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Analysis of the United Nation's clean development mechanism carbon emission reduction projects from a life cycle assessment perspective

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Analysis of the United Nation's clean development mechanism carbon emission reduction projects from a life cycle assessment perspective
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Chernomordik, Tamara Balick
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Master's ( Master of Engineering)
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University of Colorado Denver
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Department of Civil Engineering, CU Denver
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Civil engineering

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ANALYSIS OF THE UNITED NATIONS CLEAN DEVELOPMENT MECHANISM
CARBON EMISSION REDUCTION PROJECTS FROM A LIFE CYCLE ASSESSMENT
PERSPECTIVE
by
TAMARA BALICK CHERNOMORDIK B.S., Washington University in St. Louis, 2009
A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Master of Engineering Civil Engineering Program
2016


This thesis for the Master of Engineering degree by Tamara Balick Chemomordik has been approved for the Civil Engineering Program by
Bruce Janson, Chair Arun Karunanithi, Advisor Caroline Clevenger
December 17th, 2016
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Chemomordik, Tamara Balick (M.Eng., Civil Engineering, Sustainable Infrastructure)
Analysis of the United Nations Clean Development Mechanism Carbon Emission Reduction Projects from a Life Cycle Assessment Perspective Thesis directed by Professor Arun Karunanithi
ABSTRACT
I analyze, from a life cycle perspective, the effectiveness of the United Nations Clean Development Mechanism (CDM) emission reduction projects implemented in developing countries. Typically, the carbon offset credit allocated to these projects account for avoided direct emissions of GHGs but do not include indirect emissions that occur during upstream and downstream steps (for both avoided as well as the project emissions). I explore, through a case study approach, how these projects perform when life cycle calculations are used. Further, I also explore if these projects lead to lower (or higher) health and ecosystem impacts (co-benefits). A small but diverse set of renewable energy generation CDM projects are compared on an equivalent basis to assess any potential problem shifting issues. Results from this study can help policy makers assess effectiveness of such projects in a more holistic manner and fine tune their emission calculation methodologies.
The form and content of this abstract are approved. I recommend its publication.
Approved: Arun Karunanithi
ill


TABLE OF CONTENTS
CHAPTER
I. INTRODUCTION................................................1
II. A BRIEF HISTORY OF THE UNITED NATIONS FRAMEWORK CONVENTION ON
CLIMATE CHANGE...............................................4
III. THE CLEAN DEVELOPMENT MECHANISM.............................6
IV. EVALUATION OF THE ADVANTAGES AND DISADVANTAGES OF THE CLEAN
DEVELOPMENT MECHANISM........................................8
V. UNITED NATIONS CLEAN DEVELOPMENT MECHANISM METHODOLOGIES...11
VI. UNITED NATIONS CLEAN DEVELOPMENT MECHANISM PROJECT
BACKGROUNDS.................................................13
VII. METHODS....................................................16
The Honduras Hydropower Project.............................16
The China Windfarm Project..................................18
The India Biomass Project...................................20
The South Africa Solar PV Project...........................23
VIII. RESULTS...................................................26
IX. CONCLUSION AND FUTURE RESEARCH............................31
REFERENCES.......................................................33
APPENDIX
A. Information/GaBi processes used in Life Cycle Assessments..37
IV


CHAPTER I
INTRODUCTION
Human-generated emissions have had a clear and powerful effect on global climate change, ecological systems, and human health. Atmospheric and oceanic concentrations of carbon dioxide, methane, and nitrous oxides exist at an unprecedented level, and the amount of pollutants in global systems are on the rise. If these emissions continue to grow, the negative impacts will continue to increase and worsen. International governmental intervention has been and will continue to be extremely important in the fight to control anthropogenic greenhouse gas emissions1.
In 1997, the United Nations passed the Kyoto Protocol in response to the growing threat of climate change from anthropogenic carbon dioxide emissions. The Clean Development Mechanism (CDM) arose from this agreement with the intention to help the heavy polluting countries effectively reduce their carbon emissions, while promoting economic and social development in partner countries. Through the carbon credit trading program, sponsor countries can implement carbon emission reduction projects in developing countries in order to earn Carbon Emission Reduction (CER) credits, each is worth one ton of carbon dioxide equivalent, subtracted from their own emissions2.
The methodologies used to calculate CERs under this UN mechanism do not reflect life cycle emissions. Life cycle assessment can be a powerful tool to provide key decision-makers with a cradle-to-grave, holistic understanding of the global warming, ecological, and human health impacts stemming from an international development project. In addition to providing an understanding of global warming impacts, life cycle assessment can help indicate problem shifting into other areas.
Governmental standards and codes can be a useful tool in the fight against climate change as well. According to the International Organization for Standardization (ISO), a Life Cycle Assessment (LCA) is defined as a compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product or process throughout its life cycle; in more colloquial terms, this is known as the cradle-to-grave approach. It allows for the complete analysis of carbon dioxide
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emissions and emission equivalents of the holistic process and all of its inputs, versus focusing solely on emissions stemming from project activities. LCA studies are powerful tools that help identify upstream and downstream emissions, help to understand consequential impacts, and can help key decision-makers make educated judgements based on comprehensive data3.
According to the ISO, there are four phases in an LCA study4:
the goal and scope definition phase
the inventory analysis phase
the impact assessment phase
the interpretation phase
In this paper, I review these four phases for four UN CDM projects and calculate the life cycle emissions and impacts from each of them.
In order to gain a comprehensive perspective of the types of carbon emission reduction projects implemented under the United Nations, I decided to look at four projects, each focusing on a separate renewable energy technology in a different country and on a different scale. Table 1 shows the projects that I chose to analyze, their host and sponsoring countries, the methodologies each project used to calculate carbon emission reductions, and the estimated carbon dioxide emission reductions each project calculated using their methodology (which in turn translates to carbon credits gained from the project):
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Project Name Host Country Methodology Used Electricity Generation Capacity of Renewable Technology Estimated credits (CO2 eq) Emissions Reductions*
0028: RIO BLANCO Small Hydroelectric Project Honduras AMS-1.D.4: Grid connected renewable electricity generation Installed capacity of 5.24 MW 288,170 tonnes of CO2 eq emissions reduction
0064: China: Huitengxile Windfarm Project China AM0005: Small grid-connected zero-emissions renewable electricity generation Installed capacity of 25.8 MW 514,296 tonnes of CO2 eq emissions reduction
0058: Biomass in Rajasthan -Electricity generation from mustard crop residues India AMS-1.D.4: Grid connected renewable electricity generation Installed capacity of 7.8 MW 313,743 tonnes of CO2 eq emissions reduction
Project 8148: Karoo Renewable Energy Facility (Nobelsfontein Solar PV) South Africa ACM0002 / Version 13.0.0: Consolidated baseline methodology for grid-connected electricity generation from renewable sources Installed capacity of 50.4 MW 917,855 tonnes of CO2 eq emissions reduction
Table 1. Key information from the four analyzed Clean Development Mechanism projects. *Note: Total emissions reflect UN CDM project crediting period of 10 years for all cases
Since the operational implementation of the CDM program in 2006, the mechanism has registered more than 1650 projects with a combined estimated 2.9 billion tons of carbon dioxide equivalent emission reductions. This international agreement has created positive movement towards global carbon dioxide emissions reductions, and the methods in which the carbon dioxide emissions have been calculated has been continuously improving5.1 believe that further fundamental improvements need to be made in order to holistically understand and increase the benefits and improve information flow surrounding these projects. This paper aims to make a case for the following: to more accurately calculate greenhouse gas emission reductions for UN CDM (or future mechanism) projects and carbon trading, the current methodologies need to reflect Life Cycle Assessment emissions.
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CHAPTER II
A BRIEF HISTORY OF THE UNITED NATIONS FRAMEWORK CONVENTION ON CLIMATE CHANGE
In 1988, the World Meteorological Organization (WMO) and the UN Environment Programme (UNEP) established the Intergovernmental Panel on Climate Change (IPCC)6. The IPCC is the intergovernmental body responsible for calculating and assessing the science behind climate change7. In 1990, the IPCC released their first comprehensive report stating that climate change was being driven by anthropogenic sources, which prompted a call for a world leadership meeting to discuss an international climate treaty. In 1992, the United Nations Framework Convention on Climate Change (UNFCCC), an international convention with the purpose of reducing human-caused climate change, was formed at the Earth Summit in Rio. During the international meeting in Berlin in 1995, countries agreed that the initial commitments made were inadequate in fighting climate change and meeting goals; this paved the way for the Kyoto Protocol, which was adopted on December 11th, 1997. The first of its kind, this treaty focused on greenhouse gas emissions reductions. In 2001, this treaty was ratified to include specific operational rules on international emissions trading and established the Clean Development Mechanism and Joint Implementation. After numerous countries signed onto this program, the Kyoto protocol officiated in 2005 and the Clean Development Mechanism opened in 2006. In 2015, the IPCC released their fifth assessment report, which indicated the dire need of countries to take action against anthropogenic carbon emissions, furthering the drive for international cooperation6.
In December 2015, the Conference of the Parties (COP) met for COP 21 in Paris and created a new, more aggressive climate agreement. The significance of this meeting was evident in the fact that both developing and developed countries were coming together to fight a common cause; climate change and global warming mitigation. The major agreement between the 115 countries that have currently ratified this proposal (as of December 2016) is to make the best international effort to keep global warming below the threshold of two degrees Celsius above pre-industrial levels. This is a
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monumental perception and paradigm shift in the political and global outlook of climate change. Only 55 countries, representing at least 55% of global greenhouse gas emissions, were needed to ratify and implement this agreement; that number has far been surpassed. There is a scientific understanding that this level of global warming, even a 1.5-degree difference, will have major, irreversible, and detrimental effects on human life, oceans, ecosystems, animals, and the planet. The countries that have ratified will commit to these goals by driving country-wide, and region-wide initiatives in order to build a knowledge base, promote and improve technology development, and secure funding for projects that will help curb carbon emissions8. While skeptics are unsure of the effectiveness of this treaty above what has already been done after the Kyoto Protocol, as more national and international detailed plans come into light over the coming months and years, there is a global sense of hope that the Kyoto Protocol and Paris Agreement will have long-term, positive effects9.
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CHAPTER III
THE CLEAN DEVELOPMENT MECHANISM
According to the UNFCCC website, The Clean Development Mechanism (CDM), defined in Article 12 of the Protocol, allows a country with an emission-reduction or emission-limitation commitment under the Kyoto Protocol (Annex B Party) to implement an emission-reduction project in developing countries. Such projects can earn saleable certified emission reduction (CER) credits, each equivalent to one metric ton of CCLeq, which can be counted towards meeting Kyoto targets5. The Paris Treaty did establish a new mechanism called a mechanism to contribute to the mitigation of greenhouse gas emissions and support sustainable development, which may end up replacing the current CDM10. As new specific details have not yet emerged from the Paris Agreement specifically addressing the replacement of the CDM, the current methodologies and programs remain.
Overseen by the CDM Executive Board (under the authority and guidance of the Conference of the Parties serving as the Meeting of the Parties to the Kyoto Protocol (CMP))11, the CDM program allows companies in developed countries to fund and develop renewable energy resources in developing countries, such as solar PV installations, hydroelectric plants, biomass facilities, and wind farms. This program benefits developing countries by allowing them to reduce their net carbon emissions through trade while they work on reducing at-home emissions, while at the same time, developing resources in countries that lack the financial means to develop these projects on their own5.
It is through a detailed process and review that the UNFCCC matches sponsoring countries and recipient countries. Once the project has been funded by an entity, and the emissions credits have been claimed by this entity, this entity then has the right to sell off their Carbon Emission Reduction credits (CERs) for the purpose of offsetting the cost, in a process called voluntary cancellation.
Once CERs are purchased by a different party for the purpose of voluntary cancellation, they are effectively pulled out of existence. CERs can be set at a price chosen by the Providers of CERs (countries that sponsored the CDM projects in the developing nations) and can only be sold once to
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Purchasers. Purchasers, with the goal of working towards climate neutrality, are instructed to measure their climate footprint, reduce their emissions as much as possible, then offset what they cannot reduce with UN certified emission reduction cancellations. Typically, offset CER prices are set between $0.50 and $5.00 per metric ton and can be chosen from any project of the Purchasers choosing. This mechanism provides the Providers the ability to recuperate some of their original project costs (or even turn a profit of the CERs are set at a high enough price), as well as allow individuals (Any individual 18 years of age and older, and any organization with access to a PayPal account or credit card can purchase the cancellation of CERs on the platform.) to buy and voluntarily cancel CERs for any number of carbon equivalent tons offset in order to meet their own sustainability goals12.
A similar program to the Clean Development Mechanism, the mechanism of Joint Implementation allows a sponsoring country in need of reducing net carbon emissions to earn Emission Reduction units (ERUs) from the project that they sponsor in a nation with financial need. Each ERU is equivalent to one metric ton of CO2 eq13. Together with the Clean Development Mechanism (CDM) and International Emissions Trading, the Joint Implementation formed the core of the UNs flagship climate change policy via the Kyoto Protocol. Both programs initiated in 2005, and allow countries to work together in order to promote sustainable economic development and reduce GHG emissions5.
One of the main differences between the CDM Mechanism and the JI Mechanism is that the Joint Implementation Mechanism allows industrialized (Annex 1) countries to subsidize projects in other Annex 1 countries. In addition, the JI parties act within a capped environment (in terms of carbon credits), whereas the CDM projects create new CERs. Within the JI Mechanism, the host country issues the emissions units and there is more flexibility within the JI program with how ERUs are created14. As details emerge from the Paris Agreement, these policies may alter to better capture the true amount of carbon emission reductions and effects of international development in this space.
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CHAPTER IV
EVALUATION OF THE ADVANTAGES AND DISADVANTAGES
OF THE CLEAN DEVELOPMENT MECHANISM
The intention of the CDM international development projects is to promote sustainable economic development as well as reduce overall GHG emissions globally. While there are multiple benefits stemming from these projects, the twin objectives (greenhouse gas emission reductions and sustainable economic development) can create an overlap issue in which one objective may step over the other. Critics of the CDM point out numerous concerns on the practical effectiveness of the program15. One such issue is additionality, considered when anthropogenic GHG emissions are reduced below those that would have occurred in the absence of the registered CDM project activity16. The intention behind CDM projects is to reduce the overall GHG emissions worldwide through sustainable development, however, this concept comes into question as CDM projects develop new resources, therefore adding to global GHG emissions and taking away the idea of a zero sum game. This issue has been debated, as in theory, the CDM projects replace what would have been developed in the place of renewable energy, but it is impossible to predict the needs of the future, therefore is left as an open discussion item17.
In order to combat false CER awards for emissions reductions that did not actually occur from a project, the Marrakech Accord, named after COP 7 which took place in Marrakesh, established an elaborate system for ensuring the real climate benefit from the CDM projects. However, this methodology is often criticized for being very complex and costly to the project developers. While the Marrakech Accord aimed to help test for additionality, the practical applications of these steps and safeguards make business interactions difficult and long, sometimes creating an impractical scenario for the involved parties. In fact, these complex processes and sets of approvals are actually blamed for the small number of CDM projects that are implemented and completed. The correct balance of progress and measurement needs to be addressed for each CDM project to ensure quick and effective implementation and carbon emission reductions18.
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CDM projects are also critiqued on aspects other than GHG emission reductions; one such study by Christoph Sutter and Juan Carlos Parreno in Climate Change addressed issues such as job creation/local employment, improvements in air quality, and distribution of CER revenues. Each CDM project assessed in this study yields different results in each category. General trends in employment generation conclude that many CDM projects do not create many long-term local jobs in the host countries, with an exception of select biomass projects. For example, comparing three projects assessed from the study which are included in this thesis, the Rio Blanco Small Hydroelectric Project created an estimated .225 person months/1000 CERs of new employment and the Huitengxile Windfarm Project created an estimated .005 person months/1000 CERs, while the Biomass in Rajasthan project created an estimated 165.742 person months/1000 CERs. However, when assessing the distribution of CER revenues, the Rio Blanco Small Hydroelectric Project received an A rating, while the Biomass Rajasthan and Huitengxile Windfarm Projects received a B rating. From this study, in terms of air quality improvement, the Rio Blanco Small Hydroelectric Project received an A rating, while the Biomass Rajasthan and Huitengxile Windfarm Projects received a B rating. As can be seen from this study, each project must be assessed on an individual level, and that holistic benefits depend on the individual scenario. Inconsistent results in these three categories suggest that the CDM projects do not fully deliver on their objectives15.
In addition to the above mentioned study, a study by Emily Boyd et. al reviewed 10 CDM projects and found that while they reduced carbon dioxide emissions, they fall short on delivering direct local benefits. Local jobs are not generally created, especially long-term opportunities. The renewable energy technologies implemented did not appear to benefit local communities, and in some cases, actually hurt local people (methane emissions causing decreased air quality). The projects in this study showed no causal relationship between project types and sustainable development outcomes. The study pointed out that the project documentation may be misleading in this case as it sometimes proved to leave out these negative details. Given this type of data, individual projects seem
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to create inconsistent benefits, and sometimes do not even meet the sustainable economic development goal of the CDM19.
Technology diffusion from northern hemisphere countries to southern hemisphere countries is seen as an advantage of the CDM20. Island countries, in particular, can benefit from CDM projects as a host country. Due to lack of access to the inland supply chain, resources and technologies cost more on island nations. Installing solar PV panels in Haiti might be more expensive than in Argentina, for example, due to the fact that Haiti is separated from the mainland by a large body of water. Lack of funding can be a standstill in getting renewable energy technologies to island countries that cannot outright pay for these installations. Access to CDM funding and international partnership can help developing, remote island countries gain easier access to renewable energy technologies that they might not have otherwise had access to. As the COP determines future details surrounding access to funding for these projects, these types of projects will be able to reach developing nations easier21.
The mechanism to contribute to the mitigation of greenhouse gas emissions and support sustainable development, the potential CDM replacement which stemmed from the Paris Treaty, may help to mitigate some of the key issues the CDM currently faces. According to Carbon Market Watch: Many key elements [of this mechanism] will be defined in the future, including what defines sustainable development, how to deliver net mitigation, moving beyond projects to broader policies and measures, and how double counting is to be avoided. Rules will also need to be established for transparent governance, and to ensure robust and verifiable accounting. All countries will be able to generate and/or use these offset credits, meaning that developed countries will compete with developing countries for the investment in mitigation activities. Since so much remains to be agreed on, its value in limiting warming to 1.5C can only be understood once more details have been negotiated10.
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CHAPTER V
UNITED NATIONS CLEAN DEVELOPMENT MECHANISM METHODOLOGIES
Within the Clean Development Mechanism framework, there are a number of methodologies from which to derive a value for CERs. While three different UN CDM approved methodologies were used for calculating CO2 eq emission reductions in the four projects I studied, the same general themes applied to all four of the analyzed projects. The project boundaries only needed to include physical project activities, with CERs earned for emission reductions calculated from these technologies. Most renewable technologies were grouped into the same methodology, such as this example from the Solar PV Project, The project activity is the installation, capacity addition, retrofit or replacement of a power plant/unit of one of the following types: hydropower plant/unit (either with a run-of-river reservoir or an accumulation reservoir), wind power plant/unit, geothermal power plant/unit, solar power plant/unit, wave power plant/unit or tidal power plant/unit22. This generalization of renewable technologies does not account for life cycle emissions of the different technologies, it assumes that all renewable technologies are zero emission, and awards CERs without accounting for how these specific technologies were created, transported to the project site, or decommissioned.
The calculations for each project using these methodologies measured displaced electricity from the grid and/or other sources; the baseline scenario. The baseline emissions were quantified by multiplying net electricity generation produced through the renewable technologies in these projects and sent to the grid, and multiplying them by a CO2 eq emission factor. Depending on the methodology, the carbon emission factor could be retrieved by understanding what baseline factor was displaced (emissions from burning wood, operational, non-life cycle emissions factors for burning coal, etc.)23. The Rio Blanco Small Hydroelectric Project calculated the annual electricity to be generated from the dam and credited that amount against the emission coefficient for a modem diesel generating unit of the relevant capacity24. The Huitengxile Windfarm Project calculated the annual electricity generation from the installed turbines and credited that amount against emissions
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generated from the grid electricity mix25. The Biomass in Rajasthan Project calculated the annual electricity to be generated from burning the biomass waste and credited that amount against emissions from the grid electricity mix26. The Karoo Solar PV Project calculated the annual electricity generation from the installed photovoltaic panels and credited that amount against emissions from sub sectors of the grid electricity mix22.
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CHAPTER VI
UNITED NATIONS CLEAN DEVELOPMENT MECHANISM PROJECT BACKGROUNDS
The UN CDM hydropower project in was initiated in 2013 and was financed by Finland. In 2013, Honduras was vulnerable to international oil prices, and was victim to multiple extreme climate variations, such as El Nino. Without a strong, existing national power program based on renewables, the poor of the country were especially vulnerable to these energy price swings, and would supplement their energy supply by deforesting the natural forests. The goal of the project was to reduce the Honduran imported petroleum expenses, as well as reduce the countrys carbon dioxide emissions. In order to generate clean energy, the project built a run-off-river renewable hydroelectric generating plant with a generating capacity of 5MW, a Tyrol type diversion dam, a forebay, a 233m tunnel, a penstock, and a powerhouse. Along with these goals, the overarching project means of sustainable development were:
Generation of improved quality electricity for the San Francisco de Yojoa Municipality, which would foster the productive use of electricity in communities that still do not have it, as well than in the rest of the country
Help the country to reduce the imported oil bill, which would strengthen energy self sufficiency
Reduction of GHG emissions, specifically CO2
Strengthening of the countrys rural electrification coverage
Serve as a small demonstrative project for clean renewable energy generation in the country
Preservation of the Rio Blanco River basin
Reforestation of project's area of influence
Permanent and temporary job generation through the projects implementation
Production of indirect employment in the area
Improvement of hand quality labor in the area by training in different technical areas
Contribution to local community by payment of taxes
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The project estimated an average electricity production of 36 GWh/year, causing a reduction of 28,817 metric tons of carbon dioxide equivalent per year according to UN CDM methodology. Using 10 years as a project baseline, the Rio Blanco Hydroelectric Project estimated a total of 288,170 metric tons of CO2 eq abated from diesel emissions through electricity production between 2004 and 201424
The wind farm project in Huitengxile, China began in 2004 and was financed by The Netherlands. The objective of the project was to generate renewable energy using wind turbine power and to sell the generated electricity to the Inner Mongolian Western Grid on the basis of the Power Purchase Agreement (PPA). The project also aimed at reducing GHG emissions of the grid, which was dominated by coal, serving as a showcase of renewable energy options in China, as well as improving air quality, improving energy security, and improving local livelihoods through employment and pollution reduction.
Through installing 22 turbines, 12 with a 900kW capacity and 10 with a 1500 kW capacity, the project had a total capacity of 25.8MWs. The site chosen was proven to have excellent wind resources from multiple studies, and the already existing transmission system with a nearby power generation base made this region the optimal site. The 22 wind turbines would contribute a net amount of 59.19 GWh of electricity to the grid a year. With a project emission factor of .915 tCC>2 eq/MWH, the annual carbon dioxide equivalent reduction would be 54,136 tCC>2 eq or atotal of 514,296 tC02 eq over a ten-year crediting period25.
The biomass project in Rajasthan, India was initiated in 2003 and was financed by The Netherlands and Germany. Mustard is a cash crop commonly grown in Rajasthan, and the crop is harvested for its seeds. However, the stalk and other waste products of the plant are commonly left on the field to either rot or to bum. In order to reduce this waste and benefit from this practice of waste removal, the local government decided to use this agricultural waste product to create a source of energy for the grid. Rajasthan had a peak deficit of 2.9% in 2003, and the mustard biomass electricity plant aimed to contribute to bridging the gap between supply and demand. Due to the rural location of
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the plant (Ganganagar), the project also aimed to improve air quality in the region (by replacing coal as the main energy option), as well as to promote employment in the local population.
The mustard biomass-based power plant that was built consisted of direct combustion and high steam pressure power generation technologies with an installed capacity of 7.8 MW. Using only 33% of the agricultural mustard residue, or 50,000 metric tons a year, the project intended to generate power as well as leave enough biomass for household fuel consumption. The goal was to produce
51.2 GWh per year; using 5.9 GWh/year in auxiliary production would leave the plant with a net of 45.4 GWh per year to export to the grid. The project estimated that this would reduce CO2 eq emissions from the grid by 32,563 tons a year, or sum to a total reduction of 313,743 tons of CO2 eq between 2003 and 201326.
The solar PV project through the UN CDM was initiated there in 2015 and was financed by the United Kingdom of Great Britain and Northern Ireland. Karoo, South Africa is a desert region with vast amounts of open space27. Almost 93% of South Africas electricity is generated in coal-fired power stations and the primary objective of the project was to generate electricity from polycrystalline solar voltaic panels in order to provide cleaner, renewable energy to the South African national grid. The project also looked at improving the environmental well-being of the region by reducing air pollution and improving socio-economic well-being by stimulating a green economy by sourcing materials locally and creating jobs in the sustainability space.
The project had an installed capacity of 50.4 MW, and was equipped with 25 sub-fields with
2.02 MW each. Each subfield was made up of 8400 polycrystalline modules, divided into 420 strings made of 20 modules connected in series. Overall, the project took up 343,728 square meters of space in the Karoo desert. By producing a net of 94,527 MWh a year for the grid, the plant expected to reduce CO2 eq emissions by 921,636 metric tons a year, or a total of 9,216,360 metric tons CO2 eq over the ten-year crediting period22.
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CHAPTER VII
METHODS
The Honduras Hydropower Project
In order to estimate the life cycle emissions associated with this project I considered the following unit processes: Hydroelectric Plant Construction2829 and Installation30, Hydroelectric Plant Operation31 and Maintenance, and Hydroelectric Plant Decommissioning and Sedimentation. Figure 1 below displays the key unit processes considered in this LCA.
r a Hydroelectric Plant Construction and r ^ Hydroelectric Plant Operation and r ^ Hydroelectric Plant Decommissioning
Installation L J Maintenance L J and Sedimentation L J

Avoided Emission -Diesel Generation
Figure 1. Framework used to build the life cycle assessment of the hydropower project.
The functional unit was fixed as 1 MWh electricity generated. I modeled the life cycle of this project based on the generation of 36,000 MWh/year consistent with the actual UN CDM project. However, I assumed a lifespan of 50 years and the life cycle emissions were normalized over this time span. Further in line with the project documentation, I modeled the hydroelectric plant as a run-of-river model, requiring no external electricity for operation (other than what is created by the hydroelectric plant), and that the project would displace grid electricity from a diesel based thermal generation unit. The inventory related to the plant was obtained from the Ecoinvent database32 with run-of-river classification. I further validated the material inputs by cross-checking with other
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sources. It was assumed that the emissions associated with the operation and maintenance phase to be nominal. I also assumed that materials from the dam decommissioning would be recycled and hence no emissions were assigned towards this. The biggest contributor to the carbon emissions during the decommissioning stage was the sedimentation-related emissions, with an estimate of 691 kg of carbon dioxide and 69.1 kg of methane emitted to the air per 1 MWh of electricity produced33. The project was credited with avoided emissions due to electricity generation through a diesel thermal generating unit. The avoided emissions were also calculated on a life cycle basis (unlike the actual UN CDM project estimates) using data from US LCI. This project received a certified emission reduction (CER) credit of 28,817 CERs as estimated using the UN CDM grid connected renewable electricity generation methodology.
Figure 2 shows the detailed processes flow diagram along with the materials flows for the functional unit (1 MWh of electricity). As can be seen in the diagram, the project activities include the building, use, and decommissioning of the hydropower plant, while the Credit process represents the avoided emissions from diesel electricity generation. The RoW: Honduras hydropower plant construction process represents an aggregated process in GaBi; this process represents the cradle to grave impact of the construction of the hydropower plant, including all lifecycle emissions and impacts.
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Honduras Hydropower LCA
Process plan: Reference quantities
The names of the basic processes are shown.
Figure 2. The life cycle assessment model built in GaBi for the hydropower project.
The China Windfarm Project
To estimate life cycle emissions of this project I considered the three major unit processes Windfarm Turbine Construction34353637, Windfarm Operation38 and Maintenance, and Windfarm Decommissioning39. Figure 3 below displays the key processes considered in this LCA.
r i r r ^
Windfarm Windfarm Operations and Maintenance L J
Construction (From Components on Site) L J E E Windfarm Decommissioning L J

Avoided Emission -Grid Electricity
Figure 3. Framework used to build the life cycle assessment of the windfarm project.


The functional unit of 1 MWh was considered, with atotal generation capacity of 1,183,800 MWhs over the lifespan of 20 years (the lifetime of a wind turbine). The emissions data related to the windfarm construction was obtained from Ecoinvent (Onshore turbine network construction and onshore turbine construction) while the emissions related to the transport of materials was obtained from the US LCI database (transport of materials to the site via combination truck). I adjusted the Ecoinvent data, which was based on a 2.59 MW capacity windfarm, to match the 25.8 MW capacity of the project. The project involves the installation of 22 turbines and I assumed an average weight of 164 tons per turbine. I assumed that the turbines were manufactured in Pune, India and transported 6060 km to Huitengxile, China. The emissions from transportation were based on 2.19E10 kgkm. In addition, I verified all data with other LCAs. The total generation was based on net electricity after adjusting for auxiliary electricity used for operation. It was assumed that maintenance emissions would be minimal over the 20-year period, and would only include lubricating oil changes, covered by the aggregated process for lubricating oil in Ecoinvent (1 oil change a year, 150 liters each time). Consistent with literature I assumed that during the decommissioning of the windfarm; the turbine materials of iron, steel, and copper would be recycled at the end of the turbine lifetime, while fiberglass, plastic PVC, and concrete would be landfilled, and oil and rubber would be combusted.
The relevant emissions for these end-of-life steps were taken from the Ecoinvent and US LCI databases.
The project was credited with avoided life cycle emissions in line with electricity displaced from the avoided grid usage. The local grid mix consisted of: coal 92.47%, hydro 6.51%, and wind 1.02%. The life cycle emission factors for coal was obtained from the US LCI database, with electricity from lignite for Canada (Canadian aggregated processes were used when US or country-specific processes were not available in GaBi). For the hydropower and wind processes, the emissions data was obtained from Ecoinvent using China-specific aggregated processes. This project received a certified emission reduction (CER) credit of 54,136 CERs as estimated using the UN CDM small grid connected zero emissions renewable electricity generation methodology.
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Figure 4 below shows the GaBi processes used to build this assessment along with flow values as per the functional unit (1 MWh of electricity). The project processes are represented in this process flow from construction to decommissioning. In this case, the avoided emissions stem from replacing electricity from the local grid mix. It should be noted that this grid mix is local to the region both in percentages of the different technologies represented in the grid mix, and also because the aggregated processes from GaBi are China-specific as much as possible.
China Windfarm LCA
Process plan! Reference quantities
Figure 4. The life cycle assessment model built in GaBi for the windfarm project.
The India Biomass Project
I considered the following unit processes for this project: Mustard Biomass Waste Transportation, Mustard Biomass Storage, Mustard Biomass Processing and Electricity Generation, and Decommissioning and Disposal of the Biomass based power plant40. Figure 5 below displays the key processes considered in this LCA.
20


r Transportation of Mustard Biomass II r ^ r ^ Mustard Biomass II r ^ Mustard Biomass
Mustard Biomass Processing and Plant
to Site k . Storage Electricity Decommissioning
ll ll Generation and Disposal k j
Avoided Emission-Grid Electricity
Figure 5. Framework used to build the life cycle assessment of the mustard biomass project.
Since the mustard is grown as a food crop and electricity generation is only a byproduct I considered the functional unit for this project as 1 kg biomass, with a total of 1,000,000,000 kg biomass used over a 20-year period (the lifetime of the boiler). However, for comparative purposes I also normalized the results based on the unit of 1 MWh. It was assumed that the mustard plants would have been grown regardless of this biomass electricity project and therefore inputs and emissions associated with the growing of the mustard plants was ignored in this analysis. In order to transport the mustard biomass waste to the electricity plant, camels and tractor trolleys were used. I estimated that emissions associated with the transport of 50,000,000,000 kgkms per year needs to be considered and I used US LCI's emission factor for a combination truck41 for this purpose. In addition, methane emissions associated with the camels involved in transport were included42"43. It was assumed that a storage silo holds the biomass waste and I accounted for the emissions associated with the main materials used for construction of the silo44. More importantly, I also accounted for the methane emissions that would occur from storage of the biomass (usually associated with anaerobic digestion as pointed out in the project documentation)26.1 modeled the biomass electricity generation step based on information from the National Institute of Building Sciences45 and accounted for upstream emissions due to the production of a boiler with a lifespan of 20 years46 and a turbine with a lifespan of 40 years47. The emission factors for the boiler and turbine were obtained from the Ecoinvent database. For the decommissioning step I only included the electricity required to take down the
21


boiler, since it is assumed that the boiler and the turbine parts would be recycled and that the plant would continue to run after 20 years, just replacing equipment as needed. The project was credited with preventing electricity generation grid electricity. The information for the grid mix came from the UN CDM Project. The grid emission factors for the grid credits were all taken from GaBi: using US data for electricity from natural gas (11.19%) (PE US LCI48) and Indian data for electricity production from lignite coal (61.41%) (Ecoinvent), electricity production from 1-3MW wind turbines (.06%) (Ecoinvent), electricity production from run-of-river hydro (22.98%) (Ecoinvent), and electricity production from nuclear, pressure water reactor (4.36%) (Ecoinvent). The carbon dioxide emissions from burning the wood were ignored, as the trees would have initially taken in that much carbon dioxide throughout growth.
Figure 6 below shows the GaBi processes used to build this assessment along with flow values as per the functional unit (1 kg of mustard biomass waste). Please note that for the purposes of comparison to the other projects, 1.16E3 kgs of mustard biomass waste equate to 1 MWh of electricity. It should also be noted that the avoided grid emissions in this process flow are region-specific, and the aggregated processes are India-specific (as much as the database would allow).
India Biomass LCA
US: Iron and steel, P GLO: market for wire production mix USLCI/ts drawing, steel ecoinvent
Electridty, at grid, US IM 0.0173 kg |l.51E-005kg
RoW: alkyd paint $ production, white, J4.12E|006 kg
2.13E-007 MWh
Production of Storage Silo P** RoW: Mustard Biomass $ RoW: Mustard Biomass $ US' Electricity at grid HP
Boiler Production, 7.8 MW Turbine Construction (gas Eastern US USLCI/ts
(ROW Oil Boiler Production, turbine construction, 10MW
lOOkWl ecoinvent electri call ecoinvent
11.16E003 kg 1,16E-006 pcs. b1.16E-006 pcs. lo.321MWh
Growth of/separation X

Transport, combination P truck, diesel powered, and Mustard Biomass Storage P" Mustard Biomass P* Processing and Electridty Mustard Biomass Plant B* Decommissioning and
1.16E003 kg camel, mustard biomass 11.16E003 cargo USLCI/PE 1.16E003 kg Generation 1.16E003 kg Disposal
1.16E003 kg
Credit Electricity CP*
IN: Credit electricity IN: Credit electricity production, hydro, production, nudear,
run-of-river (Biomass) pressure water reactor
Figure 6. The life cycle assessment model built in GaBi for the mustard biomass project.
22


The South Africa Solar PV Project
I considered the following unit processes for this project: Solar Polycrystalline PV Panel Production, Solar PV Transportation to Site49, Solar PV Plant Construction and Installation, and Solar PV Plant Decommissioning and Disposal5". Figure 7 below displays the key processes considered in this LCA.
r Solar Polycrystalline PV H r ^ Solar PV Transportation to B r i Solar PV Plant Construction and B r ^ Solar PV Plant Decommissioning
Panel Production L A Site L A Installation L A and Disposal L A
4
Avoided Emission -Grid Electricity
Figure 7. Framework used to build the life cycle assessment of the solar PV project.
The functional unit for this project is 1 MWh, with a total of 2,363,175 MWh being produced over a 25-year period (the lifetime of a solar PV panel). The production of the solar panels was taken from an aggregated process in Ecoinvent; the aggregated process used were photovoltaic module production, building-integrated, for slanted-roof installation, which was the closest match that could be found for open ground installation. The project site is located in Republic of South Africa within the Northern Cape and Western Cape provinces, approximately 90 km north-east of the town of Beaufort West and 34 km south of the town of Victoria West. Given that the project had mentioned that materials would be sourced as locally as possible, Setsolar was used as the production facility for the PV panels, requiring that the solar panels and inverters be shipped 600 km from Setsolar to the project site (3,507,000,000 kgkm total)51. For the plant construction phase, the "ROW: photovoltaic mounting system production, for flat-roof installation' aggregated process was used from Ecoinvent to capture the 343,728 sqm of land that would be used to build this solar PV farm. For the
23


decommissioning and disposal step, I accounted for landfilling of glass/inert (USLCI), ZA: electricity, high voltage, production mix (Ecoinvent), RoW: water production, ultrapure (Ecoinvent), and RoW: market for diesel (Ecoinvent). These aggregated processes represent landfilling of the glass from the PV panels, electricity needed to recycle these materials, water used during the recycling process, and diesel needed to break apart the PV panels52"53. The credit was based off of contributing electricity to the grid, and displacing the current methods of electricity creation; dominated mainly by bituminous coal (92.78%), hydropower through pumped storage (1.23%), natural gas (.14%), nuclear (5.29%), and hydropower through a hydroelectric run-of-river plant (.65%). Emission factors for the grid credits were from South African electricity production from hard coal (Ecoinvent) and electricity production from hydro, pumped storage (Ecoinvent). In addition, the US unit processes used were electricity from hydropower (US LCI) and electricity from natural gas (US LCI). Due to lack of other available GaBi processes, Canadian data was used for electricity from nuclear (US LCI).
Figure 8 below shows the GaBi processes used to build this assessment along with flow values as per the functional unit (1 MWh of electricity). Note that the avoided emissions form the grid mix are region-specific in both technologies and aggregated processes.
24


South Africa Solar PV LCA
Procss plan: Reference quantities
The names of the base processes are shown.
RoW: photovoltaic module production, building-integrated, for slanted-roof installation US: Transport, combination truck, diesel powered (Solar PV) USLCI/PE
r P
Solar Polychristalline PV panel production Solar PV Transportation to Site
lMWh lMWh
Credit Electricity created from Solar PV Plant
US: Credit Electricity EP* from natural gas (Solar PV)
PE
Figure 8. The life cycle assessment model built in GaBi for the solar PV project.
25


CHAPTER VIII
RESULTS
Figure 9 and Table 2 below represents the per MWh comparison data between the four analyzed projects, from a carbon emissions perspective. Net avoided carbon emission represents the difference between life cycle project emissions and life cycle emissions of the baseline (avoided) scenario. The UN CDM avoided emission represents the non-LCA carbon emissions associated with the baseline scenario and also ignores the emissions from the project activity itself. Figure 1 shows the comparison between avoided emission credits, for one Megawatt hour energy, that each of the UN CDM projects received and the estimated life cycle avoided emissions. There is a high degree of variability across the projects. In relation to life cycle carbon emissions, the biomass and the windfarm projects actually received fewer carbon credits while the hydropower and solar projects received substantially more credits. From Table 1 it is clear that hydropower and solar projects would have received -46% and -30% fewer credits respectively if life cycle emissions were considered. Alternately the biomass and windfarm projects would have received -14% and 8% more credits respectively.
When looking solely at the LCA avoided emissions and the UN CDM avoided emissions (taking the life cycle project activities out of consideration), the differences between the two methodologies can be seen in greater context. Take the Honduras Hydropower project, for example; the project emissions are high enough to drive the net avoided LCA emissions to be less when compared to the UN CDM project methodology. Had the avoided LCA emissions been solely considered, the number of credits the project would have received would have been even greater than the UN CDM project. Compare this example to the China Windfarm project, which has almost no project-related emissions, but lower LCAA avoided emissions than the Honduras Hydropower project. This reiterates the importance of assessing the project from a comprehensive lifecycle perspective. Project activities and avoided emissions can vary greatly and need to be assessed together to understand holistic project impacts.
26


Avoided Emissions Per Megawatt Hour
HONDURAS SOUTH AFRICA SOLAR
INDIA BIOMASS CHINA WINDFARM HYDROPOWER PV
1000 500
O
m -500 -1000 -1500
Project Carbon Emissions (LCA) Abated/Avoided Carbon Emissions (LCA)
(kg C02 eq/MWh) (kg C02 eq/MWh)
Net Avoided Carbon Emissions (LCA) UNCDM Avoided Carbon Emissions (not LCA)
(kg C02 eq/MWh) (kg C02 eq/MWh)
Figure 9. Graphical comparison between life cycle carbon dioxide emission per functional unit of 1
MWh and UN CDM emissions per MWh.
Total Result Unit/MWH Project Carbon Emissions (LCA) (kg C02 eq/MWh) Abated/Avoided Carbon Emissions (LCA) (kg C02 eq/MWh) Net Avoided Carbon Emissions (LCA) (kg C02 eq/MWh) UN CDM Avoided Carbon Emissions (not LCA) (kg C02 eq/MWh) % Difference
India Biomass 247 -1066 -819 -717 -14.2%
China Windfarm 14 -1000 -986 -915 -7.8%
Honduras Hydropower 698 -1130 -432 -800 46.0%
South Africa Solar PV 384 -1060 -676 -971 30.4%
Table 2. Numerical comparison between life cycle carbon dioxide emission per functional unit of 1
MWh and UN CDM emissions per MWh.
The current UN CDM methodology does not require non carbon emissions impacts to be considered or calculated during these international development projects. In Table 3, the non-GHG impacts have been calculated in GaBi using the TRACI methodology from the life cycle assessments of these four projects. While each impact category cannot be compared to the number of an impact category (e.g. Net ODP vs. Net Ecotox), the four projects can be compared to each other within each
27


impact category (e.g. Net AP Biomass vs. Net AP Wind) The green highlighted number represents the highest avoided impacts in each category, indicating the project that performed the best for each impact factor. The red highlighted numbers represent instances in which the renewable energy projects minus avoided grid electricity actually performed worse (i.e. avoiding electricity generation from the grid mix did not make up for the negative impacts created by the implementation of the renewable energy technology in this case. This represents problem shifting (avoiding carbon emissions while creating other impacts).
Category Net AP Net EP Net ODP Net Smog Air Net Ecotox (Air/Soil/ Water) Net Human Health Cancer (Air/Soil/ Water) Net Human Health Criteria Air Net Human Health Non Cancer Air Net Human Health Non Cancer Soil Net Human Health Non Cancer Water
TRACI Result Unit/MWH H+ moles xlO2 eq/ MWh kgN eq/ MWh kg CFC 11 eq/ MWh kg 03x10 eq/ MWh CTUxlO3 eco/ MWh Cases/ MWh PMlOxlO eq/ MWh kg xlO2 Toluene eq/ MWh Cases/ MWh Cases/ MWh
India Biomass -2.71 -18.2 9.99E- 06 -4.8 1.45E+01 -1.47E- 04 -7.45 -3.23 -1.57E- 07 -6.16E- 04
China Windfaim -3.33 -0.182 2.07E- 06 -6.33 5.74E-01 6.65E-06 -0.157 -3.52 1.03E- 07 1.99E- 05
Honduras Hydropower -1.58 -0.12 5.22E- 07 -4.82 -5.67E- 01 1.05E-06 -0.0428 -5.95 1.19E- 08 -1.10E- 05
South Africa Solar PV -3.65 -3.66 5.57E- 06 -6.93 3.15E+00 -3.90E- 05 -0.174 -7.53 -1.41E- 07 -1.16E- 04
Table 3. Comprehensive impact comparison between UN CDM projects.
Each of the four examined UN CDM projects not only focused on a different renewable energy technology, but also took place in a different country than each of the others. While these four samples do not represent the entirety of the UN CDM project database, it is important to be able to compare them to each other.
In each of the created life cycle assessments in GaBi, the majority, if not the entirety of the project activities (manufacturing through decommissioning, not including avoided emissions from credit) were US/Canada-focused due to database limitations. The main processes in each of these
28


projects that were country-specific were those existing in the avoided grid electricity generation flows. This essentially gave us the freedom to interchange the avoided emissions of each unique country grid with unique country data between the projects. Table 4 below shows the data matrix of country vs. renewable energy project, allowing for an evaluation of the performance of each project in different countries. For example, the original biomass project took place in India, with -819 kg CO2 eq/MWh as the original LCA findings for carbon emission reductions (original project allocations represented in bold numbering). However, when the biomass project is evaluated against the Chinese grid, the results change dramatically, to -752 kg CO2 eq/MWh. Figure 10 below represents this data graphically, showing the original project life cycle calculations and showing the maximum/minimum value change based on country. This data provides clear patterns. Hydropower projects do not vary across countries as emissions from diesel generation do not vary across countries. Wind tends to perform best (have the most carbon emission reductions), across countries, while hydropower has the worst due to sedimentation emissions.
Given this data it is important to understand, however, that this model does not take into account renewable potentials/financials/govemments/corruption/project feasibilities in all of the regions. The purpose of this result is not to make claims that wind would be better in one location vs. another (what if China has better wind potential than Honduras?). It is solely shown for the purpose of assessing trends. For example, all else equal (resource potential, etc.), this analysis would be used to show a certain preference for one technology over the other. However, more information would need to be added to this model to truly represent which technologies and/or countries would perform best for these CDM projects.
29


India China South Africa Honduras
(kg C02 (kg C02 (kg C02 (kg C02
eq/MWh) eq/MWh) eq/MWh) eq/MWh)
Biomass -819 -752.8982 -812.8343 -882.8343
Wind -1052.1018 -986 -1045.9361 -1115.9361
Solar PV -682.1657 -616.0639 -676 -746
Hydropower -432 -432 -432 -432
Table 4. Technology comparison between countries.
*Note: this analysis does not take into account technology-specific requirements, such as solar/wind/biomass/hydropower potential of each region.
Country/Project Analysis
Biomass Wind Solar PV Hydropower
-1200
Figure 10. Graphical representation of carbon dioxide emission reduction differences when technologies are assessed in different regions.
30


CHAPTER IX
CONCLUSION AND FUTURE RESEARCH
After reviewing four unique UN CDM projects and performing life cycle assessments on each of them, it is clear that to more accurately calculate GHG emission reductions for UN CDM projects and carbon trading, the current UN CDM and future methodologies need to reflect LCA emissions. In addition, the LCA methodology allows for a more holistic view of both positive and negative impacts each project might have, instead of purely focusing on carbon emissions. It is important to account for ecological impacts, as well as those on human health, in order to properly assess each project and avoid problem shifting. Dynamic modeling of comprehensive cradle-to-grave studies would help international decision-makers understand the true impacts of development projects on people, places, and environments. It is important to provide decision makers with comprehensive information, however, this information alone does not drive decisions; this is an important distinction that needs to be made. Data is a powerful tool that can be used to aid in decision-making.
While the research and literature review in this thesis are comprehensive as of 2016, there are many research directions that could stem from this paper. Life cycle assessments could be performed on the projects which use CERs from the CDM projects in order to provide a comprehensive comparison of whether what is being replaced through these international development projects is truly one-to-one. For example, if a company in Germany produces adhesives and wants to offset their carbon credits by purchasing CERs from a solar PV UN CDM project, these two scenarios could be compared to understand the LCA offsetting perspective of the project vs. the companys processes. Additionally, as Life Cycle Cost Assessments (LCCAs) become more prevalent and widely used, LCCAs could be performed in tandem to understand the economic impacts occurring from these projects, as well as the economic benefits gained or lost from developing renewable energy resources. While adding on this level of research is a giant undertaking, as more projects are assessed, patterns could be extracted from more complicated models that incorporate data such as renewable resource potential, politics, corruption, exchange rates, and economics.
31


As the global methodologies and priorities change for the UNFCCC, it will be interesting to revisit this study in the future in order to fill in the blanks. For example, given the example of additionality, perhaps it would be important for the scientific community to agree on the time period that should be associated with assessing the value of the CDM projects. Many individuals invest money in the stock market with the long-term goal of improving their financial future, without knowing whether it will pay off in 30-40 years (but still having faith enough to invest). Should the same approach be taken with developing renewable energy? Understanding that the worlds population will increase to 9 billion by 2050 and will have increased energy needs, does it make sense to invest in renewable energy now and count the offset of non-renewable sources that would be developed to make up for that in the future? This important discussion could and should be researched from an economic/policy/philosophical perspective, as well as from a scientific/engineering perspective.
32


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APPENDIX A
Information/GaBi processes used in Life Cycle Assessments
LCA Process GaBi process Database
China Windfarm LCA Windfarm Turbine Construction US: Transport, combination truck, diesel powered US LCI
RoW: wind turbine network connection construction, 2MW, onshore Ecoinvent
RoW: wind turbine construction, 750kW, onshore Ecoinvent
Windfarm Operation and Maintenance GLO: market for lubricating oil Ecoinvent
Windfarm Decommissioning CH: treatment of waste concrete, inert material landfill Ecoinvent
US: Plastic waste on landfill USLCI
US: Glass/inert on landfill USLCI
CH: Residual fuel oil, combusted in industrial boiler USLCI
Avoided Electricity from Grid CA: Electricity from lignite USLCI
CH: Electricity production, hydro, run-of-river USLCI
CH: Electricity production, wind, 1-3MW turbine, onshore USLCI
Honduras Hydropower LCA Hydropower Plant Construction and Installation RoW: hydropower plant construction, run-of-river Ecoinvent
37


Hydropower Plant Operation and Maintenance N/A N/A
Hydropower Plant Decommissioning and Sedimentation US: Electricity, diesel, at Electricity plant USLCI
Sedimentation Pacca, S. Impacts from decommissioning of hydroelectric dams: a life cycle perspective Climatic Change 2007 84: 281. doi: 10.1007/sl0584-007-9261-4
India Biomass LCA Growth of/Separation of Mustard Biomass N/A
Transport of Biomass US: Transport, combination truck, diesel powered USLCI
Methane emissions from camels http://camelfarm.com/camels/camels_life.html http://www.livescience.com/27503- camels.html
Mustard Biomass Storage US: Electricity, at grid, US USLCI
US: Iron and Steel, production mix USLCI
RoW: alkyd paint production, white, solvent-based, product in 60% solution state Ecoinvent
GLO: market for wire drawing, steel Ecoinvent
Mustard Biomass Processing and Electricity Generation RoW: Oil Boiler Production, lOOkW Ecoinvent
RoW: Gas turbine construction, 10MW electrical Ecoinvent
Mustard Biomass Plant Decommissioning and Disposal US: Electricity, at grid, Eastern US USLCI
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Avoided Electricity from Grid IN: Electricity production, lignite Ecoinvent
IN: Electricity production, hydro, run-of-river Ecoinvent
US: Electricity from natural gas USLCI
IN: Electricity production, nuclear, pressure water reactor Ecoinvent
IN: Electricity production, wind, 1-3MW turbine, onshore Ecoinvent
South Africa Solar PVLCA Solar Polycrystalline PV panel production RoW: photovoltaic module production, building- integrated, for slanted-roof installation Ecoinvent
Solar PV Transportation to Site US: Transport, combination truck, diesel powered USLCI
Solar PV Plant Construction and Installation RoW: photovoltaic mounting system production, for flat-roof installation Ecoinvent
Solar PV Plant Decommissioning and Disposal ZA: electricity, high voltage, production mix Ecoinvent
RoW: market for diesel Ecoinvent
RoW: water production, ultrapure Ecoinvent
US: Glass/inert on landfill USLCI
Disposal/Landfill of materials Life Cycle Greenhouse Gas Emissions from Solar Photovoltaics; NREL, 2012; httn: //www .nrel. aov/docs/fV 13 osti/5 6487 .ndf.
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Avoided Electricity from Grid ZA: Electricity production, hard coal Ecoinvent
ZA: Electricity production, hydro, pumped storage Ecoinvent
US: Electricity from natural gas USLCI
US: Electricity from hydro power USLCI
CA: Electricity from nuclear USLCI
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CARBON EMISSION REDUCTION PROJECTS FROM A LIFE CYCLE ASSESSMENT PERSPECTIVE by TAMARA BALICK CHERNOMORDIK B.S., Washington University in St. Louis, 2009 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Master of Engineering Civil Engineeri ng Program 2016

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ii This thesis for the Master of Engineering degree by Tamara Balick Chernomordik has been approved for the Civil Engineeri ng Program by Bruce Janson Chair Arun Karunanithi, Advisor Caroline Clevenger December 17 th 2016

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iii Chernomordik, Tamara Balick (M.Eng., Civil Engineering, Sustainable Infrastructure) Analysis of the United from a Life Cycle Assessment Perspective Thesis directed by Professor Arun Karunanithi ABSTRACT I analyze, from a life cycle perspective, the effectiveness of the United Nations Clean Development Mechanism (CDM) emission reduction projects implemented in developing countries. Typically, the carbon offset credit allocated to these projects account for avoided direct emissions of GHGs but do not include indirect emissions that occur durin g upstream and downstream steps (for both avoided as well as the project emissions). I explore, through a case study approach, how these projects perform when life cycle calculations are used. Further, I also explore if these projects lead to lower (or hig her) health and ecosystem impacts (co benefits). A small but diverse set of renewable energy generation CDM projects are compared on an equivalent basis to assess any potential problem shifting issues. Results from this study can help policy makers assess effectiveness of such projects in a more holistic manner and fine tune their emission calculation methodologies. The form and content of this abstract are approved. I recommend its publication. Approved: Arun Karunanithi

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iv TABLE OF CONTENTS CHAPTER I. INTROD 1 II. A BRIEF HISTORY OF THE UNITED NATIONS FRAMEWORK CONVENTION ON CLIMATE 4 III. THE CLEAN DEVE 6 IV. EVALUATION OF THE AD VANTAGES AND DISADVA NTAGES OF THE CLEAN DEVELOPMENT MECHANIS M .. 8 V. UNITED NATIONS CLEAN DEVELOPMENT M ECHANISM METHODOLOGI ES 11 VI. UNITED NATIONS CLEAN DEVELOPMENT MECHANIS M PROJECT BACKGRO 13 VII. METHODS 16 The Honduras Hydr opower Project 16 The China Windfarm Project 18 The India Biomass Project 20 The South Africa Solar PV Project 23 VIII. RE 26 IX. CONCLUSION AND FUTUR E RESEARCH 31 REFERENCES .. 33 A PPENDIX A. Information/GaBi processes used in 37

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1 C HAPTER I I NTRODUCTION Human generated emissions have had a clear and powerful effect on global climate change, ecological systems, and human health. Atmospheric and oceanic concentrations of carbon dioxide, methane, and nitrous oxides exist at an unprecedented level and the amount of pollutants in global systems are on the rise. If these emissions continue to grow, the negative impacts will continue to increase and worsen. International governmental inter vention has been and will continue to be extremely important in the fight to control anthropogenic greenhouse gas emissions 1 In 1997, the United Nations passed the Kyoto Protocol in response to the growing threat of climate change from anthropogenic car bon dioxide emissions. The Clean Development Mechanism (CDM) arose from this agreement with the intention to help the heavy polluting countries effectively reduce their carbon emissions, while promoting economic and social development in partner countries. Through the carbon credit trading program, sponsor countries can implement carbon emission reduction projects in developing countries in order to earn Carbon Emission Reduction (CER) credits, each is worth one ton of carbon dioxide equivalent subtracted from their own emissions 2 The methodologies used to calculate CERs under this UN mechanism do not reflect life cycle emissions. Life cycle assessment can be a powerful tool to provide key decision makers with a cradle to grave, holistic understanding of t he global warming, ecological, and human health impacts stemming from an international development project. In addition to providing an understanding of global warming impacts, life cycle assessment can help indicate problem shifting into other areas. Governmental standards and codes can be a useful tool in the fight against climate change as well. According to the International Organization for Standardization (ISO), a Life Cycle Assessment (LCA) is defined as a compilation and evaluation of the inputs outputs and the potential environmental impacts of a product or process throughout its life cycle; in more colloquial terms, this to

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2 emissions and emission equ ivalents of the holistic process and all of its inputs, versus focusing solely on emissions stemming from projec t activities. LCA studies are powerful tools that help iden tify upstream and downstream emissions, help to understand consequential impacts, and can help key decision makers make educated judgements based on comprehensive data 3 According to the ISO t here a re four phases in an LCA study 4 : the goal and scope definition phase the inventory analysis phase the impact assessment phase the interpretat ion phase In this paper, I review these four phases for four UN CDM projects and calculate the life cycle emissions and impacts from each of them. In order to gain a comprehensive perspective of the types of carbon emission reduction projects implemented under the United Nations, I decided to look at four projects, each focusing on a separate renewable energy technology in a different country and on a different scale Ta ble 1 shows the projects that I chose to analyze, their host and sponsoring countries, the methodologies each project used to calculate carbon emission reductions, and the estimated carbon dioxide emission reductions each project calculated using their methodology (which in turn translates to carbon credits gained from the project):

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3 Proje ct Name Host Country Methodology Used Electricity Generation Capacity of Renewable Technology Estimated credits ( CO 2 eq) Emissions Reductions 0028: RIO BLANCO Small Hydroelectric Project Honduras AMS 1.D.4: Grid connected renewable electricity generation Installed capacity of 5.24 MW 288,170 tonnes of CO 2 eq emissions reduction 0064: China: Huitengxile Windfarm Project China AM0005: Small grid connected zero emissions renewable electricity generation Installed capacity of 25.8 MW 514,296 tonnes of CO 2 eq emissions reduction 0058: Biomass in Rajasthan Electricity generation from mustard crop residues India AMS 1.D.4: Grid connected renewable electricity generation Installed capacity of 7.8 MW 313,743 tonnes of CO 2 eq emissions reduction Project 8148 : Karoo Renewable Energy Facility (Nobelsfontein Solar PV) South Africa ACM0002 / Version 13.0.0: Consolidated baseline methodology for grid connected electricity generation from renewable sources Installed capacity of 50.4 MW 917,855 tonnes of CO 2 eq emissions reduction Table 1 K ey information from the four analyz ed Clean Development Mechanism p rojects Note: Total emissions reflect UN CDM p roject crediting period of 10 years for all cases Since the operational implementation of the CDM program in 2006, the mechanism has registered more than 1650 projects with a combined estimated 2.9 billion tons of carbon dioxide equivalent emission reductions. This international agreement has created positive movement towards global carbon dioxide emissions reductions, and the methods in which the carbon dioxide emissions have been cal culated has been continuously improving 5 I believe that further fundamental improvements need to be made in order to holistically understand and increase the benefits and improve information flow surrounding these projects. This paper aims to make a case for the following: to more accurately calculate greenhouse gas emission reductions for UN CDM (or future mechanism) projects and carbon trading, the current methodologies need to reflect Life Cycle Assessment emissions.

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4 C HAPTER II A BRIEF HISTORY OF THE U NITED NATIONS FRAMEWORK CONVENTION ON CLIMATE CHANGE In 1988, the World Meteorological Organization (WMO) and the UN Environment Programme (UNEP) established the Intergovernmental Panel on Climate Change (IPCC) 6 The IPCC is the intergovernmental body responsible for calculating and assessing the science behind climate change 7 In 1990, the IPCC released their first comprehensive report stating that climate change was being driven by anthropogenic sources, which prompted a call for a world leadership me eting to discuss an international climate treaty. In 1992, the United Nations Framework Convention on Climate Change (UNFCCC), an international convention with the purpose of reducing human caused climate change, was formed at the Earth Summit in Rio. During the international meeting in Berlin in 1995, countries agreed that the initial commitments made were inadequate in fighting climate change and meeting goals ; this paved the way for the Kyoto Protocol, which was adopted on December 11th, 1997. The fi rst of its kind, this treaty focused on greenhouse gas emissions reductions. In 2001, this treaty was ratified to include specific operational rules on international emissions trading and established the Clean Development Mechanism and Joint Implementation After numerous countries signed onto this program the Kyoto protocol officiated in 2005 and the Clean Development Mechanism opened in 2006. In 2015, the IPCC released their fifth assessment report, which indicated the dire need of countries to take acti on against anthropogenic carbon emissions furthering the drive for international cooperation 6 In December 2015, the Conference of the Parties (C OP) met for COP 21 in Paris and created a new, more aggressive climate agreement. The significance of this meeting was evident in the fact that both deve loping and developed countries we re coming together to fight a common cause; climate change and global warming mitigation. Th e major agreement between the 115 countries that have currently ratified this proposal (as of December 2016) is to make the best international effort to keep global warming below the threshold of two degrees Celsius above pre industri al levels. This is a

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5 monumental perception and paradigm shift in the political and global outlook of climate change. O nly 55 countries, representing at least 55% of global greenhouse gas emissions were needed to ratify and impl ement this agreement; that n umber has far been surpassed. There is a scientific understanding that this leve l of global warming, even a 1.5 degree difference, will have major, irreversible, and detrimental effects on human life, oceans, ecosystems, animals, and the planet. The count ries that have ratified will commit to these goals by driving country wide, and region wide initiatives in order to build a knowledge base, promote and improve technology development, and secure funding for projects that will help curb carbon emissions 8 While skeptics are unsure of t he effectiveness of this treaty above what has already been done after the Kyoto Protocol, as more national and international detailed plans come into light over the coming months and years, there is a global sense of hope tha t th e Kyoto Protocol and Paris Agreement will have long term positive effects 9

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6 CHAPTER III THE CLEAN DEVELOPMEN T MECHANISM Article 12 of the Protocol, allows a count ry with an emission reduction or emission limitation commitment under the Kyoto Protocol (Annex B Party) to implement an emission reduction project in developing countries. Such projects can earn saleable certified emission reduction (CER) credits, each eq uivalent to one metric ton of CO 2 eq, which can be counted towards meeting K yoto targets 5 ng the current CDM 10 As new specific details have not yet emerged from the Paris Agreement specifically addressing the replacement of the CDM, the current methodologies and programs remain. Overseen by the CDM Executive Board (under the authority and guida nce of the Conference of the Parties serving as the Meeting of the Parties to the Kyoto Protocol (CMP)) 11 the CDM program allows companies in developed countries to fund and develop renewable energy resources in developing countries, such as solar PV insta llations, hydroelectric plants, biomass facilities, and wind farms This program benefits developing countries by allowing them to reduce their net carbon emissions through trade while they work on reducing at home emissions, while at the same time, developing resources in countries that lack the financial means to develop these projects on their own 5 It is through a detail ed process and review that the UNFCCC matches sponsoring countries and recipient countries. Once the project has been funded by an entity and the emissions credits have been claimed by this entity this entity then has the right to sell off their Carbon E mission Reduction Once CERs are purchased by a different party for the purpose of voluntary cancellation they are effectively pulled out of existence. CER (countries that sponsored the CDM projects in the developing nations) and can only be sold once to

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7 me asure their climate footprint, reduce their emissions as much as possible, then offset what they cannot reduce with UN certified emission reduction cancellations Typically, offset CER prices are set between $0.50 and $5.00 per metric ton and can be chosen choosing. This mechanism provides the Providers the ability to recuperate some of their original project costs (or even turn a profit of the CERs are set at a high enough price), as well as allow idual 18 years of age and older, and any organization with access to a PayPal can cel CERs for any number of carbon equivalent ton s offset in order to mee t their own sustainability goals 12 Emission Reduction units (ERUs) from the project that they sponsor in a nation with financial need. Each ERU is equivalent to on e metric ton of CO 2 eq 13 Clean Development Mechanism (CDM) and International Emissions Trading the Joint Implementat ion formed the core of via the Kyoto Protocol initiate d in 2005, and allow countries to work together in order to promote sustainable economic development and reduce G HG emissions 5 One of the main d ifferences between the CDM Mec hanism and the JI Mechanism is that the Joint Implementation Mechanism allows industrialized (Annex 1) countries to subsidize projects in other Annex 1 countries. In addition, the JI parties act within a capped environment (in terms of carbon credits), whereas the CDM projects create new CERs. Within the JI Mechanism, the host country issues the emissions units and there is more flexibility within the JI program with how ERUs are created 14 As details emerge from the Paris Agreement, these policies may alter to better capture the true amount of carbon emission reductions and effects of international development in this space.

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8 CHAPTER IV EVALUATION OF THE AD VANTAGES AND DISADVA NTAGES OF TH E C LEAN DEVELOPMENT MEC HANISM The intention of the CDM international development projects is to promote sustainable economic development as well as reduce overall GHG emissions globally. While there are multiple benefits stemming from these projects, the t win objectives ( greenhouse gas emission reductions and sustainable economic development) can create an overlap issue in which one objective may step over the other. Critics of the CDM point out numerous concerns on the practical effectiveness of the program 15 One such issue is a reduced below those that would have occurred in the absence of the registered CDM project activity 16 emissions worldwide through sustainable development, however, this concept comes into question as CDM projects develop new resources, therefore adding to global GHG emissions and taking away the idea of a have been developed in the place of renewable energy, but it is impossible to predict the needs of the future, therefore is left as an open discussion item 17 In order to combat false CER awards for emissions reductions that did not actually oc cur from a project, the Marrakec h Accord, named after COP 7 which took place in Marrakesh, established an elaborate system for ensuring the real climate benefit from the CDM projects. However, this methodology is often c riticized for being very complex and costly to the project developers. While the Marrakech Accord aimed to help test for additionality, the practical applications of these steps and safeguards make business interactions difficult and long, sometimes creati ng an impractical scenario for the involved parties. In fact, these complex processes and sets of approvals are actually blamed for the small number of CDM projects that are implemented and completed. The correct balance of progress and measurement needs t o be addressed for each CDM project to ensure quick and effective implementation and carbon emission reductions 18

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9 CDM projects are also critiqued on aspects other than GHG emission reductions ; one such study by Christoph Sutter and Juan Carlos Par reo in C limate Change addressed issues such as job creation/local employment, improvements in air quality, and distribution of CER revenues. Each CDM project assessed in this study yields different results in each category. General trends in employment generation conclude that many CDM projects do not create many long term local jobs in the host countries, with an exception of select biomass projects. For example, comparing three projects assessed from the study which are included in this thesis the Rio Blanco Sma ll Hydroelectric Project created an estimated .225 person months/1000 CERs of new employment and the Huitengxi le Windfarm Project created an estimated .005 person months /1000 CERs, while the Biomass in Rajasthan project created an estimated 165.742 person months/1000 CERs. However, when assessing the distribution of CER revenues, the Rio Blanco Small Hydroelectric Project received an A rating, while the Biomass Rajasthan and Huitengxile Windfarm Projects received a B rating. From this study, in terms of air quality improvement, the Rio Blanco Small Hydroelectric Project received an A rating, while the Biomass Rajasthan and Huitengxile Windfarm Projects received a B rating. As can be see n from this study each project must be assessed on an individual level, and that holistic benefits depend on the individual scenario Inconsistent results in these three categories suggest that the CDM projects do not fully deliver on their objectives 15 In addition to the above mentioned study, a study by Emily Boyd et. al reviewed 10 CDM Local jobs are not generally created, especially long term opportunities. The renewable energy technologies implemented did not appear to benefit local communities, and in some cases, actually hurt local people (methane emissions causing decreased air qual ity). The projects in this study showed no causal relationship between project types and sustainable development outcomes. The study pointed out that the project documentation may be misleading in this case as it sometimes proved to leave out these negativ e details. Given this type of data, individual projects seem

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10 to create inconsis tent benefits, and sometimes do not even meet the sustainable economic development goal of the CDM 19 phere countries is seen as an advantage of the CDM 20 Island countries, in particular, can benefit from CDM projects as a host country. Due to lack of access to the inland supply chain, resources and technologies cost more on island nations. Installing sola r PV panels in Haiti might be more expensive than in Argentina, for example, due to the fact that Haiti is separated from the mainland by a large body of water. Lack of funding can be a standstill in getting renewable energy technologies to island countrie s that cannot outright pay for these installations. Access to CDM funding and international partnership can help developing, remote island countries gain easier access to renewable energy technologies that they might not have otherwise had access to. As th e COP determines future details surrounding access to funding for these projects, these types of projects will be able to reach developing nations easier 21 sustainable d may help to mitigate some of the key issues the CDM currently faces. According to Carbon Market luding what defines sustainable development, how to deliver net mitigation, moving beyond projects to broader policies and measures, and how double counting is to be avoided. Rules will also need to be established for transparent governance, and to ensure robust and verifiable accounting. All countrie s will be able to generate and/ or use these offset credits, meaning that developed countries will compete with developing countries for the investment in mitigation activities. Since so much remains to be agree d on, its value in limiting warming to 1.5C can only be understood once more details have been negotiated 10

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11 CHAPTER V UNITED NATIONS CLEAN DEVELOPMENT ME CHANISM METHODOLOGIES Within the Clean Development Mechanism framework, there are a number of methodologies from which to derive a value for CERs. While three different UN CDM approved methodologies were used for calculating CO 2 eq emission reductions in the four projects I studied the same general themes applied to all four of the analyzed projects. The project boundaries only needed to include physical project activities, with CERs earned for emission reductions calculated from these technologies. Most renewable technologies were grouped into the same methodology, such as this he installation, capacity addition, retrofit or replacement of a power plant/unit of on e of the following types: hydro power plant/unit (either with a run of river reservoir or an accumulation reservoir), wind power plant/unit, geothermal power plant/unit, solar power plant/unit, wave power plant/unit or tidal power plant/unit 22 generalization of renewable technologies does not account for life cycle emissions of the different technologies, it assumes that all renewable technologies are zero emission, and awards CERs without accounting for how these specifi c technologies were created, transported to the project site or decommissioned The calculations for each project using these methodologies measured displaced electricity from the grid and/or other sources; the baseline scenario. The baseline emissions were quantified by multiplying net electricity generation produced through the renewable technologies in these projects and sent to the grid, and multiplying them by a CO 2 eq emission factor. Depending on the m ethodology, the carbon emission factor could be retrieved by understanding what baseline factor was displaced (emissions from burning wood, operational, non life cycle emissions f actors for burning coal, etc.) 23 The Rio Blanco Small Hydroelectric Project calculated the annual electricity to be generated from the dam and credited that amount against the emission coefficient for a modern diesel generatin g unit of the relevant capacity 24 The Huitengxile Windfarm Project calculated the annual electrici ty generation from the installed turbines and credited that amount against emissions

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12 generated from the grid electricity mix 25 The Biomass in Rajasthan Project calculated the annual electricity to be generated from burning the biomass waste and credited th at amount against emissions from the grid electricity mix 26 The Karoo Solar PV Project calculated the annual electricity generation from the installed photovoltaic panels and credited that amount against emissions from sub sectors of the grid electricity m ix 22

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13 CHAPTER VI UNITED NATIONS CLEAN DEVELOPMENT ME CHANISM PROJECT BACKGROUNDS T he UN CDM h ydropower project in was initiated in 2013 and was financed by Finland. In 2013, Honduras was vulnerable to international oil prices, and was victim to multiple extreme climate variations such as El Ni o. Without a strong, existing national power program based on renewables, the poor of the country were especially vulnerable to these energy price swings, and would supplement their energy supply by de foresting the natural forests. The goal of the project was to reduce the Honduran imported petroleum expenses, as well as reduce emissions. In order to generate clean energy, the project built a run off river renewable hydroelectric generating plant with a generating capacity of 5MW, a Tyrol type diversion dam, a forebay, a 233m tunnel, a penstock, and a powerhouse. Along with these goals, the overarching project means of sustainable development were: Generation of improved quality electricity for the San Francisco d e Yojoa Municipality, which would foster the productive use of electricit y in communities that still do no t have it, as well than in the rest of the country Help the country to reduce the imported oil bill, which would strengthen energy self sufficiency Reduction of GHG emissions, specifically CO 2 cation coverage Serve as a small demonstrative project for clean renewable energy generation in the country Preservation of the Rio Blanco River basin Reforestation of project's area of influence implementation Production of indirect employment in the area Improvement of hand quality labor in the area by training in different technical areas Contribution to local community by payment of taxes

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14 The project estimated an average electricity production of 36 GWh/year, causing a reduction of 28,817 metric tons of carbon d ioxide equivalent per year according to UN CDM methodology Using 10 years as a project baseline, the Rio Blanco Hydroelectric Project estimated a total of 288,170 metric tons of CO 2 eq abated from diesel emissions through electricity production between 2004 and 2014 24 The wind f arm project in Huitengxile, China bega n in 2004 and was financed by T he Netherlands. The objective of the project was to generate renewable energy using wind turbine power and to sell the generate d electricity to the Inner Mongolian Western Grid on the basis of the Power P urchase Agreement (PPA). The project also aimed at reducing GHG emissions of the grid, which was dominated by coal, serving as a showcase of renewable energy options in China, as well as improving air quality, improving energy security, and improving local livelihoods through employment and pollution reduction. Through installing 22 turbines, 12 with a 900kW capacity and 10 with a 1500 kW capacity the project had a total capacity of 25.8MWs. The site chosen was proven to have excellent wind resources from multiple studies, and the already existing transmission system with a nearby power generation base made this region the optimal site. The 22 wind turbines would contribute a net amount of 59.19 GWh of elect ricity to the grid a year. With a project emission factor of .915 tCO 2 eq/ MWH, the annual c arb on d ioxide equivalent reduction would be 54,136 tCO 2 eq or a total of 514,296 tCO 2 eq over a ten year crediting perio d 25 The biomass project in Rajasthan, India was initiat ed in 2003 a nd was financed by T he Netherlands and Germany Mustard is a cash cro p commonly grown in Rajasthan, and the crop is harvested for its seeds. H owever, the stalk and other waste product s of the plant are commonly left on the field to either rot or to burn. In order to reduce this waste and benefit from this practice of waste removal, the local government decided to use th is agricultural waste product to create a source of energy for the grid. Rajasthan had a peak d eficit of 2.9% in 2003, and the mustard biomass electricity plant aimed to contribute to bridging the gap between supply and demand. Due to the rural location of

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15 the plant (Ganganagar), the project also aimed to improve air quality in the region (by replacing coal as the main energy option), as well as to promote employment in the local population. The mustard biomass based power plant that was built consisted of direct combustion and high steam pressure power generation technologies with an installed capacity of 7.8 MW. Using only 33% of the agricultural mustard re sidue, or 50,000 metric tons a year, the project intended to generate power as well as leave enough biomass for household fuel consumption. The goal was to produce 51.2 GWh per year; using 5.9 GWh/year in auxiliary production would leave the plant with a net of 45.4 GWh per year to export to the grid. The project estimated that this would reduce CO 2 eq e missions from the grid by 32,563 tons a year, or sum to a total reduction of 313,743 ton s of CO 2 eq between 2003 and 2013 26 The s olar PV project through the UN CDM was initiated there in 2015 and was financed by the United Kingdom of Great Britain and Northern Ireland. Karoo, South Africa is a desert region with vast amounts of open space 27 fired power stations and the primary objective of the project was to generate electricity from polycrystalline solar voltaic panels in order to provide cleaner, rene wable energy to the South African national grid. The project also looked at improving the environmental well being of the region by reducing air pollution and improving socio economic well being by stimulating a green economy by sourcing materials locally and creating jobs in the sustainability space. The project had an installed capacity of 50.4 MW, and was equipped with 25 sub fields with 2.02 MW each. Each subfield was made up of 8400 polycrystalline modules, div ided into 420 strings made of 20 modules c onnected in series. Overall, the project took up 343,728 square meters of space in the Karoo desert. By producing a net of 94,527 MWh a year for the grid, the plant expected to reduce CO 2 eq emissions by 921,636 metric tons a year, or a total of 9,216,360 metric tons CO 2 eq over the ten year crediting period 22

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16 CHAPTER VII METHODS The Honduras Hydrop ower Project In order to estimate the life cycle emis sions associated with this project I considered the following unit processes: Hydroelectric Plant Construction 28 29 and Installation 30 Hydroelectric Plant Operation 31 and Maintenance, and Hydroelectric Plant Decommissioning and Sedimentation. Figure 1 be low displays the key unit processes considered in this LCA. Figure 1 F ramework used to build the life cycle assessment of the hydropower project The functional unit was fixed as 1 MWh electricity generated I modeled the life cycle of this project based on the generation of 36 000 MWh/year consistent with the actual UN CDM project. However I assumed a lifespan of 50 years and the life cycle emissions were normaliz ed over this time span. Further in line w ith the project documentation, I modeled the hydroelectric plant as a run of river model, requiring no external electricity for operation (other than what is created by the hydroelectric plant), and that the project would displace grid electricity from a diesel based thermal generation uni t. The inv entory related to the plant was obtained f rom the Ecoinvent database 32 with run of river classification. I further validat ed the material inputs by cross checking with other

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17 sources. It was assumed that the emissions associated with the operation and mainte nance phase to be nominal. I also assumed that materials from the dam decommissioning would be recycled and hence no emissions were assigned towards this. The biggest contributor to the carbon emissions during the decommission ing stage was the sedimentation related emissions, with an estimate of 691 kg of carbon dioxide and 69.1 kg of m ethane emitted to the air per 1 MWh of electricity produced 33 The project was credited with avoided emissions due to electricity generation thro ugh a diesel thermal generating unit. The avoided emissions were also calculated on a life cycle basis (unlike the actual UN CDM project estimates ) using data from US LCI. This project received a certified emission reduction (CER) credit of 28 817 CERs as estimated using the UN CDM grid connected renewable electricity generation methodology. Figure 2 shows the detailed processes flow diagram along with the materials flows for the functional unit (1 MWh of electricity). As can be seen in the diagram, the pro ject activities include aggregated process in GaBi; this process represents the cradle to grave impact of the construction of the hydropower plant, including all lifecycle emissions and impacts.

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18 Figure 2. The life cycle assessment model built in GaBi for the hydropower project. The China Windf arm Project To estimate life cy cle emissions of this project I considered the three major unit processes: Windfarm Turbine Construction 34 35 36 37 Windfarm Operation 38 a nd Maintenance, and Windfarm Decommissioning 39 Figure 3 below displays the key processes considered in this LCA. Figure 3. Framework used to build the life cycle assessment of the windfarm project.

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19 The functional unit of 1 MWh was considered, with a total generation capacity of 1,183,800 MWhs over the lifespan of 20 years (the lifetime of a wind turbine). The emission s data related to the windfarm c onstruction was obtained from Ecoinvent (Onshore turbine network construction and onshore turbine constr uction) while the emissions related to the transport of materials was obtained from the US LCI database (transport of materials to the site via combination truck). I adjusted the Ecoinvent data, which was based on a 2.59 MW capacity windfarm, to match the 25.8 MW capacity of the project. The project involves the in stallation of 22 turbines and I assumed an average we ight of 164 tons per turbine. I assumed that the turbines were manufactured in Pune, India and transported 6060 km to Huitengxile, China. The e missions from transportation were based on 2.19E10 kgkm. In addition, I verified all data with other LCAs. The total generation was based on net electricity after adjusting for auxiliary electricity used for operation. It was assumed that maintenance emiss ions would be minimal over the 20 year period, and would only include lubricating oil changes, covered by the aggregated process for lubricating oil in Ecoinvent (1 oil change a year, 150 liters each time ). Consistent with literature I assumed that during the decommissioning of the wind farm; the turbine materials of iron, steel, and c opper would be recycled at the end of the turbine lifetime, while fiberglass, plastic PVC, and concrete would be landfilled, and oil and rubber would be combusted. The relevant emissions for these end of life steps were taken from the Ecoinvent and US LCI databases. The project was credited with avoided life cycle emissions in line with electricity displaced from the avoided grid usage. The local grid mix consisted of: coal 92. 47%, hydro 6.51%, and wind 1.02%. The life cycle emission factors for coal was obtained from the US LCI database, with electricity from lignite for Canada (Canadian aggregated processes were used when US or country specific processes were not available in GaBi). For the hydro power and wind processes, the emissions data was obtained from Ecoinvent using China specific aggregated processes. This project received a certified emission reduction (CER) credit of 54,136 CERs as estimated using the UN CDM small grid connected zero emissions renewable electricity generation methodology.

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20 Figure 4 below shows the GaBi processes used to build this assessment along with flow values as per the functional unit (1 MWh of electricity). The project processes are rep resented in this process flow from construction to decommissioning. In this case, the avoided emissions stem from replacing electricity from the local grid mix. It should be noted that this grid mix is local to the region both in percentages of the differe nt technologies represented in the grid mix, and also because the aggregated processes from GaBi are China specific as much as possible. Figure 4. The life cycle assessment model built in GaBi for the windfarm project. The India Biomass Project I consi dered the following unit processes for this project: Mustard Biomass Waste Transportation, Mustard Biomass Storage, Mustard Biomass Processing and Electricity Generation, and Decommissioning and Disposal of the Biomass based power plant 40 Figure 5 below di splays the key processes considered in this LCA.

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21 Figure 5. Framework used to build the life cycle assessment of the mustard biomass project. Since the mustard is grown as a food crop and electricity g eneration is only a byproduct I considered the functional unit for this project as 1 kg biomass, with a total of 1,000,000,000 kg biomass used over a 20 year period (the lifetime of the boiler). Howe ver, for comparative purposes I also normalized the results based on the unit of 1 MWh. It was assumed that the mustard plants would have been grown regardless of this biomass electricity project and therefore inputs and emissions associated with the growing of the mustard plants was ignored in this analysis. In order to transport the mustard biomass waste to the electricity plant, camels an d tractor trolleys were used. I estimate d that emissions associated with the transport of 50,000,000,000 kgkms per ye ar needs to be considered and I used ombination truck 41 fo r this purpose. In addition, methane emissions associated with the camels involved in transport were included 42 43 It was assumed that a storage sil o holds the biomass waste and I accounted for the emissions associated with the main materials used for const ruction of the silo 44 More importantly, I also accounted for the methane emissions that would occur from storage of the biomass (usually associated with anaerobic digestion as pointed out in the project documentation) 26 I modeled the biomass electricity generation step based on information from the National Institute of Building Sciences 45 and accounted for upstream emissions due to the production of a boiler with a lifespan of 20 years 46 and a turbine with a lifespan of 40 years 47 The emission factors for the boiler and turbine were obtained from the Ecoinvent database. For the decommission ing step I only included the electricity required to take down the

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22 boiler, since it is assumed that the boiler and the turbine parts would be recycled and that the plant would continue to run after 20 years, just replacing equipment as needed. The project was credited with preventing electricity generation grid electricity. The information for the grid mix came from the UN CDM Project. The grid emission factors for the grid credits were all take n from GaBi: using US data for electricity from natural g as (11 .19%) (PE US LCI 48 ) and Indian data for elect ricity production from lignite coal (61.41%) (Ecoinvent), e lectricity production from 1 3MW win d turbines (.06%) (Ecoinvent), e lectricity production from run of river h ydro (22.98%) (Ecoinvent), and electricity p roduction from n uclear, pressure water re actor (4.36%) (Ecoinvent). The carbon d ioxide emissions from burning the wood were ignored, as the trees would hav e initially taken in that much carbon d ioxide throughout growth. Figure 6 below shows the GaBi proc esses used to build this assessment along with flow values as per the functional unit (1 kg of mustard biomass waste). Please note that for the purposes of comparison to the other projects, 1.16E3 kgs of mustard biomass waste equate to 1 MWh of electricity It should also be noted that the avoided grid emissions in this process flow are region specific, and the aggregated processes are India specific (as much as the database would allow). Figure 6. The life cycle assessment model built in GaBi for the mustard biomass project.

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23 The South Africa Solar PV Project I considered the following unit processes for this project: Solar Polycrystalline PV Panel Production, Solar PV Transportation to Site 49 Solar PV Plant Construction and Installation, and Solar PV Plant Decommissioning and Disposal 50 Figure 7 below displays the key processes considered in this LCA. Figure 7. Framework used to build the life cycle assessment of the solar PV project. The functio nal unit for this project is 1 MWh, with a total of 2,363,175 MWh being produced over a 25 year period (the lifetime of a solar PV panel). The production of the solar panels was taken from an aggregated process in Ecoinvent; the aggregated process used wer e photovoltaic module production, building integrated, for slanted roof i nstallation, which was the closest match that could be found for open ground installation. The project site is located in Republic of South Africa within the Northern Cape and Western Cape provinces, approximately 90 km north east of the town of Beaufort West and 34 km south of the town of Victoria West. Given that the project had mentioned that materials would be sourced as locally as possible, Setsolar was used as the production faci lity for the PV panels, requiring that the solar panels and inverters be shipped 600 km from Setsolar to the project site (3,507,000,000 kgkm total) 51 mounting system production, for flat roof instal to capture the 343,728 sqm of land that would be used to build this solar PV farm. For the

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24 decom missioning and disposal step, I accounted f or l andfilling of glass/inert (USLCI), ZA: electricity, high volta ge, production mix (Ecoinvent), RoW: water production, ultrapure (Ecoinvent), and RoW: market for diesel (Ecoinvent). These aggregated processes represent landfilling of the glass from the PV panels, electricity needed to recycle these materials, water use d during the recycling process, and diesel needed to break apart the PV panels 52 53 The credit was based off of contributing electricity to the grid, and displacing the current methods of electricity creation; dominated mainly by bituminous coal (92.78%), h ydropower through pumped storage (1.23%), natural gas (.14%), nuclear (5.29%), and hydropower through a hydroelectric run of river plant (.65%). Emission factors for the grid credits were from South African electricity production from hard coal (Ecoinvent) and electricity production from hydro, pumped storage (Ecoinvent). In addition, t he US unit processes used were electricity from hydropower (US LCI) and electricity from natural g as (US LCI). Due to lack of other available GaBi process es, Canadian data wa s used for electricity from n uclear (US LCI). Figure 8 below shows the GaBi processes used to build this assessment along with flow values as per the functional unit (1 MWh of electricity). Note that the avoided emissions form the grid mix are region spe cific in both technologies and aggregated processes.

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25 Figure 8. The life cycle assessment model built in GaBi for the solar PV project.

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26 CHAPTER VIII RESULTS Figure 9 and Table 2 below represents the per MWh comparison data between the four analyzed projects, from a carbon emissions perspective. Net avoided carbon emission represents the difference between life cycle project emissions and life cycle emissions o f the baseline (avoided) scenario. The UN CDM avoided emission represents the non LCA carbon emissions associated with the baseline scenario and also ignores the emissions from the project activity itself. Figure 1 shows the comparison between avoided emis sion credits, for one Megawatt hour energy, that each of the UN CDM projects received and the estimated life cycle avoided emissions. There is a high degree of variability across the projects. In relation to li fe cycle carbon emissions, the biomass and the w indfarm projects actually received fewer carbon credits while the hydropower and solar projects received substantially more credits. From Table 1 it is clear that hydropower and solar projects would have received ~46% and ~30% fewer credits respectively if life cycle emissions were considered. Alternately the biomass and windfarm projects would have received ~14% and ~ 8% more credits respectively. When looking solely at the LCA avoided emissions and the UN CDM avoided emissions (taking the life cycle pr oject activities out of consideration), the differences between the two methodologies can be seen in greater context. Take the Honduras Hydropower project, for example; the project emissions are high enough to drive the net avoided LCA emissions to be less when compared to the UN CDM project methodology. Had the avoided LCA emissions been solely considered, the number of credits the project would have received would have been even greater than the UN CDM project. Compare this example to the China Windfarm p roject, which has almost no project related emissions, but lower LCAA avoided emissions than the Honduras Hydropower project. This reiterates the importance of assessing the project from a comprehensive lifecycle perspective. Project activities and avoided emissions can vary greatly and need to be assessed together to understand holistic project impacts.

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27 Figure 9. Graphical comparison between life cycle carbon dioxide emission per functional unit of 1 MWh and UN CDM emissions per MWh. Total Result Unit/MWH Project Carbon Emissions (LCA) (kg CO 2 eq/MWh) Abated/Avoided Carbon Emissions (LCA) (kg CO 2 eq/MWh) Net Avoided Carbon Emissions (LCA) (kg CO 2 eq/MWh) UN CDM Avoided Carbon Emissions (not LCA) (kg CO 2 eq/MWh) % Difference India Biomass 247 1066 819 717 14.2% China Windfarm 14 1000 986 915 7.8% Honduras Hydropower 698 1130 432 800 46.0% South Africa Solar PV 384 1060 676 971 30.4% Table 2. Numerical comparison between life cycle carbon dioxide emission per functional unit of 1 MWh and UN CDM emissions per MWh. The current UN CDM methodology does not require non carbon emissions impacts to be considered or calculated during these international dev elopment projects. In Table 3, t he non GHG impacts have been calculated in GaBi using the TRACI methodology from the life cycle assessme nts of these four projects. While each impact category cannot be compared to the number of an impact category (e.g. Net ODP vs. Net Ecotox), the four projects can be compared to each other within each 247 14 698 384 1066 1000 1130 1060 819 986 432 676 717 915 800 971 -1500 -1000 -500 0 500 1000 INDIA BIOMASS CHINA WINDFARM HONDURAS HYDROPOWER SOUTH AFRICA SOLAR PV kg CO2 eq Avoided Emissions Per Megawatt Hour Project Carbon Emissions (LCA) (kg CO2 eq/MWh) Abated/Avoided Carbon Emissions (LCA) (kg CO2 eq/MWh) Net Avoided Carbon Emissions (LCA) (kg CO2 eq/MWh) UNCDM Avoided Carbon Emissions (not LCA) (kg CO2 eq/MWh)

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28 impact category (e.g. Net AP Biomass vs. Net AP Wind) T he green highlighted number represents the highest avoided impacts in each category, indicating the project that performed the best for each impact factor. The red highlighted numbers represent instances in which the renewable energy projects minus avoided grid electricity actually performed worse (i.e. avoiding electricity generation from the grid mix did not make up for the negative impacts created by the implementation of the renewable energy technology in this case. This represents problem shifting (avo iding carbon emissions while creating other impacts). Category Net AP Net EP Net ODP Net Smog Air Net Ecotox (Air/Soil/ Water) Net Human Health Cancer (Air/Soil/ Water) Net Human Health Criteria Air Net Human Health Non Cancer Air Net Human Health Non Cancer Soil Net Human Health Non Cancer Water TRACI Result Unit/MWH H+ moles x10 2 eq/ MWh kg N eq/ MWh kg CFC 11 eq/ MWh kg O3x10 eq/ MWh CTUx10 3 eco/ MWh Cases/ MWh PM10x10 eq/ MWh kg x10 2 Toluene eq/ MWh Cases/ MWh Cases/ MWh India Biomass 2.71 18.2 9.99E 06 4.8 1.45E+01 1.47E 04 7.45 3.23 1.57E 07 6.16E 04 China Windfarm 3.33 0.182 2.07E 06 6.33 5.74E 01 6.65E 06 0.157 3.52 1.03E 07 1.99E 05 Honduras Hydropower 1.58 0.12 5.22E 07 4.82 5.67E 01 1.05E 06 0.0428 5.95 1.19E 08 1.10E 05 South Africa Solar PV 3.65 3.66 5.57E 06 6.93 3.15E+00 3.90E 05 0.174 7.53 1.41E 07 1.16E 04 Table 3. Comprehensive impact comparison between UN CDM projects. Each of the four examined UN CDM projects not only focused on a different renewable energy technology, but also took place in a different country than each of the others. While these four samples do not represent the entirety of the UN CDM project database, it is important to be able to compare them to each other. In each of the created life cycle assessments in GaBi, the majority, if not the entirety of the project activities (manufacturing through decommissioning, not including avoided emissi ons from credit) were US/Canada focused due to database limitations. The main processes in each of t hese

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29 projects that were country specific were those existing in the avoided grid electricity generation flows. This essentially gave us the freedom to interchange the avoided emissions of each unique country grid with unique country data between the projects. Table 4 below shows the data matrix of country vs. renewable energy project, allowing for an evaluation of the performance of each project in different countries. For exa mple, t he original b iomass project took place in India, with 819 kg CO 2 eq/MWh as the original LCA findings for carbon emission reductions (original project allocations represented in bold numbering) However, when the biomass project is evaluated against the Chinese grid, the res ults change dramatically, to 752 kg CO 2 eq/MWh. Figure 10 below represents this data graphically, showing the original project life cycle calculations and showing the maximum/minimum value change based on country. This data provides clear patterns. Hydrop ower projects do not vary across countries as emissions from diesel generation do not vary across countries. Wind tends to perform best (have the most carbon emission reductions), across countries, while hydropower has the worst due to sedimentation emissi ons. Given this data it is important to understand, however, that this model does not take into account renewable potentials/financials/governments/corruption/project feasibilities in all of the regions. The purpose of this result is not to make claims th at wind would be better in one location vs. another (what if China has better wind potential than Honduras?). It is solely shown for the purpose of assessing trends. For example, all else equal (resource potential, etc.), this analysis would be used to sho w a certain preference for one technology over the other. However, m ore information would need to be added to this model to truly represent which technologies and/or countries would perform best for these CDM projects.

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30 India (kg CO 2 eq/MWh) China (kg CO 2 eq/MWh) South Africa (kg CO 2 eq/MWh) Honduras (kg CO 2 eq/MWh) Biomass 819 752.8982 812.8343 882.8343 Wind 1052.1018 986 1045.9361 1115.9361 Solar PV 682.1657 616.0639 676 746 Hydropower 432 432 432 432 Table 4. Technology comparison between countries. *Note: this analysis does not take into account technology specific requirements, such as solar/wind/biomass/hydropower potential of each region. Figure 10. Graphical representation of carbon dioxide emission re duction differences when technologies are assessed in different regions. -1200 -1000 -800 -600 -400 -200 0 Biomass Wind Solar PV Hydropower (kg CO 2 eq/MWh) Country/Project Analysis

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31 CHAPTER IX CONCLUSION AND FUTUR E RESEARCH After reviewing four unique UN CDM projects and performing life cycle assessments on each of them, it is clear that to more accurately calculate GHG emission reductions for UN CDM projects and carbon trading, the current UN CDM and future methodologies need to reflect LCA emissions. In addition, the LCA methodology allows for a more holistic view of both positive and negative impacts each project might have, instead of purely focusing on carbon emissions. It is important to account for ecol ogical impacts, as well as those on human health, in order to properly assess each project and avoid problem shifting. Dynamic modeling of comprehensive cradle to grave studies would help international decision makers understand the true impacts of develop ment projects on people, places, and environments. It is important to provide decision makers with comprehensive information, however, this information alone does not drive decisions; this is an important distinction that needs to be made. Data is a powerf ul tool that can be used to aid in decision making. While the research and literature review in this thesis are comprehensive as of 2016, there are many research directions that could stem from this paper. Life cycle assessments could be performed on the projects which use CERs from the CDM projects in order to provide a comprehensive comparison of whether what is being replaced through these international development projects is truly one to one. For example, if a company in Germany produces adhesives and wants to offset their carbon credits by purchasing CERs from a solar PV UN CDM project, these two scenarios could be compared to understand the LCA offsetting perspective Additionally, as Life Cycle Cost Assessm ents (LCCAs) become more prevalent and widely used, LCCAs could be performed in tandem to understand the economic impacts occurring from these projects, as well as the economic benefits gained or lost from developing renewable energy resources. While addin g on this level of research is a giant undertaking, as more projects are assessed, patterns could be extracted from more complicated models that incorporate data such as renewable resource potential, politics, corruption, exchange rates, and economics.

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3 2 As the global methodologies and priorities change for the UNFCCC, it w ill be interesting to additionality, perhaps it would be important for the scientific c ommunity to agree on the time period that should be associated with assessing the value of the CDM projects. Many individuals invest money in the stock market with the long term goal of improving their financial future, without knowing whether it will pay off in 30 40 years (but still having faith enough to invest). Should the population will increase to 9 billion by 2050 and will have increased energy needs, does it mak e sense to invest in renewable energy now and count the offset of non renewable sources that would be developed to make up for that in the future? This important discussion could and should be researched from an economic/policy /philosophical perspective, a s well as from a scientific/engineering perspective.

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33 REFERENCES 1 IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp. 2 Kyoto Protocol; http://unfccc.int/kyoto_protocol/items/2830.php 3 Farahipour, Reza; Karunanithi, Arunprakash T.; Life Cycle Environmental Implications of CO 2 Capture and Sequestration with Ionic Liquid 1 Butyl 3 methylimidazolium Acetate ACS Sustainable Chem. Eng 2014 2, 2495 2500. 4 ISO 14040:2006 Environmental mana gement Life cycle assessment Principles and framework; https://www.iso.org/obp/ui/#iso:std:iso:14040:ed 2:v1:en 5 Clean Development Mechanism (CDM); http://unfccc.int/kyoto_protocol/mechanisms/clean_development_mechanism/items/2718.php 6 UNFCCC -20 Years of Effort and Achievement: Key Milestones in the Evolution of International Climate Policy; http://unfccc.int/timeline/ 7 IPCC Factsheet: What is the IPCC?; http://www.ipcc.ch/news_and_events/docs/factsheets/FS_what_ipcc.pdf 8 The Paris Agreement; http://unfccc.int/paris_agreement/items/9485.php 9 Kyoto Treaty Fizzled, But Climate Talkers I nsist Paris is Different; http://www.npr.org/2015/11/30/452971667/kyoto treaty fizzled but climate talkers insist paris is different 10 NEWS: Paris treaty establishes new carbon trading mechanisms; http://carbonmarketwatch.org/news paris treaty establishes new carbon trading mech anisms/ 11 EB Meetings; http://cdm.unfccc.int/EB/index.html 12 Your Three Steps to a Climate Neutral World; http://climateneutralnow.org/Pages/How.aspx 13 Joint Implementation (JI); http://unfccc.int/kyoto_protocol/mechanisms/joint_implementation/items/1674.php

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34 14 RTCC Q&A: Joint Implementation; http://www.climatechangenews.com/2011/11/17/rtcc qa joint implementation/ 15 Sutter, C.; Parreo, J. C. Does the current Clean Dev elopment Mechanism (CDM) deliver its sustainable development claim? An analysis of officially registered CDM projects. Clim. Change 2007 84 (1), 75 90. 16 UNFCCC ( 2002 ): CMP.1 Art.43. http://unfccc.int/meetings/montreal_nov_2005/session/6260.php 17 Alexeew, J.; Bergset, L.; Meyer, K.; Petersen, J.; Schneider, L.; Unger, C. An analysis of the relationship between the additionality of CDM projects and their contribution to sustainable development. Int. Environ. Agreements Polit. Law Econ 2010, 10 (3), 233 248. 18 Sterk, W.; Wittneben, B. Enhancing the clean development mechanism through sectora l approaches: Definitions, applications and ways forward. Int. Environ. Agreements Polit. Law Econ. 2006 6 (3), 271 287. 19 Boyd, E.; Hultman, N.; Timmons Roberts, J.; Corbera, E.; Cole, J.; Bozmoski, A.; Ebeling, J.; Tippman, R.; Mann, P.; Brown, K.; Liv erman, D.; Reforming the CDM for sustainable development: lessons learned and policy futures. Environmental Science & Policy 2009 Volume 12, Issue 7 20 Dechezleprtre, A.; Glachant, M.; Mnire, Y. The Clean Development Mechanism and the international diffusion of technologies: An empirical study. Energy Policy 2008 36 (4), 1273 1283, 820 831. 21 Duic, N.; Alves, L. M.; Chen, F.; Da Graa Carvalho, M. Potential of Kyoto protocol clean development mechanism in transfer of clean energy technologies to small island developing states: Case study of Cape Verde. Renew. Sustain. Energy Rev. 2003 7 (1), 83 98. 22 CDM: Project 8148 : Karoo Renewable Energy Facility (Nobelsfontein Solar PV); http://cdm.unfccc.int/Projects/DB/JCI1352355819.62/view 23 CDM: AMS I.D.: Grid connected renewable electricity generation --Version 18.0; http://cdm.unfccc.int/methodologies/DB/W3TINZ7KKWCK7L8WTXFQQOFQQH4SBK 24 CDM: Project 0028 : RIO BLANCO Small Hydroe lectric Project; http://cdm.unfccc.int/Projects/DB/DNV CUK1101980215.28/view 25 CDM: Project 0064 : Huitengxile Windfarm Project; http://cdm.unfccc.int/Projects/DB/TUEV SUED1113481234.64/view 26 CDM: Project 0058 : Biomass in Rajasthan Electricity generation from mustard crop residues; http://cdm.unfccc.int/Projects/DB/TUEV SUED1112801052.32/view 27 The Magical Great Karoo; http://www.southafrica.net/za/en/art icles/entry/article southafrica.net the magical great karoo 28 U.S. Department of the Interior Bureau of Reclamation: Reclamation: Managing Water in the West ; http://www.usbr.gov/pn/grandcoulee/pubs/factsheet.pdf

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35 29 Pacca, S.; Horvath, A.; Greenhouse Gas Emissions from Building and Operating Electric Power Plants in the Upper Colorado River Basin. Environ. Sci. Technol 2002 36, 3`94 3200. 30 Hydropower Turbine Repair and Replacement; http://www.canyonhydro.com/products/refurbish.html 31 Flury, K; Frischknecht, R.; Life Cycle Inventories of Hydroelectric Power Generation ESU services. file:///C:/Users/chernomt/Downloads/flury 2012 hydroelectric power generation.pdf 32 The Ecoinvent Database; http://www.Ecoinvent.org/database/database.html 33 Pacca, S. Impacts from decommissioning of hydroelectric dams: a life cycle perspective Climatic Change 2007 84: 281. doi:10.1007/s10584 007 9261 4. 34 Schleisner, L.; Life Cycle Assessment of a Wind Farm and Related Externalities. Renewable Energy 2000 Volume 20, Issue 3, Pages 279 288. 35 Research and Manufacturing; http://www.ge .com/in/wind energy/research manfucturing 36 Presenting the Facts about Industrial Wind Power, FAQ Size; https://www.wind watch.org/faq size.php 37 Chen, G.Q.; Yang, Q.; Zhao, Y.H.; Renewability of wind power in China: A case study of nonrenewable energy cost and greenhouse gas emission by a plant in Guangxi. Renewable and Sustainable Energy Reviews 2011 Volume 15, Issue 5, Pages 2322 2329. 38 1.7 100/103 Wind Turbine; https://www.gerenewableenergy.com/wind energy/turbines/1 7 100 103.html 39 Ghenai, C.; Life Cycle Analysis of Wind Turbine. Ocean and Mechanical Engineering Department, Florida Atlantic University. 2012 http://cdn.intechopen.com/pdfs/29930.pdf 40 Jorgenson, Jennie; Gilman, Paul; and Dobos, Aron. Technical Manual for the SAM Biomass Power Generation Model. NREL, 2011 ; http://www.nrel.gov/docs/fy11osti/52688.pdf 41 Grisso, Robert; Perumpral, John V.; Roberson, Gary T.; Pitman, Robert; Predicting Tractor Diesel Fuel Consumption Virginia Cooperative Extens ion, 2014 ; https://pubs.ext.vt.edu/442/442 073/442 073_pdf.pdf 42 ; http://camelfarm.com/camels/camels_life .html 43 Crutzen, P. J.; Aselmann, I.; and Seiler, W.; Methane production by domestic animals, wild ruminants, other herbivorous fauna, and humans. Tellus 1986 B. 38B: 271 284. DOI:10.1111/j.1600 0889.1986.tb00193.x.

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36 44 Heller, Martin C.; Keoleian, Gregory A.; Mahn, Margaret K.; Volk, Timothy A.; Life Cycle Energy and Environmental Benefits of Generating Electricity from Willow Biomass. Renewable Energy 2004 Volume 29, Issue 7, 1023 1042. 45 Biomass for Electricity Gene ration; Whole Building Design Guide: a program of the National Institute of Building Sciences; https://www.wbdg.org/resources/biomasselectric.php 46 Thermax AFBC Boilers, CFB Boilers, HR SGs, Waste Heat Boilers, Biomass Boilers and R&M Solutions; http://www.power technology.com/contractors/boilers/thermax/thermax4.html 47 Single Stage Back Pressure S team Turbines (Horizontal or Vertical); http://www.snm.co.jp/products/turbines/haiatsu_02.html 48 U.S. Life Cycle Inventory Database; http://www.nrel.gov/lci/ 49 Solar Panels Manufacturers from Africa; http://www.enfsolar.com/directory/panel/Africa 50 Life Cycle Greenhouse Gas Emissions from Solar Photovoltaics; NREL, 2012; http://www.nrel.gov/docs/fy13osti/56487.pdf 51 Solar Panel Manufacturers from Africa; http://www.enfsolar.com/directory/panel/Afr ica 52 Roof Load Considerations for PV Arrays; https://www.civicsolar.com/support/installer/articles/roof load considerations pv arrays 53 Fthe nakis, Vasilis M.; End of life management and recycling of PV modules. Energy Policy 2000 28, 1051 1058.

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37 APPENDIX A Information/GaBi processes used in Life Cycle Assessments LCA Process GaBi process Database China Windfarm LCA Windfarm Turbine Construction US: Transport, combination truck, diesel powered US LCI RoW: wind turbine network connection construction, 2MW, onshore Ecoinvent RoW: wind turbine construction, 750kW, onshore Ecoinvent Windfarm Operation and Maintenance GLO: market for lubricating oil Ecoinvent Windfarm Decommissioning CH: treatment of waste concrete, inert material landfill Ecoinvent US: Plastic waste on landfill USLCI US: Glass/inert on landfill USLCI CH: Residual fuel oil, combusted in industrial boiler USLCI Avoided Electricity from Grid CA: Electricity from lignite USLCI CH: Electricity production, hydro, run of river USLCI CH: Electricity production, wind, 1 3MW turbine, onshore USLCI Honduras Hydropower LCA Hydropower Plant Construction and Installation RoW: hydropower plant construction, run of river Ecoinvent

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38 Hydropower Plant Operation and Maintenance N/A N/A Hydropower Plant Decommissioning and Sedimentation US: Electricity, diesel, at Electricity plant USLCI Sedimentation Pacca, S. Impacts from decommissioning of hydroelectric dams: a life cycle perspective Climatic Change 2007 84: 281. doi:10.1007/s10584 007 9261 4 India Biomass LCA Growth of/Separation of Mustard Biomass N/A Transport of Biomass US: Transport, combination truck, diesel powered USLCI M ethane emissions from camels http://camelfarm.com/camels/camels_life.html http://www.livescience.com/27503 camels.html Mustard Biomass Storage US: Electricity, at grid, US USLCI US: Iron and Steel, production mix USLCI RoW: alkyd paint production, white, solvent based, product in 60% solution state Ecoinvent GLO: market for wire drawing, steel Ecoinvent Mustard Biomass Processing and Electricity Generation RoW: Oil Boiler Production, 100kW Ecoinvent RoW: Gas turbine construction, 10MW electrical Ecoinvent Mustard Biomass Plant Decommissioning and Disposal US: Electricity, at grid, Eastern US USLCI

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39 Avoided Electricity from Grid IN: Electricity production, lignite Ecoinvent IN: Electricity production, hydro, run of river Ecoinvent US: Electricity from natural gas USLCI IN: Electricity production, nuclear, pressure water reactor Ecoinvent IN: Electricity production, wind, 1 3MW turbine, onshore Ecoinvent South Africa Solar PV LCA Solar Polycrystalline PV panel production RoW: photovoltaic module production, building integrated, for slanted roof installation Ecoinvent Solar PV Transportation to Site US: Transport, combination truck, diesel powered USLCI Solar PV Plant Construction and Installation RoW: photovoltaic mounting system production, for flat roof installation Ecoinvent Solar PV Plant Decommissioning and Disposal ZA: electricity, high voltage, production mix Ecoinvent RoW: market for diesel Ecoinvent RoW: water production, ultrapure Ecoinvent US: Glass/inert on landfill USLCI Disposal/Landfill of materials Life Cycle Greenhouse Gas Emissions from Solar Photovoltaics; NREL, 2012; http://www.nrel.gov/docs/fy13osti/56487.pdf

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40 Avoided Electricity from Grid ZA: Electricity production, hard coal Ecoinvent ZA: Electricity production, hydro, pumped storage Ecoinvent US: Electricity from natural gas USLCI US: Electricity from hydro power USLCI CA: Electricity from nuclear USLCI