. This situation can also be applied to new entrants of an industry (Wagner, 2000). 2.2.4 Low Costs Technology-based standards are less expensive to enforce. Based on the standards, environmental inspectors are only required to determine whether a firm has installed and properly operated the required technology. On the contrary, economic instruments such as emissions trading and pollution taxes require inspectors to monitor constantly the amount of pollution that a plant emits. As a consequence, monitoring all of the possible discharge points will be far more expensive and difficult than simply identifying whether a firm is using a required technology (Shapiro and McGarity, 1991; Wagner, 2000). 2.2.5 Technology Innovation Being required to reduce the emissions and meet the specific standards, industries will be forced to seek out new ways to reduce pollution in the most 15

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efficient and effective manner. The most common response from the industries is to innovate around the existing technologies and/or create brand new technologies and entirely change the manufacturing process. This rationale not only can be applied to the existing firms and industries, but also to the new plants and industries. As the new companies and/or new industries are thinking of entering the market, they have to devise and design newer technologies and mechanisms in advance to enhance their competitiveness (Andrews, 1994; Davies and Mazurek, 1996; Heaton and Banks, 1998). In comparison, economic instruments, such as subsidies or taxation, do not necessarily encourage environmental improvement and may even result in fewer emission-reducing innovations than command and control mechanisms. Economic subsidies actions that provide commodities, capital, or services at below market cost are especially unlikely to stimulate technological advancement (Zellmer, 2000). Counter arguments against this rationale can be found in the section of pro-economic approach below. 2.2.6 Public Involvement and Normative Considerations Technology-based systems are more effective and enforceable because they offer opportunities for public involvement. On the contrary, economic initiatives generally lack this feature. Take the CW A permit program as an example. Before a permit may be issued, the EPA must allow public comments and determine whether the discharge will comply with the applicable requirements. Input obtained during 16

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the public comment period is included as part of the official record. At the end of the comment period, the Regional Administrator decides whether to issue or deny the permit. Also, any interested individual may request a formal hearing within thirty days of the decision. These involvements during the decision making process allow the EPA to reach a well-informed and enforceable decision. In contrast, economic instruments such as subsidies or taxation generally inhibit citizen involvement (Zellmer, 2000). Moreover, many social factors such as emotions, feelings, and attitudes are unlikely to be measured. Despite this difficulty, or improbability, some economists still try to convert everything, including normative concepts, to the simple metric of economic efficiency in monetary terms. Consequently, these calculations may be biased based on the analysts' self-interest and the interests of their clients such as environmental groups and industries. In turn, the final choices of environmental control often become political decisions according to the political powers of the groups. The scientific facts of pollution are often neglected (Campbell, 1996; Grossman and Krueger, 1995; Jacobs, 1991). 2.2. 7 The Moral Imperative From a moral and normative stance, technology-based standards send out a message that the regulated entities must do their best, or nearly their best, to fulfill their responsibility of guaranteeing the public health and environmental quality. 17

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These standards assume that there is pollution, that it is undesirable, and that a strong effort to reduce the pollution is needed. These standards can also be designed to place the burden on the polluters and demonstrate that the pollution control technology they selected is inappropriate. Oftentimes, these standards are criticized as cost-blind and will cause damages to the industries (Sunstein, 1991 ). However, from the consideration ofhuman health and environmental quality, technology-based standards should still represent a fundamental regulatory principle (Wagner, 2000). Critiques on the above rationales are discussed in the section of pro-economic approaches. 2.3 Technology-Based Standards: The Foundation of RCRA The above rationale seems to have a profound impact on the Congressional enactment of RCRA. In this act, specific and detailed technology-based standards are utilized to regulate different types of solid and hazardous waste management. However, Congress also leaves tremendous discretion to the states to administer this act in a highly flexible manner. 2.3.1 Defining Technology-Based Standards Technology-based standards are one of the primary regulatory tools to control pollution entering surface waters, the atmosphere, public drinking water supplies, workplaces, and the land. Their purpose is to regulate the pollution control 18

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technology employed by major emitters of the regulated pollutants. They first appeared in the Section 111 ofthe Clean Air Act (42 U.S.C. (b), 1970) that required the EPA to set technology-based emission limitations for new major sources of air pollution. Subsequently, they were adopted in the control of point source discharges of organic pollutants and toxics in the Clean Water Act (33 U.S.C. 1251-1385, 1974) and in setting drinking water standards under the Safe Drink Water Act (SDWA, 33 U.S.C. g-1(b)(4), 1974). They were also used to regulate toxic health risks in the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA, 7 U.S.C. et seq., 1972) and the Toxic Substances Control Act (TSCA, 15 U.S.C. et seq., 1976), and to set land-disposal standards under RCRA (42 U.S.C. 1-6992(k), 1976). In these acts, Congress requires the EPA to review currently available or soon-to-be-available pollution control technologies for the industries to adopt. In most instances, the EPA uses a three-step strategy in setting the standards. First, the EPA divides the industries into different categories, which is the SIC code system mentioned above. Next, the EPA surveys the available technologies in each industrial category and chooses the technology that best fits congressional goals. Third, the EPA transfers the pollution reduction capabilities of the chosen technology to numerical effluent or emission limits for each pollutant (Gaines, 1977; La Pierre, 1977). To do so, the EPA must become familiar with the performance ofthe selected technology in reducing pollution and the average volume of pollution for each and 19

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every industrial category. Otherwise, it would become controversial if the standards are set simply according to assumptions. 2.3.2 Types of Technology-Based Standards The types of technology-based standards are diverse. They can broadly be divided into two types-design standards and performance standards. Design standards are more onerous. They specify how a certain plant, piece of machinery, or pollution control apparatus should be designed. The well known examples of this type are the previously mentioned BAT and BPT, and the best conventional pollutant control technology (BCT). BCT is required for conventional pollutants, such as total suspended solids and oil and grease (33 U.S.C. (b)(2)(E)). Performance standards, on the other hand, allow facilities more flexibility to determine how they will control their emissions. In other words, these standards set a performance level for the facilities and allow them to determine how they will achieve it. Owing to this greater flexibility, performance standards are now more widely used among agencies than design standards (Gartenstein-Ross, 2003; Percival and Alevizators, 2000). A typical example of performance standards is the best demonstrated available technology (BOAT). BOAT refers to the most effective commercially available means oftreating specific types ofhazardous waste. The BOAT may change with advances in treatment technologies. BOAT is the basis for the new source performance standards (NSPS) in the Clean Air Act, (NSPS 42 U.S.C. 20

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7671(q)) and the Clean Water Act (33 U.S.C. ). The NSPS are applied to all new stationary sources that the EPA determines to cause significant pollution and endanger public health or welfare. After the EPA designates such sources, it promulgates regulations to establish performance standards for them. The standards are set according to the different categories of industrial activity (Gartenstein-Ross, 2003). In RCRA, standards are also established based on the BDA T pursuant to the legislative principles of the 1984 RCRA amendments (Plater, Abrams, and Goldfarb, 1998; Wagner, 1999; Hazardous Waste Treatment Council v. EPA, 886 F.2d 355 (D. C. Cir. 1989)). RCRA regulates twelve hazardous waste activities and units: (1) container storage units, (2) tank systems, (3) surface impoundments, (4) waste piles, (5) land treatment areas, (6) landfills, (7) incinerators, (8) thermal treatment units, (9) chemical, physical, and biological treatment units, (10) miscellaneous units, (11) containment buildings, (12) underground injection wells. Each ofthem is assigned specific technical standards for management. Take landfills ( 40 CFR 268) for example, solid and hazardous wastes are required to be treated in a specified manner or treated to meet specific constituent levels before land disposal. The treatment standards of the wastes therefore include: (1) constituent concentrations in milligrams per kilogram (mg/kg) of waste, which must be met before land disposal, (2) constituent concentrations in an extract of the waste in milligrams per liter (mgll), which must be met before land disposal, and (3) 21

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treatment standards expressed as specified technologies and represented by a five letter code contained in 40 CFR 268.42. These standards are established based on BOAT as mentioned above. 2.4 State Authorization 2.4.1 States with Different Programs While the federal government sets the foundation for hazardous waste management, states play a crucial role in its implementation. RCRA explicitly intends () to have the Nation's hazardous waste management program administered by qualified states with only minimal oversight from the federal government. Any state that seeks authorization for its hazardous waste program must submit to the EPA an application containing a request letter from the state's governor, all applicable state statutes and regulations, a description of the program, a statement by the state's attorney general, and a memorandum of agreement (40 CFR 271.5). The EPA has 90 days after receiving the application to make a decision ( 40 CFR 217.4). Moreover, after approving the state's application, the EPA holds the authority to revise and/or reverse the state program thereafter (40 CFR 271.21). A state with authorization may have a program that is more stringent or broader in scope than the federal program (). Being more stringent indicates that a state can enact stricter regulations than its federal equivalent. For example, a state may require annual reporting by a generator instead of the biennial reporting 22

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required by the federal RCRA program. Being broader in scope means that a state may increase the size or scope of the regulated community. For instance, a state may regulate a nonhazardous waste as a RCRA hazardous waste. The distinction between more stringent and broader in scope is significant: the EPA may enforce a more stringent state requirement, but not state requirements that are broader in scope. For example, the EPA may enforce any provision of an authorized state's approved program. However, if the state provisions are broader in scope and not part of the federal approved RCRA program, the EPA cannot enforce them (40 CFR 271.1(i). Accordingly, and most importantly, a state may adopt additional regulatory tools to meet the program's needs. Table 2.1 and Table 2.2 list the key differences between each state's programs (Wagner, 1999; HTRWCE, 2002). Table 2.1 Summary of State Hazardous Waste Management Programs State Hazardous Waste Generator or Additional Hazardous Wastes Fees Transporter Permits Alabama Landfills Transporters No Alaska No No No Arizona No Yes No Arkansas Yes Yes PCBs California Yes Transporters No Colorado Yes No No Connecticut Yes Transporters No 23

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Table 2.1 (Cont.) State Hazardous Waste Generator or Additional Hazardous Wastes Fees Transporter Permits Delaware No No No DC No No No Florida No No Mercury-containing lamps Georgia Yes No Mercury containing lamps Hawaii No No Oil, gas, and geothermal exploration, development, and production wastes Idaho Only for disposal No No Illinois Yes Transporters There are designate "special wastes. Fluorescent lamps, if they exhibit a characteristic Indiana Yes No Mercury-containing lamps Iowa No No No Kansas Yes No No Kentucky Yes No Nerve and blistering agents Louisiana Yes No No Maine Yes Yes PCBs< 50 ppm Maryland No TSDFsand PCBs transporters Massachusetts Yes Transporters Waste oil, PCBs, pain-related wastes Michigan Yes Transporters No Minnesota Yes No PCBs Mississippi Yes No No 24

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Table 2.1 (Cont.) State Hazardous Waste Generator or Additional Hazardous Wastes Fees Transporter Permits Missouri Yes Transporters PCBs and used oil, not recycled Montana Yes No No Nebraska TSDFs No No Nevada TSDFs No No New Generators and No Used oil, strontium sulfide, solid Hampshire TSDFs corrosives New Jersey Generators, TSDFs, Transporters No and transporters need a DEP license New Mexico Yes No Mercury containing lamps that exhibit a hazardous characteristic New York Yes No PCBs North Carolina Yes No No North Dakota No Transporters No Ohio Transporters TSDFs No Oklahoma Yes Transporters Drum cleaning waste Oregon Yes No Pesticide residues, nerve agents Pennsylvania Yes Transporters No exclusion for residues from "empty'' containers Rhode Island Transporters and Transporters Solid corrosives, ignitable waste with TSDFs flash point <200F, PCBs, used oil South Carolina TSDFs Transporters No South Dakota No No No 25

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Table 2.1 (Cont.) State Hazardous Waste Fees Tennessee Yes Texas Yes Utah Commercial TSDFs Vermont No Virginia No Washington Yes West Virginia Yes Wisconsin Yes Wyoming TSDFs Source: Wagner (1999). Explanation of Codes Generator or Additional Hazardous Wastes Transporter Permits Transporters No Transporters Some used oil No No Transporters PCBs, petroleum distillates, pesticides, infections waste, paintrelated waste, waste ethylene-glycolbased coolants, metal grinding wastes Transporters Fluorescent lamps that exhibit a characteristic No No No No Transporters F500 wastes containing halogenated compounds No No Yes =The state has adopted the federal provision as written. Hazardous Waste Management Fee= This refers to fees charged by the state for generators, transporters, or waste management facilities. Generator or Transporter Permits = This refers to the requirement for generators or transporters to obtain a permit or license. All hazardous waste management facilities must have a permit. Additional Hazardous Wastes= This refers to the classification, identification, or regulation, of any hazardous waste beyond the federal program. 26

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Table 2.2 State Hazardous Waste Fee and Tax Systems Fee I Tax Systems State Hazardous waste management Arizona, Arkansas, California, Colorado, Delaware, fees and direct treatment Illinois, Kansas, Kentucky, Maine, Nevada, North disposal fees Carolina, Ohio, Oklahoma, Oregon, South Dakota, Washington, Wisconsin Hazardous waste management Florida, Indiana, Louisiana, Maryland, fees but no direct treatment or Massachusetts, Mississippi, Montana, New Mexico, disposal fees Rhode Island, Tennessee, Virginia, Wyoming Direct treatment or disposal Alabama, Georgia, Idaho, Iowa, Michigan, fees Minnesota, Missouri, Nebraska, Pennsylvania, South Carolina, Utah, Vermont, West Virginia Direct treatment or disposal Connecticut, New Hampshire, New Jersey, New fees that also specifically York, Texas target out-of-state waste No taxes or fees imposed Alaska, District of Columbia, Hawaii, North Dakota Total Source: HTRWCE (2002) 2.4.2 RCRA Supplemental Environmental Projects (SEPs) Number of States 17 12 13 5 4 51 State RCRA SEPs are projects that incorporate pollution prevention and/or waste minimization principles into their final enforcement orders. Those projects can also be used as a settlement tool under RCRA (EPA, 2005). A survey done by the RCRA Enforcement Task Force ofthe Association of State and Territorial Solid Waste Management Officials (ASTSWMO, 1997) showed that among the 34 sates (out of 56 states/territories) that responded to the survey, 25 states had SEPs and 9 states did not have SEPs. ASTSWMO indicated that although some states did not have "written" procedures, the remainder of the survey showed that they still had some forms of SEPs. 27

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The survey also showed that states utilized different programs in their pollution prevention/waste minimization SEPs. A significant number of states included training (81%), educational outreach (81%), environmental audits (72%), household hazardous waste collection/disposal (69%), grants (56%), stream/stream sediment cleanups (50%), and other specified projects ( 41%) into their SEPs. Moreover, when being asked whether the SEPs are a high priority, 16 states reported "yes" and 8 states responded "no" (NC no response). In other words, about 67% of the respondents alleged that pollution prevention and waste minimization projects were considered a higher priority in their states. The summary of the survey is listed in Table 2.3 and Table 2.4. Table 2.3 Procedure, Guidance, or Rules for SEPs State Yes No State Yes No State Yes No AL ME X PA AK X MD RI X AZ X* MA sc X AR X MI SD CA X MN X TN co MS TX X CT X MO X* UT X DE X* MT X VT DC X* NE X VA FL X NV WA GA NH X* wv X HI X NJ X WI X* ID X NM X WY X IL X NY X VI IN X NC X AS lA X ND X* GU 28

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Table 2.3 (Cont.) State Yes No State Yes No State Yes No KS OH X PR KY OK LA X OR X Source: ASTSWMO (1997) X*: Checked no originally, but later counted as yes by ASTSWMO. According to ASTSWMO, the remainder of the survey indicated that SEPs are utilized in the State. The question may have been interpreted by the respondent to mean written procedures, policies, guidance or rules when it was intended just to determine if SEPs are allowed in settlement negotiations. Table 2.4 SEPs are a Higher Priority than Other Pollution Prevention/Waste Minimization Projects State Yes No AL AK X AZ X** AR X CA X co CT X DE X* DC X* FL X GA HI X ID X IL X IN X IA KS KY LA X Source: ASTSWMO (1997) NC: No Response. State Yes ME X MD MA MI MN X MS MO MT X NE X** NV NH X** NJ X NM X NY X NC ND OH X OK OR X IA: No Response, but commented: Yes, if we did them. No State Yes PA RI sc X SD TN TX X X* UT VT VA WA wv X WI WY X VI AS X* GU PR X*: Checked no in Table 2.3, but responded to the question as no in Table 2.4. X**: Checked no in Table 2.3, but checked yes in Table 2.4. 29 No X X X*

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2.5 Alternative Regulatory Tools 2.5.1 Hazardous Waste Fees As showed in Table 2.1 and Table 2.2, hazardous waste fees are the major alternative some states utilize to control hazardous wastes. Hazardous waste fees or any type of pollution fees apply the principle of market economics. They require regulated facilities to internalize the costs of the damages they impose on society by making them pay fixed dollar amount for each unit of pollution they generate (O'Leary, Durant, Fiorino, and Weiland, 1999; Opschoor and Vos, 1989). Different from the technology-based approach that makes polluters control to the same level of stringency regardless of the costs, hazardous waste fees recognize that some polluters can control emissions at lower costs than others can. Polluters with low costs stay within the pollution limits and pay less in fees. On the other hand, polluters with high control costs will fall short of the standards but pay high fees. The result should be the same or less pollution. However, the total cost to society will be less (O'Leary, Durant, Fiorino, and Weiland, 1999; Repetto, 1997). Scholars also argue that fees provide a constant financial incentive and demand for innovation and pollution reduction. A fee system depends less than technology-based standards on the availability of pollution control technology. Therefore, it can be introduced more quickly at lower costs by reducing demands on regulatory process to decide complex, detailed engineering and economic questions. 30

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Moreover, to further reduce the costs, polluters are forced not only to focus on the end-of-pipe pollution reduction technologies that have been overwhelmingly applied in the past, but also innovative ways to integrate the whole manufacturing process (Stewart, 1981 ). 2.5.2 Penalties In addition to the fee systems, RCRA violators are subject to civil and criminal liability. Nowadays, many courts adopt Superfund's strict liability, joint and several liability, and retroactive liability standards to RCRA (Stem, 1992). Intentional violations such as falsification of documents, dumping hazardous waste in unapproved sites, or any illegal disposure of hazardous wastes may be subject to criminal liability (42 U.S.C. ). Moreover, based on the offense, violators may be subject to fines from $5,000 per day for failing to follow monitoring and reporting requirements (42 U.S.C. ) to $25,000 per day for violating a compliance order (42 U.S.C. ). The exact fines are decided by weighing the severity of the offence. In extremely grave violations, violators' permits may be suspended or revoked, in addition to civil penalties (42 U.S.C. ). Citizens can also bring suit against any violators or any individual who is contributing or has contributed to any situation that poses an imminent and substantial endangerment to health or the environment. However, citizen suits can be barred if government has initiated a suit against the violators (42 U.S.C. ). Also, citizens 31

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can bring suit challenging state agencies that breach their duty of enforcing RCRA provisions (42 U.S.C. -6992k). 2.5.3 Permits Permitting is the key element in the implementation ofhazardous waste programs under Subtitle C. A RCRA permit establishes the authorized waste management activities a facility may engage in and under what conditions the activities must be conducted. It also regulates the administrative requirements such as record keeping, reporting, waste analyses for the facilities. Its general purpose is to ensure that hazardous wastes are directed to and maintained by a suitable facility (Wagner, 1999). Operators or owners of hazardous waste facilities have to obtain a RCRA permit to start or to continue the operation, unless they are specifically excluded ( 40 C.F.R. 270.1 (c)(l)). The RCRA permit application procedure consists oftwo parts: Part A and Part B. Part A comprises EPA Form 8700-23, along with maps, drawings, and photographs of the site. Part B contains no specific form, but need to submit detailed, site-specific information. For new facilities, operators or owners need to submit both parts simultaneously. For existing facilities, since the application is time consuming, Congress established an interim authorization and allowed certain facilities to operate legally after submitting Part A. After the facilities submit Part B, they may obtain a full permit. 32

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There is only one type of permit for regular operations, namely, the RCRA or hazardous waste management permit. However, it is important to note the distinction between facility and unit. A facility may have one or more units, and a permit is issued for individual units such as tank, incinerator, or surface impoundment, not for an entire facility. Therefore, to cover different phases of operations, the permits can be referred as active permit, final permit, post-closure permit, etc. Although all hazardous waste management facilities must have a permit, each state may still have leeway to design its own permit systems for generators or transporters. As showed in Table 2.1, the decision to issue, not to issue, or issue only to generators or transporters is made by each state. In addition to the permits for regular operations, the EPA also issue some limited special permits like the emergency permits and the research, demonstration, and development (RD&D) permits. Ifthere is an imminent and substantial endangerment to human health or the environment, the EPA may issue a temporary emergency permit (40 C.F.R. 270.61). This permit may require a non-permitted unit to treat, store, or dispose hazardous wastes, or a permitted unit to treat, store, or dispose wastes that are not covered by an effective permit. RD&D permits are for innovative and experimental treatment technologies or processes that have not been established under 40 C.F.R. 264. The EPA may establish permit terms, conditions, and technical standards for each RD&D activity to protect human health and the environment (Wagner, 1999). 33

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Again, citizens can challenge the EPA's decisions to issue, deny, modify, or revoke any permit for the facilities. Citizens can also bring suits challenging state permit decisions if the state fails to comply with applicable state law, or if state requirements are less stringent than federal standards (42 U.S.C. (b)). 2.5.4 Subsidies This is an additional regulatory tool of RCRA that offers financial assistance to state, local, and private agencies for their efforts to research, promote, or demonstrate the reduction of solid waste and unsalvageable waste materials ( 42 U.S.C. (a)(5)). Due to the financial situation ofthe RCRA authorities, this program is currently underfunded and underutilized. Compared to the R&D investments of the chemical industry, the governments' subsidies and funding for hazardous waste reduction are considerably low (Aboody and Lev, 2001; Zare, 2000; IRDIS, 1998, 2005). 2.5.5 Voluntary and Partnership Programs Voluntary and partnership programs are the most recent environmental control efforts by the governments. They include the EPA's 33/50 programs, the EPA's Common Sense Initiative, Occupational Safety and Health Administration's (OSHA) Voluntary Protection Programs, and the EPA's Energy Star Program and Project XL, and the SEPs mentioned above (Bergeson, 2000; EPA, 1995; EPA, 2005; Franz, 2002; Hogue, 2003). Those regulatory innovations encourage the industries to submit 34

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innovative and creative pollution reduction proposals. EPA in tum offers operational flexibility to allow the industries to put the proposals to test. Voluntary programs are a moral commitment ofthe companies. With a set of principles and guidance from the environmental agencies, pollution problems are addressed through a more collaborative and less directive manner (Johnson, 1999; Rose, 1991). In recent years, the number of the facilities that participate in those programs has increased rapidly (Fiorino and Friedman, 2002). Nevertheless, while a huge number of firms have signed and joined the programs, the issues of commitment to innovate and honesty to carry out the programs are still under debate (Berry and Rondinelli, 1998; Kirschner, 1995; Service and Avasthi, 2005). 2.6 Conflicting Research Findings Based on the above, it seems that in principle, all of the regulatory tools are effective. However, according to the studies in the field of air and water pollution, the relative capabilities between command-and-control regulations (technology-based standards) and economic approaches in reducing pollution are still controversial. In other words, scholars and analysts differ in their judgment as to which approach performs better in pollution reduction. In this section, research findings are divided into pro-technology/command and control approaches and pro-economic approaches. 35

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2.6.1 Pro-Technology/Command and Control Approaches 2.6.1.1 Theoretical Arguments McHuge (1985) examined the implications of technological indivisibilities, or lumpiness, for the dynamic efficiency of tax based, economic instruments. In this study, pollution control and reduction technologies are discrete and identified with particular control efficiency. McHuge argued that there are two types of innovations in pollution abatement technology: technology stretching innovation and inframarginal cost-reducing innovations. The former innovations are those that lead to a higher proportion of potential emissions controlled at an acceptable cost. The later innovations are those which control a lower proportion of emissions than the currently employed control, however, at a cost low enough to induce firms to switch to a control technique which controls a power amount of emissions (p. 59). McHuge's analysis focused mainly on the second type of innovation technology. He argued that given any existing tax rate or permit price, the firm(s) in the affected sector (in which the inframarginal technological innovations occur) may find it more attractive to use the new inframarginal technology and reduce the level of emissions, because the marginal cost of the presently employed technology has increased above the tax rate. The policy application of this theory is that the pollution control authorities may raise the level of the tax to meet the emissions reductions goal. However, total 36

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industry's compliance costs may increase, which means that a tax-based environmental policy may lead to dynamic inefficiencies. Mendelsohn (1984) tackled the issues of regulation under uncertainty. This study showed that when the regulator is uncertain about the locus of the linear marginal cost curve, quantity regulations (standards) are likely to be more efficient than price regulations. This contradicts the traditional economist's argument that price rules, such as emission taxes in environmental policy, are more efficient than quantity rules. Mendelsohn found that quantity rules tend to encourage more efficient levels of technical change. Under price rules, firms tend to overreact and produce either too much or too little R&D. Mendelsohn therefore concluded that technical change will induce an additional welfare loss with price rules. Firms in turn will overreact to the price rule, producing too much or too little abatement output and stimulating too much or too little R&D. Over the long run, the quantity rule will induce more efficient levels of technical change and waste reduction. Nentjes (1988) based his study on the economic theory of bureaucracy. In this study, government agencies are motivated not by the maximization of social welfare but by output maximization. In turn, the goal of the control agencies is to maximize pollution reduction. However, the agencies will not try to achieve emissions reductions at all costs. The abatement costs may not exceed a certain level. As in real life, the control agencies are careful not to impose costs too high for the polluting firms. 37

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In this study, higher control efficiency may be achieved through the use of new pollution control techniques. The range of pollution control technologies runs from well-known and proven technologies to highly uncertain technologies with high control efficiencies. However, a risk-averse regulator with a high time preference and a low cost ceiling will choose a point on the technology choice curve not far from the best available abatement technology (BAA T). In such a situation, there is little incentive for the polluting firm to develop innovations with higher control efficiency. According to Nentjes, this has been the situation in Europe, where cost ceilings have often been chosen on the basis of well-known and relatively cheap available reduction technologies. In addition, scholars argue that the relationship between command-and control standards and pollution control innovation is positive from different perspectives. Porter ( 1991) maintained that environmental regulations do not necessarily constrain the innovation related to competitiveness. Rather, regulations that focus on process change often result in entirely new production technologies. Also, strict standards and regulations would encourage companies to develop new products which are less polluting, use resources more efficiently, and carry a higher perceived value. In a similar vein, Meyer (1982) and Marcus and Weber (1989) argued that environmental regulations can be seen as an external jolt that stimulates innovation within a firm. Without external jolts, firms will continue their old routines. Their 38

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members will also resist innovation because they want to maintain the status quo. Moreover, their organizational practices will stay the same unless an event such as the imposition of environmental regulations occurs that requires them to change. Further, Mitnick (1981 ), Caimcross (1992), and Shrivastava (1995) alleged that strict regulations can create entrepreneurial opportunities for the firms. In tum, they will design and develop new procedure and/or equipment to satisfy the regulatory provisions. In other words, strict mandates can promote innovation and provide unforeseen opportunities for profit by forcing the firms to upgrade their technologies, and result in increased efficiency. Firms that manage to innovate and obtain technological expertise in response to the environmental mandates will hold an advantage over their competitors. The latter therefore are only compelled to purchase and learn to use the new technology. 2.6.1.2 Empirical and Case Studies Empirical and case studies also demonstrate that technology-based standards have triggered industries to adopt new management styles and manufacturing procedures that dramatically reduced the pollutants/emission. For example, stringent standards forced companies to innovate their refineries to improve production and increase operating efficiencies: Texaco reduced TRI emissions by 80% between 1989 and 1996, while refinery production increased by 12%. Besides, Texaco also reduced water pollution spills by 12% since the 1990s. Ashland Oil reduced its toxic releases 39

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of 17 target chemicals by 33% before the end of 1992 and by 50% by the end of 1995. Baxter International reduced its per unit air toxic and chlorofluorocarbon emissions by 94%, its nonhazadous waste by 45% (34 million pounds), and its hazardous waste by more than 48%. In addition, the 3M Corporation cut its air emissions by 70%, its water releases by 52%, and its solid waste by 32% in its worldwide operations from 1990 to 1996. Since the late 1980s, PepsiCo also has reduced the amount of materials in its packages (aluminum cans by 35%, polyethylene terephthalate in plastic bottles by 28%, and glass in bottles by 25%) (Rondinelli and Berry, 2000). Xerox reduced hazardous-waste generation by 50% between 1900 and 1995. Nortel, the Canadian-based telecommunications, established specific targets for the year 1993 to 2000: a 50% reduction in pollutant releases, a 50% reduction in solid wastes, a 30% reduction in paper purchases, and 10% improvement in energy efficiency (Kerr, 1995). Milliken and Co., a major textile manufacturing company, reduced its sold waste materials by 21% in 1989, its energy consumption by 9%, from 0.93 to 0.68 EEBL per thousand pounds produced between 1990 and 1994 (DPPEA, 1995). Moreover, Dow Chemical decreased its emissions of compounds by 53% (more than 51,000 pounds) in its facilities around the globe and made tremendous profits by using the following strategies: It sold its pollution control technology to companies and manufacturers that could not to develop it themselves; it sold its 40

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expertise and equipment to the government; and it reduced manufacturing waste by developing new uses for factory by-products (Marcus, 1984). Likewise, cases in chlorofluorocarbons (CFCs) reduction demonstrate that although strict regulations and standards are viewed by the firms as a threat, they tum out to be an opportunity for innovation and emission reduction. At first, Du Pont openly opposed any laws or treaties to reduce CFCs. However, other companies such as AT&T, Motorola, and Northern Telecom realized that the future CFC restrictions would be a big threat to their survival, and the need to innovate alternatives to CFCs was urgent. Accordingly, they formed the Industry Cooperative for Ozone Layer Protection (ICOLP) in 1990, which was a coalition that allowed industry competitors to pool R&D resources for similar research goals. By the end of 1990, A&T & had met its goal of reducing CFC emissions by 50%. Du Pont eventually realized the threats from the future restrictions and started radically its new technology initiatives. As a result, Du Pont reduced its R&D time from the industry norm of more than a decade to only five years (Piasecki, 1995; Sanchez, 1997; Weber, 1993). A similar case also shows that by responding to the regulatory requirements, a cardboard recycling firm, Jackson Paper, established an innovative series of conservation and reuse projects to obtain considerable positive results in terms of regulatory compliance. For example, the newly designed on-site pretreatment facility ofthe firm can cut effluent discharges from 100,000 gallons per day to 30,000 to 40,000 gallons per day. The new holding tank for the sludge belt press showers can 41

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reduce discharge to an average of 22,000 gallons per day. Together, the total effluent discharge reduction was 78,000 gallons per day, or a 78% reduction of the previous discharge level. These new facilities helped reduce the annual manufacturing costs approximately $112,000. The transportation and handling costs have also reduced around $72,000 pear year (DPPEA, 1998). The case of the professional garment and textile care industry, however, displays a more "gentle" way of technology-based approach. As part of a cooperative effort between the EPA and the industry, the EPA's Design for the Environment (DfE) Program recognizes the wet cleaning process, or the water-based cleaning systems, as an environmentally-preferable technology to clean garments. Currently, most ofthe country's 34,000 commercial drycleaners use perchloroethylene (PCE or perc) as a solvent to clean garments. In response to the growing health and environmental concerns about perc, the EPA initiated this program in 1992 and "encouraged" professional clothes cleaners to explore those environmentally-preferable technologies. The new technologies turn out to be a great success. As the study indicated, the new technologies performed much better in certain types of clothes, generated no hazardous waste and air pollution, and reduced annual operating costs from approximately $10,000 to 20,000 among participants (EPA, 1999). In addition, a series of case studies done by the Division of Pollution Prevention and Environmental Assistance (DPPEA), North Carolina Department of 42

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Environment and Natural Resources (NCDENR, 2005) has demonstrated the successfulness of technology-based approach. The cases are listed in Appendix B. 2.6.2 Pro-Economic Approaches In this section, the discussion of the pro-economic approach towards pollution control is also divided into two parts. The first part depicts the theoretical foundation and arguments, while the second part illustrates the empirical findings that support this pollution control approach. 2.6.2.1 Theoretical Arguments Downing and White ( 1986) analyzed the effects of four pollution reduction instruments-effluent fees, emission control subsidies, marketable permits, and direct regulation (standards)-in three contexts: (1) the situation where the marginal conditions are not changed, that is, the reduction in the polluter's emissions can be valued at the existing social value of emissions reduction; (2) the situation where the innovation changes marginal conditions, but the control authority, fails to adjust; and (3) the situation where innovation changes marginal conditions and the control authority adjusts properly, which is referred to as "ratcheting." In all three contexts, Downing and White assumed that the innovating polluter correctly predicts the reaction of the government authority and bases its innovation decisions on the prediction. In addition, two properties of the regulatory regimes are -taken into account: the incentives for innovation in pollution control, and the dynamic 43

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efficiency of these incentives, which refers to the efficiency of the allocation of resources after the innovation. Downing and White summarized their findings in the following two tables. Table 2.5 demonstrates the incentives for innovation under various pollution control arrangements. Table 2.6 shows the emissions levels under various pollution control arrangements. In Table 2.5, "optimal" indicates the equilibrium between the social value of emissions reductions and government pollution control arrangements. "Excessive" means that the arrangements cause an excessive amount of innovation and pollution reduction, while "deficient" is the other way around. Also, as shown in Table 2.6, when ratcheting happens, the emissions levels can be adjusted to the optimal status. Table 2.5 Incentives for Innovation under Various Pollution Control Arrangements Effluent Fees Subsidies Marketable Permits Direct Control No change in Optimal Optimal Optimal Deficient marginal conditions Change in marginal Excessive Excessive Indeterminate Deficient conditions; no ratcheting Change in marginal Excessive Deficient Deficient Deficient conditions; ratcheting Source: Downing and White (1986, p.28) 44

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Table 2.6 Emissions Levels under Various Pollution Control Arrangements Effluent Fees Subsidies Marketable Direct Control Permits No change in Optimal Optimal Optimal Too high marginal conditions Change in marginal Too high Too Low Indeterminate Too high conditions; no ratcheting Change in marginal Optimal Optimal Optimal Optimal conditions; ratcheting Source: Downing and White (1986, p.28) According to the tables, Downing and White (1986) argued that ifthe innovation does not change the social value of emissions reduction, the incentive for innovation in pollution reduction will be optimal except for direct control. This situation is similar in the calculation of emissions levels, which suggests that if the innovative polluter (or polluters) is the only one that innovates among other polluters, it will be beneficial by the innovation. On the other hand, when the social value of emissions reduction has changed, the incentives for innovation will not be optimal no matter whether the government has made socially appropriate adjustments or not. Consequently, the results will not be optimal. Nevertheless, if proper ratcheting is applied, the emissions levels will all be optimal as shown in Table 2.6. This indicates that government should pay attention to the innovative efforts of the industries and make proper responses for optimal emission levels. 45

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Similar to the above, Milliman and Price (1989) examined the linkage between regulations and pollution reduction through technological change. However, their study was broader than Downing and White's in that: (1) they assessed the entire process of technological change-from innovation to diffusion; (2) they analyzed five regulatory regimes: direct control (standards), emission subsidies, emission taxes, free marketable permits, and auctioned marketable permits; (3) they assessed incentives that promoted optimal agency response via political lobbying or information withholding, for both innovating and non-innovating firms; and (4) they examined technological change incentives for both non-patented and patented innovations, and for innovations that occurred outside the polluting industry. This theory assumes a large number of firms in a competitive industry, each discharging a homogenous emission into a body of water, air, or land. Also, it assumes that the regulator holds perfect information on current abatement technology. However, lags in perceiving a discovery and the political pressures prevent the regulator from imposing optimal agency response prior to the completion of diffusion. The relative rankings of the regulatory regimes are listed in Table 2.7. Table 2.7 Summary of Relative Rankings of the Incentives to Promote Technological Change in Pollution Control and the Attitude Towards Optimal Agency Response Direct Emission Free Permits Au ct. Emission Control Subsidies Permits Taxes Innovation 5 1 1 1 1 Diffusion Inno., N-P 2 2 5 1 2 N-1, N-P 4 2 4 1 2 46

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Table 2.7 (Cont.) Direct Emission Free Permits Au ct. Emission Control Subsidies Permits Taxes Inno., P 4 2 5 1 2 N-P, P 4 2 4 1 2 0-F, P 4 2 4 1 2 Optimal Agency Response Ind., N-P 2-5 2-5 2-5 2-5 1 CAS Oppose Oppose Oppose Owose Favor Inno., P 1-4 5 1-4 1-4 1-4 CAS Uncertain Oppose Uncertain Uncertain Uncertain N-1, P 2-5 2-5 2-5 2-5 1 CAS Oppose Oppose Oppose Oppose Favor 0-F, P 1 4 1 3 4 CAS Favor Oppose Favor Uncertain Oppose Source: Milliman and Prince (1989, p.257). Inno.: Innovator; N-P: Non-Patent Innovation; N-1: Non-Innovator; P: Patent Innovation; O F: Outside Firm; Ind.: Industry; CAS: Control Adjustment Stance. The firms' stance towards governmental patent protection In general, as shown in Table 2. 7, this study argues that emission taxes and auctioned permits clearly reward positive gains to an industry innovator from the entire process of a technological change. Therefore, these two regulatory regimes are better facilitators of technological changes. Wender (1975) analyzed the relationships between pollution abatement technologies and a polluting firm's costs ofutilizing them under three pollution reduction approaches: (1) a tax per unit of pollution emitted, where tax is used as another word for fee or charge; (2) a subsidy per unit of emission reduction; and (3) emission standards. 47

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In this study, innovation in pollution control is firm-specific. The firm tries to minimize its costs (abatement costs plus tax payments minus any subsides), while the pollution control agency possesses full information about the marginal cost and damage functions ofthe firm. Therein, three situations are considered: (1) the case in which the pollution control board does not change the emission standard or the tax subsidy rate when innovation is available; (2) the case of control adjustment; and (3) the case where the firm can change the form of the cost abatement function, besides its position. Wender concluded that: (1) both taxes and subsidies offer more inducement to innovation than the emission standard approach. This result is similar to the above theories; (2) If the pollution control board reacts to the improvement in abatement, then the inducement to innovation for the firm operating under the corrective tax becomes greater than the inducement for the firm operating under the subsidy or the emission standards. This, again, is identical to the results of the theories above; and (3) If a firm is able to control the direction of its R&D, the firm operating under either emission controls or a corrective subsidy will prefer innovation which raise the established level of pollution abatement as little as possible, whereas the firm operating under a tax will prefer the kind of technological change that raises the optimal level of abatement as much as possible. Magat (1978) analyzed the effects oftwo pollution control policies, namely effluent taxes and effluent standards, on the path of technological change chosen by a 48

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finn that produces an effluent by-product. In this study, the finn may invest resources to improve its abatement technology, its production technology, or both. In other words, this finn engages in an R&D program to improve its current technology of output production and effluent abatement. In this study, Magat aimed to decipher the interactions between these two efforts. For each level of R&D spending, this study demonstrated the tradeoffs available between improving production technology and advancing effluent abatement technology: a high decrease in the improvement in production technology is only possible if the increase in the improvement in effluent abatement technology is low, and vice versa. Based on the above, Magat (1979) extended his research to analyze five types of regulatory tools: effluent charges, non-technology-based effluent standards, marketable permits, technology-based effluent standards, and subsidies for abatement capital. Margat's conclusions in this paper (1979) were somewhat different from the theories above. He concludes that if standards and marketable permits that induce the same level of effluent discharge over the entire period of analysis, they will provide exactly the same incentive for both abatement technology and output technology innovation. In addition, if the regulator reduces the effluent charge to induce the same abatement as under the effluent standard, the innovator will still maintain a transfer gain. Moreover, non-technology-based effluent standards create a stronger incentive for abatement technology innovation than technology-based effluent 49

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standards. Regulatory agencies that adopt technology-based standards may need to reconsider their approaches. Lastly, scholars also question technology instruments from the following aspects: First, research shows that while the water quality has been improved, technology instruments still have not helped achieve major goals such as "fishable swimmable" waters in the United States. Second, though surface water has been cleaned, the contamination of ground water still cannot be resolved by the technology instruments because there are myriad of non-point pollution sources that are not possible to be controlled (Allenby, 2000; Plater, Abrams, and Goldfarb, 1998). Third, the problem of cross-media pollution cannot be resolved under the technology instruments. Cross-media pollution occurs when pollutants such as toxic substances and acid deposition transfer and transport through multiple media like water and air simultaneously. If regulations are designed to tackle pollution problems separately, such as air program, water program, and land program, etc., cross-media problems will unlikely be handled in an efficient and effective manner. Unfortunately, technology instruments are single-source tools, which are limited in tackling the cross-media problems (John and Mlay 1999; Rabe 1986). Fourth, while one of the rationales of technology-based approach is that it is simple to implement, research suggests that technology instruments are actually laborand information-intensive for regulators. Those tools require knowledge of the 50

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operational processes of polluters; of widely used technologies for controlling pollutions; and of the costs and feasibility of installing and maintaining these technologies across a wide range of facilities. Besides, the administrative process for developing and issuing technology standards is long, cumbersome, and difficult. Accordingly, technology instruments create huge regulatory lag for the agencies (National Academy of Public Administration, 1995). Fifth, it is questionable whether the technologies identified by the government are actually the most proper ones in controlling the pollution. As government regulates that certain filtering system is the "best" available technology to clean the emissions to the air, industries may complain that those technologies may not be the most cost efficient and cost effective ones. Furthermore, studies suggest that technology-based standards are actually freezing in-house technology innovation because, instead of finding new ways, most industries turn to make minor improvements on traditional technologies (Eggers, Villani, and Andrews, 2000). Sixth, scholars state that the relationship between regulation and pollution reduction innovation is negative because the costs and bureaucracy of environmental regulation will undermine innovative efforts and restrict firms to pursue advanced technologies (Breyer, 1982; Carter, 1990). Strict technology instruments add sizable compliance costs to firms, which forces them to cut back their R&D efforts and limits their innovative initiatives. Accordingly, the net effect of these constraints is reduced innovation and put them at a competitive disadvantage status (Caves, 1982; 51

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Guttmann, Sierck, and Friedland, 1992; Scherer and Ross, 1990). Firms and facilities also argue that it is difficult to innovate since regulations often change unexpectedly and unpredictable. Case studies show that small X-ray companies invest less in new product inventions over the short term because environmental and other regulations increase uncertainty in those companies (Birnbaum, 1984). More empirical and case studies are discussed below. 2.6.2.2 Empirical and Case Studies The Clariant Corporation in Mount Holly, NC is a major, nationwide manufacturer of dyes and textile chemicals. During its manufacture procedures, it produces sulfuric acid, sodium thiosulfate, and ammonium sulfate as co-products. This company has found that if they can remove some organics from the waste streams, those co-products can be eliminated from the hazardous wasteD-list and become resalable products. This market approach not only encourages the company to innovate its technology, but also helps them keep out of the waste streams, meet regulatory requirements, reduce waste disposal costs, and increase the sales revenue to 1.1 million dollars per year (DPPEA, 1997). Similarly, due to market resale incentives, a kitchen and bath plumbing products manufacturer, Moen Incorporated, developed an environmental plan in 1995 to reduce emissions and wastes. This plan helped reduce the firm's aqueous wash waste by approximately 45% (400,000 lbs.) in 1995, hazardous wastes by 90% 52

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(1,000,000 lbs.), process water use by 54% (40,000,000 gal.), and recycling wooden pallets and cardboard by 42% (1,800,000 lbs.) in 1997. The total annual savings of this firm was $2,745,000 per year (DPPEA, 1997). Studies also suggest that taxes can successfully change behavior. A study of the generation and management of a major group ofwastes-spent solvents from cleaning and degreasing metal products-has indicated that state taxes can actually help reduce the amount of wastes generated by the related facilities. Although the reduction was small (between 5 and 12 percent), compared to the taxes levied (only $10 to $20 per ton), the reduction ofthe management costs was huge (more than $100 a ton) (Sigman, 1996). In addition, state taxes can alter generators' behavior as to where to manage their wastes. Levison (1997) maintained that, first, state taxes have major influence on the extensive interstate shipment of waste; and, second, high taxes will deter waste management significantly. Waste management has especially low environmental costs in states with low population density and arid conditions. If those states choose low taxes, interstate shipment in response to differentiated taxes would reduce the environmental costs of waste management. However, if politics is the main force to decide the pattern of tax rates, the responses to taxes would be costly. Nonetheless, research findings illustrate that waste generators respond to price signals in ways that a good tax policy can harness. 53

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A pilot program in water pollution trading also showed promising results. A Minnesota-based Rahr Malting Co. planed to increase its production in 1997. However, the state and federal EPA found that the Minnesota River could not handle the extra load from the company's new treatment facility. To resolve the problem, the environmental agencies developed a pilot program and issued the company a point/nonpoint-polluant-trading permit. This permit allowed the company to reduce the amount of pollution from non point sources in exchange for the pollution it discharged from its plant. In response, Rahr created the Minnesota River Corporate Sponsorship Program to target nonpoint sources-such as highly erodible lands and livestock-damaged riparian zones-within the Minnesota River's 16,770 square-mile (43,400 square-kilometer) drainage area. Through the program, Rahr purchased easements on sensitive agricultural lands and protected these lands from erosion in return for the right to discharge into the river. Results showed that this program reduced not only the pollution in the watershed, but also the company's control and management costs (Peplin, 1998). Additional successful cases concerning market-based approaches include: (1) The U.S. Acid Rain Program (sulfur dioxides (S02) and nitrogen oxides (NOx) reduction) proposed by the Congress and the National Acid Precipitation Assessment Program (NAPAP); (2) the case ofthe Wisconsin Electric Power Company that successfully reduced S02 and NOx under the Acid Rain Program (ETEI, 2005); (3) the Federal NOx Emission Trading Program by the EPA (EPA, 2003; Zingale, 2002); 54

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(4) the Greenhouse Gas Programs (carbon dioxide (C02 ) reduction) that utilize tradable permits and carbon taxes (Pakerr, 2002); (5) the tradable air quality control permit systems (hydrocarbons discharges) in Portland, Oregon; (6) the air pollutant discharge fee systems in southern California (Lee and Sexton, 1993); (7) the fuel tax, parking fee, congestion pricing, third party van subsidies, and carpools in many metropolitan areas (Giuliano and Washs, 1992); (8) and the market-based mechanisms/initiatives to control mercury depositions in Minnesota (Hagen, Vincent, and Welle, 1999), etc. Moreover, a range of marked-based environmental policies at the federal and state levels are listed in Appendix C. 2.6.3 RCRA Related Policy Studies Compared to the studies in the field of air and water pollution above, RCRA related policy studies were fairly scant. With a thorough search of the literature in the academic and research databases and websites, most studies under RCRA were in the field of environmental science and/or cases studies at the firm or facility level. Moreover, the number of RCRA related policy studies found under keyword search (RCRA and waste reduction) was limited. For graduate level studies, among the 44 dissertations and theses found under keyword RCRA in the Digital Dissertations database, 19 were policy and management related: Four dissertations addressed the issue of RCRA enforcement and compliance at the state level (Hachey, 1996; Jones, 1994; Okere, 1995; Port, 55

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1988). Two dissertations analyzed the economic tools: contracting out hazardous waste management (Jarvinen, 1995) and commercial insurance under RCRA (Willingham, 1993). One thesis in the field of environmental science tackled the issue of hazardous waste minimization of a facility in Ohio (Delay, 1994). The rest of the studies focused on a variety of topics, such as regulatory process of environmental laws (Holland, 2003; Keefe, 1993 ), equity issues in implementation (Firestone, 2000), regulation of radioactive mixed waste cleanup (St. Clair, 1993 ), environmental inspections (Bailey, 1988; Spitzer, 1992), used oil management (Mueller, 1999), environmental restoration (Dinwiddie, 1997), impact of presidential administration on environmental regulations (Floyd, 1990), non-regulated environmentally conscious decisions (Sharp, 1996), environmental justice and participatory democracy (Gott, 1995), and social regulation and RCRA implementation (Quinlan, 1993). None of the dissertations and theses analyzed the relationship between regulatory tools and solid and hazardous waste reduction at the state level. An additional search was conducted for related books and research articles. For example, in Infotrac's Expanded Academic database, 1,287 articles could be found under RCRA. However, when narrowing down to RCRA and waste reduction, the search engine only found 8 articles. With the same searching procedure in other databases, the results were: EBSCO's Academic Search Premierfrom 166 articles to 1 article; Lexus-Nexus-from over 1000 to 190 articles (25 ofthem were policy 56

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related); and Blackwell Synergy-from 65 to 30. Again, none of them focused on the relationships between regulatory tools and chemical industry's waste reduction performance at the state level. Accordingly, it is believed that this dissertation would serve the purpose of bridging the research gap between regulatory tools and solid and hazardous waste reduction under RCRA. 57

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3. Research Design 3.1 Hypotheses As the literature above shows, most studies tackling the relationship between regulatory tools and pollution reduction were done in the fields of air and water pollution control. Not much research has been done in the field of solid and hazardous waste control. Also, the relative capabilities between technology-based standards and economic approaches in reducing pollution were controversial. Scholars and analysts differed in their judgment as to which approach performed better in pollution reduction. Moreover, most RCRA related studies were conducted in the field of environmental science and/or at the firm level. Policy research at the state level was fairly scant. Accordingly, with the unique and flexible regulatory background of RCRA, it would be proper to hypothesize based on the findings of both command-and-control and economic approaches. In doing so, we may obtain a broader and better understanding of the field of solid and hazardous waste reduction at the state level. To fulfill this purpose, I listed the following hypotheses. 3.1.1 Technology-Based Standards Technology-based standards have been regarded as an effective pollution control mechanism by scholars from different perspectives. As discussed earlier, 58

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HcHuge (1985) stated that a tax-based environmental policy may cause more (total) compliance cost to the industry and in turn led to dynamic inefficiencies. Mendelsohn (1984) argued that when the regulator was uncertain about the locus of the linear marginal cost curve, quantity regulations (standards) would likely be more efficient than price regulations. Nentjes (1988) pointed out that the control agencies were usually careful not to impose too large costs on the polluting firms. Also, higher control efficiency could be achieved through the use of new pollution control techniques. Porter ( 1991) maintained that strict standards and regulations often triggered the innovation relating to competitiveness. In a similar vein, Meyer (1982) and Marcus and Weber (1989) argued that environmental regulations could be seen as an external jolt that stimulated innovation within a firm. Further, Mitnick (1981 ), Cairncross (1992), and Shrivastava (1995) alleged that strict regulations could create entrepreneurial opportunities for the firms. Based on the arguments and the empirical findings in section 2.6.1.2, I hypothesized that: H 1: The government's stringent technology-based standards will promote the reduction of solid and hazardous waste. In this hypothesis, the independent variable (states) was categorized in two ways. First, states were divided into two groups according to Wagner's ( 1999) survey: states that utilized and did not utilize additional standards. Second, states' waste reduction performance was divided and measured before and after the implementation of the more stringent Hazardous Waste Minimization National Plan 59

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of 1995 (EPA, 1996). Detailed description of the variable measurements is presented in section 3.2.3. 3.1.2 Hazardous Waste Fees Since technology-based standards are the regulatory foundation of RCRA and the authorized states have the discretion to enact programs broader in scope than the federal program, it would be worthwhile to compare the performance of the states that utilized different types ofhazardous waste fees. Scholars in the camp of pro economic approaches strongly argued that direct control or strict standards provided the least or no incentives for innovation and pollution reduction (Downing and White, 1986; Milliman and Prince, 1989; Wender, 1975; and Magat, 1978). Other problems such as non-point sources (Allenby, 2000), cross-media pollution (John and Mlay 1999; Rabe 1986); administrative costs (National Academy of Public Administration, 1995); in-house technology freeze (Eggers, Villani, and Andrews, 2000); and high compliance costs and R&D cuts due to strict standards (Caves, 1982; Guttmann, Sierck, and Friedland, 1992; Scherer and Ross, 1990) all suggested that economic approaches are a more effective tool. Based on those studies and the empirical findings in section 2.6.2.2, I hypothesized that: H2: There will be significant differences in the performance of solid and hazardous waste reduction among the states that utilize different hazardous waste fee systems. 60

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In this hypothesis, each state's fee systems were based on the surveys of Wagner (1999) and HTRWCE (2002). In Wagner's survey, three types of regulatory adoptions were identified: did not utilize, partially utilized, and fully utilized hazardous waste fees. In HTRWCE's survey, hazardous waste fees were divided into five groups: (1) no taxes or fees imposed, (2) hazardous waste management fees and direct treatment disposal fees, (3) hazardous waste management fees but no direct treatment or disposal fees, (4) direct treatment or disposal fees, and (5) direct treatment or disposal fees that also specifically target out-of-state waste. 3.1.3 Permits Permitting is the key element in the implementation of hazardous waste programs under Subtitle C. As previously mentioned, all RCRA regulated facilities have to obtain a RCRA or hazardous waste management permit before operating. However, based on the state authorization, states may develop and design their own permit systems for generators and transporters. As permits are one of the major regulatory tools, it would be meaningful to compare the performance of the states that issued permits, partially issued permits, and issued no permits to generators and transporters based on Wagner's (1999) survey. Similar to the above, according to Downing and White (1986), Milliman and Price ( 1989), Magat ( 1978), and the findings of the empirical and case studies mentioned in section 2.6.2.2, I hypothesized that: 61

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H3: There will be significant differences in the performance of solid and hazardous waste reduction among the states that issue, partially issue, and issue no permits to generators and transporters. 3.1.4 Other Contextual Variables As mentioned in the literature review, in addition to technology-based standards and other economic approaches, there are other contextual variables that may also be related to the performance of pollution reduction. Those variables include state SEPs; the importance of SEPs recognized by the states (ASTSWMO, 1997; EPA, 2005); the R&D funds ofthe chemical industry (Guttmann, Sierck, and Friedland, 1992; Scherer and Ross, 1990); the number of third-party treatment facilities; and the number of technical assistance (U.S. Congress, 1995; O'Leary, Durant, Fiorino, and Weiland, 1999). Detailed description of the (contextual) variables is also presented in the section of data measurements. Again, while the relative performance of technology-based standards and other economic approaches was undecided, it would be worthwhile to compare the relative performance of those independent variables. Therefore I hypothesized that: H4: Technology-based standards are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. H5: Hazardous waste fees are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. 62

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H6: Permits are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. 3.2 Research Data 3.2.1 Industry Selection In this study, my focus was on the chemical industry. The chemical industry has long been recognized as a major source of pollution. From a toxic and hazardous emissions point of view, the chemical industry can further be regarded as the most critical industry because it accounts for almost half of the total emissions for all industries in this country (Dooley and Fryxell, 1999). Among all of the chemical related industries, I specifically focused on the chemical manufacturing industries. These facilities are listed in the category of"Chemicals and Allied Products" of the EPA's Standard Industrial Classification (SIC, 1987) Codes, and are coded from 2812 to 2899. 3.2.2 Data and Sources 3.2.2.1 Solid and Hazardous Waste This research utilized the EPA's solid and hazardous waste databases: the Resource Conservation and Recovery Act Information System (RCRAinfo or RCRIS) and the Chemical Industry Biennial Reporting System (BRS). The major contents ofthese two databases include: (1) facility identification and certification, 63

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which identified the facilities' EPA ID number, waste management status, and waste reduction activity; (2) waste treatment streams, which demonstrate facilities' waste treatment activities such as on-site or off-site treatment; (3) detailed information of treatment, recycling, and disposal facilities (TRDFs) such as waste form, waste quantity, and system type; and (4) specific information ofthe technologies used in treatment, disposal, or recycling process. Longitudinal data were collected from the year 1989 to 1999. As of 2005, EPA has been converting and matching data between SIC and NACIS coding systems. Therefore, the complete datasets later than 1999 had not been available from the EPA's RCRAinfo and BRS databases before the finish ofthis dissertation. The updated data could be found from the Right to Know Network's databases. However, first, there was no industry search function (SIC/NACIS) for the new databases. Second, the new NACIS codes were not matched with the old SIC codes in those databases. Third, most importantly, more industries were included in the NACIS system compared to the SIC system, as can be seen in the matching tables (Appendix D). Since there was no consistency between the datasets of 89-99 and 0103, I focused on the 89-99 data. Once the matched datasets are released, new analysis can be conducted. 64

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3.2.2.2 Regulatory Tools For technology-based standards, the typology was based on Wagner's (1999) survey. As discussed above, states may adopt standards that are broader in scope and/or more stringent than the federal requirements. For example, Florida and Georg regulated mercury as an additional hazardous waste in their RCRA program, while Colorado and Kansas did not regulate any additional hazardous wastes. Each state's fee systems were based on the surveys of Wagner (1999) and HTRWCE (2002). For instance, Nevada levied hazardous waste fees from the treatment, storage, and disposal facilities (TSDFs). However, Ohio's fees were designed for the transporters. As in HTRWCE's system, both Nevada and Ohio were in the category of states that levied hazardous waste management fees and direct treatment disposal fees. As for the permit systems, they were also based on the survey of Wagner (1999). For example, in Florida, there were no fee systems. In Illinois, transporters needed to apply permits before operating. In Maryland, both generators and transporters were required permits. In addition, more rating systems were utilized, which include: ( 1) the "Green Index," (2) the levels of fees charged by state governments (Appendix E), and (3) the sizes of facilities and the production capacities of the chemical industry in the states (Table G.l, Table G.2, and Table G.3). Based on these rating systems, the variations within and among the groups such as the state governments' eagerness and 65

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willingness to enforce the regulations, the relative degree of regulatory assertiveness of the states, and the size and development of the industry could be revealed and controlled. Accordingly, detailed and in depth explanations of the relative performance of the regulatory tools could be offered. 3.2.2.3 Contextual Variables Contextual variables were gathered from a variety of surveys and databases. The state RCRA SEPs were based on the survey done by the Association of State and Territorial Solid Waste Management Officials (ASTSWMO, 1997). Data for the R&D funds by company, the R&D funds by the governments, the number of R&D performing companies, and the pollution reduction R&D funds by the governments and industry were gathered from the datasets provided by the Industrial Research and Development Information System (IRIS) of the National Science Foundation. The number of third-party treatment facilities in each state was calculated based on the RCRAinfo/RCRIS and BRS databases. These databases contain detailed information about the treatment facilities that import solid and hazardous wastes from other facilities. Technical assistance is one of the major environmental policy tools used by the governments (U.S. Congress, 1995). It is the additional/new technical knowledge provided by the federal and/or local governments to the facilities to innovate the existing technologies (U.S. Congress, 1995; O'Leary, Durant, Fiorino, and Weiland, 66

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1999). According to the EPA, the major technical knowledge and assistance to the industries come from the publications of its technical support centers. Hence, the data for the number of technical assistance was obtained by calculating the number of the hazardous waste related articles published and posted on the centers' websites. Detailed information of the data sources is presented in Table 3 .1. Table 3.1 Research Data and Sources Data Agency or Source or Publishing Data Author EPA htto://www.eoa.gov/eoaoswer/hazwaste/data/#brs BRS Data The Righthttg:/ /www .rtknet.orginew/brs/ to-Know Network RCRAinfo EPA htto://www.eoa.gov/enviro/htmllrcris/rcris querv iava.html The Rightht!Q://www.rtknet.orginew/rcris/ I RCRIS Data to-Know Network ASTSWMO Supplemental Environmental Projects (SPEs): Survey of (1997) states and territories. Washington DC: ASTSWMO. Wagner, The Complete Guide to the Hazardous Waste Regulations. Travis P. New York: John Wiley & Sons, Inc. State (1999). Regulations HTRWCE Report on Treatment, Storage & Disposal Facilities (2002) (TSDFs) for hazardous, toxic, and radioactive waste. US Army Corps of Engineers, Retrieved April, 2005 from httg :/ /www .environmental. usace.army.mil/libriDIQubs/tsdf/ tsdf.html National htto://www.nsf.gov/sbe/srs/iris/histon: data.cfin R&D Data Science Foundation 67

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Table 3.1 (Cont.) Data Agency or Source or Publishing Data Author Hazardous Substance Technical Liaisons http://epa.gov/osplhstl.htm National Environmental Publications Information System (NEPIS) http://www .epa.gov/nepis/ National Service Center for Environmental Publications (NSCEP) EPA htffi:/ /www .epa.gov/ncepihorn/ Technical Pollution Prevention Information Clearinghouse (PPIC) Assistance http://www .epa. gov/ opptintrllibrarv/ppicindex.htm Pollution Prevention Technical Assistance http://www .epa. gov /p2/ assist/index.htm Publications on the EPA Site http://www .epa. gov I epahome/pub lications2 .htm Technical Support Projects http://www.eoa.gov/tio/tsp/index.htm CLU-IN Hazardous Waste Technology Innovations htto:/ /www .clu-in.org/oub 1.cfm 3.2.3 Data Measurements For hypotheses 1, there were two sets of independent variables that served two statistical procedures separately. The first independent variable was a nominal variable, which indicated before and after the utilization of more stringent technology-based standards. The dividing point was 1995, the implementation of the Hazardous Waste Minimization and Combustion Strategy (HWMCS) and the Hazardous Waste Minimization National Plan (HWMNP) of 1995 (EPA, 1996) that updated and strengthened the standards under RCRA. The second was also a nominal 68

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variable, which included (1) states that did not utilize additional standards and (2) states that utilized additional standards. The dependent variable was an interval variable the rate of solid and hazardous waste reduction. It was calculated not by the actual volume of waste reduction, but by the rate between the reduced waste and total waste. The higher the rate, the more proactive and effective the states/regulatory tools were. This was to account for possible growth in the chemical industry in a given state as a confounding variable. Also, a positive rate indicated waste volume growth, while a negative rate represented waste volume reduction. The time span for BRS database was from 1989 to 1999. For hypotheses 2, the independent variable was a nominal variable, namely, the types ofhazardous fees. Based on Wagner's (1999) study, the fees were divided into three types: ( 1) states that did not utilize fees, (2) states that partially utilized fees, and (3) states that fully utilized fees. However, based on the survey of the Hazardous, Toxic and Radioactive Waste Center of Expertise (HTRWCE, 2002), the fee systems were divided into five: (1) no taxes or fees imposed; (2) hazardous waste management fees but no direct treatment or disposal fees; (3) hazardous waste management fees and direct treatment disposal fees; ( 4) direct treatment or disposal fees; and (5) direct treatment or disposal fees that also specifically target out-of-state waste. Separate statistical analyses were administered based on the two systems. The dependent variable was an interval variable the rates of solid and hazardous waste reduction based on the BRS database. 69

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For hypotheses 3, again, the independent variable was a nominal variable, namely, the three types of permit systems: did not issue permits, partially issued permits, and fully issued permits to generators and transporters. The dependent variable was an interval variable the rates of solid and hazardous waste reduction based on the BRS database. Lastly, the independent variable measurements for hypothesis 4, 5, and 6, as mentioned above, were: First, nominal variables: technology-based standards, hazardous waste fees, generator/transporter permits, state SEPs, and SEPs importance. For state SEPs and SEPs importance, they indicated whether the state has the projects or not; and whether the state regards SEPs as important or not. Second, interval variables: the R&D funds of the chemical industry; the number of third-party treatment facilities, and the number of technical assistance. The dependent variable, again, was an interval variable the rates of solid and hazardous waste reduction based on the BRS database. The summary of the data type and description is showed in Table 3.2 below. Table 3.2 Variable Type and Description Independent Data Type Description Variables State Nominal 50 states and District of Columbia Technology-based Nominal States with or without additional standards Standards Hazardous Waste Nominal 3 types of fees by Wagner (1999) Fees Wagner Hazardous Waste Nominal 5 types of fees by HTRWCE (2002) FeesHTRWCE 70

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Table 3.2 (Cont.) Independent Data Type Description Variables Generator or Nominal 3 types of permits by Wagner (1999) Transporter Permits SEPs Nominal State Supplemental Environmental Projects SEPs Importance Nominal The importance of SEPs recognized by each state RCRIS Third Party Interval The average number of third party treatment Treatment Facilities facilities in each state The average of total R&D funds (in millions of Total R&D Funds Interval dollars) to each state (1985-2001), including federal and company Fed R&D Funds Interval The average of federal R&D funds (in millions of dollars) to each state (1985-2001) Comp R&D Funds Interval The average of company R&D funds (in millions of dollars) by state (1985-2001) The average of chemical industry R&D funds CIR&DFunds Interval (in millions of dollars) by major state (19852001) Dependent Data Type Description Variables BRS Reduction The average of reduction rates calculated by the Rate Interval total volume of waste in each state/year ( 19891999) BRS Pre Reduction Interval The average of pre reduction rates of each state Rate (1989-1995) BRS Post Interval The average of post reduction rates of each state Reduction Rate (1995-1999) 3.3 Statistical Analysis To test the hypotheses, the following statistical procedures were used. First, for hypotheses 1, two t-test procedures were exercised. The first was a pairedsamples t-test procedure and the second was an independent-samples t-test. The former computed the mean difference between the reduction rates before and after the 71

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implementation of HWMCS and HWMNP of 1995. The latter compared the reduction rates between states that utilized and did not utilize additional (broader and/or more stringent) standards. Second, procedures of one-way ANOVA were utilized for hypotheses 2 and 3. The purpose of this statistical method was to test whether the means of reduction rates of different types of fee I permit systems were equal. If the differences existed, post hoc tests could be used to verify which means were significantly different. Third, for hypotheses 4, 5, and 6, procedures of multiple regression analysis were exercised. The regression analyses estimated the coefficients of the linear equation (one or more independent variables or predictors) that best predict the value of the dependent variable. The equation was as follows: Y= a.+PtXt+ PzXz+P3X3+ P4X..+PsXs+ ei Where: Y: Solid and hazardous waste reduction rate a: Intercept p: Coefficients X1 : Vector of regulatory tools X2 : Vector of R&D activities X3: SEPs X.: Third-party treatment facilities X5 : Technical assistance by the governments ei: The error or residual term 72

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4. Results and Findings Based on the data collected from the sources, hypotheses were tested through the utilization of computer statistical program SPSS 13.0. Also, research results and findings were organized into three sections: general trends and state solid and hazardous waste status, hypothesis testing, and additional analysis. For detailed descriptions of the variables, data types, and data conversion procedures, please refer to Table 3.2 and Appendix F. 4.1 General Trends and State Solid and Hazardous Waste Status To obtain a big picture of the trends and current status of solid and hazardous waste, time series data and geographical data were analyzed. Analyzing the national trends would help realize whether the data had certain patterns and/or directions or not. The trends analyzed were: (1) BRS waste volumes and reduction rates from 1989 to 1999; (2) R&D funds from 1989 to 2001; (3) the number of technical assistance from 1988 to 2002; and (4) the number of third party treatment facility from 1989 to 1999. For state status, the analysis was to understand and to rank the capacity of the chemical industry in each state. The rankings included: (1) the rankings of waste volume, the rankings of the number of facility, and the rankings of waste volume per 73

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facility, based on BRS data from 1989 to 1999; (2) the rankings of different R&D funds from 1989 to 2001; and (3) the rankings of the number of third party treatment facility based on RCRIS data from 1989 to 1999. With these rankings, we may obtain a better understanding in terms of the "dirtiness" of each and every state. More importantly, additional analyses were conducted based on these rankings, which are presented in the third section of this chapter. A summary of the directions of the trends is showed in Table 4.1 below. The figures ofthe trends and the tables of state capacity and status can be found in Appendix G. 4.1.1 General Trends 4.1.1.1 BRS Waste Volumes and Number of Facility from 1989 to 1999 The trend of BRS waste volumes and number of facility are demonstrated in Figure G.1 and G.2. The trends revealed an interesting situation: by setting different baseline years, the direction of the trends would be different. In other words, if we set 1989 as the baseline year, they would show an overall increasing pattern. However, ifwe neglected 1989 and set 1991 as the baseline year, the trends would become decreasing trends. The different direction of the trends may lead to different policy implications. And a clearer pattern can only be obtained when new data are 74

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released. In this research, I set the baseline year in 1989 in order to cover the full spectrum of data released by the EPA. 4.1.1.2 R&D Funds from 1989 to 2001 Chemical industry related R&D data included: federal and company R&D funds, federal and company pollution reduction funds, R&D performing company funds, company R&D contract out funds, and the number of R&D company. As illustrated from Figure G.3 to Figure G.5, we may observe that chemical companies were the major supporter and source of R&D funds. Compared to the companies, the federal government's funds were minimal. Similar situation could be found in the category of pollution reduction funds, which is showed from Figure G.6 to Figure G.8. As for the trend direction, data with an increasing trend included: federal R&D funds, company R&D funds, federal pollution reduction funds, R&D performing company funds, and company R&D contract out funds. Conversely, data with a decreasing trend were: company pollution reduction funds and the number of R&D company. 4.1.1.3 Technical Assistance and Third Party Treatment Facilities According to the publications on the EPA websites, the trend ofthe number of technical assistance from 1988 to 2002 is presented in Figure G .12. In the figure, we 75

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may find that the trend was an increasing trend. As for the number of third party treatment from 1989 to 1999, the data from the RCRAinfo and RCRIS databases is illustrated in Figure G.13. The trend was a decreasing trend, though the number in 1989 was relatively small. Table 4.1 Directions of the General Trends Increasing Trends Decreasing Trends BRS Waste Volume BRS Number of Facility Federal R&D Funds Company Pollution Reduction Funds Company R&D Funds The Number of R&D Company Federal Pollution Reduction Funds R&D Performing Company Funds Company R&D Contract Out Funds The Number of Technical Assistance The Number of Third Party Treatment Facility 4.1.2 State Solid and Hazardous Waste Capacity and Status As previously mentioned, the rankings of status capacity and status included: (1) the rankings of waste volume, the rankings of the number of facility, and the rankings of waste volume per facility, based on BRS data from 1989 to 1999; (2) the rankings of different R&D funds from 1989 to 2001; and (3) the rankings of the number of third party treatment facility based on RCRIS data from 1989 to 1999. To improve the readability, the lengthy tables are listed in Appendix G. The numbers in 76

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the tables are the averages of certain time span of each state. Also, a negative rate in the tables indicates waste volume reduce, while a positive rate shows waste volume mcrease. 4.2 Hypothesis Testing To answer the research questions, hypotheses were tested based on the statistical results. Among the six hypotheses, Hypothesis 1 was confirmed and Hypotheses 2, 3, 4, 5, and 6 were not confirmed. In the original design, technical assistance was a contextual variable for H4 to H6. However, due to the limitation of the data type (time series data, and could not be broken down by state), it was not included in the hypothesis testing and was put into the section of additional analysis. The summary of the hypotheses, statistical procedures, and testing results are listed in the end of this section (Table 4.15). 4.2.1 Descriptive Statistics and Assumption Tests 4.2.1.1 Descriptive Statistics The descriptive statistics are listed from Table 4.2 to 4.4. Table 4.2 presents the raw data ofBRS database. Table 4.3 demonstrates the descriptive statistics for nominal variables, which include technology-based standards, fees, permits, SEPs, and SEPs importance. The table contains the case numbers and percentages of each and every variable. Table 4.4 shows the descriptive statistics for interval variables, 77

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which are RCRIS third party treatment facilities, total R&D funds, and BRS reduction rates. Table 4.2 BRS Raw Data Summary States and Washington D.C. Valid Missing Total N Percent N Percent N Percent 89BRS 43 84.3% 8 15.7% 51 100.0% 91 BRS 48 94.1% 3 5.9% 51 100.0% 93 BRS 48 94.1% 3 5.9% 51 100.0% 95BRS 46 90.2% 5 9.8% 51 100.0% 97BRS 45 88.2% 6 11.8% 51 100.0% 99BRS 44 86.3% 7 13.7% 51 100.0% Table 4.3 Descriptive Statistics for Nominal Variables Variable Description N Percent Technology-Based No Additional Standards 28 54.9 Additional Standards 23 45.1 Standards Total 51 100 No Fees 12 23.5 Solid and Hazardous Partial Fees 11 21.6 Waste Fees, Wagner Full Fees 28 54.9 Total 51 100 No Fees 4 7.8 Hazardous Waste Management 12 23.5 Fees (HWMFs) Solid and Hazardous HWMFs but no Direct Treatment or 17 33.3 Disposal Fees (DTDFs) Waste Fees, HTRWCE DTDFs 13 25.5 DTDFs that also Specifically Target 5 9.8 Out-of-State Waste Total 51 100 No Permits 28 54.9 Generator and Partial Permits 18 35.3 Transporter Permits Full Permits 5 9.8 Total 51 100 78

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Table 4.3 (Cont.) Variable Description N Percent No SEPs 9 26.5 SEPs SEPs 25 73.5 Total 34 100 Not a High Priority 13 40.6 SEPs Importance High Priority 19 59.4 Total 32 100 Table 4.4 Descriptive Statistics for Interval Variables Variable N and Percent Min. Max. Mean SD Description Valid Missine: Total RCRIS Third Party 44 7 51 I 46 6.368939 7.4205304 Treatment 86.3% 13.7% 100% Facilities Total R&D 51 0 51 14.29 27178.57 2530.163 4445.205 Funds 100% 0% 100% BRS 48 3 51 Reduction 94.1% 5.9% 100% -.7834 183.0471 9.005025 23.1566688 Rate BRS Pre Rate 48 3 51 -.7834 229.8129 13.447841 38.0745760 94.1% 5.9% 100% BRS Post 45 6 51 -.4321 57.1838 1.707168 8.5474093 Rate 88.2% 11.8% 100% 4.2.1.2 Assumption Tests Also, to ensure sound statistical results, data must meet certain assumptions. The major assumption for independent-samples t-tests and one-way ANOV A is homogeneity of variance-the variance within each of the populations is equal. For regression analysis, the major assumptions are homoscedasticity and multicollinearity. The former indicates that all observations have constant (equal) 79

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variances, while the latter requires no exact linear relation exists between any subset of explanatory variables. The results of Levene's test ofhomogeneity of variance fort-test statistics (F=l2.591, p=.OOI) suggested that the homogeneity assumption was not met. Therefore, the statistics in the row labeled "Equal variances not assumed" should be used for hypothesis testing (Table 4.1 0.2). However, as can be seen in the table, the hypothesis testing results were the same (significant) with or without assuming equal variances. Consequently, we may safely say that even if the assumption was violated, it was not drastically affecting the results. For one-way ANOVA statistics, the results of Welch's tests suggested that the assumption was not violated. The testing results for the fee systems were: Wagner's system (Welch statistic= 2.282, p=.l41) and HTRWCE's system (Welch statistic= 665, p=.637). For Wagner's permit system, the results were: Welch statistic= 2.639, p=.088. Since the null hypothesis of the tests could not be rejected, it indicated that the assumption of equal variance was met. As for the assumptions for regression statistics, the results also suggested that they were not violated. As showed in Table 4.5 and Table 4.6, the p-values of the variables in the heteroscedasticity test were greater than .05. Therefore, the results resumed homoscedasticity. The collinearity tests revealed a similar result. As can be seen from Table 4.7 and Table 4.8, the values of the variance-inflation factor (VIF) were less than 4 (VIF>=4 is an arbitrary but common cut-of criterion). This indicated 80

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that multicolinearity was not a problem. Accordingly, based on the assumption tests above, we may argue that the statistical results of hypothesis testing in this study were valid. Table 4.5 Heteroscedasticity-Consistent Regression Results, Wagner's Fee System Coeff SE(HC) t P>ltl Constant 34.2867 18.4592 1.8574 .0714 Technology-Based -9.4302 6.8167 -1.3834 .1751 Standards Fees (Wagner) -7.3205 7.0890 -1.0326 .3087 Permits -9.1226 6.7929 -1.3430 .1877 SEPs 6.3551 9.7830 .6496 .5201 SEPs Importance -21.1494 16.1566 -1.3090 .1988 RCRIS Third Party -.2355 1.2682 -.1857 .8537 Treatment Facilities Total R&D .0004 .0008 .4617 .6471 Table 4.6 Heteroscedasticity-Consistent Regression Results, HTRWCE's Fee System Coeff SE(HC) t P>ltl Constant 36.8162 23.3568 1.5763 .1237 Technology-Based -9.5042 7.2008 -1.3199 .1952 Standards Fees {HTRWCE) -5.2433 6.5172 -.8045 .4264 Permits -7.9100 6.4043 -1.2351 .2248 SEPs 3.3546 10.1038 .3320 .7418 SEPs Importance -19.6392 15.8681 -1.2376 .2239 RCRIS Third Party -.3892 1.4461 -.2691 .7894 Treatment Facilities Total R&D .0004 .0008 .5586 .5799 81

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Table 4.7 Multicollinearity Test Results, Wagner's Fee System Collinearity Statistics Predictors Tolerance VIF Technology-Based .923 1.083 Standards Fees .843 1.186 Permits .826 1.210 SEPs .784 1.275 SEPs Importance .863 1.159 RCRIS Third Party .848 1.179 Treatment Facilities Total R&D .756 1.323 Table 4.8 Multicollinearity Test Results, HTRWCE's Fee System Collinearity Statistics Predictors Tolerance VIF Technology-Based .919 1.088 Standards Fees .841 1.190 Permits .818 1.222 SEPs .848 1.179 SEPs Importance .804 1.243 RCRIS Third Party .850 1.177 Treatment Facilities Total R&D .765 1.307 4.2.2 Hypothesis 1 HI: The government's stringent technology-based standards will promote the reduction of solid and hazardous waste. 82

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Hypothesis 1 was tested by two statistical procedures. The first was a pairedsamples t-test procedure and the second was an independent-samples t-test. The former computed the mean difference between the reduction rates before and after the implementation of HWMCS and HWMNP of 1995 (EPA, 1996). The latter compared the reductiOif rates between states that utilized and did not utilize additional (broader and/or more stringent) standards (Wagner, 1999). The statistical results for Hypothesis 1 are listed in Table 4.9 and 4.10 consecutively. As showed in Table 4.9 and 4.1 0, Hypothesis 1 was confirmed. The paired differences between the two means were statistically significant: the two-tailed significance test indicated that the significance level p was less than 5% (t=2.022, p<.05). Similar result could be found from the independent-samples t-test (t=2.166, p<.05). Therefore, the null hypothesis can be rejected with confidence. Table 4.9 Hypothesis 1 Paired Samples T-Test Results, State Reduction Rate Differences Pairs Mean N SD SE Mean t df BRS Pre 13.922906 45 39.269836 5.8540015 Reduction Rate BRS Post 1.707168 45 8.5474093 1.2741725 Reduction Rate Paired 12.215738 40.523461 6.0408809 2.022 44 Differences *p<.05; **p<.01; ***p<.001 83 Sig. (2-tailed) .049*

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Table 4.1 0.1 Hypothesis 1 Independent-Samples TTest Results, Additional Hazardous Waste Standards Std. Error N Mean Std. Deviation Mean No Additional 25 15.451706 30.5475585 6.1095117 Standards Additional 23 1.997764 5.3887932 1.1236411 Standards Table 4.1 0.2 Hypothesis 1 Independent-Samples TTest Results, Additional Hazardous Waste Standards t-test for Equality of Means Sig.(2Mean Std. Error t df tailed) Difference Difference Equal variances 2.081 46 .043* 13.4539421 6.4654321 assumed Equal variances not 2.166 25.619 .040* 13.4539421 6.2119806 assumed *p<.05, **p<.01, ***p<.001 4.2.3 Hypothesis 2 H2: There will be significant differences in the performance of solid and hazardous waste reduction among the states that utilize different hazardous waste fee systems. This hypothesis was tested by using the one-way ANOV A procedures. The purpose of the statistical procedures was to test whether the means of reduction rates of different types of fee systems were equal. If the differences existed, post hoc tests could be used to verify which means were significantly different. In this hypothesis, 84

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Wagner (1999) and HTRWCE's (2002) hazardous waste fee systems were analyzed separately. The statistical results are listed in Table 4.11.1 and Table 4.11.2. As showed in the tables, Hypothesis 2 was not confirmed. For both hazardous waste fee systems, the mean differences between groups were not statistically significant: Wagner's system, F=2.525, p>.05; HTRWCE's system, F=.624, p>.05. Table 4.11.1 Hypothesis 2 OneWay ANOV A Results, Average Reduction Rates of States with Different Hazardous Waste Fees, Wagner's Fee System No Fees Partial Fees Full Fees F Sig. _ili=l2} (N=ll) (N=28) BRS Reduction 14.665310 18.389766 2.892326 2.525 .091 Rates Table 4.11.2 Hypothesis 2 OneWay ANOV A Results, Average Reduction Rates of States with Different Hazardous Waste Fees, HTRWCE's Fee System 0 F Si BRS Reduction 18.285578 3.118691 Rates 7.012037 15.218649 6.328521 .659 .624 0) no taxes or fees imposed, I) hazardous waste management fees and direct treatment disposal fees, 2) hazardous waste management fees but no direct treatment or disposal fees, 3) direct treatment or disposal fees, and 4) direct treatment or disposal fees that also specifically target out-of-state waste. 4.2.4 Hypothesis 3 H3: There will be significant differences in the performance of solid and hazardous waste reduction among the states that issue, partially issue, and issue no permits to generators and transporters. 85

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Hypothesis 3 was also tested by utilizing the one-way ANOVA procedure. The independent variable (three permit systems) was based on Wagner's (1999) survey. The dependent variable (reduction rates), again, was computed according to the BRS database. The testing results are listed in Table 4.12. And as can be seen from the table, Hypothesis 3 was not confirmed (F=1.573, p>.05). Table 4.12 Hypothesis 3 OneWay ANOV A Results, Average Reduction Rates of States with Different Permit Systems No Permits Partial Permits Full Permits F Sig. (N=28) (N=18) (N=S) BRS Reduction 13.972277 3.431512 1.253063 1.573 .218 Rates 4.2.5 Hypotheses 4 to 6 H4: Technology-based standards are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. H5: Hazardous waste fees are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. H6: Permits are more likely to have stronger effects on the reduction of solid and hazardous waste than other contextual variables. Hypotheses 4 to 6 were tested by regression analysis. Regression analysis estimates the coefficients of the linear equation (regulatory tools and other contextual variables) that best predict the value of the dependent variable (waste reduction rate). 86

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To test the hypotheses, two regression analysis procedures were exercised that based on the two waste fee systems. For each procedure, two tables were generated. The ANOV A table was an overall significance test that assessed whether the independent variables had a statistically significant relationship with the dependent variable. For the ability of each and every independent variable to predict the dependent variable, the results were demonstrated in the coefficients table. Hypothesis testing was based on the coefficients tables. In order to conduct regression analysis, I recoded the two fee systems and permits into dummy variables. Namely, I recoded the variables of fees and permits into 0 and 1: states that did not utilize fees/permits as 0, and states that utilized a variety of fees/permits as 1. The statistical results of regression analyses after recoding are listed in Table 4.13 and Table 4.14. As can be seen from Table 4.13.2 and 4.14.2, Hypothesis 4 (t=-1.622, p>.05; t=-1.619, p>.05), Hypotheses 5 (t=-1.058, p>.05; t=-.138, p>.05), and Hypothesis 6 (t=-1.432, p>.05; t=-1.368, p>.05) were not confirmed. Also, the results showed that the importance of the SEPs recognized by the state was the only significant predictor associated with waste reduction (t=-2.846, p<.05; t=-2.708, p<.05). 87

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Table 4.13 .1 Hypothesis 4 to 6 Multiple Regression Results, ANOV A (b), Based on BRS Data and Wagner's Fee System Sum of Squares df Mean Square F Sig. Regression 7005.459 7 1000.780 2.365 .039(a)* Residual 18197.413 43 423.196 Total 25202.872 50 a. Predictors: (Constant), Comp Total R&D, Technology-Based Standards, Hazardous Waste Fees, SEPs Importance, RCRIS Third Party Treatment, Supplemental Environmental Projects, Pennits b. Dependent Variable: BRS Reduction Rate *p<.05, "'*p<.Ol, ***p<.OOI Table 4.13.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a), Based on BRS Data and Wagner's Fee System Predictors B SE Beta t Sig. (Constant) 30.664 8.829 3.473 .001 Technology-based Standards -9.773 6.025 -.219 -1.622 .112 Hazardous Waste Fees -7.824 7.394 -.149 -1.058 .296 Permits -9.119 6.368 -.204 -1.432 .159 Supplemental Environmental 10.514 8.533 .180 1.232 .225 Projects SEPs Importance -20.255 7.116 -.397 -2.846 .007** RCRIS Third Party -.254 .459 -.078 -.554 .582 Treatment Facilities Total R&D .000 .001 .070 .472 .640 a. Dependent Vanable: BRS ReductiOn Rate, *p<.05, **p<.Ol, ***p<.OOI Table 4.14.1 Hypothesis 4 to 6 Multiple Regression Results, ANOV A (b), Based on BRS Data and HTRWCE's Fee System Sum of Squares df Mean Square F Sig. Regression 6539.912 7 934.273 2.153 .058(a) Residual 18662.960 43 434.022 Total 25202.872 50 a. Predictors: (Constant), Comp Total R&D, Technology-Based Standards, Hazardous Waste Fees, Supplemental Environmental Projects, RCRIS Third Party Treatment, SEPs Importance, Permits b. Dependent Variable: BRS Reduction Rate *p<.05, **p<.Ol, ***p<.OOI 88

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Table 4.14.2 Hypothesis 4 to 6 Multiple Regression Results, Coefficients (a), Based on BRS Data and HTRWCE's Fee System Predictors 8 SE Beta t Sig. (Constant) 26.172 11.581 2.260 .029 Technology-based Standards -9.901 6.116 -.222 -1.619 .113 Hazardous Waste Fees 1.628 11.835 .020 .138 .891 Permits -8.980 6.481 -.201 -1.386 .173 Supplemental Environmental 7.525 8.308 .129 .906 .370 Projects SEPs Importance -20.210 7.464 -.396 -2.708 .010** RCRIS Third Party -.299 .464 -.092 -.644 .523 Treatment Facilities Total R&D .000 .001 .048 .320 .751 a. Dependent Variable: BRS Reduction Rate, *p<.05, **p<.Ol, ***p<.OOI 4.2.6 Summary of Hypothesis Testing Results The testing results for the six hypotheses are listed in Table 4.15. Table 4.15 Summary ofHypothesis Testing Results Results Hypothesis Statistical Method Fee Confirmati Database System on 1. Government's stringent technologybased standards will promote the T-Test BRS Confirmed reduction of solid and hazardous waste. 2. There will be significant differences in the performance of solid and Wagner Not hazardous waste reduction among the One-Way BRS Confirmed states that utilize different hazardous ANOVA waste fee systems. HTRWCE Not Confirmed 3. There will be significant differences in the performance of solid and hazardous waste reduction One-Way BRS Not among the states that issue, partially ANOVA Confmned issue, and do not issue permits to generators and transporters. 89

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Table 4.15 (Cont.) Results Hypothesis Statistical Method Fee Confirmati Database System on 4. Technology-based standards are Not more likely to have higher effects on Wagner Confirmed the reduction of solid and hazardous Regression BRS waste than other contextual variables. HTRWCE Not Confirmed 5. Hazardous waste fees are more Not likely to have higher effects on the Wagner Conftrmed reduction of solid and hazardous Regression BRS waste than other contextual variables. HTRWCE Not Confirmed 6. Permits are more likely to have Not higher effects on the reduction of Wagner Confirmed solid and hazardous waste than other Regression BRS contextual variables. HTRWCE Not Confirmed 4.3 Additional Analysis In addition to the statistical procedures for hypothesis testing, I conducted several statistical analyses based on the state chemical industry capacity and the trends data. The results of these analyses could be regarded as supplemental proof to the findings above. 4.3.1 State Chemical Industry Capacity and Performance 4.3.1.1 Correlations between Variables The variables relating to state capacity and performance were: total waste volume, the number of facilities, the number of third party treatment facilities, R&D 90

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funds, and waste reduction rates. The analysis below was to realize the relationships between these variables. Since the data were interval data, Pearson correlation should be a proper statistical procedure to serve the purpose. The statistical are listed in Table 4.16. Table 4.16 Pearson Correlations, BRS Data and State Data BRS BRS RCRIS Fed Comp Total BRS Reductio Waste Third Party Total Total R&D Numbe n Rate Volume Treatment R&D R&D r of Facility BRS 1 -.117 -.162 -.134 -.089 -.096 -.140 Reduction .427 .306 .365 .550 .514 .342 Rate 48 48 42 48 48 48 48 BRS Waste 1 .879*** .088 .204 .212 .459** Volume .000 .539 .151 .135 .001 51 44 51 51 51 51 RCRIS 1 .231 .341 .346* .616*** Third Party .132 .023 .021 .000 Treatment 44 44 44 44 44 Fed Total I .855*** .858*** .520*** R&D .000 .000 .000 51 51 51 51 Comp Total I .991 *** .734*** R&D .000 .000 51 51 51 Total R&D I .714*** .000 51 51 BRS I Number of Facility 51 a. Stg. (2-tatled) b. Case Number *p<.05 **p<.Ol ***p<.OOI Some interesting results could be found in this analysis: none of the relationships between the (contextual) variables and reduction rate was significant (second row). This indicates that there was little or zero linear association between 91

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the variables. In other words, a state's solid and hazardous waste reduction performance did not associate with the state's chemical industry capacity, no matter how many facilities the state had, how many tons of waste the facilities generated, and how many third party treatment facilities the state had. In the same vein, the results suggested that there was no significant relationship between a state's solid and hazardous waste reduction performance and how much money the state and its chemical industry have invested in R&D. The results seemed to be consistent with the hypothesis testing results for contextual variables above. More importantly, compared to other more apparent or common sense relationships in the tables, such as the relationships between the number of facility and the hazardous waste volume, the failure to pass the significance tests for these correlations seemed to encourage and trigger us to conduct further studies in order to find other important factors relating to solid and hazardous waste reduction. 4.3.2 Trends Data To analyze trends data was to set the unit of analysis at the national level. In addition to the variables used in the previous section, more variables were included for this analysis. They were: chemical industry R&D performing company funds, R&D contract out funds, company pollution reduction funds, the number of R&D performing company, and the number of technical assistance from the EPA. These 92

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data were important contextual variables from the theoretical consideration in the literature review. Nevertheless, they were collected at the national level and could not be broken down by state. Therefore, they could only be used to analyze national status. 4.3.2.1 Correlations between Variables To realize the relationships between the variables, Pearson correlation procedures were administered. The results are showed in Table 4.17. In the table, again, I focused on the relationships between the (contextual) variables, the reduction rate, and the volume. Table 4.17 Pearson Correlations, BRS Data and National Data BRS R&D Comp Waste BRS Federal Comp R&D Contra Poll No of No of No of Red Waste R&D R&D Comp ct Out Red R&D Tech 3rd Rate Vol Funds Funds Funds Funds Funds Comp Assist Party BRS I .933* .691 -.603 -.605 .083 .475 .581 -.450 .380 Waste .021(a) .196 .281 .280 .895 .418 .304 .447 .528 Red Rate 5 5(b) 5 5 5 5 5 5 5 5 BRS I .535 .133 .173 .239 .798 .159 -.080 .615 Waste .274 .802 .743 .648 .057 .763 .880 .194 Volum 6 6 6 6 6 6 6 6 6 e Federa I .463 .443 .033 -.377 -.255 .427 -.089 I R&D .112 .129 .915 .204 .400 .145 .866 Funds 13 13 13 13 13 13 13 6 Comp I .997* .370 -.540 -.895* .765* -.398 R&D .000 .213 .057 .000 .002 .435 Funds 13 13 13 13 13 13 6 R&D I .383 -.522 -.890* .759* -.355 Comp .196 .067 .000 .003 .489 Funds 13 13 13 13 13 6 R&D I -.219 -.505 .558'" -.335 Contra .473 .079 .048 .517 ct Out 13 13 13 13 6 Funds Comp I .703* -.692* .896* Poll .007 .009 .016 Red 13 13 13 6 Funds 93

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Table 4.17 (Cont.) DRS Waste DRS Federal Red Waste R&D Rate Vol Funds No of R&D Comp No of Tech Assist No of 3rd Party a. S1g. 2-tailed; b. Case Nwnber *p<.05 Comp R&D R&D Comp Funds Funds R&D Comp Contra Poll No of No of No of ct Out Red R&D Tech 3rd Funds Funds ComD Assist Party I -.834 .623 .000 .187 13 13 6 I -.575 .232 15 6 I 6 The results for BRS reduction rate (second row, Table 4.17) were similar to that of the results at the state level. However, there was a significant relationship between waste volume and reduction rate. The sign of the correlation coefficient was positive, showing that when waste volume increased, the rate also increased. Since the dataset was an aggregated national data that did not consider the difference among states, and the BRS rate was calculated from the BRS waste volume, the significant result was not surprising. On the contrary, the interesting part was that the other variables that might have significant relationships based on the literature were failed to pass the statistical tests. Likewise, for waste volume (third row), none of the relationships was significant at the national level. 4.3.2.2 Regression Analysis In addition to the correlations, the ability of the variables to predict hazardous waste rate and volume was studied. The variables remained the same as above, and 94

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the results are listed in Table 4.18 and Table 4.19. As can be seen from the tables, none of the predictors could reliably predict both BRS reduction rate and volume. These results were similar to that of the results at the state level. Table 4.18 Regression Results, Coefficients (a), BRS Waste Reduction Rate Predictors B SE Beta t Sig. (Constant) .654 1.441 .454 .666 Federal R&D Funds .001 .001 .397 .703 .509 Company R&D Funds .000 .000 -3.995 -.771 .470 R&D Performing Company .000 .000 3.227 .631 .552 Funds R&D Contract Out Funds 9.81E-005 .000 .316 .640 .546 Company Pollution Reduction .002 .002 .511 1.295 .243 Funds Number of R&D Performing -4.75E.000 -.222 -.211 .840 Company 005 Number of Technical .000 .002 .112 .219 .834 Assistance Number of Third Party TSD .000 .001 .065 .154 .882 Facility a. Dependent Vanable: BRS Reduction Rates, *p<.05, **p<.01, ***p<.001 Table 4.19 Regression Results, Coefficients (a), BRS Waste Volume Predictors B SE Beta t Sig. (Constant) 66235367.649 122871143.399 .539 .609 Federal R&D Funds 6191.731 94404.169 .028 .066 .950 Company R&D Funds -8332.190 29889.629 -1.074 -.279 .790 R&D Performing 10302.825 27107.403 1.446 .380 .717 Company Funds R&D Contract Out 14772.157 13072.415 .415 1.130 .302 Funds Company Pollution 238474.986 152325.031 .459 1.566 .168 Reduction Funds Number of R&D 3456.816 19175.377 .141 .180 .863 Performing Company Number of Technical -70956.999 161979.419 -.166 -.438 .677 Assistance Number of Third Party 211951.023 120002.535 .553 1.766 .128 TSD Facility a. Dependent Variable: BRS Reduction Volume, *p<.05, **p<.01, ***p<.001 95

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4.3.3 Other Additional Statistical Analyses and Summary In addition to the analyses above, I have conducted independent-samples t-test procedures to compare the reduction rates between states with different SEPs options. Also, I employed UNIANOV A procedures to test whether the regulatory tools had interaction effects towards the dependent variable. The results of these tests were not statistically significant. Therefore, I decided not to include them into this chapter. In sum, the findings of the additional analyses seemed to support the results in the section of hypothesis testing. With the failure to pass the significance tests for most of the hypotheses, further studies are needed to search for more factors that could be related to solid and hazardous waste generation and reduction. Moreover, as most empirical studies in the literature review were done on the firm level and had conflicting findings, it is suggestedthat more studies can be conducted on higher levels in order to obtain a better understanding of this research field. More discussion and suggestions are presented in the concluding chapter. 96

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5. Discussion, Conclusions and Policy Recommendations 5.1 Discussion 5.1.1 Hypothesis 1: Technology-Based Standards Hypothesis 1 was tested by two statistical procedures: a paired-samples t-test procedure and an independent-samples t-test. The first procedure computed the mean difference between the reduction rates before and after the implementation of HWMCS and HWMNP of 1995 (EPA, 1996). The latter compared the reduction rates between states that utilized and did not utilize additional (broader and/or more stringent) standards (Wagner, 1999). As showed in Section 4.2.1, Hypothesis 1 was confirmed. This indicated that the government's stringent technology-based standards could be regarded as an effective policy tool to help reduce solid and hazardous waste. This result was in accordance with the theoretical arguments and empirical findings in section 2.6.1. As can be seen from Table 4.11, the two means of BRS reduction rates were positive: pre reduction rate (13.922906); post reduction rate (1.707168). This indicated that the waste volumes were actually increased over the years. However, the post rate was significantly less than the pre rate. In other words, after the 97

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implementation ofthe HWMCS and HWMNP of 1995 that set more stringent standards, the rate of waste growth has significantly reduced. Likewise, in Table 4.12.1, the two means were both positive. Yet, the rate of states that did not utilize additional standards (15.451706) was much higher than the rate of the states that utilized additional standards (1.997764). This suggested that states that adopted broader and/or more stringent standards performed much better in solid and hazardous waste reduction. Nevertheless, the results oft-tests did not exclude the influences from other confounding factors/variables. Therefore, the actual function and effectiveness of technology-based standards can only be found after analyzing with other variables. The discussion is presented in section 5.1.4 below. 5.1.2 Hypothesis 2: Solid and Hazardous Waste Fees Hypothesis 2 was tested by utilizing the one-way ANOV A procedures. The purpose of the procedures was to realize whether the means of reduction rates of different types of fee systems were equal. If the differences existed, post hoc tests could be administered to verify which means were significantly different. In this hypothesis, Wagner (1999) and HTRWCE's (2002) hazardous waste fee systems were analyzed separately. The statistical results suggested that: for Wagner's system, there were no significant differences between state governments that fully utilized, partially utilized, 98

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and did not utilize hazardous waste fees in term of waste reduction rate. That is to say, states that utilized waste fees did not perform significantly better than the states without utilizing fees. Also, there were no differences between states that fully and partially utilized fees. In the same vein, states' hazardous waste reduction performance revealed no significant differences among HTRWCE's five types of fees. Accordingly, hazardous waste fees may not be seen as an effective policy tool because states that utilized (different forms of) fees did not perform better in waste reduction. This result, apparently, was inconsistent with the theoretical arguments and empirical findings in 2.6.2. 5.1.2.1 Reasons for the Failure to Confirm the Hypothesis In order to identify the possible reasons for the failure to confirm the hypothesis, I conducted the following three analyses: First, I conducted the same one-way ANOV A statistical procedures without outliers that exceeded 3 standard deviations. The statistical results were similar to the above. Therefore, the original scores were not significantly skewed by the outliers. Second, to realize whether the results were affected by the typology (Table 5.1) ofthe fee systems, I recoded HTRWCE's systems into three: (1) no taxes or fees imposed; (2) hazardous waste management fees; and (3) direct treatment or disposal fees. Again, the hypothesis was not confirmed, which indicated that typology may not be a factor. 99

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Table 5.1 State Hazardous Waste Fee Systems Comparison Hazardous Waste Fees State Number of States Yes Arkansas, California, Colorado, Connecticut, 28 Georgia, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maine, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, New Mexico, New York, North Carolina, Oklahoma, Oregon, Pennsylvania, Tennessee, Texas, Washington, West Virginia, Wisconsin Partial: Fees either for Alabama, Idaho, Nebraska, Nevada, New 11 Landfills, Generators, Hampshire, New Jersey, Ohio, Rhode Island, South Transporters, or TSDFs Carolina, Utah, Wyoming No Alaska, Arizona, Delaware, District of Columbia, 12 Florida, Hawaii, Iowa, Maryland, North Dakota, South Dakota, Vermont, Virginia Total 51 Source:Wagner(1999) Fee I Tax Systems State Number of States Hazardous waste management Arizona, Arkansas, California, Colorado, Delaware, 17 fees and direct treatment Illinois, Kansas, Kentucky, Maine, Nevada, North disposal fees Carolina, Ohio, Oklahoma, Oregon, South Dakota, Washington, Wisconsin Hazardous waste management Florida, Indiana, Louisiana, Maryland, 12 fees but no direct treatment or Massachusetts, Mississippi, Montana, New Mexico, disposal fees Rhode Island, Tennessee, Virginia, Wyoming Direct treatment or disposal Alabama, Georgia, Idaho, Iowa, Michigan, 13 fees Minnesota, Missouri, Nebraska, Pennsylvania, South Carolina, Utah, Vermont, West Virginia Direct treatment or disposal Connecticut, New Hampshire, New Jersey, New 5 fees that also specifically York, Texas target out-of-state waste No taxes or fees imposed Alaska, District of Columbia, Hawaii, North Dakota 4 Total 51 Source: HTR WCE (2002) 100

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Third, the complexity of the fee systems may be a factor. With a thorough review of Appendix E, we may find that: (1) different types of fees were categorized in the same category of fee system. For instance, some fee items such as environmental repair fees, activity verification fees, and generator fees were all included into the hazardous waste management fees. However, some certain fees were not utilized by all of the states. (2) Fees were charged based on different units. For example, in some states, generator fees were charged by waste volume. However, in other states, similar fees were charged annually with fixed rates. And (3) the levels of fee in monetary terms were different among states within the same fee category. As a result, states' performance in solid and hazardous waste reduction may highly likely be affected by the complexity of the fee systems. For example, while a state may have low generator fees, other types of fees such as (higher) management fees or monitoring fees may play an important role in changing the facilities' behaviors. The complexity of the fee systems should be an interesting topic for future studies. Further discussion about this complexity is presented below. 5.1.3 Hypothesis 3: Generator and Transporter Permits Hypothesis 3 was also tested by using the one-way ANOV A procedure. Again, the results suggested that the waste reduction rates were not different statistically between states that utilize, partially utilize, and not utilize generator and/or transporter permits. Specifically, generator and/or transporter permits may not 101

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be regarded as an effective policy tool to help reduce solid and hazardous waste. The results were incompatible with the theories and empirical findings in section 2.6.2. 5.1.3.1 Reasons for the Failure to Confirm the Hypothesis To identify the possible reasons for this inconsistency, first, I conducted the same statistical procedure without outliers that exceeded 3 standard deviations. The results were identical and the hypothesis was not confirmed. Thus, outliers were not a factor. Second, with a quick survey of the state governments' environmental protection websites, we may find that it was relatively inexpensive to obtain a generator and/or transporter permits. The permit application procedure was also less complicated compared to other types of facility permits. Therefore, as argued by Milliman and Price (1989), free or less expensive permits may not impose heavy financial and administrative burdens to the facilities. In turn, these permits may not become an incentive for the facilities to innovate and reduce the waste volume. Third, as discussed in section 2.6.2, marketable permits were one of the most effective tools to promote innovation and waste reduction (Downing and White, 1986; Milliman and Price, 1989). However, RCRA generator or transporter permits did not seem to be tradable. It is suggested that this permit system can be converted to a more market-oriented system and allows it to become a waste control mechanism. Related suggestions and recommendations are discussed below. 102

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5.1.4 Hypotheses 4 to 6: Regulatory Tools and Contextual Variables As previously mentioned, Hypotheses 4 to 6 were tested by regression analysis. Regression analysis estimates the coefficients of the linear equation (regulatory tools and other contextual variables) that best predict the value of the dependent variable (waste reduction rate). To test the hypotheses, two regression analysis procedures were exercised that based on the two waste fee systems. The hypotheses testing results {Table 4.13 Table 4.14) suggested that: although technology-based standards could be seen as an effective tools based on the results of Hypothesis 1, they were not an effective predictor to the state governments' performance in reducing solid and hazardous waste when taking into account other contextual variables. In other words, technology-based standards may appear to be an effective factor by itself (HI). However, the actual waste reduction performance of the states may come from the combination of factors and variables {Table 4.13.1) and/or from the SEPs (Table 4.13 and 4.14). For fees and permits, again, the results suggested that they were not effective predictors towards state governments' solid and hazardous waste reduction. The explanation for this result can be found in section 5.1.2.1 and 5.1.3.1 above. As for the contextual variables, the importance of SEPs was the only effective predictor. Further discussion of this variable is presented below. 103

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5.1.4.1 The Relative Magnitude and Direction of the Regulatory Tools Although Hypotheses 4 to 6 were not confirmed, the magnitude and direction of the coefficients in Table 5.2 still revealed some interesting and important message. The beta values (weight) in the standardized coefficients column represented the relative magnitude and direction of the coefficients towards the dependent variable. For the relative magnitude, the higher the (absolute) value, the more effect the independent variable had towards waste reduction. In Table 5.2, we could find that the values of standards, Wagner's fees, and permits were relatively higher compared to other variables. This suggested that even though they were not a significant predictor, they still played a relatively important role among the regulatory tools and other contextual variables. For the directions of the standardized coefficients, they referred to the positive or negative sign of the beta values. In Table 5.2, most of the values were negative. This indicated that for every unit increase in the predictor, there was a related unit decrease (unstandardized coefficients) in the predicted waste reduction rate, holding all other constant. In the table, the signs for the regulatory tools were mostly negative, suggesting that for the states that utilized the tools, their predicted solid and hazardous waste rates would be lower. 104

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Table 5.2 Standardized and Unstandardized Coefficients from Table 4.13 and 4.14 BRS Wagner HTRWCE Predictors Standardized Unstandardized Standardized Unstandardized Coefficients Coefficients (B) Coefficients Coefficients (Beta) (Beta) (B) Technology--.219 -9.773 -.222 -9.901 based Standards Hazardous Waste -.149 -7.824 .020 1.628 Fees Generator or Transporter -.204 -9.119 -.201 -8.980 Permits SEPs .180 10.514 .129 7.525 SEPs Importance -.397 -20.255 -.396 -20.210 RCRIS Third Party Treatment -.078 -.254 -.092 -.299 Facilities Total R&D .070 .000 .048 .000 5.1.4.2 The Importance of the RCRA SEPs As can be seen from Table 5.2, SEPs importance had the highest beta values (1-.3971; l-.3961) among the predictors. This indicated that it was the most effective predictor for states' solid and hazardous waste reduction rate. Moreover, the negative signs of the values indicated that for every unit increase in SEPs importance, there was a 20.255/20.210 unit decrease in the predicted rate, holding all other variables constant. Since the variable was coded as 0/1, this result is interpreted as: for the states that regarded SEPs as a higher priority, the predicted solid and hazardous waste rate would be 20.255%/20.210% lower. 105

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As discussed in the literature review, state RCRA SEPs were projects that incorporate pollution prevention and/or waste minimization principles into their final enforcement orders. Those projects could be used as a settlement tool under RCRA (EPA, 2005). The ASTSWMO' survey (1997) showed that different states utilize different programs in their pollution prevention/waste minimization SEPs, such as training, education outreach, and environmental audits, etc. And about 67% of the respondents alleged that pollution prevention and waste minimization projects were considered a higher priority in their states. Based on the results above, state governments may need to seriously consider SEPs as an effective mechanism to help reduce solid and hazardous waste. 5.1.5 National Trends, State Status, and Additional Analysis Time series data and geographical data provided us a clear picture about the trends and current status of solid and hazardous waste. For trends data, they were collected at the national level, so they could not be used to test the hypotheses. However, they gave us a broad understanding of the national status and could be supplemental evidence to Hypotheses 4 to 6. Among the trends analyzed, the ones that demonstrated an increasing pattern include: BRS Waste Volume; BRS Number of Facility; Federal R&D Funds; Company R&D Funds; Federal Pollution Reduction Funds; R&D Performing Company Funds; Company R&D Contract Out Funds; and the Number of Technical Assistance from the EPA. Conversely, the decreasing 106

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trends were: Company Pollution Reduction Funds; the number of R&D Company; and the Number of Third Party Treatment Facility (see Table 4.1). From the results in the additional analysis, first, it was interesting or somewhat surprising to see the decreasing trends of company pollution reduction funds and the number of third party treatment facility. As chemical industries' R&D expenditures are more towards process improvement and waste reduction in recent years (Chemical Vision, 2004, 2005), these decreasing trends seemed to be the results of the increasing trends of company R&D funds and company R&D contract out funds. However, the correlation analysis results in Section 4.3.2.1 did not suggest that those correlations were statistically significant. Therefore, further studies are needed if we intend to obtain a better understanding as to why the trends were decreasing and their relationships with other variables. Second, there was an interesting negative correlation between R&D performing company funds and the number of R&D performing company (-.890, p<.001, Table 4.13). It seemed to suggest that R&D tasks tended to be concentrating on the larger or financially stronger companies. Again, since this result was not directly related to this research, it could be an interesting topic for future studies. Third, as can be seen in Section 4.3.2.1 and Table 4.18, none of the trends (contextual variables) had a significant correlation with waste reduction rate at the national level. The results were compatible with that of the findings from Hypotheses 4 to 6, and might be regarded as supporting evidence to this research. 107

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As for states' solid and hazardous waste status, first, by juxtaposing the different ranking items (Table G.l to Table G.3), we may find that the waste reduction performance for higher ranking states (in facility number and waste volume) was not necessarily worse than the lower ranking states. Vise versa, the lower ranking states did not necessarily show better reduction rates than the higher ranking states. Second, the correlation analysis in the additional analysis (Section 4.3 .I, Table 4.16) demonstrated that facility number and waste volume did not significantly associate with waste reduction rate. The results thus were consistent with the argument to use waste reduction rates as the statistical unit to account for possible growth in the chemical industry in a given state as a confounding variable. 5.2 Conclusions and Recommendations As the literature and empirical findings were controversial in terms of the relative capabilities of different regulatory tools, in the same vein, the results of this research did not provide statistically significant evidence as to which regulatory tool was more effective and more likely to relate to solid and hazardous waste reduction. Nevertheless, constructive policy suggestions and recommendations can still be offered based on the findings above. Namely, although the regulatory tools studied may not be seen as effective mechanisms, their relatively higher coefficients (magnitude and directions) still showed that they were more likely to have higher effects than other contextual variables on waste reduction. In addition, since SEPs 108

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importance was the only effective factor towards waste reduction, states governments may need to seriously consider SEPs as a regulatory tool to help reduce solid and hazardous waste. Based on these main findings, recommendations are presented below. 5.2.1 Recognize the Policy Context From a simple and straightforward point of view, to further protect the public health and the environment, states should design a program that is at least as stringent as or more stringent and/or broader in scope than the federal program. However, the actual political environment of the states may not allow such an optimistic situation to happen easily. From the considerations of the politics of interest, pluralism, and capture theory (Cortner and Moot, 1999; Hendee and Pitstick, 1992; Ingram and Wallace, 1997; Moote, McClaran, and Chickering, 1997; Sirmon, Shands, and Liggitt, 1993), we understand that environmental issues oftentimes are highly complicated with the interactions among different groups (as illustrated in the simple figure below). Therefore, the decision making for environmental issues may vary due to the contextual differences of the states. In turn, states may have various regulatory choices to address their own particular problems. By adopting a contextual and flexible approach, the governments may discover the most proper regulatory tools or combinations that best meet their needs in their complicated political environment. 109

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Chemical Industries Facilities Federal Government State Government Environmental R&D Industries Environmental Groups General Public Figure 5.1 The Interaction among Major Groups of Solid and Hazardous Waste 5.2.2 Strengthen Technology-Based Standards According to the testing results of Hypothesis 1, technology-based standards could be regarded as an effective tool. Although Hypothesis 4 was not confirmed, the relative higher coefficients still indicated that standards were a more effective factor compared to other variables. Accordingly, these results may offer a good support for the governments, especially the federal government, to remain using standards, like HWMCS and HWMNP, as the fundamental regulatory tool. 110

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In addition, based on the RCRA's state authority, a state with authorization may have a program that is more stringent or broader in scope than the EPA's. For example, a state may require annual reporting by a generator instead of the biennial reporting required by the federal RCRA program. Or a state may regulate a nonhazardous waste as a RCRA hazardous waste. As the statistical results showed that additional standards were helpful to reduce waste, it is suggested that all state governments need to adopt this approach to further protect the environment. Strengthening the regulations may enjoy the benefits of further reducing hazardous waste; promoting R&D and technology innovation; and changing the current environmental status in a more timely fashion. However, at the same time, it may cause financial burdens to the industries/facilities; administrative burdens to the government and the industries/facilities; and increase conflicts among interest groups, such as between environmental groups and the industries. Apparently, it is not feasible to ask the state governments to achieve the goals of waste reduction at all costs. The decision making process may still function as a buffer to coordinate different opinions and reach agreements. More discussion about how to achieve a balance between different regulatory approaches is presented in section 5.2.6. 5.2.3 Modify and Improve the Solid and Hazardous Waste Fee Systems Similarly, as solid and hazardous waste fees may not be considered as an effective tool from the statistical consideration, we may still discern some patterns 111

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that were in accordance with the literature and findings in section 2.6.2. As showed in Table 5.3 and 5.4 (presented in section 5.2.6 below), in general, states with fee systems had lower waste rates than that of the states without fees. Though the differences were not statistically significant, these patterns were still encouraging for the justification of utilizing this economic approach. Also, as discussed above, the complexity of the current fee systems may affect the states' performance in waste reduction. In Appendix E, we could find that: ( 1) different types of fees were categorized in the same category of fee system, (2) fees were charged based on different units, and (3) the levels of fee in monetary terms were different among states in the same category of fee system. Facing this complexity, states may collaborate with one another to design similar fee systems for a certain industry. A state can also design different fees for different industries, instead of charging a general fee to different types of generators. Moreover, if financial concern is one of the major drives to promote technology innovation and waste reduction, it is suggested that the states can increase the level of the fees to expedite the pace of innovation and waste reduction. Nonetheless, this approach may still encounter difficulties and barriers such as: financial burdens to the industries/facilities; time-consuming process to design the proper systems; and conflicts among interest groups. 112

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5.2.4 Modify and Improve the Permit Systems The research results for Hypothesis 3 and 6 revealed a similar pattern: the hypotheses were not confirmed, however, permits may still be utilized as a useful mechanism if proper modification was made. As can be seen from Table 5.5.1 and 5.5.2, states with permit systems performed relatively better in waste reduction than states without permits. The beta values (Table 5.2) in regression analysis suggested that permits were a more effective variable relating to waste reduction compared to other factors. As stated earlier, with a quick survey of the state governments' environmental protection websites, we may find that it was relatively inexpensive to obtain a permit. The application procedure was also less complicated compared to other types of facility permits. Therefore, as argued by Milliman and Price ( 1989), free or less expensive permits may not impose heavy financial and administrative burdens to the facilities. In addition, scholars alleged that marketable permits were one of the most effective tools to promote innovation and waste reduction (Downing and White, 1986; Milliman and Price, 1989). However, RCRA generator or transporter permits did not seem to be tradable. Accordingly, it is suggested that, first, state governments may increase the level of fees as a financial and administrative burden for the facilities to innovate and reduce waste. Second, state governments may convert the fees to a more market oriented system and tum them into a waste control mechanism. Again, since this tool 113

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is also an economic approach, it may face the similar difficulties mentioned in the previous section. 5.2.5 Recognize the Importance of the SEPs and Other Factors Among the contextual variables, the importance of the RCRA SEPs recognized by the state was the only reliably predictor towards solid and hazardous waste reduction. This indicates that states that recognized the RCRA SEPs as a high priority would have significant lower waste rates. As showed in the ASTSWMO' survey (1997), different states utilize different programs in their pollution prevention/waste minimization SEPs. And about 67% of the respondents alleged that pollution prevention and waste minimization projects were considered a higher priority in their states. The SEPs therefore can be regarded as a promising mechanism to help reduce hazardous waste. However, related research seems to be limited and scarce. Further studies need to be conducted in order to recognize how those programs can contribute to solid and hazardous waste reduction. From a practical consideration, it is suggested that all state governments need to implement the SEPs. Also, more resources need to be invested in order to design more programs to enrich the plans and enhance their capability in reducing waste. As for other factors/variables such as R&D funds, third party treatment facilities, and technical assistance, though statistical results suggested that they were 114

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not significantly correlated to hazardous waste reduction, efforts such as adding more funds to hazardous waste reduction R&D and conducting more studies on multiple ways to reduce certain pollutants should be helpful to further reduce waste. 5.2.6 Towards a Contextual Approach for Solid and Hazardous Waste Reduction With different geographical location, different industry capacity, and different political context, the solid and hazardous waste reduction issues in each state are highly complicated. To minimize the negative impacts when tackling the issues, it would be beneficial if we adopt a flexible and contextual approach. Accordingly, I suggest that, first, states can take an industry-oriented policy making procedure. Namely, a state may rank the level of"dirtiness" of all the chemical industries in its territory as a first step. This should be fairly easy since each state should have kept detailed "cradle to grave" information of the facilities. After the leading polluters/industries are pinpointed, the state may utilize more stringent mechanisms to regulate these industries. If the industries are a relatively powerful political figure in the state, they may strongly oppose the stringent regulations. The state government then may negotiate with the industries and choose to strengthen one of the regulatory tools (standards, fees, or permits) as a start. If the state's regulations are already extremely strict compared to other states, the government may utilize other programs or mechanisms to achieve its goals, such 115

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as public-private partnerships, voluntary waste reduction programs, require certain amount of R&D funds towards waste reduction research, technical assistance through training and education, and design new programs for state SEPs, etc. Second, states may choose a combination of regulatory tools to meet their specific needs. Although the statistical results did not endorse the capacity and usefulness of all the regulatory tools, states still need to make efforts to search for the best policy tool combinations that best fit their unique contexts. From Table 5.3 to 5.6, I list the relative performance of different regulatory tools towards solid and hazardous waste reduction. Rates with a positive sign indicate that the average waste volumes are increased. A negative sign indicates otherwise. Also, the lower the rate, the better the performance in waste reduction. These rankings should serve as a reference for state governments to choose their combinations of tools. Moreover, the function and importance of other contextual factors mentioned in this research should be chosen wisely to help further reduce the waste. Designing a proper combination of regulatory tools is a highly complicated task. However, it is believed that the hazardous waste related parties in each state should have the wisdom to tackle the issue and to minimize the conflicts. Third, due to the complexity of each state's context, it is suggested that the government should take a cautious stance and conduct changes in an incremental manner. 116

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Table 5.3 .1 Rankings of Solid and Hazardous Waste Reduction Performance, Wagner' Fee System Database Wagner Case Number Mean Rankings(a) No Fees 12 14.665310 2 BRS Partial 11 18.389766 3 Full 28 2.892326 1 a. 1 mdtcates the lower/lowest rate. The lower the rate, the better the reductton perfonnance. Table 5.3.2 Rankings of Solid and Hazardous Waste Reduction Performance, Wagner's Fee System, Recoded Database Wagner Case Number Mean Rankings(a) No Fees 12 14.665310 2 BRS Fees 39 7.263399 1 a. 1 indicates the lower/lowest rate. The lower the rate, the better the reduction perfonnance. Table 5.4.1 Rankings of Solid and Hazardous Waste Reduction Performance, HTRWCE's Fee System Database HTRWCE(b) Case Mean Rankings(a) Number 0 4 18.28578 5 BRS 1 12 3.118691 1 2 17 7.012037 3 117

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Table 5.4.1 (Cont.) Database HTRWCE(b) Case Mean Rankings(a) Number 3 13 15.218649 4 BRS 4 5 6.328521 2 a. 1 md1cates the lower/lowest rate. The lower the rate, the better the reduct10n performance. b. 0: no fees; 1: hazardous waste management fees (HWMFs); 2:HWMFs but no direct treatment or disposal fees (DTDFs); 3: DTDFs; 4:DTDFs that also specifically target out-of-state waste Table 5.4.2 Rankings of Solid and Hazardous Waste Reduction Performance, HTRWCE's Fee System, Recoded Database HTRWCE Case Number Mean Rankings(a) No Fees 4 18.285578 2 BRS Fees 47 8.215191 1 a. 1 md1cates the lower/lowest rate. The lower the rate, the better the reduct10n performance. Table 5.5.1 Rankings ofSolid and Hazardous Waste Reduction Performance, Permits Database Permits Case Number Mean Rankings(a) No Permits 28 13.972277 3 BRS Partial 18 3.431512 2 Full 5 1.253063 1 a. 1 md1cates the lower/lowest rate. The lower the rate, the better the reduct10n performance. 118

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Table 5.5.2 Rankings of Solid and Hazardous Waste Reduction Performance, Permits, Recoded Database Permits Case Number Mean Rankings(a) No Permits 28 13.972277 2 BRS Permits 23 2.957936 1 a. I mdtcates the lower/lowest rate. The lower the rate, the better the reductiOn performance. Table 5.6 Rankings of Solid and Hazardous Waste Reduction Performance, SEPs Importance Database SEPs Case Number Mean Rankings(a) No 13 22.670790 2 BRS Yes 19 5.742483 1 a. I mdtcates the lower/lowest rate. The lower the rate, the better the reduction performance. 5.3 Contributions 5.3.1 To Academia As mentioned in the literature review, most studies on the relationships between regulatory tools and waste reduction were conducted in the areas of water and air pollution control. Very little research was done in the field of solid and hazardous waste. Also, the relative capabilities between technology-based standards and economic approaches in reducing pollution were controversial. Scholars and analysts differed in their judgment as to which approach performed better in pollution 119

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reduction. Moreover, most of those studies were conducted at the firm level. Related research at the state level was fairly scant. By testing the stated hypotheses, this research helps obtain a better understanding of the relative performance of regulatory tools in reducing solid and hazardous waste in the chemical industry, identify important contextual variables relating to solid and hazardous waste reduction, bridge the research gap between regulatory tools and waste reduction, and enrich the research field in solid and hazardous waste control. 5.3.2 To State Implementing Agencies and the EPA This study provides specific suggestions to the state governments and/or other levels of government in terms of how to modify and improve regulatory tools to help further reduce solid and hazardous waste. Also, this study offered a contextual approach to the governments as to flexibly design proper mechanisms in order to enforce the state RCRA programs in the most effective manner. These suggestions, in tum, may facilitate the implementation of RCRA and help achieve the solid and hazardous waste control goals set by the Congress. 5.3.3 To the National Security The terrorist attack on September 11th, 2001 has drastically increased the sense of security in many aspects of this country. One of them is the concern of chemical terrorism. The major methods of this type of terrorist attack include using 120

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chemicals as a weapon or by attacking facilities containing toxic chemicals. To minimize the possibility of being attacked, especially in the latter method, the federal government has severely reduced the number of chemical documents accessible to the public and the terrorists. Nevertheless, this may lead to the conflicts between national security, public safety, and people's right to know (Drew, 2005; Durham-Hammer, 2004; Henderson, Henderson, Raskob, and Boatright, 2004). Namely, the general public may become more vulnerable to environmental accidents if the information that identifies hazardous materials has been removed from their access. This research, however, may offer possible remedies to the conflicts above. First, this research provides the information of each and every state's current waste status and their relative performance in reducing solid and hazardous waste. With the publication of this research, this information is accessible to the public. This information may also become the foundation for states to set up their waste reduction goals in order to maintain the health requirements. Second, by tackling the issue of waste reduction from a regulatory perspective and at the state level, this research offers a big picture and a broader pollution control mechanism for public safety compared to tackling the waste reduction issue facility by facility. Third, as mentioned above, one of the purposes of this research is to help the state governments design an effective waste reduction policy and RCRA program. This may partially address the concern of national security by reducing the damages of chemical 121

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terrorism and industrial sabotage to the minimum with the reduced solid and hazardous waste. 5.4 Limitations and Future Studies Due to the problem of missing value and the nature of data such as the number of technical assistance, some statistical calculations may not be conducted or completely correct. More accurate analysis can only be achieved until the new or more complete data are released. Also, with the constraints in time and budget, this study could not dig deeper into other interesting questions/topics such as: ( 1) the factors/reasons that prompt states to select certain regulatory tools, (2) to what extent are states using technology-related regulations in other chemical industries, and (3) the strengths and weaknesses of the states in utilizing technological environmental regulations. For future studies, in addition to answering the above three research questions, more studies are needed (1) to search for additional variables that could be related to solid and hazardous waste generation and reduction, (2) to further study the relationships between contextual variables, (3) to design new programs for the RCRA SEPs and analyze their performance in reducing waste, and ( 4) to conduct research at higher levels such as state and national level in order to obtain a better understanding of this underdeveloped research field. 122

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APPENDIX A. RCRA DEFINITIONS A.l Solid Waste Congress defined solid waste as: "Any garbage, refuse, sludge from a wastewater treatment plant or air pollution control facility, and other discarded material, including solid, liquid, semisolid or contained gaseous material, resulting from industrial, commercial, mining and agricultural operations, and from community activities" (42 U.S.C.A. (27)). However, certain categories of waste have been exempted from RCRA, which include domestic sewage and household wastes. As stated in RCRA, solid waste ... does not include solid or dissolved material in domestic sewage, or solid or dissolved materials in irrigation return flows or industrial discharges which are point sources subject to permits under of the Federal Water Pollution Control Act [33 U.S.C.A. 1342], or source, special nuclear, or byproduct material as defined by the Atomic Energy Act of 1954 [42 U.S.C.A. et seq.]" (42 U.S.C.A. (27)). Pursuant to the above, EPA defined and classified solid wastes in four ways: 1) Abandoned materials ( 40 CFR 261.2(b) ). If a material is disposed of, burned or incinerated, or treated (but not recycled) or stored before being disposed of or burned 123

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or incinerated, then the material is considered a waste. 2) Recycled materials ( 40 CFR 261.2( c)). If a material is being recycled in a manner specified in 40 CFR 261.2(c), then it is considered a waste. 3) Inherently waste-like materials (40 CFR 261.2(d)). EPA lists several materials that are considered to be inherently waste-like, which means that these materials are automatically wastes unless excluded; this category includes specific dioxins being discarded. 4) Military munitions (40 CFR 261.2(a)(4)). A.2 Hazardous Waste Solid wastes are hazardous if they meet the following criteria, and will be regulated by the more rigorous segments ofRCRA Subtitle C (42 U.S.C.A. et seq.): 1) If they meet the statutory definition ofhazardous waste. 2) Ifthey exhibit one of the four characteristics of a hazardous waste. 3) If they are named on one of the lists promulgated by EPA. 4) If they meet the "mixture rule" and/or the "derived from rule" (Bergeson, 2001; Caccavale, 1997; Plater, Abrams, and Goldfarb, 1998). The statutory definition of hazardous waste is that:" ... a solid waste, or wastes, which because of its quantity, concentration, or physical, chemical, or infectious characteristics may-(A) cause, or significantly contribute to an increase in mortality or an increase in serious irreversible, or incapacitating reversible, illness; or (B) pose a substantial present or potential hazard to human health or the environment 124

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when improperly treated, store, transported, or disposed of, or otherwise managed" (42 U.S.C.A. (5)). In addition, in another section ofRCRA, 42 U.S.C.A. (a), EPA was directed to regulate hazardous wastes if they are toxic; if they have the potential to accumulate in plants and animals; and if they are flammable and corrosive. Under this portion of the statute, EPA promulgated four criteria based on the wastes' characteristics, which include ignitability, corrosivity, reactivity, and toxicity ( 40 CFR Subpart C). Moreover, EPA produced three lists for hazardous wastes identification. I) Hazardous waste from non-specified sources, the F list. 2) Hazardous waste from specific sources, the K list. 3) Acutely and non-acutely hazardous chemicals, the P and U lists. Lastly, the "mixture rule" and the "derived from rule" are established to prevent facilities from evading regulations by diluting or changing the composition of listed waste streams. For the former, any mixture of the listed waste with another solid waste is regarded as a hazardous. For the latter, any waste derived from a listed waste through the treatment, storage, or disposal process is also deemed as a hazardous waste (Plater, Abrams, and Goldfarb, 1998). 125

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B. CASE STUDIES OF HAZARDOUS WASTE REDUCTION Table B. I Hazardous Waste Reduction Cases Title Author Abstract Case Study: Baxter DPPEA (1995) Baxter Healthcare intravenous solutions Healthcare Corporation production facility has implemented a variety of source reduction activities, including lab chemical substitution, freon cleaning elimination, solvent substitution, packaging redesign, plastic waste reuse, oil filtering and reuse, installation of a chemical inventory management system, recycling programs, and switching to wood waste as a boiler fuel. Waste reduction and annual savings calculations are included. Case Study: C & R Hard DPPEA (1995) C&R Hard Chrome and Electroless Nickel Service Chrome and Electroless is a small metal plating company. The facility Nickel Service, Inc. modified its wet-packed fume scrubbers several times to improve the capture efficiency through mist eliminators, allowing reuse of the captured waste and eliminating the off-site shipment of chromium-contaminated waste. Addition of porous pots increased chrome plating bath life. Additionally, the facility installed an electroless nickel plating line and increased its efficiency through the use of new tanks, in-tank filtration systems, a dry mesh-pad ventilations system to reduce air emissions, and replacement of nitric acid stripping solution with hydrogen peroxide, which allows nickel sulfate to be reclaimed from the wastewater. The facility received Challenge Grants from DPPEA for these projects. Waste reduction and cost savings are included. 126

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Table B.l (Cont.) Title Author Abstract Case Study: Camp DPPEA (1995) Camp Lejeune has a population of over 142,000, Lejeune Marine Corps presenting the area with waste reduction Base challenges similar to those of a small city. Waste reduction programs there have been very successful and include solvent distillation, replacing of hazardous solvents with nonhazardous, biodegradable ones, recovery and recycling of silver from photographic waste, reuse of old asphalt in new paving, recycling, and composting. Waste reduction data is included. Case Study: Cooper DPPEA (1995) Cooper Hand Tools' Lufkin facility manufactures Hand Tools-Lufkin specialty measuring tapes. Cooper Tools has Manufacturing Facility reduced their air emissions by substituting nonHAP solvents and water-based paints in their coatings, switched to better wastewater treatment chemicals, changed their chromic acid tank to nondischarge, and now filter nickel out of wastewater, reducing the hazardous waste sludge generated. Waste reduction and annual savings data are included. Case Study: Duke Power DPPEA (1995) Duke Power's facilities have implemented Corporation programs to reuse wooden cable reels and existing structures, and have switched to reusable oil absorbents, towels, and scaffolding. The maintenance program tests oil to prevent premature changing, and checks fans for wear. Hazardous waste generation has been greatly reduced through product substitution, chemical inventory control, switching to non-hazardous parts washer solvent, recycling programs, and new paint mixing and removal techniques. Waste reduction and savings data is included. 127

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Table B. I (Cont.) Title Author Abstract Case Study: Exide DPPEA (1995) Exide Electronics manufacturers uninterruptible Electronics power supplies to protect electronic equipment during power disruptions. Exide replaced their enamel painting process with a water wash system for collecting overspray (generating aqueous hazardous waste) with a urethane coating. Overspray is now collected on filters and disposed as non-hazardous solid waste. Additionally, HVLP spray guns, solvent distillation and reuse, and replacement of solvent-based varnishes with aqueous-based ones greatly reduced the facility's waste. Cost savings, solvent use, and hazardous waste reduction estimates are included. Case Study: Hamilton DPPEA ( 1995) Hamilton Beach I Proctor Silex manufacturers Beach I Proctor Silex, toasters and toaster ovens. The facility's waste Inc. reduction efforts include elimination of a halogenated solvent for parts washing/ degreasing, recycling of aqueous cleaners, reduction of hazardous wastewater sludge, water reuse, and recycling and raw materials reuse. Waste reduction and annual savings information is included. Case Study: DPPEA ( 1995) Weyerhaeuser Pulp Facility has worked to reduce Weyerhaeuser Pulp hazardous waste generation since the late 1980's Facility by switching to a citrus-based or grain-based degreasers, eliminating all PCB transformers, and scheduling regular maintenance of their vehicles. Additionally, the facility requires special permission for ordering non-standard chemicals, buys chemicals in reusable containers, recycles oil, batteries, tires, and drums, salvages metal scraps, and uses bark and wood reject as boiler fuel. Estimates of hazardous and solid waste reduction and associated cost savings are included. 128

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Table B. I (Cont.) Title Author Abstract Case Study: Marine Corp DPPEA (1996) The Marine Corp Air Station (MCAS) at Cherry Air Station at Cherry Point operates and maintains aircraft and mobile Point equipment. In response to environmental concerns and Federal Executive Order 12856 mandating a 50% reduction in toxic chemicals, the facility has implemented a variety of waste reduction programs. A Hazardous Material Control Center consolidates all reusable hazardous materials at one site and advertises them as free for use by other military bases in NC, SC, and VA. By controlling stocking, delivery, and reclamation, the facility eliminates waste management and disposal costs by preventing disposal of unused chemicals. A recycling and recovery program at the base includes steel and other metals, batteries, waste oil, wood waste, jet fuel, used solvents, and household recycling. Waste reduction and annual savings are included for the Hazardous Material Control Center and for each recycling program. Case Study: R.J. DPPEA (1996) This case study describes some ofR.J. Reynolds' Reynolds Company extensive waste reduction programs, such as switching from solvent-based to water-based coatings on packaging, recycling, solvent recovery, closed-loop solvent parts washing, use of ash waste in agricultural applications and concrete, and use of pelletized waste paper as boiler fuel. Includes annual waste reduction and savings calculations. Case Study: Thompson DPPEA (1996) Thompson Crown Wood Products manufactures Crown Wood Products wood and wood-finished cabinets. The company implement a Quality Leadership Process for employees which trains them in problem solving techniques. Teams of employees then work to solve the company's problems, including working to reduce waste generated. Ten different waste reduction projects are described, each created by an employee team, including glaze substitution, scrap waste reduction, glue application, conversion to water-based finishing, and recycling. Waste reduction and annual savings calculations for each project is included. 129

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Table B.l (Cont.) Title Author Abstract Case Study: Alcatel DPPEA (1997) Alcatel Telecommunications manufactures optical Telecommunications fiber and cable. Alcatel installed a germanium Cable recovery system in place of their original wastewater treatment facility, eliminating the release of germanium in wastewater and recovering it for sale and reuse. Also, Alcatel eliminated methyl ethyl ketone (MEKO, a solvent and hazardous compound) from their process by switching from a color coating of the fibers to including color in the fiber itself. Annual waste reduction and cost savings calculations are included. Case Study: NC DPPEA (1997) The NC Department of Transportation (DOT) Department of implemented waste reduction and recycling Transportation programs in response to the 1989 Solid Waste Management Act. The Department now recycles and reuse office supplies and buys recyclable or recycled contant products. Driver's License procedures were updated to reduce paper waste by half. The Ferry Division recycles metals, recovers oil for recycling, and is replacing creosote pilings with recycled plastic ones. The Rail Division also recycles and collects petroleum waste. The Division of Highways is working to find ways to incorporate recycled materials into road construction, such as fly ash, shingles, recycled plastics, asphalt, municipal sludge, concrete, and hog waste. Additional programs include recovery of equipment repair fluids, use of organic waste to amend roadside soils, recycling at all rest areas, roadside cleanup, "no-burn" landclearing policies, and inmate repair of small tools. 130

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Table B. I (Cont.) Title Author Abstract Case Study : North DPPEA (1997) The North Carolina National Guard Combined Carolina National Guard Support Maintenance Shop services military Combined Support vehicles from I 00 armories in NC. In response to Maintenance Shop environmental concerns and Federal Executive (CSMS) Order 12856 mandating a 50% reduction in toxic chemicals, the facility has implemented a variety of waste reduction programs. The facility installed an aqueous jet parts washer which eliminates hazardous waste from parts washing, and are testing a biodegradable solvent in regular parts washers. When vehicles come in for maintenance, the oil is tested for metals to determine if changing is required, thus reducing oil usage and labor. Used oil and antifreeze are collected and recycled. Floors are cleaned with a biodegradable cleaner and shop rags are laundered and reused. Annual savings are included Case Study : Research DPPEA ( 1997) Research Triangle Institute is a not-for-profit Triangle Institute research organization in RTP which includes several laboratory facilities. Waste reduction programs have been conducted there since 1988, including recycling programs, a Hazardous Material Committee, participation in EPA's Green Lights program, a switch to less toxic scintillation fluids, a tritium gas metering system to reduce waste and improve safety, a solvent splitter to separate low-level radioactive waste and reduce the amount of high-level waste produced, and a chemical acquisition system to alert chemical purchasers to difficultto-dispose waste and encourage the use of alternative chemicals 131

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Table B. I (Cont.) Title Author Abstract Case Study: Seymour DPPEA ( 1997) Seymour Johnson Air Force Base has implemented Johnson Air Force Base a variety of waste reduction efforts, such as purchasing a centrifuge for separation of petroleum waste from absorbent spill pads, and a centralized computer-based hazardous material tracking system for the entire base. Additionally, Seymour Johnson is constructing a new building under Green Building specifications, which require the contractor to divert 75% of waste from landfills through recycling. Paint waste is donated to area non-profit groups, mercury vapors are recovered from crushed fluorescent lamps, used oil is collected and donated for alternative fuel, yard and wood waste are composted, household waste is recycled, and petroleum-contaminated waste is being bioremediated on site. Waste reduced and cost savings are included in a table format. Case Study: Steelfab DPPEA (1997) Steelfab, a manufacturer of structural steel, reduced its coating options to customers to three standard choices and switched to lowVOC/HAP coatings. This reduced emissions, waste, solvents (used for clean-out, coating changes, thinning), personnel hours, purchasing requirements, contract costs to customers, and eliminated some regulatory requirements. Steelfab reduced MEKO usage by educating personnel and allowing them to introduce and implement new practices to reduce usage. Waste reduction and cost savings included. Case Study: The Tirnken DPPEA (1997) The Timken Company manufacturers bearings and Company alloy steel. The company has implemented a continuous improvement program to improve their environmental performance, and have implemented such programs as reusable packaging, recycling, waste separation and reuse, use of laternative fuel, and water and energy use reduction. 132

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Table B. I (Cont.) Title Author Abstract Case Study: U.S. Coast DPPEA (1997) The U.S. Coast Guard Support Center at Elizabeth Guard Support Center City is one of the largest Coast Guard bases in the country. The Pollution Prevention Committee was established in 1994 to create and implement P2 programs, including the Pollution Prevention and Opportunity Assessment (P20A) Plan to reduce hazardous waste by more than 50%. The Metals Processing Shop was converted to non-discharge metal treatment tanks through water filtering and reuse. Additionally, parts washers have been converted to water-based systems and hazardous materials are handled at a single base-wide location to improve efficiency of use. Waste reduced and annual savings are included. Case Study: U.S. Postal DPPEA (1997) The Greensboro Bulk Mail Center implemented Service, Greensboro recycling and reuse programs which reduced their Bulk Mail Center solid waste by 75%. Also, they have reduced hazardous waste by eliminating CFCs in aerosol cans and the HV AC system, and switching to water-based paints. Case Study: Bayer DPPEA (1998) Bayer Corporation manufactures hwnan blood Corporation Clayton plasma products and uses solvent waste reduction Facility and recycling to lower operating costs. Bayer worked to include more waste streams in the alcohol recycling process, improved the efficiency of their acetone distillation process, and then automated the systems. Bayer has also improved their wastewater pretreatment process and reduced chemical usage through automation and aeration, and reduced sludge with a dewatering device. Also, the facility has reduced their isopropanol waste, reuses parts washer fluid, and recycles many solid wastes. Waste reduction and cost savings estimates are included. 133

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Table B. I (Cont.) Title Author Abstract Case Study: National DPPEA (1998) The National Institute of Environmental Health Institute of Sciences (NIEHS), a component of the National Environmental Health Institutes of Health (NIH), is a biomedical research Sciences facility in RTP. NIEHS implemented a recycling program in 1993 that has reduced their solid waste by over 32%. Additionally, the facility buys products with recycled content and vermicomposts their organic and animal waste. NIEHS has also instituted a chemical waste minimization program to reduce waste volume and toxicity. The program includes material substitution, waste segregation, chemical inventory and control, solvent recovery, and employee training. Chemical-related waste was reduced by 35% over four years. Annual savings data are included. Hospital Case Study ACF/ACTU Flinders Medical Centre initiated the Healthy Flinders Medical Centre Green Jobs Unit Environment Project in December 1991 with the Disposing of the throw(1991) aim of minimizing waste and exploring other away mentality environmental initiatives. Hotel Case Study ACF/ACTU A four to five star hotel, the Parkroyal on St K.ilda Parkroyal on St K.ilda Green Jobs Unit Rd involved the whole of its staff in 1993 in an Road Putting (1993) environmental audit. This was achieved through environmental learning their participation in an Environmental Education into practice Strategy, focusing on identifying, and putting into practice, achievable actions aimed at reducing the hotel's environmental impact and generating operational savings. Source: DPPEA, NCDENR (2005). Information retrieved from http://www .p2pays.org/mainl case. asp. 134

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C. MARKET-BASED ENVIRONMENTAL POLICIES Table C. I Major Federal Tradable Permit Systems Program Traded Commodity Period of Environmental and Operation Economic Effects Emissions Criteria air pollutants 1974Environmental Trading Program under the Clean Air Present performance unaffected; Act total savings of $5-12 billion Lead Phasedown Rights for lead in 1982-1987 More rapid phase out of gasoline among leaded gasoline; $250 refineries million annual savings Water Quality Point-nonpoint 1984-1986 No trading occurred, Trading sources of nitrogen because ambient & phosphorous standards not binding CFC Trading for Production rights for 1987Environmental targets Ozone Protection some CFCs, based Present achieved ahead of on depletion schedule; effect of tp potential system unclear Acid Rain S02 emission 1995Environmental targets Reduction reduction credits; Present achieved ahead of mainly among schedule; annual electric utilities savings of $1 billion 135

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Table C.1 (Cont.) Program Traded Commodity Period of Environmental and Operation Economic Effects RECLAIM Local S02 and NOx 1994Unknown as of 1997 Program emissions trading Present among stationary sources Source: Stavins ( 1998). Table C.2 Deposit-Refund Systems Regulated Jurisdiction Date of Initiation Size of Deposit Products Specified Oregon 1972 5 (2 refillables) Beverage Containers (for Vermont 1973 5 deposits I refunds) Maine 1978 5 Michigan 1978 10 Iowa 1979 5 Connecticut 1980 5 Delaware 1983 5 Massachusetts 1983 5 New York 1983 5 136

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Table C.2 (Cont.) Regulated Jurisdiction Date of Initiation Size of Deposit Products Specified California 1987 Beverage Containers (for Florida 1988 1 advance disposal fees) Auto Batteries Minnesota 1988 $5.00 Rhode Island 1989 Washington 1989 Arizona 1990 Connecticut 1990 Idaho 1991 New York 1991 Wisconsin 1991 Michigan 1990 $6.00 Maine 1989 $10.00 Arkansas 1991 In California, deposits for aluminum and bi-metal beverage containers smaller than 24 ounces are 2.5 and 5, respectively, and 3 and 6, respectively, for containers 24 ounces and larger. SOURCE: U.S. General Accounting Office. (1990). 137

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Table C.3 Federal User Charges Item Taxed First Rate Use of Revenues Enacted/Modified Motor fuels 1932/1993 $.183/gal Highway Trust Fund/Mass Annual use of 195111993 $1 00-$500/vehicle Transit Account heavy vehicles Trucks and trailers 191711984 12% (excise tax) Noncommercial 1932-1992 $.183/gal Aquatic Resource motorboat fuels Trust Fund Inland waterways 197811993 $.233/gal Inland Waterways fuels Trust Fund Non-highway 1932/1993 $.183/gal gasoline National recreational fuels $.243/gal diesel Recreational and small-engine Trails; Trust Fund motor fuels and Wetlands; Account of Aquatic; Resources Trust Fund Sport fishing 1917/1984 10% (except 3% Sport Fishing equipment for Restoration; outboard motors) Account of Aquatic; Resources Trust Fund 138

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Table C.3 (Cont.) Item Taxed First Rate Use of Revenues Enacted/Modified Bows and arrows 1972/1984 11% Federal Aid to Wildlife Firearms and 1918/1969 10% Program ammunition SOURCE: Barthold, Thomas A. (1994). Table C.4 Federal Insurance Premium Taxes Item/Action Taxed First Enacted I Rate Use of Revenues Modified Chemical 1980/1986 $.22 to $4.88/ton Superfund production (CERCLA) Petroleum 1980/1986 $.097 /barrel crude production Corporate income 1986 0.12% Petroleum and 1989/1990 $.05/barrel Oil Spill Liability petroleum products Trust Fund Petroleum-based 1986/1990 (expired $.001/gal Leaking fuels, except 1995) Underground; propane Storage Trust Fund Coal production 1977/1987 $1.10/ton Black Lung underground $.55/ton Disability Trust surface Fund SOURCE: Barthold, Thomas A. (1994). 139

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Table C.5 Federal Sales Taxes Item/Action First Rate Use of Revenues Taxed Enacted/Modified New automobiles 197811990 $1,000-$7,700 per U.S. Treasury exceeding fuel auto efficiency maxtma Ozone-depleting 198911992 $4.35/pound U.S. Treasury substances New tires 1918/1984 $.15-$.50/pound U.S. Treasury SOURCE: Barthold, Thomas A. (1994). Table C.6 Administrative Charges Item/ Action First Rate Use of Revenues Taxed Enacted/Modified Water Pollutant 1972 Varies by State administrative cost Discharges substance ofNational Pollution Discharge Elimination System, Clean Water Act Criteria Air 1990 Varies by State administrative cost Pollutants implementing of state clean air state programs under Clean Air Act Source: U.S. Office ofTechnology Assessment (OTA). (1995). 140

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Table C.7 Federal Tax Differentiation Item/ Action Provision First Rate Taxed Enacted/Modified Motor Fuels Natural Gas 1978/1990 $.07/gal Excise Tax Exemptions Methanol 1978/1990 $.06/gal Ethanol 1978/1990 $.054/gal Income Tax Alcohol Fuels 198011990 $.60/gal methanol Credits $.54/gal ethanol Business Energy 1980/1990 10% solar 1 0% geothermal Non-conventional 1980/1990 $3 .00/Btu-barrel Fuels equivalent of oil Wind Production 1992 1.5/kWh Biomass 1992 1.5/kWh Production Electric 1992 10% credit Automobiles 141

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Table C.7 (Cont.) Item/ Action Provision First Rate Taxed Enacted/Modified Other Income Tax Van Pools 1978 Tax-free Provisions employer Mass Transit 1984/1992 provided benefits Passes Utility Rebates 1992 Exclusion of subsidies from utilities for energy conservation measures Tax Exempt Mass Transit 1968/1986 Interest exempt Private Activity from Federal Bonds Sewage Treatment 1968/1986 taxation Solid Waste 1968/1986 Disposal Waster Treatment 1968/1986 High Speed Rail 1988/1993 SOURCE: Barthold, Thomas A. (1994). Table C.8 Federal Information Programs Information Program Year of Implementation Enabling Legislation Energy Efficiency 1975 Energy Policy and Product Labeling Conservation Act, Title V NJ Hazardous Chemical 1984 New Jersey Community Emissions Right-to-Know Act 142

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Table C.8 (Cont.) Information Program Year of Implementation Enabling Legislation Toxic Release Inventory 1986 Emergency Planning and Community Right-toKnow Act CA Hazardous Chemical 1987 California Air Toxics Hot Emissions Spots and Information Assessment Act CA Proposition 65 1988 California Safe Drinking Water Act and Toxic Enforcement Act Energy Star 1993 Joint program of the U.S. EPA and the U.S. DOE Source: Stavins (1998). 143

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D. SIC AND NAICS CORRESPONDENCE TABLES Table D.1 1987 SIC and 1997 NAICS Correspondence Table 1987 1997 SIC 1987 U.S. SIC Description NAICS 1997 NAICS U.S. Description 28 Chemicals and allied products 2812 Alkalies and Chlorine 325181 Alkalies and Chlorine Manufacturing 2813 Industrial Gases 32512 Industrial Gas Manufacturing (pt) 2816 Inorganic Pigments Except Bone and Lamp Black 325131 Inorganic Dye and Pigment Manufacturing (pt) Bone and Lamp Black 325182 Carbon Black Manufacturing (pt) 2819@ Industrial Inorganic Chemicals, NEC Recovering Sulfur from 211112 Natural Gas Liquid Extraction (pt) Natural Gas Activated Carbon and Charcoal 325998 All Other Miscellaneous Chemical Product and Preparation Manufacturing (pt) Alumina 331311 Alumina Refining Inorganic Dyes 325131 Inorganic Dye and Pigment Manufacturing (pt) 144

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Table D. I (Cont.) 1987 1987 U.S. SIC Description 1997 1997 NAICS U.S. Description SIC NAICS Other 325188 All Other Basic Inorganic Chemical Manufacturing (pt) 2821 Plastics Material and Synthetic 325211 Plastics Material and Resin Resins, and Nonvulcanizable Manufacturing Elastomers 2822 Synthetic Rubber 325212 Synthetic Rubber Manufacturing 2823 Cellulosic Manmade Fibers 325221 Cellulosic Organic Fiber Manufacturing 2824 Manmade Organic Fibers, 325222 Noncellulosic Organic Fiber Except Cellulosic Manufacturing 2833 Medicinal Chemicals and 325411 Medicinal and Botanical Manufacturing Botanical Products 2834 Pharmaceutical Preparations 325412 Pharmaceutical Preparation Manufacturing (pt) 2835@ In Vitro and In Vivo Diagnostic Substances Except In Vitro Diagnostic 325412 Pharmaceutical Preparation Manufacturing (pt) In Vitro Diagnostic Substances 325413 In-Vitro Diagnostic Substance Manufacturing 2836 Biological Products, Except 325414 Biological Product (except Diagnostic) Diagnostic Substances Manufacturing 2841 Soaps and Other Detergents, 325611 Soap and Other Detergent Except Speciality Cleaners Manufacturing (pt) 2842 Speciality Cleaning, Polishing, 325612 Polish and Other Sanitation Good and Sanitary Preparations Manufacturing 145

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Table D.1 (Cont.) 1987 1987 U.S. SIC Description 1997 1997 NAICS U.S. Description SIC NAICS 2843 Surface Active Agents, 325613 Surface Active Agent Finishing Agents, Sulfonated Manufacturing Oils, and Assistants 2844 Perfumes, Cosmetics, and Other Toilet Preparations Toilet Preparations, Except 32562 Toilet Preparation Manufacturing Toothpaste Toothpaste 325611 Soap and Other Detergent Manufacturing (pt) 2851 Paints, V ami shes, Lacquers, 32551 Paint and Coating Manufacturing Enamels, and Allied Products (pt) 2861 Gum and Wood Chemicals 325191 Gum and Wood Chemical Manufacturing 2865@ Cyclic Organic Crudes and Intermediates, and Organic Dyes and Pigments Aromatics 32511 Petrochemical Manufacturing (pt) Organic Dyes and Pigments 325132 Synthetic Organic Dye and Pigment Manufacturing Other 325192 Cyclic Crude and Intermediate Manufacturing 2869@ Industrial Organic Chemicals, NEC Aliphatics 32511 Petrochemical Manufacturing (pt) 146

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Table D.1 (Cont.) 1987 1987 U.S. SIC Description 1997 1997 NAICS U.S. Description SIC NAICS Carbon Bisulfide 325188 All Other Basic Inorganic Chemical Manufacturing (pt) Ethyl Alcohol 325193 Ethyl Alcohol Manufacturing Fluorocarbon Gases 32512 Industrial Gas Manufacturing (pt) Other 325199 All Other Basic Organic Chemical Manufacturing (pt) 2873 Nitrogenous Fertilizers 325311 Nitrogenous Fertilizer Manufacturing 2874 Phosphatic Fertilizers 325312 Phosphatic Fertilizer Manufacturing 2875 Fertilizers, Mixing Only 325314 Fertilizer (Mixing Only) Manufacturing 2879 Pesticides and Agricultural 32532 Pesticide and Other Agricultural Chemicals, NEC Chemical Manufacturing 2891 Adhesives and Sealants 32552 Adhesive Manufacturing 2892 Explosives 32592 Explosives Manufacturing 2893 Printing Ink 32591 Printing Ink Manufacturing 2895 Carbon Black 325182 Carbon Black Manufacturing (pt) 2899 Chemicals and Chemical Preparations, NEC Frit 32551 Paint and Coating Manufacturing (pt) 147

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Table D.l (Cont.) 1987 1987 U.S. SIC Description 1997 1997 NAICS U.S. Description SIC NAICS Table Salt 311942 Spice and Extract Manufacturing (pt) Fatty Acids 325199 All Other Basic Organic Chemical Manufacturing (pt) Other 325998 All Other Miscellaneous Chemical Product and Preparation Manufacturing (pt) Source: U.S. Census Bureau (2005). 148

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Table D.2 1987 SIC and 2002 NAICS Correspondence Table 1987 1987 U.S. SIC Description 2002 2002 NAICS U.S. Description SIC (with link to def"mition) NAICS (with link to def"mition) 28 Chemicals and allied Qroducts 281 Industrial inorganic chemicals 2812 Alkalies and Chlorine 325181 Alkalies and Chlorine Manufacturing 2813 Industrial Gases 325120 Industrial Gas Manufacturing (part) 2816 Inorganic Pigments Except bone and lamp black 325131 Inorganic Dye and Pigment Manufacturing (part) Bone and lamp black 325182 Carbon Black Manufacturing (part) 2819 Industrial Inorganic Chemicals, NEC Recovering sulfur from 211112 Natural Gas Liguid Extraction (part) natural gas Inorganic dyes 325131 Inorganic Dye and Pigment Manufacturing (part) Except activated carbon and 325188 All Other Basic Inorganic Chemical charcoal, alumina, recovering Manufacturing (part) sulfur from natural gas, and inorganic dyes Activated carbon and 325998 All Other Miscellaneous Chemical charcoal Product and PreQaration Manufacturing (part} 149

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Table 0.2 (Cont.) 1987 1987 U.S. SIC DescriJ!tion 2002 2002 NAICS U.S. Description SIC (with link to defmition} NAICS (with link to defmition) Alumina 331311 Alumina Refining 282 Plastics materials and SY!!thetics 2821 Plastics Materials, Synthetic 325211 Plastics Material and Resin and Resins, and Manufacturing Nonvulcanizable Elastomers 2822 Synthetic Rubber 325212 Synthetic Rubber Manufacturing 2823 Cellulosic Manmade Fibers 325221 Cellulosic Organic Fiber Manufacturing 2824 Manmade Organic Fibers, 325222 Noncellulosic Organic Fiber Cellulosic Manufacturing 283 Drugs 2833 Medicinal Chemicals and 325411 Medicinal and Botanical Botanical Products Manufacturing 2834 Pharmaceutical PreQarations 325412 Pharmaceutical PreQaration Manufacturing (part) 2835 In Vitro and In Vivo Diagnostic Substances Except in-vitro diagnostic 325412 Pharmaceutical substances Manufacturing (part) In-vitro diagnostic 325413 InVitro Diagnostic Substance substances Manufacturing 150

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Table D.2 (Cont.) 1987 1987 U.S. SIC DescriRtion 2002 2002 NAICS U.S. Description SIC {with link to defmition} NAICS (with link to defmition) 2836 Biological Products, Exc92t 325414 Biological Product (excegt Diagnostic Substances Diagnostic} Manufacturing 284 and toilet goods 2841 Soags and Other Detergents, 325611 Soag and Other Detergent Exc92t Sgecialty Cleaners Manufacturing (part) 2842 Sgecialtv Cleaning, Polishing, 325612 Polish and Other Sanitation Good and Sanitation Pr92arations Manufacturing 2843 Surface Active Agents, 325613 Surface Active Agent Finishing Agents, Sulfonated Manufacturing Oils, and Assistants 2844 Perfumes, Cosmetics, and Other Toilet Pregarations Toothpaste, gel, and 325611 Soag and Other Detergent dentifrice powders Manufacturing (part) Except toothpaste, gel, and 325620 Toilet Pregaration Manufacturing dentifrice powders 285 Paints and allied Rroducts 2851 Paints, Varnishes, Lacguers, 325510 Paint and Coating Manufacturing Enamels and Allied Products (part) 286 Industrial organic chemicals 2861 Gum and Wood Chemicals 325191 Gum and Wood Chemical Manufacturing 151

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Table 0.2 (Cont.) 1987 1987 U.S. SIC 2002 2002 NAICS U.S. Description SIC {with link to definition} NAICS (with link to def"mition) 2865 Cyclic Organic Crudes and Intermediates. and Organic Dyes and Pigments Aromatics 325110 Petrochemical Manufacturing (part) Organic dyes and pigments 325132 Synthetic Organic Dye and Pigment Manufacturing Except aromatics and 325192 Cyclic Crude and Intermediate organic dyes and pigments Manufacturing (part) 2869 Industrial Organic Chemicals. NEC Aliphatics 325110 Petrochemical Manufacturing (part) Fluorocarbon gases 325120 Industrial Gas Manufacturing (part) Carbon bisulfide 325188 All Other Basic Inorganic Chemical Manufacturing (part) Cyclopropane, 325192 Cyclic Crude and Intermediate diethylcyclohexane, Manufacturing (part) naphthalene sulfonic acid Ethyl alcohol 325193 Ethyl Alcohol Manufacturing Except aliphatics, carbon 325199 All Other Basic Organic Chemical bisulfide, ethyl alcohol, Manufacturing (part) cyclopropane, diethylcyclohexane, napthalene sulfonic acid, synthetic hydraulic fluids, and fluorocarbon gases 152

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Table D.2 (Cont.) 1987 1987 U.S. SIC Descril!tion 2002 2002 NAICS U.S. Description SIC {with link to defmition} NAICS (with link to defmition) Synthetic hydraulic fluids 325998 All Other Miscellaneous Chemical Product and PreQaration Manufacturing (part) 287 Agricultural chemicals 2873 Nitrogenous Fertilizers 325311 Nitrogenous Fertilizer Manufacturing 2874 PhosQhatic Fertilizers 325312 PhosQhatic Fertilizer Manufacturing 2875 Fertilizers2 Mixing Only 325314 Fertilizer (Mixing Only) Manufacturing 2879 Pesticides and Agricultural 325320 Pesticide and Other Agricultural Chemicals2 NEC Chemical Manufacturing 289 Miscellaneous chemical l!roducts 2891 Adhesives and Sealants 325520 Adhesive Manufacturing 2892 ExQlosives 325920 ExQlosives Manufacturing 2893 Printing Ink 325910 Printing Ink Manufacturing 2895 Carbon Black 325182 Carbon Black Manufacturing (part) 2899 Chemicals and Chemical PreQarations, NEC Table salt 311942 SQice and Extract Manufacturing (part) 153

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Table D.2 (Cont.) 1987 1987 U.S. SIC 2002 2002 NAICS U.S. Description SIC (with link to def'mition} NAICS (with link to def'mition) Fatty acids 325199 All Other Basic Organic Chemical Manufacturing (part) Frit and plastic wood fillers 325510 Paint and Coating Manufacturing (part) Except frit, fatty acids, 325998 All Other Miscellaneous Chemical plastic wood fillers, and table Product and PreQaration salt Manufacturing (part) Source: U.S. Census Bureau (2005). 154

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E. STATE HAZARDOUS WASTE FEE IT AX SYSTEMS Table E.1 State Hazardous Waste Fee I Tax Systems ALABAMA 1 (334) 270-563o !Montgomery, AL Disposal Fees: RCRA, PCB=$ 51.00 I ton "P" Listed Waste= 113.00 I ton "U" Listed Waste= 76.00 I ton Industrial Waste= 21.00 I ton ALASKA 1<907) 465-5150 !Juneau, AK No taxes or fees imposed. ARIZONA 1(602) 207-4232 !Phoenix, AZ The state charges TSDFs for permits and other waste management fees. Hazardous Waste Fees: Generators who ship the waste off-site (exempt if the off-site facility is in the state and owned or operated by the same person who generates the waste)=$ 10.00 I ton Owner/Operator of facility that disposes waste (exempt if the facility is owned or operated by the same person who generates the waste)= 40.00 I ton Generators of waste that retain the waste on-site for disposal or who ship it off-site to a facility owned or operated by that generator= 4.00 I ton Any generator that complies with the pollution prevention planning requirements shall pay one-half the applicable fee listed above. Any owner or operator of a disposal facility that accepts waste from someone that complies with the pollution prevention planning requirements shall pay one-half the applicable fee listed above. 155

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Table E. I (Cont.) ARKANSAS 1(501) 682-7187 I Little Rock, AR The state charges TSDFs for permits and other waste management fees. Each hazardous waste management facility or unit in which hazardous wastes are treated, stored or disposed of will be charged the following additional fees: Container Storage = $ 10.00 I 100 gal Tank Treatment and/or Storage = 100.00 I 1000 gal Waste Pile Storage and/or Disposal= 10.00 Icy Surface Impoundment Treatment, Storage and/or Disposal= 60.00 I 1000 gal Land Treatment/Land Farm Treatment or Disposal = 10,000 I acre Landfill Disposal= 5,000 I acre-ft Open Burning/Detonation ofWaste = 2.00 I lb I day Other Thermal Treatment= 3,000 I ton I hr Other Treatment not included above = 20.00 I 100 gall day Monitoring/Inspection fees: Treatment, Storage, and Disposal Facilities = $ 2,250 Generators of> 250,00 lbs I yr = 1 000 Generators of< 249,999lbs I yr and> 26,401 lbs I yr = 500 Generators of< 2200 lbs lmo and > 220 lbs I mo = 150 Transporters = 50 CALIFORNIA 1(916) 322-8676 I Sacramento, CA The state charges TSDFs for permits and other waste management fees. Land Disposal fees: Non-RCRA cleanup wastes (Excluding Asbestos)=$ 7.50 I ton OtherNon-RCRA Waste= 18.221ton Ores and Minerals= 14.52 I ton Extremely Hazardous Waste = 223.44 I ton Restricted Hazardous Waste= 223.44 I ton Hazardous Waste (RCRA) = 45.13 I ton Incineration or Dechlorination disposed in state= 5.58 I ton Waste Disposed out of state= None Generator fees: Less than 5 tons I yr = $ 0 5 but less than 25 tons I yr = 171 25 but less than 50 tons I yr = 1 ,3 70 50 but less than 250 tons I yr = 3,424 250 but less than 500 tons I yr = 17,120 156

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Table E. I (Cont.) CALIFORNIA 1(916) 322-8676 !Sacramento, CA 500 but less than 1 ,000 tons I yr = 34,240 1,000 but less than 2,000 tons I yr = 51,360 More than 2,000 tons I yr = 68,480 Generator Waste Reporting surcharge: Less than 5 tons I yr = $ 0 5 but less than 25 tons I yr = 6 25 but less than 50 tons I yr = 59 50 but less than 250 tons I yr = 148 250 but less than 500 tons I yr = 738 500 but less than 1 ,000 tons I yr = 1 ,4 77 I ,000 but less than 2,000 tons I yr = 2,213 More than 2,000 tons I yr = 2,952 COLORADO 1 (303) 692-3342 !Denver, CO The state charges a fee to TSDF's for permits, document review and activities. Hazardous waste treatment, storage and disposal unit annual operating fee: Class I = $ 6.00 I ton Class II = 4.40 I ton Class III (except resource recovery)= 4.40 I ton Class III (resource recovery) = 2.50 I ton Class N = 2.00 I ton CONNECTICUT 1(203) 566-8843 I Hartford, CT Hazardous waste tax: Generators = $ 0.04 I gal Out of State Generator shipping to Connecticut = 0.04 I gal or 0.005 I lb or 8.00 Icy Treatment Facility generating Metal Hydroxide Sludge from treatment= 0.05 I gal or 0.005 I lb or 10.00 I cy Treatment Facility generating Other Hazardous Waste= 0.06 I gal or 0.0075 I lb or 12.00 Icy 157

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Table E.1 (Cont.) DELAWARE 1 (302) 739-3689 I Dover, DE The state charges TSDFs for permits and other waste management fees. Dis:gosal Fees for :gersons engaged in the generation of hazardous waste generated after October 1, 1986: Disposed of into or on any land = $ 21.00 I ton Treated or disposal of off site = 16.00 I ton (exclusive ofland disposal and incineration) Incinerated= 4.00 I ton DISTRICT OF COLUMBIA 1(202) 645-6080 I Washington, DC No taxes or fees imposed. FLORIDA 1(904) 488-0300 !Tallahassee, FL The state charges a fee to TSDF's for permits and the county may charge an annual tax of3% on gross receipts. GEORGIA 1<404) 656-7802 !Atlanta, GA Hazardous Waste Management Fees: Small Quantity Generator=$ 100.00 I yr Large Quantity Generator (wastes managed on site) Incineration or Disposal = 10.00 I ton Treatment or Storage= 4.00 I ton Burning for Energy Recovery= 2.50 I ton Recycling or Reuse = 1. 00 I ton Large Quantity Generator (wastes managed off site) Incineration or Disposal= 20.00 I ton Treatment or Storage= 16.00 I ton Burning for Energy Recovery= 9.00 I ton Recycling or Reuse= 2.00 I ton HAWAII l (808) 586-4226 I Honolulu, HI No taxes or fees imposed. 158

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Table E.1 (Cont.) IDAHO 1 (208) 334-o5o2 !Boise, ID Hazardous Waste Fees: Hazardous wastes defined by RCRA = $ 30.00 I ton PCB and other manifested wastes= 25.00 I ton Hazardous waste that is delisted or treated so that it is no longer hazardous= 5.00 I ton Wastes with PCB concentrations less than 50 parts per million and not TSCA regulated = 5. 00 I ton ILLINOIS 1<217) 785-8637 Jspringfield, IL The state charges TSDFs for permits and other waste management fees. Manifest Fee: 0-20 Manifests= None More than 20 mainifests (maximum fee $500) = $1.00 I manifest Hazardous Waste Fees: Disposal Fee=$ 0.09 I gal or 18.18 Icy Treatment Fee = 0.03 I gal or 6.06 I cy Monofill = 30,000 I yr Underground Injection Well Fees 10 million gallons or less = 6,000 I yr 10 million gallons to 50 million gallons= 15,000 I yr 50 million gallons or more = 27,000 I yr INDIANA 1 (317) 233-o4o8 I Indianapolis, IN The state charges TSDFs for permits and other waste management fees. IOWA 1(515) 281-8801 I Des Moines, lA Generator Fees: Generators who dispose of their waste off-site=$ 10.00 I ton Generators who dispose of or treat their waste on-site Waste placed, deposited, dumped or disposed of onto or into the land= 40.00 I ton Waste destroyed or treated to render the waste nonhazardous= 2.00 I ton 159

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Table E.1 (Cont.) KANSAS 1(913) 296-1590 !Topeka, KS Storage Facility Annual Monitoring Fee: On-site storage facility=$ 2,500 Off-site storage facility= 3,500 Treatment Facility Annual Monitoring Fee: On-site storage facility= $ 4,000 Off-site storage facility= 5,000 Off-site incinerator facility= 10,000 DisQosal Facility Annual Monitoring Fee: On-site landfill or underground injection well = $ 10,000 Off-site landfill or underground injection well = 15,000 Generator Annual Monitoring Fee Based on Volume: 5 tons=$ 100 5 50 tons= 500 50 500 tons= 1,000 > 500 tons= 5,000 Hazardous Waste Pemetual Care Trust Fund: Disposal in Landfills = $ 0.005 I lb Disposal by Deep Well Injection= 0.00000455 I lb Disposal by Other Methods= 0.001 I lb Off-site Hazardous Waste Treatment Fee: Dioxin=$ 20.00 I ton Fewer than 5,000 BTUs I lb = 10.00 I ton Equal to or Greater than 5,000 BTUs I lb = 2.00 I ton KENTUCKY 1(502) 564-6716 !Frankfort, KY The state charges TSDFs for permits and other waste management fees. Generator Hazardous Waste Assessment: Solid Hazardous Waste sent off-site = $ 0.002 I lb Solid Hazardous Waste kept on .... site = 0.001 I lb Liquid Hazardous Waste sent off-site= 0.012 I lb Liquid Hazardous Waste kept on-site= 0.006 I lb Generator Notification Fee: 1 -5 Wastestreams = $ 300 610 Wastestreams = 350 11 -15 W astestreams = 400 16 20 Wastestreams = 450 160

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Table E.1 (Cont.) KENTUCKY 1<502) 564-6716 !Frankfort, KY 21 25 W astestreams = 500 2630 Wastestreams = 550 Over 30 Wastestreams = 600 LOUISIANA j(504) 765-0355 I Baton Rouge, LA The state charges TSDFs for permits and other waste management fees. Generator Fees: Annual Monitoring and Maintenance Fee=$ 283.65 I yr Annual prohibited waste fee = 100.00 I yr Transgorter Fees: Hazardous Waste Facility within Louisiana=$ 200.00 I yr No Hazardous Waste Facility within Louisiana= 10.00 I veh MAINE (207) 287-7688 Augusta, ME The state charges TSDFs for permits and other waste management fees. Fees for actions taken on the site of generation: Disposal = $ 0.02 I lb Storage of more that 90 days (every 6 months)= 0.005 I lb Fees for actions taken off the site of generation: Disposal = $ 0.02 I lb Treatment, Storage or Handling= 0.015 I lb Note: The person who transports the waste into Maine from another state is required to pay a fee of twice the amount indicated above (Fees for actions taken off the site of generation). MARYLAND (410) 631-3304 Baltimore, MD The state charges TSDFs for permits and other waste management fees. MASSACHUSETTS j(617) 292-5853 jBoston, MA The state charges TSDFs for permits and other waste management fees. MICHIGAN j(517) 373-2730 I Lansing, MI Disgosal fees: Land disposal or solidification = $ 10.00 I ton = 10.00 I cy = 0.005 I lb 161

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Table E.1 (Cont.) MINNESOTA (612) 297-8330 St. Paul, MN The state charges generators of hazardous waste both a Quantity Fee and Quantity Tax for each waste stream. The Quantity Tax is calculated as follows: (Quantity for each Waste Stream)* (Tax Rate for that Waste Stream) The Quantity Fee is calculated for each waste stream with different levels of rates based on the volume. Each step is calculated and added together and then multiplied by a Statewide Program Fee Rate. The formula is as follows: [(Step 1 Quantity) (Reduction Factor) (Step 1 Rate Factor)+ (Step 2 Quantity) (Reduction Factor)* (Step 2 Rate Factor), etc]* Statewide Program Fee Rate The reduction factor is 0.7 for gallons and 0.5 for pounds. The following tables depict the step factors and fee rates for each waste: Step Factor Table Quantity Step Rate Factor Pounds Gallons Step 1 100% 0-4,000 0-400 Step 2 25% 4,001-26,400 4012,640 Step 3 12.5% 26,401-2,641100,000 10,000 Step 4 1.25% 100,001-10,001-500,000 50,000 Step 5 0% > 500,000 > 50,000 Rate Table Management Method Description Code Quantity Tax Fee Rate Burning for Fuel BF $0.36 Exempt Incineration/Thermal Treatment (except Chemolite) IT $0.71 $0.15 Land Disposal (Hazardous Waste Landfill) LD $0.71 $0.30 Multiple Treatment Options Reported MM $0.71 $0.30 Other Disposal OT $0.71 $0.30 162

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Table E.1 (Cont.) MINNESOTA (612) 297-8330 St. Paul, MN Rate Table Management Method Description Code Quantity Tax Fee Rate Pretreated to Nonhazardous, Sewered, but does not have a RN $0.18 Exempt Hazardous Residual Sewered after Pretreatment but still Hazardous SA $0.50 $0.15 Sewered to Generator's NPDES Permitted Facility SG Exempt Exempt Sewered after Pretreatment to a Nonhazardous State SN Exempt Exempt Sewered without Treatment sw $0.71 $0.15 Sewered after Pretreatment in an Open-Loop System to a sz $0.36 Exempt Nonhazardous State MISSISSIPPI 1<601) 961-5171 !Jackson, MS Pollution Prevention Fee for Generators: 0 to 9.99 tons=$ 250 10 to 99.99 tons= 500 100 to 999.99 tons= 1,500 1,000 to 9,999.99 tons= 2,500 10,000 to 49,999.99 tons= 10,000 50,000 tons and above= 50,000 MISSOURI 1(314) 751-3176 !Jefferson City, MO Hazardous Waste Fees: Generators of> 10 metric tons I yr = $ 1.00 I ton Landfill Disposal of> 10 metric tons I yr = 25.00 I ton Category Tax: Landfill or Storage=$ ((20 + (.07 x Tonnage)) x Tonnage) Treatment or Incineration=$ ((20 + (.07 x Tonnage)) x Tonnage) 163

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Table E.1 (Cont.) MONTANA 1 < 406) 444-1430 !Helena, MT Generator Fees: Class I=$ 75.00 Class II = 200.00 Class III = 600.00 Class IV = 1,000.00 Class V = 1 ,500,00 NEBRASKA 1<402) 471-4217 I Lincoln, NE Treatment. Storage and Disposal Facility Fee assessment: Treated or Incinerated = $ 0.06 I cf or 0.00096 I lb Disposal= 0.70 I cf or 0.0112 I lb NEVADA 1(702) 687-5872 !carson City, NV The state charges TSDFs for permits and other waste management fees. Treatment. Storage and Disposal Facility Fee assessment: Hazardous Waste (RCRA) = $40.20 I ton State Hazardous (Non-RCRA) = 35.00 I ton Treated to Non-Hazardous= 17.75 I ton Non Hazardous, No Treatment= 3.00 I ton NEW HAMPSHIRE 1(603) 271-2946 !concord, NH Hazardous Waste Fee: Generators (> 660 lbs I 3 mo) = $ .03 I lb Facility accepting out of state waste= 0.003 I lb NEW JERSEY j(609) 292-8341 !Trenton, NJ The state charges TSDFs for permits and other waste management fees. Hazardous Waste Generator Biennial Fee: Manifesting less than 1.3 2 tons = $ 67.00 I yr Manifesting 1.32 tons but < 10 tons = 134.00 I yr Manifesting 10 tons but < 100 tons = 248.00 I yr Manifesting 100 tons but< 150 tons= 501.00 I yr Manifesting equal to or grater than 150 tons= 801.00 I yr Manifest Processing Fees: Generators=$ 9.00 I manifest 164

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Table E.1 (Cont.) NEW JERSEY 1<609) 292-8341 !Trenton, NJ Hazardous Waste Facilities (for waste received from generators outside of New Jersey)=$ 9.00 I manifest Hazardous Waste facilities (for waste received from New Jersey generators)= None Inspection and Compliance Review Fees: Major Commercial Hazardous Waste Facility= NJ Formula used Commercial Hazardous Waste Facility=$ 930 I inspection Non-Commercial Hazardous Waste Facility= 1,639 I inspection Large Quantity Generator = 2,180 I inspection Small Quantity Generator = 517 I inspection Compliance Inspection = 829 I inspection Compliance Review = 454 I review NEW MEXICO 1<800) 219-6157 I Sante Fe, NM Generation Fees: Large Quantity Generator o Generated at the site=$ 0.01 I lb o Any wastewater that is designated as= 0.01 I ton hazardous because it exhibits characteristics defined in 40 CFR 261, Subpart C Small Quantity Generator o 1 500 lbs I mo = $ 35 I yr o 501-1,000lbslmo= 1001yr o 1,001-2,205 lbs I mo = 250 I yr Business Fees: Small Quantity Generator = $ 200 I site Large Quantity Generator = 2,500 I site Treatment or Storage, including closure o First unit at facility= 3,500 I unit o Each additional unit= 1,750 I unit Disposal, including closure o First unit at facility= 5,000 I unit o Each additional unit = 2,500 I unit Post Closure Care o First unit at facility= 1,000 I unit o Each additional unit= 500 I unit 165

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Table E.1 (Cont.) NEW YORK 1(518) 457-9254 !Albany, NY The state charges TSDFs for permits and other waste management fees. Hazardous Waste Program Fees for Generators: I5IOO tons ofHazardous waste per year=$ I,OOO I yr 1 00 500 tons of Hazardous waste per year = 6,000 I yr 500 -1 ,000 tons of Hazardous waste per year = 20,000 I yr Greater than 1 ,000 tons of Hazardous waste per year = 40,000 I yr Greater than I5 tons of Hazardous wastewater per year, in addition to the fees above= 3,000 I yr Special Assessment on Generation, Treatment or Disposal of Hazardous Waste: Disposed of in a landfill on-site of generation= $ 27.00 I ton Designated for removal or removed from the site of generation for disposal in a landfill or for storage prior to disposal in a landfill= 27.00 I ton Designated for removal or removed from the site of generation for treatment or disposal (other than landfill or incineration) or for storage prior to such treatment or disposal = I6.00 I ton Designated for removal or removed from the site of generation for incineration or for storage prior to incineration= 9.00 I ton Incinerated on-site of generation = 2.00 I ton Received from out-of-state for landfill disposal or for storage prior to disposal in a landfill =27.00 I ton Received from out-of-state for treatment or disposal (other than landfill or incineration) or for storage prior to such treatment or disposal = I6.00 I ton Received from out-of-state for incineration or for storage prior to incineration = 9.00 I ton NORTH CAROLINA 1(919) 733-2178IRaleigh, NC Generator Fee: 1 kg of acute hazardous waste= $ 500.00 I yr 100 kg but< I,OOO kg ofhazardous waste= 25.00 I yr I kg of acute hazardous waste or= 0.50 I ton I yr I,OOO kg ofhazardous waste= maximum of25,000 Storage, Treatment, or Disposal Facility: Activity fee = $ I ,200 I yr Storage fee= 1.75 I ton Operation fee= 4I.OO I hr 166

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Table E.1 (Cont.) NORTH DAKOTA 1(701) 328-5116!Bismarck, ND No taxes or fees imposed. OHIO 1<614) 644-2917 !Columbus, OH The state charges TSDFs for permits and other waste management fees. Hazardous Waste Treatment and Disposal Fees: Off-site land application or landfilling (monthly)=$ 9.00 I ton Off-site deep well injection (monthly) = 4.50 I ton On-site deep well injection (annually)= 2.00 I ton Off-site land application or landfilling (annually)= 4.00 I ton Off-site treatment (monthly) = 2.00 I ton OKLAHOMA 1<405) 271-5338 I oklahoma City, OK The state charges a fee to TSDF's for permits and monitoring and inspection. Generator Fees: Disposal Plan (1-2 Wastestreams) = $ 100 I yr Each additional W astestream = 50 I yr Small quantity generator monitoring and inspection = 25 I yr All other generators monitoring and inspection = 100 I yr Annual Fees: Off-site storage, treatment or land disposal=$ 9.00 I ton Off-site recycling= 4.00 I ton On-site or Off-site underground injection = 0.03 I gal Note: If the generator treats the waste on site to meet the Best Demonstrated Available Technology (BDA T) Standards and disposes the waste on-site, the waste shall be subject to a reduced treatment or on-site disposal fee of one-half the above rates. Minimum Facility Fees: Off-site treatment or disposal facility= $ 50,000 I yr On-site treatment or disposal facility= 20,000 I yr Off-site storage or recycling (> 10 tons lyr) = 20,000 I yr Off-site facility conduction research or design tests = 10,000 I yr 167

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Table E.1 (Cont.) OREGON j(503) 229-5913 !Portland, OR Annual Activity Verification Fees: Large quantity generators=$ 525 I yr Small quantity generators= 300 I yr Conditionally exempt quantity generators = 0 I yr Annual Hazardous Waste Generation Fees: Management method unknown or not reported = $ 180.00 I ton Land Disposal = 135.00 I ton Incineration, Stabilization, Sludge Treatment Aqueous Organic, Inorganic and Combined Treatment, and Other Treatment= 90.00 I ton Energy Recovery, Fuel Blending, and Neutralization= 67.50 I ton Solvents Recovery, Metals Recovery, Other Recovery= 45.00 I ton RCRA-Exempt Management= 0.00 I ton PENNSYLVANIA 1(717) 787-6329 !Harrisburg, PA Treatment, Storage, or Dis:Qosal Facility Quarterly O:Qerations and Fee for Hazardous Waste: Treatment=$ 5.00 I ton Storage= 2.00 I ton Disposal= 12.00 I ton Incineration= 5.00 I ton Recycle and Exempt Cleanup= None RHODE ISLAND j(401) 277-4700 jProvidence, RI The state charges TSDFs for permits and other waste management fees. SOUTH CAROLINA 1(803) 896-4141 I Columbia, SC Annual Hazardous Waste Fees: Hazardous=$ 34.00 I ton Non-hazardous= 13.70 I ton Incinerated = 10.00 I ton Storage of over 50 tons = 1.00 I ton 168

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Table E.l (Cont.) SOUTH DAKOTA 1(605) 773-5559 !Pierre, SD The state charges TSDFs for permits and other waste management fees. Annual Fees: Inspection, investigation, monitoring fee for each disposal facility disposing of> 500 tons I yr = $ 25,000 I yr Waste disposal fee (excluding energy recovery)= 50.00 I ton In addition, the county or municipality may impose a disposal fee upon any facility within or operated under its jurisdiction (excluding energy recovery). TENNESSEE 1(615) 532-0882 !Nashville, TN The state charges TSDFs for permits and other waste management fees. Annual Generator Fees: Small quantity generator= $ 550 I yr Large quantity generator = 900 I yr Trans)2orter Fees: Permit Application = $ 1 00 I ea Permit Maintenance and Renewal Fee= 200 I yr TEXAS 1(512) 239-6611 Generation Fee Assessment: Hazardous Waste Less than 1 ton = None 1 to 50 tons=$ 100.00 I yr Greater than 50 tons= 2.00 I ton Non-hazardous waste Less than 1 ton= None 1 to 50 tons = $ 50.00 I yr Greater than 50 tons = 0.50 I ton Facility Fee Assessment: Hazardous Waste !Austin, TX o Storage/Processing (tanks or containers)=$ 0.02 I gal o Land Treatment or Waste Pile= 4,000 I acre o Surface Impoundment or Landfill= 5,000 I acre o Injection Well = 1 0,000 /well o Closed Disposal Unit or Other Unit = 2,500 I unit Non-hazardous waste o Storage/Processing (tanks or containers)=$ 250 I yr 169

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Table E.1 (Cont.) TEXAS 1(512) 239-6611 !Austin, TX o Land Treatment or Waste Pile = 400 I acre o Surface hnpoundment or Landfill = 500 I acre o Injection Well= 1,000 /well o Closed Disposal Unit or Other Unit= 250 I unit Industrial Solid Waste and Hazardous Waste Management Fee Assessment: Hazardous Waste o Landfill o In state=$ 30.00 I ton o hnported = 3 7.50 I ton o Land Treatment o In state= 24.00 I ton o hnported = 30.00 I ton o Underground Injection o In state = 18.00 I ton o hnported = 22.50 I ton o Incineration o In state= 16.00 I ton o hnported = 20.00 I ton o Processing o In state= 8.00 I ton o hnported = 10.00 I ton o Storage= 2.00 I ton o Energy Recovery = 8.00 I ton o Fuel Processing= 6.00 I toh Class I non-hazardous Waste o Landfill o In state= $ 6.00 I ton o hnported = 7.50 I ton o Land Treatment o In state= 4.80 I ton o hnported = 6.00 I ton o Underground Injection o In state= 3.60 I ton o hnported = 4.50 I ton o Incineration o In state = 3 .20 I ton o hnported = 4. 00 I ton 170

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Table E.1 (Cont.) UTAH 1<801) 538-6170 I salt Lake City, UT Disposal Fees: Hazardous Waste=$ 28.00 I ton PCBs = 4.75 I ton Non-hazardous= 2.50 I ton VERMONT 1 (802) 241-3888 !waterbury, VT Hazardous Waste Generation Fees: Destined to be reclaimed, recycled, or recovered=$ 0.11 I gal or $0.014 I lb Destined for long term storage= 0.33 I gal or 0.042 I lb Destined for land disposal = 0.44 I gal or 0.056 I lb Destined for other treatment= 0.22 I gal or 0.028 I lb VIRGINIA 1<804) 698-4129 I Richmond, VA The state charges TSDFs for permits and other waste management fees. WASHINGTON 1 (8oo> 633-7585 !olympia, WA The state requires each generator of hazardous waste to pay the Hazardous Waste Education Fee of $35 I yr. In addition, the state will charge the generator a Hazardous Waste Planning Fee. In 1997, the fee cannot exceed $11,773 for any individual facility or an interrelated facility preparing a single plan. The total for all facilities cannot exceed $1,177,282 in 1997. The fee for each individual facility is calculated based upon a statewide rate per pound. Statewide rate per lb = $1,177,282 I { ( 10 x state totallbs of extremely hazardous waste) + (state total lbs of dangerous waste) +(state totallbs of toxic releases)} Fee for individual facility= {(10 x totallbs of extremely hazardous waste)+ (total lbs of dangerous waste)+ (totallbs of toxic releases)} x statewide rate per pound 171

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Table E.1 (Cont.) WEST VIRGINIA IC304) 558-2745 !Charleston, WV The state will charge the generator a rate per ton that is determined each year based on the amount ofwastes reported. For 1997 the Revenues from Total Fees Assessed = $500,000. Rate per Ton= (Revenues from Total Fees Assessed) I (W + (0.9) X+ (0.75) Y + (0.25) Z) Where W =the amount ofhazardous waste generated in West Virginia and treated or disposed off-site (remaining hazardous) X= the amount ofhazardous waste generated in West Virginia and treated or disposed on-site (remaining hazardous) Y =the amount ofhazardous waste generated in West Virginia and treated off-site rendering it non-hazardous Z =the amount ofhazardous waste generated in West Virginia and treated on-site rendering -it non-hazardous The rate will then be applied in the following manner: Hazardous waste treated or disposed off site = 1 00 % Hazardous waste treated or disposed on site = 90 % Hazardous waste treated off-site to be rendered non-hazardous= 75% Hazardous waste treated on-site to be rendered non-hazardous = 25 % WISCONSIN 1(608) 266-0061 !Madison, WI The state charges TSDFs for permits and other waste management fees. Tonnage Fees: Certain hazardous wastes = 0.15 I ton Wastes containing ashes and sludges from electric and process steam generating facilities, sludges from waste treatment processes or manufacturing processes at pulpor paper mills, manufacturing process solid waste from foundries, and sludges from municipal wastewatertreatment facilities= 0.015 I ton Prospecting or Mining Wastes o Hazardous tailing solids=$ 0.015 I ton o Non-hazardous tailing solids or nonacid producing taconite tailing solids = 0.002 I ton o Hazardous sludge= 0.010 I ton o Non-hazardous sludge= 0.005 I ton Hazardous waste rock= 0.003 I ton 172

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Table E.l (Cont.) WISCONSIN 1<608) 266-0061 I Madison, WI 0 Non-hazardous waste rock or nonacid producing taconite tailing waste rock= 0.001 I ton 0 Other prospecting or mining waste= 0.005 I ton Other Hazardous Waste DisQosal Fees imQosed on generators: Groundwater Fee = $ 0.1 0 I ton Well Compensation Fee= 0.01 I ton Solid Waste Facility Siting Board Fee= 0.017 I ton Environmental Repair Fee 0 High-volume waste (includes fly and bottom ash, papermill sludge, and foundry process waste)=$ 0.20 I ton 0 Non high-volume waste= 0.50 I ton Other Hazardous Waste Fees imQosed on generators: Environmental Repair Fee 0 Base Fee=$ 125.00 I yr 0 Waste Generated= 12.00 I ton Manifest Fee= 2.00 I manifest WYOMING 1(307) 777-7938 !Cheyenne, WY The state charges TSDFs for permits and other waste management fees. Source: HTRWCE (2002) 173

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F. VARIABLES DESCRIPTION AND DATA CONVERSION Table F. I Trends Data Variable Data Type Description Year Nominal Time series from 1988 to 2002 BRS Total Interval I Ratio BRS waste volume (in tons) by year BRS Reduction Interval BRS waste reduction rate by year Rate Total R&D Funds Interval I Ratio Total R&D funds in million dollars by year Federal R&D Interval I Ratio Federal R&D funds in millions of dollars by Funds year Company R&D Interval I Ratio Company R&D funds in millions of dollars by Funds year R&D Performing Interval I Ratio R&D performing company R&D funds in Company Funds millions of dollars by year R&D Contract Out Interval I Ratio R&D contract out funds in millions of dollars Funds by year Total Pollution Interval I Ratio Total pollution reduction funds in millions of Reduction Funds dollars by year Pollution Interval I Ratio Pollution reduction funds of private company in Reduction millions of dollars by year Company Funds NumberofR&D Interval I Ratio The number of R&D performing company by Company year Technical Interval I Ratio The number of technology assistance by federal Assistance government by year Third Party Interval I Ratio The number of third party treatment facility by Treatment Facility year 174

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F.l Data Conversion Procedures F.l.l Data Collection and Data Type Raw data collected from the sources are usually in the format of spread sheet and/or text file and are coded in different ways. BRS and RCRIS data collected from the Right to Know Network (RTKN) are in the format of comma-delimited ASCII files. They combine multiple years of information into a single text file. TRI data can be collected from the RTKN and/or the EPA. The format ofthe former is identical to the above. However, the latter is in the format of spread sheet and the files are usually separated by different categories such as trends or geography. R&D data from the National Science Foundation (NSF) are spread sheet files. Similar to the format ofthe files from the RTKN, multiple years of information are combined into a single file. State regulations and technical assistance data are based on hard copies and/or web pages. F.1.2 Data Conversion For single files such as BRS data, the first step is to convert them into SPSS dataset. Second, by using the syntax such as "select if," data can be (temporarily) subtracted by year and by state. The subtracted data then are saved into different files with titles such as BRS 1989 by state, etc. Third, subtract the same item such as waste volume or TSDF status from each and every sub-file and put them side by side into a new file. The new file then has the same item/variable of multiple years by 175

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state. Fourth, calculate the mean or average waste reduction rates based on the multiple years of data and obtain the values of certain variables, such as the average BRS reduction rate or average number of facility. Fifth, put all the final values of variables into the final SPSS dataset for statistical analysis and hypothesis testing. Sixth, for data files that have been separated by year, the second step can be neglected. For national trends, the data are organized by year. Seventh, nominal data or the number of technical assistance is input by hand in to the SPSS dataset. 176

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3 00E 8 Gl 2 50E 8 E :I 0 > 2 00E 8 s Ill > 1 50E 6-If) a: ID !: 1 00E 6S .OOE 7 O.OOE 0 G.GENERALTRENDSANDSTATESTATUS BRS Waste Volume (tons) by Year ,..--r-,..-r--,..--I I I I I I I I I I I I I I I 1988 1989 1990 1991 1992 1993 1994 1995 199e 1997 1998 1999 2000 2001 2002 Year Data from 1989 to 1999 FigureG.l BRS WasteVolumes(tons)byYear 177

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3000 2500 .... 2000 Ill j 1500 E ;:, z 1000 .. ;:, 500 BRS Number of Facility by Year rrr1U88 1118U 1gg() 1UU1 1UU2 1UU3 1UU4 1UU!i 1UII8 1UU7 111U8 1ggg 2000 2001 2002 Year Data from 1989 lo 1999 Figure 0.2 BRS Number of Facility by Year Federal R&D Funds In Millions of Dollars ... 500 0 ,.....-.. c 400 ::E .5 .. l!!! 300 ;:, .. "-= co oec a:: 200 '! ,.....r-.. "0 .. .... 100 .. ;:, ii > On 1gaa 19UO 1GQ1 1QG2 1H3 1H4 1DG5 1QQI 1Q97 1QQ8 1QW 2000 2001 2002 Year Data from 1989 lo 2001 Figure 0.3 Federal R&D Funds in Millions of Dollars 178

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... 25000 0 .. 0:: i 20000 .5 .. 5 I!! 1 5000 """' c= ..,o a::D >o 10000 0:: a E 0 (.) 5000 :I ii > Company R&D Funds In Millions of Dollars ;--;--__ ;--;--rYear Data from 1989 to 2001 Figure G.4 Company R&D Funds in Millions of Dollars 25000 20000 -u 1 5000 -:::1 iii > 10000 5000 Federal and Company R&D Funds Comparison in in Year Data from 1989 to 2001 Figure G.5 Federal and Company R&D Funds Comparison 179

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-0 Federal Pollution Reduction Funds In Millions of Dollars r-1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Year Data from 1989 to 2001 Figure G.6 Federal Pollution Reduction Funds in Millions of Dollars Ill 200 'C c :I L&. c .2 g!! 150 'Cftl a::o cc 0 ... -0 15111 :C 100 oo ftl c Q.E 50 0 u Gl :I iij > Company Pollution Reduction Funds in Millions of Dollars rr--r-rD Year from 1989 lo 2001 Figure G. 7 Company Pollution Reduction Funds in Millions of Dollars 180

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Gl :I 200 1 50 Federal and Company Pollution Reduction Funds Comparison Federal Pollution Reduction Funds in Millions of Dollars Company Pollution Reduction Funds in Millions o1 DoUars ;: 1 00 50 I 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Year Data from 1989 to 2001 Figure G.8 Federal and Company Pollution Reduction Funds Comparison Chemical Industry R&D Performing Company R&D Funds In Millions of Dollars .5 25000 ., "0 c :I Ll.. r-r-->-20000 -c "'I!! E: 0 0 15000 CJC 1:11 ... c 0 r--....---r-r--,_r--o.2 10000 t:= _c "" 5000 a: Gl :I ii > I 1Q88 1QBQ 1Q90 19Q1 1QQ2 1QQ3 1GG4 1H5 1QQ6 1W7 1GGS 1QQQ 2000 2001 2002 Year Data from 1989 to 2001 Figure G.9 R&D Performing Company R&D Funds in Millions of Dollars 181

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Chemical Industry R&D Contract Out Funds In Millions of Dollars ., 3000 c i 2500 .E ., '1:1 c 2000 :I a..e .. ., :::1-co 1 500 .. c -e 0 1000 0 c .., a:: 500 Ill :I ii > -r-r-r-r-r-r--11188 1118U 1ggo 1UU1 1UU2 1UU3 111U4 1UU5 1uue 1UU7 1UU8 1ggg 2000 2001 2002 Year Data from 1989 to 2001 Figure G .1 0 R&D Contract Out Funds in Millions of Dollars >o 2500.00 c .. ... 5 0 2000 .00 Ill c .g 1 500 00 Ill D.. c .., 1000.00 l E :I 500 .00 z ., ::J ii > 0 00 Number of R&D Company In Chemical Industry r---r-r--r---lnnn 1Q88 1G88 1QIKI 1QQ1 1GQ2 1QQ3 1Q94 1VG5 1M 1QQ7 19518 1QQQ 2000 2001 2002 Year Data from 1989 to 2001 Figure G .11 Number of R&D Company in Chemical Industry 182

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150 .00 ::! Oi 120. 00 .. < Oi I) 90.00 I) 0 ... 60.00 .c E :I z 30.00 :I Number of Technical Assistance from the EPA Year Data from 1988 to 2002 Figure G.l2 Number ofTechnical Assistance from the EPA u "' u.. c !!? 300 00 "' D. l! :c 200.00 1... .c 100 00 z :I 0 00 Number of Third Party Treatment Facility r-r-I 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Year Data from 1989 to 1999 Figure G.l3 Number of Third Party Treatment Facilities 183

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Table G.l Rankings of State Capacity and Status, BRS Data from 1989 to 1999 State Number State Waste State Waste of Volume (tons) Reduction Facility Rate New Jersey 287.00 Texas 53350114.00 Hawaii -0.7834 California 205.83 Tennessee 33676190.00 Rhode Island -0.3964 Texas 187.83 Louisiana 22044387.00 Michigan -0.294 Illinois 172.83 West Virginia 15432214.00 Nevada -0.1799 Ohio 162.50 Michigan 14054382.00 Virginia -0.1138 Pennsylvania 145.67 New Jersey 11416882.00 North Carolina -0.0899 New York 145.60 New York 8509683.00 Ohio -0.0112 Michigan 88.83 Virginia 7725103.00 Tennessee 0.0091 North Carolina 82.50 Georgia 5864299.00 Kansas 0.0142 Georgia 79.67 Pennsylvania 5610007.00 Texas 0.1071 Louisiana 75.83 Kentucky 5275747.00 Arkansas 0.1235 Missouri 74.83 California 5211915.00 Vermont 0.1382 Indiana 70.17 Alabama 2950840.00 Georgia 0.1395 Tennessee 67.60 Connecticut 2509801.00 Kentucky 0.1702 Massachusetts 63.40 Indiana 1777083.00 Connecticut 0.1781 South Carolina 62.00 Mississippi 1618509.00 West Virginia 0.2019 Kentucky 51.00 Illinois 1520180.00 Maine 0.2169 Maryland 47.17 Kansas 1514893.00 Mississippi 0.2397 Wisconsin 47.17 Idaho 1354603.00 Oklahoma 0.2685 Alabama 42.83 Ohio 1141433.00 Pennsylvania 0.2848 Florida 42.00 North Carolina 1053127.00 Alabama 0.299 Connecticut 41.33 Delaware 952382.50 Wisconsin 0.3572 Virginia 38.50 Arkansas 814953.60 Louisiana 0.5087 Washington 37.00 Missouri 681624.50 Florida 0.5429 Kansas 33.17 Maryland 641477.10 New York 0.8298 West Virginia 28.50 Iowa 562460.30 New Mexico 0.8363 Iowa 23.50 Florida 419357.10 Illinois 0.9333 Arkansas Rhode Island New 21.67 382480.80 Hampshire 0.9643 Mississippi 21.50 Washington 292062.20 Colorado 0.9667 Colorado 18.17 Minnesota 291130.40 Iowa 1.092 Minnesota 18.17 Massachusetts 206436.20 Maryland 1.2289 184

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Table G. I (Cont.) State Number State Waste State Waste of Volume (tons) Reduction Facility Rate Delaware 17.17 Wisconsin 117622.30 Missouri 1.427 Oregon 15.00 Alaska 98083.62 Nebraska 1.8138 Arizona 13.00 Utah 67991.43 California 2.2471 Rhode Island 10.60 South Carolina 52925.55 Massachusetts 3.2345 Oklahoma 9.33 Oklahoma 50842.18 Wyoming 3.2831 Utah 8.83 Oregon 20709.44 Indiana 4.4204 New Hampshire New Arizona 8.60 Hampshire 13526.47 4.7072 Nebraska 8.00 Nebraska 11693.14 Oregon 5.2299 Maine 5.40 Arizona 10380.07 North Dakota 14.5191 Idaho 4.50 Colorado 8380.52 Utah 19.8993 Nevada 4.33 Maine 1008.45 Montana 23.6307 Montana 2.83 Montana 977.39 Minnesota 25.7888 Alaska 2.67 Nevada 942.07 New Jersey 29.5633 Hawaii 2.00 New Mexico 464.43 South Dakota 39.0163 New Mexico 1.83 North Dakota 394.19 Alaska 50.4016 Wyoming 1.83 Vermont 268.65 Delaware 56.2297 District of Wyoming Idaho Columbia 1.50 196.76 138.0471 Vermont Hawaii District of 1.50 103.20 Columbia (a) South Dakota South Dakota South Carolina 1.20 93.62 (b) North Dakota District of Washington 1.00 Columbia 2.27 (c) a. Only had data m 1989 and 1999 b. Only had data in 1991 c. Only had data in 1993 185

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Table 0.2 Rankings ofR&D Funds by State, from 1989 to 2001 State Federal State Company State Total R&D R&D Funds R&D Funds Funds (mil (mil ds) (mil ds) ds) California 3973.71 California 23134.86 California 27108.57 Massachusetts 1733.57 Michigan 9351.57 Michigan 9442.71 New York 1648.43 New Jersey 8530.29 New York 9401.43 Florida 1113.00 New York 7753.00 New Jersey 8885.86 Pennsylvania 966.29 Massachusetts 6382.14 Massachusetts 8115.71 Virginia 835.57 Pennsylvania 5547.14 Pennsylvania 6513.43 Ohio 722.14 Texas 5291.43 Texas 5947.43 Maryland 717.43 Illinois 5113.71 Illinois 5318.00 Texas 656.00 Ohio 4343.29 Ohio 5065.43 Colorado 445.29 Connecticut 2635.71 Florida 3137.57 Arizona 390.86 North Carolina 2514.57 Connecticut 3005.42 Connecticut 369.71 Minnesota 2278.57 North Carolina 2547.86 New Jersey 355.57 Florida 2024.57 Minnesota 2528.00 New Mexico 353.71 Colorado 1814.57 Colorado 2259.86 Minnesota 249.43 Washington 1739.43 Washington 1946.00 Washington 206.57 Wisconsin 1130.29 Virginia 1762.28 Alabama 205.29 Arizona 1115.86 Maryland 1756.14 Illinois 204.29 Indiana 1088.71 Arizona 1506.72 Utah 111.00 Maryland 1038.71 Indiana 1184.57 Missouri 108.00 Oregon 998.71 Wisconsin 1146.86 Indiana 95.86 Delaware 986.86 Georgia 1075.85 Georgia 92.71 Georgia 983.14 Oregon 1027.00 Michigan 91.14 Virginia 926.71 Delaware 996.43 North Carolina 33.29 Missouri 621.86 Missouri 729.86 District of Utah Utah Columbia 31.71 578.86 689.86 Oregon 28.29 Alabama 430.14 Alabama 635.43 Alaska 26.00 Oklahoma 300.43 New Mexico 399.71 Tennessee 22.00 Kentucky 277.14 Oklahoma 315.14 Kansas District of District of 20.14 Columbia 256.86 Columbia 288.57 Wisconsin 16.57 South Carolina 229.14 Kentucky 280.28 186

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Table 0.2 (Cont.) State Federal State Company State Total R&D R&D Funds R&D Funds Funds (mil (mil ds) (mil ds) ds) Oklahoma 14.71 Tennessee 192.57 South Carolina 243.43 South Carolina 14.29 Idaho 149.00 Tennessee 214.57 Hawaii 10.14 Iowa 113.71 Idaho 149.43 Nevada New Iowa 10.14 Hampshire 90.43 116.71 Delaware 9.57 Kansas 79.29 Kansas 99.43 Maine Louisiana New 7.00 78.14 Hampshire 95.57 Louisiana 6.14 Nebraska 66.14 Louisiana 84.28 Vermont 5.57 North Dakota 62.86 Nebraska 70.43 New Vermont Vermont Hampshire 5.14 58.86 64.43 Nebraska 4.29 West Virginia 50.57 North Dakota 63.00 Mississippi 3.43 New Mexico 46.00 Nevada 53.28 Rhode Island 3.29 Rhode Island 43.57 West Virginia 51.43 Kentucky 3.14 Nevada 43.14 Maine 48.71 Iowa 3.00 Maine 41.71 Rhode Island 46.86 West Virginia 0.86 Mississippi 38.43 Mississippi 41.86 Arkansas 0.71 Arkansas 35.57 Alaska 36.71 Idaho 0.43 South Dakota 20.71 Arkansas 36.28 Montana 0.43 Hawaii 16.86 Hawaii 27.00 South Dakota 0.29 Montana 12.29 South Dakota 21.00 North Dakota 0.14 Alaska 10.71 Montana 12.72 Wyoming 0.14 Wyoming 10.57 Wyoming 10.71 187

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Table G.3 Rankings of the Average Number of the Third Party Treatment Facilities by State State No of the Third State Number of the Party Treatment Third Party Facility Treatment Facility Texas 46.83 Kansas 3.67 Louisiana 15.67 Maryland 3.17 Tennessee 15.5 Mississippi 2.5 California 13.83 Utah 2.17 New Jersey 11 Colorado 2 Pennsylvania 11 New Mexico 2 South Carolina 11 Oklahoma 2 Ohio 9.17 Iowa 1.83 Missouri 9 Arizona 1.8 New York 8.8 Maine 1.75 West Virginia 8.33 Delaware 1.67 Indiana 8.17 Nevada 1.5 Michigan 8 Minnesota 1.33 New Ham_p_shire 8 Rhode Island 1.33 lllinois 7 Idaho 1.25 North Carolina 6.83 Montana 1 Georgia 6.17 Nebraska 1 Alabama 6 Vermont 1 Kentucky 6 Alaska 0 Connecticut 4.8 District of Columbia 0 Massachusetts 4.8 Hawaii 0 Arkansas 4.5 North Dakota 0 Wisconsin 4.5 Oregon 0 Florida 4.2 South Dakota 0 Virginia 4.17 Wyoming 0 Washington 4 188

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