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Development of British Columbia wood pellet life cycle inventory and its utilization in the evaluation… Pa, Ann An 2010

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Development of British Columbia Wood Pellet Life Cycle Inventory and its Utilization in the Evaluation of Domestic Pellet Applications by Ann An Pa B.ASc., The University of British Columbia, 2008  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in The Faculty of Graduate Studies (Chemical and Biological Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  December, 2010 © Ann An Pa, 2010  ABSTRACT An in-house life cycle inventory (LCI) database for British Columbia (BC) wood pellets is established. The LCI database is used to compare the performance of BC pellets exported to Rotterdam and BC pellets staying within BC in terms of energy penalty, percent of fossil fuel content in pellets arriving destination, and impacts (human health, ecosystem quality and climate change) by performing life cycle impact assessment (LCIA) in a commercial LCA software. The database is also utilized to assess two domestic applications of BC wood pellets: replacing natural gas combustion in UBC district heating facility with wood waste or wood pellet gasification, and replacing firewood in BC residential heating with wood pellets. Overall, the analysis indicated that marine transportation is responsible for over 40% of the life cycle energy consumption and more than 50% of each of the impact categories investigated. The energy penalty and fossil fuel content of exported pellets are roughly 50% and 90% higher than that of the non-exported pellets. For the district heating case study, the base scenario performs much better than all biomass gasification systems in all impact categories other than climate change. The saving in GHG emission is approximately 81% if woody biomasses are utilized. Over the entire life cycle, controlled wood waste gasification system performs better than controlled wood pellet gasification system due to the extra processing required for wood pellets. However, when looking at the health impact associated with stack emissions only, controlled wood pellet gasification would raise the health impact by 12% from the base case while controlled wood waste gasification would raise the impact by 133%. By switching from firewood to wood pellets for BC residential heating, the primary energy consumption and impacts on human health, ecosystem quality and climate change can be reduced by 34%, 95%, 27% and 17%, respectively. Over 90% reduction in external costs can also be achieved. In terms of economic viability, when bulk pellets are to be utilized, switching from firewood to pellet units would be reasonable as long as the unit to be replaced is not a fireplace insert.  ii  PREFACE The preliminary version of the BC wood pellet life cycle inventory (LCI) database presented in Chapter 1 was first constructed by Jill Craven, a visiting scholar at UBC in the summer of 2008. She has devised and distributed survey to pellet plants in BC with the help of Staffan Melin from the Wood Pellet Association of Canada. The LCI was since then refined and updated in terms of the amount of survey data incorporated, methodology used and the inclusions of updated emission factors, more detailed logistics, and a more thorough life cycle impact assessment (LCIA). Parts of Chapter 1 were presented in the 8th World Congress of Chemical Engineering held in Montréal from August 23rd to 27th, 2009 under the title “Life-Cycle Analysis of Exported Wood Pellets from Canada to Europe”. A version of Chapter 1 was prepared for publication. Other than Jill Craven, other co-authors include Xiaotao Bi, Staffan Melin and Shahab Sokhansanj. Parts of the content in Chapter 2 and 3 were presented in the Life Cycle Assessment IX Conference on September 29th, 2009 at Boston under the title of “Evaluations of Domestic Applications of British Columbia Wood Pellets based on Life Cycle Analysis”. A version of Chapter 2 and 3 were prepared and submitted for publication with the help of co-authors Xiaotao Bi and Shahab Sokhansanj. Lastly, Appendix A, an article titled “Modeling of Off-Gas Emissions from Wood Pellets during Marine Transportation” was published on page 833 to 841 of volume 54, issue 7 of the Annals of Occupational Hygiene on in July, 2010. The co-author of this article is Xiaotao Bi.  iii  TABLE OF CONTENT Abstract ................................................................................................................................. ii Preface ................................................................................................................................. iii Table of Content ................................................................................................................... iv List of Tables ......................................................................................................................... vi List of Figures ........................................................................................................................ ix Lists of Symbols and Selected Units ........................................................................................ x List of Abbreviations ............................................................................................................. xi Acknowledgements ............................................................................................................. xii Dedication .......................................................................................................................... xiii 1  Introduction .................................................................................................................... 1  2  British Columbia Wood Pellet Life Cycle Inventory Database ............................................ 6  3  2.1  Introduction...................................................................................................................... 6  2.2  Methods and Calculation ................................................................................................. 8  2.2.1  Life Cycle Inventory Data ......................................................................................... 9  2.2.2  Life Cycle Impact Assessments............................................................................... 17  2.3  Results and Discussion ................................................................................................... 19  2.4  Conclusions..................................................................................................................... 26  A Life Cycle Evaluation of Wood Pellet Gasification for District Heating in British Columbia ..................................................................................................................................... 28 3.1  Introduction.................................................................................................................... 28  3.2  Methods and Calculation .............................................................................................. 30  3.2.1  Base Scenario ......................................................................................................... 31  3.2.2  Woody Biomass Gasification.................................................................................. 32  3.2.3  Life Cycle Impact Assessments............................................................................... 38  3.3  Results and Discussion .................................................................................................. 40  3.4  Conclusions.................................................................................................................... 51 iv  4  5  Evaluation of Wood Pellet Application for Residential Heating in British Columbia based on a Streamlined Life Cycle Analysis .............................................................................. 53 4.1  Introduction.................................................................................................................... 53  4.2  Methods and Calculation ............................................................................................... 55  4.2.1  Data collection for Wood-based Residential Heating in British Columbia ............. 55  4.2.2  Life Cycle Inventory Data for the Production and Transportation of Fuels............ 58  4.2.3  Inventory Data for the End Stage Combustion of Wood Fuels............................... 61  4.2.4  Economic Analysis ................................................................................................... 61  4.3  Results and Discussion ................................................................................................... 66  4.4  Conclusions..................................................................................................................... 73  Conclusions ................................................................................................................... 75  References ........................................................................................................................... 79 Appendix A – Modeling of Off-Gas Emissions from Wood Pellets during Marine Transportation ............................................................................................... 90 Appendix B – Emission Factors and Primary Energy Consumptions for Various Energy Products ...................................................................................................................... 99 Appendix C – Numerical Values for Figures in Chapter 2 ..................................................... 106 Appendix D – Numerical Values for Figures in Chapter 3 ..................................................... 108 Appendix E – Numerical Values for Figures in Chapter 4 ..................................................... 113  v  LIST OF TABLES Table 2.1: Sources of Emission Factors and Primary Energy Requirements Utilized in the LCA 11 Table 2.2: Stage-wise Secondary Energy Consumption.............................................................. 16 Table 2.3: Descriptions of All Transportation Segments Considered in LCA .............................. 17 Table 2.4: Life Cycle Emissions for Exported Pellets Arriving Rotterdam and Pellets Arriving North Vancouver ........................................................................................................ 19 Table 2.5: Breakdowns of Secondary Energy Consumption throughout the Life Cycles of Exported and Non-exported BC Pellets ..................................................................... 23 Table 2.6: Comparison between Exported and Non-exported BC Pellets.................................. 25 Table 2.7: Life Cycle Greenhouse Gas Emission of Various Fuels ............................................... 25  Table 3.1: Estimated Total Emission Factors for UBC Boiler House and Their Sources ............. 31 Table 3.2: List of Pellet and Wood Combustion Emission Factors from Literature.................... 37 Table 3.3: Estimated Wood Pellet Gasification Emission Factors, Wood Waste Gasification Emission Factors and Air Emission Limits for Biomass Boilers in Metro Vancouver . 38 Table 3.4: Summary of External Costs from Literature and the Values Used in this Study ....... 39 Table 3.5: Annual Air Emissions from Current and Woody Biomass Gasification Scenarios ..... 42  Table 4.1: Summary of Each Appliance's Cost, Efficiency and Base Quality in both Firewood and Wood Pellets .............................................................................................................. 57 Table 4.2: Upstream and Combustion Emission Factors for Firewood in Various Residential Heating Appliances..................................................................................................... 63 Table 4.3: Upstream and Combustion Emission Factors for Wood Pellets in Various Residential Heating Appliances..................................................................................................... 65 Table 4.4: Annual Emissions from Current and Wood Pellet Scenarios and Possible Savings in External Costs and Emissions when Wood Pellets are Utilized ................................. 66 Table 4.5: Summary of Simple Economic Analysis for Switching from Firewood to Wood Pellets Appliances Utilizing Bulk or Bagged Wood Pellets .................................................... 72 vi  Table B.1: Emission Factors for electricity generation and distribution..................................... 99 Table B.2: Emission Factors for Natural Gas ............................................................................... 99 Table B.3: Emission Factors for Heavy Fuel Oil ......................................................................... 100 Table B.4: Emission Factors for Heavy Fuel Oil for Marine Transportation ............................. 100 Table B.5: Emission Factors for Low sulphur Heavy Fuel Oil for Marine Transportation ......... 101 Table B.6: Emission Factors for Middle Distillates .................................................................... 101 Table B.7: Emission Factors for Middle Distillates for Train ..................................................... 102 Table B.8: Emission Factors for Propane .................................................................................. 102 Table B.9: Emission Factors for Wood Waste Combustion for Energy in Sawmill and Pellet plant .................................................................................................................................. 103 Table B.10: Emission Factors for Gasoline .................................................................................. 103 Table B.11: Emission Factors for Middle Distillate for HDV Operation ...................................... 104 Table B.12: Emission Factors for Steam Generated for Chemical Processes with US Electricity (from Ecoinvent) ...................................................................................................... 104 Table B.13: Upstream Emission Factors for Wood Waste Used for Electricity Generation ....... 105 Table B.14: Primary Energy Consumption of Different Fuels and Materials .............................. 105  Table C.1: Stage-wise Emissions from Exported BC Pellets ...................................................... 106 Table C.2: Stage-wise Emissions from BC Pellets Delivered to Port in North Vancouver ........ 106 Table C.3: Stage-wise Impacts from Exported and Non-exported BC Wood Pellets (impact/tonne of wood pellets) ............................................................................... 107  Table D.1: Upstream Emission Factors of Wood Waste and Wood Pellets Delivered to UBC ....... .................................................................................................................................. 108 Table D.2: UBC Boiler House Current Emissions ....................................................................... 108 vii  Table D.3: Stage-wise Emissions for Uncontrolled Wood Waste Gasification Scenario........... 109 Table D.4: Stage-wise Emissions for Uncontrolled Wood Pellet Gasification Scenario ............ 109 Table D.5: Stage-wise Emissions for Controlled Wood Waste Gasification Scenario ............... 110 Table D.6: Stage-wise Emissions for Controlled Wood Pellet Gasification Scenario ................ 110 Table D.7: Annual Impacts Associated with Base Scenario....................................................... 111 Table D.8: Annual Impacts Associated with Uncontrolled Wood Waste Gasification Scenario ..... .................................................................................................................................. 111 Table D.9: Annual Impacts Associated with Uncontrolled Wood Pellet Gasification Scenario ...... .................................................................................................................................. 111 Table D.10: Annual Impacts Associated with Controlled Wood Waste Gasification Scenario... 111 Table D.11: Annual Impacts Associated with Controlled Wood Pellet Gasification Scenario .... 112  Table E.1: Emissions in Current (Firewood) Scenario by Appliance Types ................................. 113 Table E.2: Emissions in Current (Firewood) Scenario by Life Cycle Stages ................................. 113 Table E.3: Emissions in Wood Pellet Scenario by Appliance Types ............................................ 114 Table E.4: Emissions in Wood Pellet Scenario by Life Cycle Stages ............................................ 114 Table E.5: Annual Impacts Grouped by Appliance Types for Current (Firewood) Scenario ....... 115 Table E.6: Annual Impacts Grouped by Life Cycle Stages for Current (Firewood) Scenario ...... 115 Table E.7: Annual Impacts Grouped by Appliance Types for Wood Pellet Scenario .................. 115 Table E.8: Annual Impacts Grouped by Life Cycle Stages for Wood Pellet Scenario.................. 116  viii  LIST OF FIGURES Figure 2.1: Processing stages and transportation segments considered in the life cycle of wood pellets ........................................................................................................................... 8 Figure 2.2: Overall scheme of the IMPACT 2002+ framework with modifications implemented for this study (based on Jolliet et al., 2003) ............................................................... 18 Figure 2.3: Stage -wise emissions for a) exported and b) non-exported BC pellets .................... 21 Figure 2.4: Impact assessment results for every tonne of exported and non-exported BC pellets in terms of a) human health impact, b) ecosystem quality, and c) climate change.. 22 Figure 2.5: Stage-wise primary energy consumption breakdown for exported pellets .............. 23  Figure 3.1: Stage-wise emission distribution for the current natural gas scenario ..................... 44 Figure 3.2: Stage-wise emission distribution for a) wood waste gasification, b) wood pellet gasification, c) wood waste gasification with SCR and ESP units with 80% NOX and 99% PM removal efficiency, respectively, and d) wood pellet gasification with identical emission control units ................................................................................................ 46 Figure 3.3: Stage-wise impact analysis in terms of a) human health, b) ecosystem quality, and c) climate change for base and woody biomass gasification scenarios with and without emission control units ................................................................................................ 48 Figure 3.4: Human health impacts associated with stack emissions only normalized by current scenario value ............................................................................................................ 50  Figure 4.1: Stage-wise emission distribution for BC residential heating in the a) current firewood and b) wood pellet scenarios ..................................................................... 68 Figure 4.2: Stage-wise impacts on a) human health, b) ecosystem quality, c) climate change, and d) primary energy consumption for the current and wood pellet scenarios of BC residential heating ..................................................................................................... 69  ix  LISTS OF SYMBOLS AND SELECTED UNITS Symbols  kglumber,d kgwood,d Ml,w Mp,w Mwood,w  Unit MJ input/t of pellet-equivalent material produced during harvesting MJ input/m3 of green wood harvested MJ input/t of pellet-equivalent material produced during sawmill operation MJ input/m3 of lumber produced in sawmill kg kg % % %  WPWRd  -  ρl  kg/m3 of lumber  ρwood,w  kg/m3 of green wood  Eharvest Eharvest,raw Esawmill Esawmill,raw  Unit $CAD DALY EJ Gt kg CO2-equivalent kg CO2-eqv kt Mt PDF∙m2∙yr t tkm RTK  Definition Energy consumption during harvesting for producing 1 tonne of wood pellet- equivalent material Energy consumption during harvesting as reported in literature Energy consumption during sawmill operation for producing 1 tonne of wood pelletequivalent material Energy consumption during sawmill operation as reported in literature Bone dry (0% moisture content) mass of lumber Bone dry (0% moisture content) mass of wood Moisture content of lumber, wet basis Moisture content of pellet, wet basis Moisture content of wood, wet basis The mass ratio of the amount of bone dry residue entering pellet plant and amount of bone dry pellets produced from mill Density of kiln-dried lumber (at 10.7% moisture content, wet basis, or 12%, dry basis) Density of green harvested wood (at 50% moisture content, wet basis)  Definition Canadian dollar Disability adjusted life years Exajoule, 1018 joules Gigatonne Unit for GHG, can be calculated using Global Warming Potential values Unit for GHG, can be calculated using Global Warming Potential values Kilotonne Megatonne Potentially disappeared fraction of species in a certain area and during a certain time Tonne, also known as metric ton Tonne-km, to travel one km with 1 tonne of load Total revenue tonne∙km x  LIST OF ABBREVIATIONS Abbreviation ABIN BC CHP CIEEDAC dwt EPA ESP FVRD GHG GVRD GWP HDV HFO IPCC LCA LCI LCIA LDV LFV Low-S HFO MDV NEU NG NMOC NMVOC NPV PM PM10 PM2.5 SCR TNMOC UBC UGF VOC WLAP  Full name Agricultural Biorefinery Innovation Network British Columbia Combined heat and power Canadian Industry End-Use Date & Analysis Centre Dead weight tonnage (referring to marine vessel) Environment Protection Agency Electrostatic precipitator Fraser Valley Regional District Greenhouse gas Greater Vancouver Regional District Global Warming Potential Heavy duty vehicle Heavy fuel oil Intergovernmental Panel on Climate Changes Life cycle analysis (also known as life cycle assessment) Life cycle inventory Life cycle impact assessment Light duty vehicle Lower Fraser valley Low sulfur heavy fuel oil Medium duty vehicle Neighbourhood energy utility Natural gas Non-methane organic compounds Non-methane volatile organic compounds Net present value Particular matters Particular matters with diameter less than 10 μm Particular matters with diameter less than 2.5 μm Selective catalytic reduction Total non-methane organic compounds University of British Columbia UBC Graduate Fellowship Volatile organic compounds BC Ministry of Water, Land and Air Protection  xi  ACKNOWLEDGEMENTS Special thanks to the professors on my Committee: Dr. Tony Bi, Dr. Shahab Sokhansanj and Dr. Robert Legros. I would like to especially thank my supervisor, Dr. Tony Bi, for all the support and guidance throughout my research thus making the completion of this thesis possible. For the construction of the BC wood pellet LCI database, I would like to acknowledge Jill Craven for building the framework and the first version of the database. Special thanks to Staffan Melin from the Wood Pellet Association of Canada for providing industrial data on pellet plant and shipping port operations and insight on the pellet logistics from production to usage. I would also like to thanks Jamie Meil from Athena Institute for providing information on the mass balance of Canadian softwood lumber production. For the UBC district heating case study, I would like to thank Jason Cantas and Jeff Giffin from UBC Utility, Brenda Sawada and Kelly Coulson from the Sustainability Office of UBC, and Dr. Anthony Lau from the Chemical and Biological Engineering department for supplying me with emission data from the UBC boiler house. Moreover, Dr. Michael Brauer from the School of Environmental Health and Dr. Douw Steyn from the Department of Earth and Ocean Sciences have both provided valuable insights on areas that would be interesting to cover in this case study. I would also like to thank Dejan Sparica for providing emission data from industrial wood gasification units. For the BC residential heating cast study, I would like to thank Grace Cockle from the Policy & Planning Department of Metro Vancouver for providing me with the complete version of the “GVRD Residential Wood Burning Survey” commissioned to Ipsos Reid. I would also like to express thanks to Dr. Shahab Sokhansanj and Dr. Roland Clift for valuable inputs and suggestions on my work. Lastly, I would like to thank UBC Graduate Fellowship (UGF) program and the Agricultural Biorefinery Innovation Network (ABIN) for Green Energy, Fuels and Chemicals for providing funding and making this research project possible.  xii  DEDICATION I would like to dedicate this work to my entire family, especially my parents, Ko Ba and Ling-Na Chang, who have been giving me continuous and unconditional support. Without my family, this achievement would not have been possible.  xiii  1  INTRODUCTION  The global total final consumption of energy in 2007 was 347 EJ, 77% higher than the value back in 1973 (International Energy Agency & Organisation for Economic Co-operation and Development, 2009b). Of all the energy consumed in 2007, 67% was fossil-fuel based and that translates to 29 Gt of CO2 emissions, a 32% increase from 1990 (International Energy Agency & Organisation for Economic Co-operation and Development, 2009a; International Energy Agency & Organisation for Economic Co-operation and Development, 2009b). As concerns for climate change due to greenhouse gas (GHG) emissions are gaining exposures, recognitions, and supports, various climate change adaptation and GHG emission mitigation strategies have been proposed and explored. It is estimated that in order to stabilize the atmospheric CO2 concentration, the emissions must be reduced to at least 40% of its current level (Parikka, 2004). Since approximately 80% of the current emissions is from the use of fossil fuels (Parikka, 2004), one mitigation approach is to reduce the usage of fossil fuel, either by developing technologies with a higher energy efficiency or utilizing low-carbon energy sources. Biomass has been receiving a lot of attention as an alternative energy source due to its abundance and carbon-neutral characteristics. In Brazil and the United States, bioethanol from sugar canes and corns have already been commercially produced and utilized in large quantities. However, these so-called “first generation” biofuels are often the centre of heated debates as they are linked to the increase in food price. In order to resolve this food vs. fuel controversy, “second generation” biofuels are being developed. These types of fuels are produced from lignocellulosic materials including wood residue, solid municipal waste, agriculture residue and fast-growing energy crops. These lignocellulosic materials are substances composed of hemicelluloses, cellulose and lignin, and are not suitable as food for humans. Lignocellulosic biomass can be converted to various forms of energy via thermal chemical, chemical and bio-chemical processes. Recent focus on lignocellulosic biomass feedstock results in elevated interests in waste woody biomass, especially in regions such as British Columbia (BC) where an abundance of woody 1  biomass residue is available. One important issue relating to woody biomass utilization is its high moisture content. Moisture not only adds to the weight and volume, thus increased transportation cost, it also results in lower combustion efficiency. To improve the feedstock quality and to boost the volumetric energy density, woody biomasses are commonly pretreated (drying) and compressed into briquettes and pellets. Pellets are smaller in size ranging from 4 to 6 mm in diameter and 20 to 30 mm in length. Briquettes are larger in size, having diameters from 50 to 100 mm and length from 60 to 150 mm and in some cases the briquettes resemble fire logs. Due to their smaller sizes, pellets are more free-flowing and can be used in automatic feeding systems while briquettes usually require manual feeding. Pellets are used in specialized units equipped with automatic feeding systems while briquette can be used as regular firewood in existing units. Wood pellets are more desirable than conventional wood logs in most cases as they burn more efficiently and cleanly due to uniformed size, lower moisture content and the utilization of optimized combustion units. Wood pellets also contain no insects, require less storage space and need no seasoning. In most cases, wood pellets in Canada are made of sawdust or shavings but can sometimes be made from harvest residue as well. Typical moisture contents of wood pellets are under 10%. While BC pellets are at around 5 to 6% in moisture content, the European and Japanese pellets are typically close to 10%. In 2008, about 1.4 million metric tonnes (t) of wood pellets were produced in Canada. Unlike United States and most of the European countries where the majority of their pellets are for domestic market, about 90% of the Canadian wood pellets were exported (Melin, 2008; Spelter & Toth, 2009). In 2008, 70% of the Canadian wood pellets were shipped to Europe and the other 20% to US and Japan to satisfy their market demands (Melin, 2008). There are many issues associated with transporting woody biomass overseas. These include offgassing of wood pellets in cargoes during transportation, which turns the cargo tank and its adjacent enclosed space into hazardous environments where fatal accidents may happen. More details on the off-gassing of wood pellets during ocean transportation are available in an article 2  titled “Modeling of Off-Gas Emissions from Wood Pellets during Marine Transportation” in Appendix A. Another issue with long distance transportation is that it adds uncertainty to the sustainability of the pellets delivered. As the main purpose of utilizing alternative energy such as wood pellets is to reduce environmental impacts, the true impacts and degree of sustainability of these non-fossil energies, in terms of fossil fuel content, primary energy consumption, on top of various impacts such as human health, ecosystem quality and climate change, need to be confirmed. Thus far, the most commonly utilized tool for such task is life cycle analysis (LCA). LCA requires one to first define a system boundary and the functional unit. LCA results such as emissions, energy consumptions and impacts are all reported as per functional unit. Typically for product LCA, functional unit is one unit of the product itself, may it be by volume or mass. For energy systems, the functional unit is often per energy unit produced or delivered. By choosing an appropriate functional unit, LCA results can be compared amongst different energy systems, processes or products. After defining the boundary and functional unit, the establishment of energy consumption and emission inventory within the boundary is needed. This inventory is known as the life cycle inventory (LCI) and it is region-specific and in many cases time-sensitive as well. The reason for it being region and time-specific is that different regions have varying electricity matrix and the technology adapted in one region may differ from another and these technologies may very well evolve over time. All these variations are reflected on the LCI database. LCI database would reveal hot spots that contribute significantly to emissions and energy consumptions. This would aid in the improvement of the life cycle of a product or process. The inventory can be translated into different environmental impacts via desired impact assessment method which answer the objectives of the LCA, may it be the GHG emissions or effects on air or soil quality. This stage is referred to as life cycle impact assessment (LCIA). Depending on the method applied for LCIA, different ecological impact may be weighted with varying importance. For example, the Eco-indicator `99, a damage-oriented method developed 3  by PRé Consultants in Holland looks at three damage categories, namely human health, ecosystem quality and resources. Eco-indicator ’99 has three weighting schemes based on typologies of audiences: Individualist, Egalitarian and Hierarchist. The Individualist scheme weighs human health heavily with little importance given to the use of fossil resources. On the other hand, Egalitarian`s emphasis is on ecosystem quality. Lastly, Hierarchist is more balanced and is often deemed to be more representative of the scientists` perspective (Felder & Dones, 2007). As one would have expected, using different weighting scheme would result in very different conclusions. It is thus important to keep in mind that LCA has its limitations as the result depends largely on how the system is defined, the reliability and resolution of the inventory data and the impact assessment method used. Furthermore, LCA is usually an iterative process as one often starts with a LCA looking into each processing stage but as the inventory signals out hot spots, it may be desirable to look into each stage in greater detail to pin-point the source of emissions. LCA is also a powerful tool for scenario comparisons as the incremental variation between each scenario would provide valuable insight for decision making. Up to date, LCA has been used to investigate the benefits and impacts linked to various types of projects such as the evaluation of wastewater treatment and reuse projects in China (Q. H. Zhang et al., 2010) and it has also been used extensively recently to evaluate a wide range of bioenergy systems and, sometimes for comparison purposes, fossil fuel energy systems.  Some examples include studies on  lignocellulosic ethanol productions (González-García et al., 2010; Spatari et al., 2010). Another example is fuel production from microalgae (Campbell et al., 2011; Collet et al., 2011). LCA is also a handy tool for policy development, as demonstrated in Björklund and Finnveden's work which evaluates the possible outcome of a Swedish waste incineration tax (Björklund & Finnveden, 2007). The first objective of my study is to establish a LCI database for BC wood pellets using data that are specific to BC whenever possible. If not possible, Western Canada or Canada data are used in most cases. Data are collected from published literature, reports, including government documents, and industrial survey distributed and collected with the help of the Wood Pellet 4  Association of Canada. The fossil fuel content, energy penalty and primary energy consumption, on top of human health, ecosystem quality and climate change impacts, are evaluated for BC pellets that are exported to Rotterdam and BC pellets that are to be utilized in BC. The second objective is to use the in-house BC wood pellet LCI database to evaluate possible domestic applications of these pellets. The first case investigated is the replacement of natural gas in the existing district heating facility in the University of British Columbia (UBC) by wood pellet gasification. On top of primary energy consumption, impacts on human health, ecosystem quality, and climate change, variation in external costs is also inspected. For the UBC district heating case study, a total of five scenarios will be investigated. On top of the base scenario, which is the current natural gas operation, wood waste and wood pellet gasification systems constitute two other scenarios. Wood waste and wood pellet gasification systems with electrostatic precipitator (ESP) for particulate matter (PM) removal and selective catalytic reduction (SCR) unit for NOX control make up the last two scenarios. The second case study looks into replacing firewood in the current BC residential heating practices with wood pellets. On top of investigating various impacts and external costs, a simple economic analysis is also performed to evaluate the economical feasibility for a BC resident to switch from one’s current wood burning appliance to its pellet-equivalent counterpart. Work performed in this study is first carried out in Excel and the worked data are then entered into a commercial LCA software, SimaPro, where LCIA is performed with IMPACT 2002+, one of the built-in assessment methods. The study conducted is a streamlined LCA because emissions and impacts associated with land usages and infrastructure are not included. Furthermore, only air emissions are taken into account while soil and water emission are not considered. The LCI database established in this study allows for further evaluations of BC wood pellets in other domestic or foreign applications. Moreover, the results from the two case studies would provide some insight on the pros and cons of these domestic applications, demonstrate wood pellet’s potential in reducing GHG emissions and suggest the amount of incentive that may be required for consumers to switch to wood pellets. 5  2  BRITISH COLUMBIA WOOD PELLET LIFE CYCLE INVENTORY DATABASE  2.1  INTRODUCTION  There are a large number of reported studies on the LCA of bioenergy systems and biofuels, such as the comparison of heating systems by direct combustion of wood chips synthetic natural gas, natural gas and heating oil (Felder & Dones, 2007), and comparison between biobased hydrogen and ethanol from fermentations for electricity generation and transportation (Melamu & von Blottnitz, 2009). The LCIA of “first generation” and “second generation” bioethanol along with biodiesel from micro-algae have also received great attention in recent years (Batan et al., 2010; Campbell et al., 2011; Clarens et al., 2010; Lardon et al., 2009; von Blottnitz & Curran, 2007). A recent study also compared electricity generation by coal, natural gas and wood pellets in Ontario, Canada (Y. Zhang et al., 2010). As wood pellet is a common fuel source in Europe, there has been much work carried out on the LCA of wood pellets. For instance, in 2003 a study looking into the LCA of electricity production in the Netherlands with coal co-combustion with either wood pellets from Canada or palm kernel shells from Malaysia was performed (Damen & Faaij, 2003). The report states that fossil fuel usage and GHG emission can be reduced effectively by importing biomass and co-firing them in coal-fired plants in the Netherlands. It was also indicated in the study that pellets and palm kernel shells are better exported than to be utilized domestically due to the lower efficiencies of the relatively small-scale systems in Malaysia and Canada. Furthermore, coal mining and its transportation to the Netherlands can be avoided if pellets or palm kernel shells are used instead. Lastly, the electricity mix in Canada consists of more renewable fraction thus the amount of emission avoided is lower when pellets are used in Canada for electricity generation. Another work published in 2000 investigated the transport chain of biomass, including wood pellets, for energy generation, and concluded that when traveling interregionally at approximately 1,500 km, wood pellets would still have their environmental benefits, provided modern carriers are used (Forsberg, 2000). 6  A more recent work focuses on the international logistics of wood pellets for various applications such as district heating, residential heating and power generation in Europe (Sikkema et al., 2010). One of the case studies involves Canadian pellets for power generation in the Netherlands. It was concluded that 1,937 kg of CO2-equivalent can be avoided per tonne of pellets used for electricity generation in the Netherlands and that pellets can achieve substantial GHG savings although they are much more expensive than fossil fuels such as coal . Another work that assesses the carbon footprint and the environmental impacts of Canadian wood pellets using a streamlined LCA, not accounting for land usage and infrastructure, was recently published (Magelli et al., 2009). Two pellet production scenarios were evaluated in their analysis. One system utilizes unprocessed sawdust as fuel for the drying operation, while the dryer in the second system is heated by natural gas combustion. The energy consumptions for both cases were estimated by an energy balance analysis of a rotary dryer of the audited pellet plant. The work of Magelli et al. (2009) demonstrated that pellets produced in Western Canada, namely British Columbia, and exported to Stockholm have positive net energy with an energy penalty, defined as the energy required to produce and to transport the fuel pellet divided by the energy content of the pellet itself, of 39%. Out of the 7.2 GJ required for the production and transportation of one tonne of pellets, 2.6 GJ is related to marine transportation. The data on energy consumption and emissions from the pellet plant in Magelli et al.’s work (2009) were based on densification analysis instead of actual industry data. Transportation details such as traveling distances were based on actual pellet plants in BC. To improve the data quality related to the pellet manufacturing at pellet plants in Western Canada, industrial surveys were conducted in this study among a number of pellet plants in Western Canada with the assistance of the Wood Pellet Association of Canada. Completed surveys were obtained from three pellets plants and one of two shipping ports handling the ocean transportation of wood pellets to Europe. The survey results in combination with updated emission factors including upstream processes, more detailed raw material and pellet 7  logistics, and more thorough moisture and primary energy consumption calculations allow for the construction of an updated LCI database that captures the current pellet production and logistics in Western Canada. The LCI database imported into a commercial LCA software, SimaPro, in order to use its built-in impact assessment method to estimate the environmental footprints associated with BC wood pellets. Similar to Magelli et al.’s (2009) work, the LCA performed here does not consider changes in land use, building infrastructure and the plantation of trees. The objective is to quantify the impact associated with each tonne of BC wood pellets exported to Europe in terms of human health, ecosystem quality and climate change. The total and stage-wise primary energy consumption, both fossil and renewable sources, energy penalty and fossil fuel content of the exported wood pellets are calculated to identify the hot spots in the whole production and supply chain. Lastly, the energy penalty and environmental footprints of Europe-bound and domestic pellets are also compared.  2.2  METHODS AND CALCULATION  The system boundary for this LCA is from the harvesting of woody material in forest to the arrival of wood pellets in Port Rotterdam, Netherlands, a major receiving port in Europe for Canadian wood pellets. For the process being studied, the functional unit is selected as one metric tonne of wood pellets. Figure 2.2 illustrates the main process and transportation segments involved in the LCA. Transportation B (HDV using diesel to railhead) Transportation C (Train using diesel)  Harvesting operation  Sawmill operation  Transportation A (HDV using diesel)  Pellet plant operation  Port operation  Arriving Port Rotterdam  Transportation D (ocean vessel using low-S HFO)  Figure 2.1: Processing stages and transportation segments considered in the life cycle of wood pellets 8  2.2.1  Life Cycle Inventory Data  The first step is to obtain energy consumption data for each processing stage and transportation segment. The types of energy consumption considered are electricity, natural gas, heavy fuel oil (HFO), middle distillate (diesel), propane, steam, wood waste and gasoline. Electricity is based on BC electricity mix in 2006 where the contribution from hydro, natural gas, biomass and fuel oil are 91.1%, 7.3%, 1.4% and 0.1%, respectively (Environment Canada, 2008). The composition of hydro power is taken to be 86% reservoir and 14% run-of-river (Caldicott, 2007). In order to calculate the energy input required to produce electricity, the BC electricity generation efficiency for hydro, natural gas, fuel oil and biomass are given the values 100%, 42.3%, 15.2% and 44.7%, respectively (Kohut et al., 2009). This study covers two types of energy consumption. The first type is secondary energy consumption, which keeps track of energy consumed in the form of energy product such as electricity or fuel for the vehicles or equipment. Survey results from pellet plants and port operations are all secondary energy consumptions. The other type of energy consumption is primary energy consumption, which also includes the amount of energy required to produce an energy product such as electricity and fuels. For instance, the primary energy consumption for fuel oil would include the energy content of the crude oil itself, the electricity and other forms of energy required to obtain and refine the crude oil and the fuel required to deliver the final product to point of usage. For LCA, the primary energy consumption is often more relevant as the calculation of the primary energy consumption itself requires LCA. In this study, primary energy is divided into renewable and non-renewable sources where that latter includes both fossil fuels and nuclear power. Primary energy requirement for different types of energy and fuels are obtained from Ecoinvent database (Swiss Centre for Life Cycle Inventories, 2007) in Simapro or from GHGenius v3.17 (Delucchi & Levelton, 2010). Ecoinvent database is based on European data while GHGenius v3.17 is based on Canadian values. Some Ecoinvent data utilize US electricity profile instead of European electricity profile and these data are collectively called the US-EI database (Swiss Centre for Life Cycle Inventories et al., 2008). When available, the USEI database is used instead of the Ecoinvent database. 9  The emissions from each processing stage and transportation segment are obtained by multiplying each specific secondary energy consumption and its respective emission factors. For each type of secondary energy, there is an emission factor for each of the pollutant being investigated. Each emission factor consists of upstream and usage emission factor where the first value accounts for emissions associated with the production and transportation of the energy while the second factor relates to emissions produced during fuel usage. For processing stages, the emission factors are in the unit of kg of pollutant emitted per MJ of energy input. For transportation segments, the emissions are given in kg of pollutant emitted per tkm where tkm is traveling 1 km with 1 tonne of load. As emission factors depend on method of fuel usage, emission factors for transportation depend on the type of vehicle used. Table 2.1 summarizes the sources of emission factors and primary energy requirement for all types of energy consumption considered in this study. Note that all energy units considered here are referring to higher heating value, HHV. The actual values of emission factors and primary energy consumption for the production of each fuel are included in Appendix B.  10  Table 2.1: Sources of Emission Factors and Primary Energy Requirements Utilized in the LCA Type of energy consumed  Upstream emission  Electricity  (Delucchi & Levelton, 2010; U. S. Environmental Protection Agency, 1995)  Downstream emission  (Delucchi & Levelton, 2010)  Hydro  Not applicable  (Delucchi & Levelton, 2010)  Biomass  Based on US-EI database for air dried wood residues with 20% moisture content. (Swiss Centre for Life Cycle Inventories et al., 2008)  (Delucchi & Levelton, 2010) (Delucchi & Levelton, 2010) (average of boiler and turbine emissions as the natural gas technology used to generate electricity in BC is not stated) (Delucchi & Levelton, 2010) (U. S. Environmental Protection Agency, 1995)  Primary energy requirement  Notes  (Delucchi & Levelton, 2010; U. S. Environmental Protection Agency, 1995)  British Columbia electricity mix in 2006 where the contribution from hydro, natural gas, biomass and fuel oil are 91.1%, 7.3%, 1.4% and 0.1%, respectively (Environment Canada, 2008). The BC electricity generation efficiency for hydro, natural gas, fuel oil and biomass conversions are 100%, 42.3%, 15.2% and 44.7%, respectively (Kohut et al., 2009). Upstream for electricity is emission produced during preparation of fuel and downstream emissions are related to conversion of that fuel to electricity  US-EI data of run-of-river and non-alpine reservoirs hydro power of European average with US electricity. (Swiss Centre for Life Cycle Inventories et al., 2008) Based on US-EI database for air dried wood residues with 20% moisture content. (Swiss Centre for Life Cycle Inventories et al., 2008) Based on US-EI database for high pressure natural gas delivered to consumer. (Swiss Centre for Life Cycle Inventories et al., 2008) (Delucchi & Levelton, 2010)  Natural gas  (Delucchi & Levelton, 2010)  Middle distillate Middle distillate (equipment)  (Delucchi & Levelton, 2010)  Middle distillate (HDV)  (Delucchi & Levelton, 2010)  (Delucchi & Levelton, 2010)  (Delucchi & Levelton, 2010)  Middle distillate (train)  (Delucchi & Levelton, 2010)  (Railway Association of Canada, 2008)  (Delucchi & Levelton, 2010)  Natural gas  (Delucchi & Levelton, 2010)  (U. S. Environmental Protection Agency, 1995)  Based on US-EI database for high pressure natural gas delivered to consumer. (Swiss  (Delucchi & Levelton, 2010)  Hydro power is 86% from reservoir and 14% from run-of-river (Caldicott, 2007).  Average of softwood and hardwood is used  (Delucchi & Levelton, 2010) Fuel efficiency for HDV is 2.145 MJ of diesel /tkm (Delucchi & Levelton, 2010) Fuel efficiency for train is 0.229 MJ of diesel/RTK (total revenue tonne∙km) (Railway Association of Canada, 2008)  11  Type of energy consumed  Upstream emission  Downstream emission  Primary energy requirement Centre for Life Cycle Inventories et al., 2008)  Gasoline  (Delucchi & Levelton, 2010)  Propane  (Delucchi & Levelton, 2010)  HFO (equipment)  (Delucchi & Levelton, 2010)  Low-S HFO (marine bulk vessel)  Steam  Wood waste  (Delucchi & Levelton, 2010)  Based on US-EI database for steam generated for chemical processes at plant. (Swiss Centre for Life Cycle Inventories et al., 2008) Internal use within LCA  (Delucchi & Levelton, 2010)  (Delucchi & Levelton, 2010)  (U. S. Environmental Protection Agency, 1995) (U. S. Environmental Protection Agency, 1995) (Aldrete et al., 2005; The Chamber of Shipping, 2007) Since emission factors were given for per work output, the engine efficiency of 40% was assumed (Cleveland, 2004)  Based on US-EI database for propane/ butane at refinery  Based on US-EI database for steam generated for chemical processes at plant. (Swiss Centre for Life Cycle Inventories et al., 2008)  Based on US-EI database for steam generated for chemical processes at plant. (Swiss Centre for Life Cycle Inventories et al., 2008)  (Delucchi & Levelton, 2010)  Internal use within LCA  Notes  For downstream emissions, the values are converted to kg/MJ from kg/km emissions from the “LDV (low duty vehicle) summary” sheet in GHGenius v3.17 as the only gasoline usage in the BC pellet life cycle is during port operation where it is consumed by trucks driven by foreman and supervisor on site The on-road average fuel efficiency for LDV is taken to be 0.236 km/MJ (Natural Resources Canada’s Office of Energy Efficiency, 2010c)  (Delucchi & Levelton, 2010)  (Delucchi & Levelton, 2010)  The upstream and primary energy requirements are for regular HFO instead of low-S HFO. Fuel efficiency for marine vessel is 0.108 MJ HFO/tkm (Delucchi & Levelton, 2010) and dead weight tonnage, dwt, is 58,844 (The Chamber of Shipping, 2007)  12  The emission species investigated in the study are fossil CO2, biogenic CO2, generic CH4, biogenic CH4, N2O, generic CO, biogenic CO, non-methane volatile organic compounds (NMVOC), NOX in NO2 equivalent, SOX in SO2 equivalent, PM and PM2.5. Biogenic and fossilbased CO2, CH4 and CO emissions are segregated in US-EI database while GHGenius v3.17 is only capable of separating biogenic and fossil-based emissions for CO2 but not for CH4 and CO. Due to this reason, CH4 and CO emissions from GHGenius v3.17 are branded “generic”, implying that a small portion of them may be biogenic. However, when performing impact assessments, these generic emissions are considered to have fossil fuel origins. There are many types of PM and by definition PM is all particulate matters while PM2.5 are those less than 2.5 μm and PM10 are those less than 10 μm, including PM2.5. PM2.5 are the ones with the most significant health impacts based on IMPACT 2002+ method (Humbert et al., 2005). The health impact factor for PM is estimated based on an average PM2.5 to PM ratio of 0.33 in ambient air (Dockery & Pope, 1994; Humbert et al., 2005). Throughout this study, care was taken to avoid double accounting. When only PM emission factors are available, such as in GHGenius database (Delucchi & Levelton, 2010), they are readily used. When both PM and PM2.5 emission factors are available, only the PM2.5 emission factors are utilized. In the result section, sometimes both PM and PM2.5 are listed but it is important to acknowledge that they do not overlap since for each process only one of the PM or PM2.5 emission factors are used, not both. In this chapter, the only process with PM2.5 emission factor is steam generation. Furthermore, although some database provides a more detailed pollutant list, only those listed previously are included in the analysis for consistency. Lastly, impacts and emissions associated with land usages and infrastructure are not included in the analysis. 2.2.1.1  Processing Stages  2.2.1.1.1  Harvesting Operation  The amount of energy consumed during harvesting is taken from Sambo (2002), which already includes the energy required for the hauling of trees from the harvesting operation to the sawmill. The values presented are in the units of MJ per cubic meter of wood 13  harvested and are referred to as Eharvest,raw. To convert the energy consumption to the unit of MJ per tonne of pellets (as received), referred to as Eharvest, equation (1) is applied: 𝐸ℎ𝑎𝑟𝑣𝑒𝑠𝑡 = 𝐸ℎ𝑎𝑟𝑣𝑒𝑠𝑡,𝑟𝑎𝑤 �  1  𝜌𝑤𝑜𝑜𝑑,𝑤  � �𝑀𝑤𝑜𝑜𝑑,𝑑 + 1� �  1 � (1 − 𝑀𝑝,𝑤 ) × 1000 𝑊𝑃𝑊𝑅𝑑  (1)  Where ρwood,w is the density of harvested green wood and is taken as the average green density of all wood indigenous to BC, 840 kg/m3 (British Columbia Ministry of Water, Land and Air Protection, 2005; Simpson, 1993). WPWRd is the tonnes of pellets produced from one tonne of wood residue and the subscript of d indicates that this ratio is on dry basis. This number is not unity because some wood residues are used as fuel in the pellet plant. The value of WPWRd used is 0.89, the weighted average of two plants. Mwood,d and Mp,w are the dry basis moisture contents of harvested green wood and wet basis moisture content of pellets, respectively. The values used are 1 for Mwood,d and 0.056 for Mp,w as measured at the North Vancouver port (Accredited Laboratory, 2007). It is important to convert all energy consumptions so that they are with respect to bone dry woody materials. Moisture content of the final product (i.e. wood pellet) can then be accounted for. Note that in Equation (1), the energy consumption is allocated among different products based on their dry mass ratios. The mass-ratio allocation method is adapted because it will give a conservative value for wood pellets. 2.2.1.1.2  Sawmill Operation  The relevant energy consumption data are taken from the CIEEDAC (Canadian Industry EndUse Data and Analysis Centre) Report from Simon Fraser University (Nyboer, 2008). The 2006 value, reported in MJ per cubic meter of lumber exiting the sawmill, is converted to MJ per tonne of pellets, denoted as Esawmill, using Equation (2). It is worth noting that some unit operations in the sawmill are not relevant to the production of the shavings and sawdust but for this study, energy usage for all operations in the sawmill is included as the sawmill operation is treated as a whole with no segregations.  14  𝐸𝑠𝑎𝑤𝑚𝑖𝑙𝑙 = 𝐸𝑠𝑎𝑤𝑚𝑖𝑙𝑙,𝑟𝑎𝑤 �  1 𝑘𝑔 𝑙𝑢𝑚𝑏𝑒𝑟𝑑 1 �� � (1 − 𝑀𝑝,𝑤 ) × 1000 �� 𝜌𝑙 ∗ (1 − 𝑀𝑙,𝑤 ) 𝑘𝑔 𝑤𝑜𝑜𝑑𝑑 𝑊𝑃𝑊𝑅𝑑  (2)  The density of kiln-dried lumber is 504 kg/m3 (British Columbia Ministry of Water, Land and Air Protection, 2005; Simpson, 1993), the average density of all wood indigenous to BC at Ml,w where Ml,w is the wet-basis moisture content of the kiln-dried lumber and the value is taken to be 0.107. The lumber to wood mass ratio is based on oven-dried value, which is needed as Esawmill,raw is in the unit of per cubic meter of lumber produced. One needs to back-calculate the mass of green wood required to produce one cubic meter of lumber in order to find how much energy is needed to produce the equal amount of residue for pellet production. This is because green wood is transformed to residue during the production of lumber. The dry mass ratio of lumber to wood is 0.46 for Canadian practices (Meil, 2009). 2.2.1.1.3  Pellet Plant Operation  Energy consumptions in pellet plant in MJ per tonne of wood pellets are obtained from industrial surveys collected with the help of Wood Pellet Association of Canada. Three sets of pellet plant data were received but since some data are more complete than others so some values used are weighted average of two plants instead of three plants. The weighting factors are based on each plant’s contribution to the total production in the calculation. The energy consumption reported under this category does not include transportations to and from the pellet plants. 2.2.1.1.4  Port Operation  Energy consumption reported includes energy needed for unloading pellets from the train, transporting pellets to the storage bins and loading the pellets onto ocean vessel, along with transportation within the port for daily operations. These data are based on survey results from a major BC ocean port specializing in the overseas shipping of woody materials including wood pellets. The annual energy consumption from the surveyed port is divided by the annual amount of pellets entering the port for shipping to yield energy consumption per tonne of pellets. 15  Table 2.2 summarizes the secondary energy consumption data for each processing stage with the values converted to MJ consumed per tonne of pellet produced in BC. Table 2.2: Stage-wise Secondary Energy Consumption Type of energy consumed  Harvesting operation (MJ/t of pellets)  Sawmill operation (MJ/t of pellets)  Electricity  0  186  Pellet plant operation (MJ/t of pellets) 490  Natural gas  0  135  0  0  Heavy fuel oil  0  14.57  0  0  Middle distillates  689  42.86  23.49  5.37  Propane  0  3.68  6.16  0  Steam  0  47.55  0  0  Wood waste  0  271  1059  0  Gasoline  0  0  0  2.01  2.2.1.2  Port operation (MJ/t of pellets) 11.12  Transportation  The transportations involved in this study are broken down into five segments: transportation from harvest field to sawmill, from sawmill to pellet plant (transportation A), from pellet plant to railhead (transportation B), from railhead to port (transportation C), and lastly, from port in North Vancouver to port in Rotterdam (transportation D). The first three segments of transportation are via heavy duty vehicles (HDV, class 8, which has a gross vehicle weight rating of above 15 t) such as trucks. Once arriving at the railhead, the transportation to the port is via train powered by diesel. During marine transportation, the fuel used for the bulk vessel is low sulfur (<1.5% S) HFO. Energy consumed in the hauling of trees to sawmill is already included in the harvesting stage while energy required for transportation A to D need to be estimated based on fuel efficiency for different modes of transportation. The values used for fuel efficiencies are presented in Table 2.1 under “Notes”. Using emission factors in the unit of kg of pollutant emitted per tkm total emissions can be calculated once the distance travelled is known. Since the function unit for this analysis is 1 tonne of wood pellets, for transportation segments that involve the delivery of the pellets itself, the emissions are obtained by simply multiplying the emission factors by distance travelled. For Transportation A, where the load being transferred is wood residues instead of wood pellets, a conversion factor needs to be included in the calculation as well. 16  This conversion factor is the mass ratio of wood residue to wood pellet (both are “as received” instead of “bone dry”), which is 0.62 from the survey. Table 2.3 summarizes the traveling distance, mode of transportation and fuel used for each segments. Distance travelled are obtained from industrial surveys while distance between North Vancouver and Port Rotterdam is from Wood Pellet Association of Canada. Table 2.3: Descriptions of All Transportation Segments Considered in LCA Description Load Fuel Distance Fuel efficiency a  Transportation A  Transportation B  From sawmill to pellet plant  From pellet plant to railhead  Wood residue such as saw dust and planer shaving Middle distillate 25.6 km 2.145 MJ/tkm  Transportation C From railhead to shipping port in North Vancouver  Transportation D From North Vancouver to Rotterdam  Bulk wood pellets  Bulk wood pellets  Bulk wood pellets  Middle distillate 99.1 km 2.145 MJ/tkm  Middle distillate 840 km a 0.229 MJ/RTK  Low-S HFO 16,668 km 0.108 MJ/tkm  total revenue tonne∙km  2.2.2  Life Cycle Impact Assessments  IMPACT 2002+ (Jolliet et al., 2003) was selected for impact assessments in this case study as it includes both midpoint and end point impacts. In IMPACT 2002+, all emissions and materials consumptions from the LCI data are linked to 15 midpoint categories and these midpoint categories are further grouped and converted into four damage, or end point, categories. The most current version of IMPACT 2002+ at time of analysis (v2.06) is adapted for analysis with two extra categories added to keep track of the primary energy consumption and external costs throughout the entire life cycle. These two new end point categories are also presented in Figure 2.2. The impacts of biogenic CH4 and CO are added under the categories of respiratory organic and inorganic, respectively, using the impact values of their fossil fuel origin counterparts. Six endpoint categories, human health, ecosystem quality, climate change, primary energy consumption, external cost and resources can be obtained. Only the first four will be evaluated in this chapter. The global warming factors listed in IMPACT 2002+ for climate change impact assessment are mostly based on the 500-year time horizon values in the IPCC’s 2001 report. The midpoint category “External Cost” and the damage 17  category “Externality” will be referred to and further explained in the subsequent chapters on BC pellet domestic application case studies. The units used for each impact category, such as DALY and PDF∙m2∙yr, are also defined in Figure 2.2 It is important to keep in mind that IMPACT 2002+ was developed in Europe so the values of parameters used for the compilation of human toxicity are calculated at a continental level for Western Europe. Therefore, the final values to be presented here only serve as indicators for scenario comparisons as the absolute values do not capture the geographical and ecological differences in Western Canada and Western Europe. Furthermore, the effects of spatial and temporal variations are not considered in this analysis. It should be noted that currently there are many controversies regarding the methodology behind DALY and the uncertainties involved, but it is still used here as it is a commonly used approach. The dashed lines indicate that the conversions into damage categories would required more scientific data and have not yet been properly established.  Figure 2.2: Overall scheme of the IMPACT 2002+ framework with modifications implemented for this study (based on Jolliet et al., 2003) 18  2.2.2.1  Energy Content  Primary energy consumptions are used to calculate the energy penalty of wood pellet that are delivered to North Vancouver or Rotterdam. This is done by dividing total primary energy consumption required to produce and deliver 1 tonne of wood pellet by the HHV of the wood pellets. The HHV of wood pellet used in calculations is 19.4 MJ/kg (Accredited Laboratory, 2007). Furthermore, amount of fossil fuel energy consumed in the production and delivery of 1 tonne of pellet is compared to the HHV of pellets to give the fossil fuel content of exported wood pellets. 2.2.2.2  Comparison with Pellets for Domestic Applications  The environmental footprints, including GHG emission, human health and ecosystem impacts, fossil fuel content and energy penalty of pellets to be used for domestic (i.e. Canadian, or more likely Western Canadian or within BC) applications are calculated to be compared with their exported counterparts. The system for domestic-bound pellets is identical to the exported pellets except that port operation and marine transportation are omitted. Since the transportation of pellets from port Rotterdam to end users are not included in this assessment, the delivery of pellets from the port in North Vancouver to end user in Canada are also not considered for consistency.  2.3  RESULTS AND DISCUSSION  The pollutant emissions over the streamlined life cycle for 1 tonne of exported pellet arriving Port Rotterdam and for 1 tonne of pellet arriving port in North Vancouver are shown in Table 2.4 as “export” and “domestic”, respectively. Percent reductions in emissions achievable by utilizing BC pellets locally are also presented in Table 2.4. Table 2.4: Life Cycle Emissions for Exported Pellets Arriving Rotterdam and Pellets Arriving North Vancouver Pollutant  Export (kg/t of pellets)  Domestic (kg/t of pellets)  Emission reduction  All CO2  417  264  36.7%  286  134  53.1%  CO2, fossil  19  Pollutant CO2, biogenic All CH4  Export (kg/t of pellets)  Domestic (kg/t of pellets)  Emission reduction  130  129  0.7%  4.95E-01  2.61E-01  47.2%  b CH4  4.83E-01  2.49E-01  48.4%  CH4, biogenic  1.24E-02  1.24E-02  0.0%  2.81E-02  2.33E-02  17.2%  1.02  7.16E-01  29.8%  6.68E-01  3.64E-01  45.6%  3.53E-01  3.53E-01  0.0%  NMVOC  3.11E-01  1.76E-01  43.3%  NOX  5.56  1.88  66.2%  SOX  6.79E-01  1.79E-01  73.6%  All PM  6.91E-01  3.80E-01  45.0%  PM  6.91E-01  3.79E-01  45.1%  a PM2.5  5.08E-04  5.08E-04  0.0%  N2O All CO CO  b  CO, biogenic  a  PM2.5 emission was available only for steam generation thus the values here are the emissions linked to steam generation alone. PM emissions for all other processes are captured under “PM”. b May include some biogenic emissions as well  It is apparent that without the marine transportation and port operation, emissions can be reduced drastically, ranging from 17.2% to 73.6%. The reductions of biogenic pollutants are close to zero because marine transportation and port operation generate minimal biogenic emissions. On the other hand, even with low-S HFO, the avoidance of marine transportation can reduce SOX emissions by 73.6%. Figure 2.3a and Figure 2.3b further illustrates how each processing stage contributes to the emission of each pollutant for exported pellets and pellets to be utilized locally in BC, respectively. For exported pellets, it is apparent that marine transportation contributes to approximately 50% or more for all non-biogenic emissions other than N2O. Harvesting stage appears to be the second-highest contributor to non-biogenic emissions. For biogenic and PM emissions, pellet plant stage contributes approximately 80% and 30%, respectively. The high biogenic and PM emissions are linked to the use of wood residue as an energy source within the pellet plants. For pellets to be utilized locally, harvesting stage remains as the hot-spot for non-biogenic emissions while pellet plant is still the main cause for biogenic emissions. These findings show that if further emission reductions are desired within the life cycle of BC wood pellets, other than finding domestic market of  these pellets, one should also look into improving the current 20  harvesting and pellet plant operations, may it be better energy efficiency or emission controls. The actual emission values for the construction of Figure 2.3 are in Appendix B.  PM  SOX  NOX  NMVOC  CO, biogenic  CO  N2O  CH4, biogenic  CH4  CO2, fossil  a  D, marine transportation C, to port via train B, to railhead via HDV A, to pellet mill via HDV Port operation Pellet plant operation Sawmill operation Harvesting operation  CO2, biogenic  0%  PM  0%  SOX  20%  NOX  20%  NMVOC  40%  CO, biogenic  40%  CO  60%  N2O  60%  CH4, biogenic  80%  CH4  80%  CO2, fossil  100%  CO2, biogenic  100%  b  Figure 2.3: Stage -wise emissions for a) exported and b) non-exported BC pellets As impact assessments are linked to emissions, it is not a surprise to see that pellets arriving Rotterdam have much higher impacts on human health, ecosystem quality and climate change when compared to pellets arriving North Vancouver. Figure 2.4 illustrates how each processing stage and transportation segment add to each type of impacts throughout the pellets’ life cycle. It is apparent from Figure 2.4 that marine transportation is responsible for over 50% of the export pellets’ impacts on human health, ecosystem quality and climate change. By removing transportation D and port operations, human health, ecosystem quality and climate change impacts can be reduced by 62%, 66% and 53%, respectively. For pellets to be utilized locally the harvesting operation is by far the most problematic processing stage, contributing to approximately 50% or more to all impacts covered in Figure 2.4. The actual emission values for the construction of Figure 2.4 are included in the Appendix C. 21  a  . .  Human health (DALY)  7.0x10-4 6.0x10-4 5.0x10-4 4.0x10-4 3.0x10-4 2.0x10-4 1.0x10-4 0.0  Export  c  300 250 200  b  35 30 25 20 15 10 5 0  Local  350  Climate change (kg CO2-equivalent)  40  Ecosystem quality (PDF m2 yr)  8.0x10-4  Export  Local  D, marine transportation C, to port via train B, to railhead via HDV A, to pellet mill via HDV Port operation Pellet plant operation Sawmill operation Harvesting operation  150 100 50 0  Export  Local  Figure 2.4: Impact assessment results for every tonne of exported and non-exported BC pellets in terms of a) human health impact, b) ecosystem quality, and c) climate change The breakdowns of secondary energy consumption by energy type for exported and local pellets are tabulated in Table 2.5. Unlike Table 2.2, Table 2.5 includes fuel consumptions during transportation segments. For exported pellets, the main type of fuel used is HFO as ocean vessels operate on HFO. When marine transportation is omitted, the main energy sources are middle distillates, mainly for harvesting operations, and wood waste, mostly utilized in pellet plants.  22  Table 2.5: Breakdowns of Secondary Energy Consumption throughout the Life Cycles of Exported and Non-exported BC Pellets Type of energy consumed  Export  Domestic  Electricity  13.0%  19.5%  Natural gas  2.5%  3.9%  HFO (includes low-S HFO)  34.5%  0.4%  Middle Distillates  23.7%  36.1%  Propane  0.2%  0.3%  Steam  0.9%  1.4%  Wood Waste  25.2%  38.4%  Gasoline  0.0%  0.0%  In terms of primary energy consumption, every tonnes of exported pellets requires 25.8 GJ of energy input, including the heating value of the wood pellets produced, while pellets remained in BC only requires 23.5 GJ. Figure 2.5 reveals the stage-wise primary energy breakdown, not including the HHV of pellet itself, for exported pellets. Transportation alone is responsible for 45% of the life cycle energy consumption while just marine transportation alone contributes 35% to the entire life cycle’s energy requirement. This finding again proves that marine transportation adds to wood pellet’s energy demand and impacts tremendously.  Pellet plant operation 27.08%  Sawmill operation 13.13%  Port operation 0.38%  A, HDV 1.80% B, HDV 4.35% C, train 3.94%  Transportation 45.31%  D, marine transportation 35.21%  Harvesting operation 14.11%  Figure 2.5: Stage-wise primary energy consumption breakdown for exported pellets 23  Table 2.6 summaries energy and GHG emission differences between pellets that are exported and pellets that are to be utilized domestically. The primary energy consumption listed does not contain the HHV of pellet itself, which is 19.43 GJ/t (Accredited Laboratory, 2007). Less than 0.6% of the non-renewable energy in both types of pellets is from nuclear power while the other 99.4% are all fossil fuel based energy. BC electricity is not generated from nuclear power but since some of the processes used in this analysis are taken from the US-EI database with US electricity included, there are some traces of nuclear power. The kg CO2-equivalent per tonnes of pellet values are calculated using IMPACT 2002+ as illustrated in Figure 2.4c. From Table 2.6 one can conclude that if BC pellets can be utilized locally, they will perform much better than pellets that are shipped to Rotterdam as the energy penalty can be lowered by 36% to only 21%. Furthermore, pellets to be used locally are much more environmentally friendly as they contain 48% less non-renewable energy than those being shipped to Rotterdam. The amount of GHG emitted from pellets to be locally utilized is less than half of those emitted by pellets that have arrived Rotterdam. Table 2.6 also compares results from this study with those from Magelli et al. (2009). It is seen that the values obtained from this study imply less impact from exported BC pellets. This mainly comes from the fact that industrial survey results reveal a much lower energy consumption rate compared to values used in Magelli et al.’s (2009) work. Despite the inclusion of more detailed logistics, primary energy, and upstream emissions, the impact calculated from this study are lower but more realistic. The significant differences in kg of CO2-equivalent emitted per tonne of pellet obtained from the two studies are also due to the different impact factors used in the two studies. In Magelli et al.’s (2009) work, Global Warming Potential (GWP) indices based on the 2001 IPCC report for 100-year time horizon were used while the 500-year time horizon GWP are applied for the current study as they were pre-defined in the assessment method. For comparison reasons, the kg of CO2equivalent emitted per tonne of pellet values for the current study calculated with 100-year time horizon indices are also presented in brackets in Table 2.6. Note that other than having 0 for biogenic CO2 emissions, all other biogenic pollutants have the same GWP value as their fossil-based counterparts for the calculation of the values in brackets. 24  Table 2.6: Comparison between Exported and Non-exported BC Pellets  Pellets arriving Rotterdam Pellets arriving North Vancouver Pellets arriving Stockholm (pellet plant uses saw b dust for drying) Pellets arriving Stockholm (pellet plant uses natural b gas for drying)  Primary energy consumption, not including HHV of pellets (MJ/t)  Energy penalty  Non-renewable energy content  kg CO2 emitted/t  kg CO2-eqv emitted/t  6372  33%  16.4%  417  295 (313)  4105  21%  8.59%  264  140 (151)  e  39%  18.7%  NA  723  e  35%  35%  NA  532  7200  6400  a  c  d  c  d  d  d  a  Includes both fossil based and biogenic (Magelli et al., 2009) c Based on IMPACT 2002+ where the climate change impact assessments are mostly based on the IPCC 2001 report's 500-year time horizon values. d Based on 2001 IPCC reports for 100-year time horizon e Secondary energy instead of primary energy b  Although exported pellets perform much worse than pellets to be utilized locally, exported pellets are still superior to other forms of fossil fuels despite the long travelling distance required for exported pellets. Table 2.7 summaries the amount of GHG emitted over the entire life cycle, including the end stage combustion, per GJ of fuel utilized. The sources of data for HFO, diesel and natural gas are listed in Table 2.1. The CO2-equivalent intensity in pellet values from Magelli et al.’s (2009) are also presented in Table 2.7 for comparison purpose. As the pellet plant energy consumption data used in that study is much greater than the values used here and due to the different set of impact conversion factors, the values from Magelli et al.’s (2009) are much higher than those from the current study. The sources of the fossil fuel values in Table 2.7 are listed in Table 2.1. Table 2.7: Life Cycle Greenhouse Gas Emission of Various Fuels Hard coal in stove  kg CO2-eqv/GJ a  a  99.1  HFO boilers  Diesel in industrial engine  Natural gas boiler  Wood pellet exported and in pellet stove  87.3  93.9  56.6  15.9  Wood pellets in pellet stove 7.9  Pellets arriving Stockholm (pellet plant uses saw dust b for drying) 29  Pellets arriving Stockholm (pellet plant uses natural gas for b drying) 39  Obtained from US-EI for "Anthracite, burned in stove 5-15kW/RER with US electricity U" b (Magelli et al., 2009), 100-year time horizon GWP from the IPCC’s 2001 report were used instead of the 500-year time horizon GWP like the other values in the table  25  One should also note that this study does not take into account the avoidance of emission in Europe due to the usage of imported pellets. For instance, by importing wood pellets from BC for co-firing with coal, emissions linked with coal production and combustion can be avoided.  2.4  CONCLUSIONS  For every tonne of BC pellets exported to Rotterdam, the resulting human health, ecosystem quality and climate change impact are 6.94E-4 DALY, 32.5 PDF∙m2∙yr and 295 kg CO2-equivalent, respectively. This study reveals that marine transportation alone is responsible for 35% of the BC exported pellets’ life cycle primary energy requirement. Furthermore, marine transportation contributes significantly to exported pellets’ impacts in terms of human health, ecosystem quality and climate change. Other than marine transportation, harvesting operation is ranked second in pollutant emissions and impacts. Comparing pellets that have arrived Rotterdam and North Vancouver, the latter has 62%, 66% and 53% less impacts in human health, ecosystem quality and climate change, respectively. Non-biogenic life cycle emissions can also be lowered significantly, ranging from 17.2% to 73.6%, if marine transportation and port operations are omitted. Furthermore, the energy penalty and non-renewable energy content of BC pellets can be reduced from 33% to 21% and 16.4% to 8.59%, respectively, if the pellets were to be used locally. Moreover, GHG emission from BC pellets that are to be utilized locally is less than half of those emitted by the pellets arriving Rotterdam. 1 GJ of BC wood pellets burnt in pellet stove in BC would produce 7.93 kg of CO2-equivalent GHG while BC pellets burnt in Rotterdam would generate 15.9 kg of CO2-equivalent GHG over their entire life cycle. However, even with the long distance overseas transportation, exported pellets burnt in Europe still performs much better than other fossil fuel combustions in terms of GHG emission as their life cycle emission ranges from 99.1 to 56.6 kg CO2-equivalent. Comparing to previous work, this study includes industrial data for energy consumptions, a more detailed logistic chain, primary energy calculations and upstream emissions. The final results  26  obtained from this study show that exported BC pellets are more sustainable than they were thought to be. Based on the findings from this study, expanding local markets and exploring various domestic applications for BC wood pellets hold great potential in impact reductions in terms of human health, ecosystem quality and climate change. This study also reveals that if further reduction in BC wood pellets’ life cycle impacts is desired, one should look into improving the harvesting and pellet plant operations. Improvements can be in the forms of better energy efficiency or air emission controls. Lastly, it should be noted that this study does not take into account of emissions avoided in Europe due to the usage of imported BC pellets. This database will become available as a part of the Canadian biomass/bioenergy LCI database that is being developed by ABIN.  27  3  A LIFE CYCLE EVALUATION OF WOOD PELLET GASIFICATION FOR DISTRICT HEATING IN BRITISH COLUMBIA  3.1  INTRODUCTION  As climate change due to GHG emissions is gaining recognitions, various methods of climate change adaptation and GHG emission mitigation have been proposed, discussed and explored. Replacing a fraction of the current fossil fuel by alternative energy sources such as bioenergy is one of the many approaches recommended by policy makers. For instance, ethanol blending requirement in transport fuel in the United States reaches 1.14 EJ in 2010 and will increase to 3.18 EJ by 2022 while the European Union target for renewable energy in the transport sector in 2020 is set to 10% , or 1.29 EJ of biofuel (European Commission, 2007; International Energy Agency & Organisation for Economic Co-operation and Development, 2009a). Other than in the transport sector, there are numerous studies that emphasize the potential of renewable energy, or more specifically, bioenergy, in district or residential heating and in combined heat and power systems (CHP) (Björklund et al., 2001; Difs et al., 2010). The importance of policy development to promote the usage of bioenergy in these sectors is also discussed (Kopetz, 2007; Rickerson et al., 2009). However, the use of biomass for district heating has been quite controversial due to concerns with possible increase in health impacts (Ries et al., 2009). This concern is especially true when the fossil fuel to be replaced is natural gas and when the community is densely populated. There are currently a few major district heating systems in Vancouver. These include one located in the stadium and entertainment district in the core of downtown (Davis, 2004) and three in Vancouver's largest hospital sites (Ministry of Energy, Mines and Petroleum Resources of British Columbia, 2010; Roger Bayley Inc, 2010). The most recent establishment is the Southeast False Creek Neighbourhood Energy Utility (NEU) which provides hot water and heat for all new buildings in the area, including the Olympic Village that was built to accommodate Olympic athletes participating in the 2010 Winter Olympic (City of Vancouver, Sustainability Group, 2010). The downtown system operates on natural gas while the NEU operates on a base-load system utilizing sewer heat recovery pump along with a natural gas peaking/back-up boiler. There was a debate at the beginning on the energy source to be 28  chosen for the base-load system and the two contenders were biomass and sewer heat (Roger Bayley Inc, 2010). In the end, sewer heat recovery heat pump system was selected because of public concerns on local air quality and traffic inconvenience that may arise from biomass utilization. Another district heating system in Vancouver is at UBC, where more than 99% of the heat is generated from natural gas and the rest from fuel oil during peak season. With UBC's ambitious plan of reducing GHG to 33%, 67% and 100% below the 2007 level by 2015, 2020 and 2050, respectively, the University has devised a detailed plan of action and replacing natural gas with renewable energy is an important part of the actions to be taken (University of British Columbia, 2010a). In fact, $26 million CAD has been allocated for the establishment of a biomass gasification cogeneration system on campus for research and demonstration purposes (University of British Columbia, 2010b). Given UBC's strong motive to become green and the large amount of GHG emissions from the boiler house, it is interesting to investigate the complete replacement of fossil fuels in its boiler house with bio-based fuels. Wood pellets -- which are made of sawmill residue, burn cleaner than unprocessed biomass residue, and are produced in abundance in BC -- are considered a strong candidate. In 2008, 9 out of 30 pellet plants in operation in Canada were located in BC and about 35 Canadian pellet plants are in the planning stage with 13 of them to be located in BC (Melin, 2008). Overall, about 90% of the pellets produced in Canada were exported and 78% of these pellets were shipped to Europe (Melin, 2008; Spelter & Toth, 2009). Finding domestic applications for these pellets would result in less transportation related air emissions. The technology to be evaluated is gasification as it is cleaner than direct combustion. The replacement of UBC's current natural gas boiler house with a wood pellet gasification system is evaluated by a streamlined LCA. There has also been LCA work on district heating. Eriksson et al. (2007) conducted a LCA study of district heating and CHP system in Sweden using three different fuels: waste incineration, biomass combustion and natural gas combustion (Eriksson et al., 2007). Another study attempted to use LCA to investigate which 29  of natural gas combustion, wood pellet combustion, sewer heat recovery and geothermal recovery would be the best choice for a district heating system in Vancouver, BC, Canada (Ghafghazi et al., 2010). The study reveals that none of the energy sources has absolute advantages over the others in all the impact categories considered although by using renewable energy at least 200 kg of CO2-equivalent can be avoided per MWh of heat produced. Furthermore, the performance of each type of energy source depends on many factors such as electricity mix and types of energy utilized for producing pellets. For this study, an in-house LCI database of BC pellets (Pa, Craven et al., 2009) is utilized to evaluate a total of five scenarios for district heating at UBC. The base scenario is the current installation and the others are wood waste gasification, wood pellet gasification and each of the two gasification operations with emission controls. The wood waste gasification scenario utilizes emission factors from the industry for wood waste gasification while the pellet scenario uses estimated wood pellet gasification emission factors based on literature values and wood waste gasification emission factors from industry. For the scenarios with emission controls, an electrostatic precipitator (ESP) for dust control and a selective catalytic reduction (SCR) unit for NOX control are included. The overall impacts such as human health, ecosystem quality and primary energy consumption in addition to GHG reduction resulting from using wood waste and wood pellets are compared to demonstrate the pros and cons of wood waste and wood pellet utilization when replacing natural gas. The externality analysis based on variations in emission profiles in different scenarios is also performed to quantify the economical benefits for each option.  3.2  METHODS AND CALCULATION  For this study, a total of five scenarios will be investigated. The base case is the current operation and the four woody biomass gasification systems are wood waste, wood pellets and each of these two systems equipped with emission control units. During the analysis, the functional unit adapted is specific to the type of fuel used in each scenario. However, the values presented in this work are all converted to either per MJ of fuel input or per year of operation. The annual operation is based on the amount of heat that is currently 30  generated in the base scenario on a yearly basis, which is 974 TJ. This is chosen as the functional unit because the amount of heat to be produced in a year is identical for all scenarios thus allowing for scenario comparison, which is also equivalent to the functional unit of per unit of energy produced.  3.2.1 Base Scenario For the base case, the LCA includes both natural gas and oil productions, their transportation or transmission to UBC, and emissions during the end usage. The emission factors for natural gas and fuel oil production and transmission are obtained from GHGenius v3.17 (Delucchi & Levelton, 2010) and are referred to as "upstream emission factors". The combustion emission factors for the current installation are from the Combustion Test Report provided by UBC boiler house (Northwest Instrument Systems Inc., 2009), EMEP CORINAIR Emission Inventory Guidebook (European Environment Agency, 2007) and US EPA AP-42 documents (U. S. Environmental Protection Agency, 1995). For the Combustion Test Report, the boiler was fired with different fuels and at different capacities. The emissions were higher if the equipment was operated at a lower capacity. For the purpose of this study, the emission factors at 50% capacity are selected. The emissions were reported as concentrations (in ppmv) of the flue gas so material balance is carried out to determine the flue gas flow rate. For natural gas firing, SOX emission is assumed to be 0 as sulfur content in the BC natural gas is negligible. Table 3.1 lists the total emission factors of the UBC boiler running on natural gas and fuel oil with the sources of emission factors specified. Table 3.1: Estimated Total Emission Factors for UBC Boiler House and Their Sources Fuel oil-firing boiler Pollutant  CO2, fossil CO2, biogenic CH4 N2O  Total emission factor (g/GJ of fuel used)  Source of emission factor Upstream  88,593 475 120 7.97  (Delucchi & Levelton, 2010)  Combustion  Natural gas-firing boiler Total emission factor (g/GJ of fuel used)  (European Environment Agency, 2007)  53,393  0  79.85  (European Environment Agency,  72.3 1.67  Source of emission factor Upstream  (Delucchi & Levelton, 2010)  Combustion (Northwest Instrument Systems Inc., 2009) 0 (European Environment Agency,  31  Fuel oil-firing boiler Pollutant  CO NMVOC  Total emission factor (g/GJ of fuel used)  Upstream  26.1 a  22.8  NOX  89.8  SOX  245  PM  5.73  a  Source of emission factor  Non-methane volatile organic compounds  3.2.2  Combustion 2007) (U. S. Environmental Protection Agency, 1995) (European Environment Agency, 2007) (Northwest Instrument Systems Inc., 2009) Mass balance based on input S content from (Podolski et al., 2008) (European Environment Agency, 2007)  Natural gas-firing boiler Total emission factor (g/GJ of fuel used)  9.14 5.05 36.1  Source of emission factor Upstream  Combustion 2007) (Northwest Instrument Systems Inc., 2009) (European Environment Agency, 2007) (Northwest Instrument Systems Inc., 2009)  6.09  Mass balance based on input S content  0.49  (European Environment Agency, 2007)  Woody Biomass Gasification  The proposed biomass utilization system is a retrofitted air gasification system because gasification generally produces lower PM, CO, VOC (volatile organics) and NOX emissions compared to direct combustion (European Environment Agency, 2007; Sparica, 2009). The syngas produced is combusted in the existing natural gas combustor to heat up water in the boiler to generate steam. The flue gas can also be treated with an ESP to remove PM and/or a SCR unit to remove NOX if desired. The thermal efficiency of this system depends on the moisture content of the biomass fuel. Typical thermal efficiency for biomass fuel with approximately 60% moisture content (dry basis) is 62% (Sparica, 2009) and this is the thermal efficiency assumed for the wood waste scenarios. For biomass with 10% moisture content, the thermal efficiency is 78% (Sparica, 2009). This number is used for wood pellet scenarios despite the moisture content of BC wood pellets is actually around 6% since the efficiency for fuels with less than 10% moisture content is not available. Combining thermal efficiency and the amount of steam produced in 2008, it is deduced that 126,015 t of wood waste, with a HHV value of 12.50 MJ/kg (Forest 32  Product Laboratory, 2004), is required annually to produce the same amount of steam as the base case. For the wood pellet scenarios, 64,257 t of wood pellets, with a HHV value 19.4 GJ/t (Accredited Laboratory, 2007), is required. Just for comparison, in 2008 the boiler house consumed 1,034 TJ of natural gas and 7.84 TJ of fuel oil to generate 350 kt of steam at 165 psig (1,138 kPa), translating to 974 TJ of heat produced (UBC Utilities, 2009). These numbers correspond to a 93% overall thermal efficiency. 3.2.2.1 Wood Waste Gasification Scenarios It is assumed that the wood waste going into UBC district heating facility consists of 50% forest residue from harvesting operations and 50% sawmill and planer mill residue. The forest residue production starts with harvesting operation with data taken from Sambo (2002), not including transportation from harvesting field to wood processing facility. The forest residue is then chopped in the forest using mobile chopper, and emissions relating to this process are obtained from US-EI (Swiss Centre for Life Cycle Inventories et al., 2008). The chopped residue is then transported to railhead via HDV over a distance of 150 km. The train would then travel 350 km from the railhead to the North Vancouver shipping port. From the shipping port, the forest residue would be delivered to UBC district heating facility via HDV over a distance of 20.2 km. The life cycle of forest residue is performed with the functional unit of per tonne of green harvest wood with 100% moisture content, dry basis. For sawmill and planer mill residue, the harvesting of wood and sawmill operation are all included and emission data are based on literature used for the pellet LCI but converted accordingly so that the functional units are per tonne of wood residue with 51% moisture content, dry basis, as gathered from the industrial survey. The sawmill residue would be transported to the railhead via HDV over a distance of 25 km. The residue then travel by train for 350 km before arriving North Vancouver port. The residue is then delivered to UBC via HDV over a distance of 20.2 km. The distances used in the calculation are estimated based on harvest field and sawmill locations in BC, Canada (Natural Resources of Canada, 2003a; Natural Resources of Canada, 2003b) and opinions from the local industry (Melin, 2010). The average moisture content of mixed wood waste delivered to UBC would be at 33  76% but since the maximum moisture allowed for smooth operation of the gasifier is 60%, it is the number used. This implies that some natural drying/aging is needed at UBC and the moisture content difference between the delivered fuel and fuel to be burnt is taken into account. Emission factors associated with the production and transportation of wood waste to UBC are presented in the Appendix D in the functional unit of 1 tonne of waste wood with moisture content at 60%, dry basis. For the wood waste scenarios, the gasification emission factors utilized are those obtained from industry contact for wood waste fixed-bed gasification. The biogenic CO2 emission is calculated based on the carbon content of wood. It was assumed that the carbon content in dry wood is 50% and the moisture content of wood waste is 60%, dry basis. At 60% moisture content, the mixed waste would give off 0.092 kg of biogenic CO2 emission per MJ of mixed wood waste gasified. The CH4, N2O and SOX emission factors are not available so they are estimated by the emissions of wood waste combustion in boiler from US AP42 document (U. S. Environmental Protection Agency, 1995). The annual emissions are obtained by multiplying the emission factors by the annual fuel consumption. Moreover, the scenario of controlled wood waste gasification is also analysed and more details on the emission control units are discussed in the following section. 3.2.2.2 Wood Pellet Gasification Scenarios The details on the construction of the BC wood pellet LCI are presented previously in Chapter 2. The same LCI database is the basis for this case study. As before, the functional unit is one tonne of wood pellets and allocations are mass-based. However, the existing database is modified slightly to reflect the changes in logistics. The streamlined life cycle now consists of harvesting, transportation of harvested material to sawmill, sawmill processing, transportation of sawmill by-products to pellet plant, pellet plant operations, pellet transportation in bulk via HDV and train to port in North Vancouver, transportation from port in North Vancouver to UBC campus and finally burnt in the UBC gasification/combustion boiler. The 20.2 km transportation from port in North Vancouver to UBC is by HDV. Emissions from infrastructure and land use changes are not included in the 34  database in view that pellets in BC are made from sawmill and forest residue. Emission factors associated with the production and transportation of wood pellets to UBC are presented in the Appendix D in the functional unit of 1 tonne of wood pellets. It is speculated that wood pellet gasification emission factors may vary quite substantially given that the combustion emission for wood waste and wood pellets do vary considerably as shown in the literature or published database (Johansson et al., 2004; Lillieblad et al., 2004; Swiss Centre for Life Cycle Inventories et al., 2008; Wierzbicka et al., 2005). In an attempt to better represent wood pellet gasification emissions in the wood pellet scenarios, which are not available in the literature, the emission factors are estimated using two types of ratios. The first ratio is the ratio between wood and pellet combustion emission factors from literature and database. This first ratio together with the wood gasification emission factors from the industry can yield a set of estimated emission factors for the wood pellet gasification system. The second ratio is the ratio between published wood combustion emissions and the wood gasification emission from the industry. This ratio can then be applied to pellet combustion emission factors from literature and database, resulting in another set of estimated emission factors for pellet gasification, provided that the values of pellet and wood combustion emissions are different from those used to calculate the first ratio, as that would yield two identical sets of wood pellet gasification emission factors In order to carry out this approximation process based on ratios, it is crucial to compare data with similar set-up in terms of emission controls, system type and type of biomass used. Different emission data are matched based on considerations mentioned and whenever possible, data from the same article or database are compared. For the calculation of the first type of ratio, no unit conversion is required as the units used are usually consistent within a single source. However, when calculating the second type of ratios, unit conversions need to be performed as industrial emission data for wood gasification are provided in mass of pollutant per energy unit of wood utilized while most literature report their data in mass of pollutant per volume of flue gas with the O2% or CO2% of flue gases provided along with the specification on dry or wet gas basis. Conversions of 35  units are performed as described in The Handbook of Biomass Combustion and Co-firing (van Loo & Koppejan , 2007). Since gasification emission factors from the industry do not include CH4 and N2O, their ratios are not calculated. For these two pollutants, the pellet combustion emission factors from the US-EI database are used as the estimated pellet gasification emission factors. Table 3.2 lists all the emission factors used in the calculation of the ratios.  36  Table 3.2: List of Pellet and Wood Combustion Emission Factors from Literature Source  (Wierzbicka et al., 2005)  (Pagels et al., 2003)  (Johansson et al., 2004) Mixed wood  Fuel  Forest residue  Pellet  Forest residue  Load  Mediu m  Mediu m  80%  Emission control  Multi cyclone  Type of equipment  1.5Mw, moving grate  High  60%  Pellet  (U. S. Environmental Protection Agency, 1995)  (Swiss Centre for Life Cycle Inventories et al., 2008)  (Lillieblad et al., 2004)  Wet wood  Mixed wood chip from forest  Shaving chips, and sawdust  45% None Median Median emissions emission for wood for pellet boilers boiler (kg/MJ input)  1Mw, moving grate  4.35E-05  1.77E-06  N2O CO, biogenic  4.10E-03  3.20E-04  NMVOC  2.85E-05  2.50E-06  NOX  7.20E-05  6.70E-05  SOX  Multi cyclone  Multi cyclone Furnace, 50kW  9.17E02 9.03E06 5.59E06 2.58E04 7.31E06 9.46E05 1.07E05  9.17E02 9.03E06 5.59E06 2.58E04 7.31E06 9.46E05 1.07E05  PM2.5  1.03E-01 7.00E-07 3.00E-06 1.18E-04 9.00E-07 1.10E-04 2.50E-06 3.40E-05  4.46E05  6.88E05  1.87E05  8.10E05  5.59E05  4.54E05  Pellet  Low  Multi cyclone  Pollutant CO2, biogenic CH4, biogenic  PM  Pellet  8.80E-05  1.90E-05  1.42E04  9.46E05  4.30E-05  9.65E02 3.00E07 2.50E06 6.50E05 1.50E06 7.40E05 2.50E06 2.00E05 2.37E05  1.5Mw, moving grate  8.93E-02  7.85E -02  4.00E-04  3.44E -05  3.31E-05  4.67E -05  2.16E-05  2.16E -05  37  Table 3.3 summarizes the two set of emission factors obtained from the two types of ratios and their average values. The average estimated pellet gasification emission factors are used for the calculation in uncontrolled pellet scenario in this study. Note that SOX is manually set to zero since SOX emission depends mostly on the sulfur content of the fuel and wood pellet contains negligible sulfur at less than 0.01%, dry basis (Johansson et al., 2004). Also in Table 3.3 is the current air emission limits, in kg per MJ of fuel consumed, for biomass boilers and heaters in Metro Vancouver (Metro Vancouver, 2008) and the wood waste gasification emission factors used in this study. Table 3.3: Estimated Wood Pellet Gasification Emission Factors, Wood Waste Gasification Emission Factors and Air Emission Limits for Biomass Boilers in Metro Vancouver Pollutant CO2, biogenic CH4, biogenic  Wood waste gasification emission factors (kg/MJ)  Estimated pellet gasification emission factors based on ratio 1 (kg/MJ)  Estimated pellet gasification emission factors based on ratio 2 (kg/MJ)  Average estimated pellet gasification emission factors (kg/MJ)  Metro Vancouver air emission limits for biomass boilers (kg/MJ)  9.17E-02  8.50E-02  8.22E-02  8.36E-02  -  9.03E-06  3.00E-07  3.00E-07  3.00E-07  -  N2O  5.59E-06  2.50E-06  2.50E-06  2.50E-06  -  CO, biogenic  1.46E-05  1.26E-06  1.14E-06  1.20E-06  1.59E-04  NMVOC  4.30E-06  3.77E-07  3.02E-07  3.39E-07  NOX  7.31E-05  6.80E-05  6.33E-05  6.56E-05  4.10E-05  PM  4.00E-05  1.92E-05  1.14E-05  1.53E-05  5.13E-06  From Table 3.3, it is apparent that emission control units need to be in place in order to stay below the local air emission limits. The numbers show that NOX and PM need to be reduced by 37% and 66%, respectively for wood pellet and 44% and 87% for wood waste gasification. Both can be easily achieved by technologies such as SCR for NOX reduction and ESP for PM removal as the typical removal efficiencies for these units are approximately 80% and 99%, respectively (De Nevers, 2000; Forzatti, 2001). These efficiencies are applied in the controlled wood waste and wood pellets gasification scenarios for both.  3.2.3  Life Cycle Impact Assessments  The modified version of IMPACT 2002+ v2.6 used for BC wood pellet LCI, as depicted in Figure 2.2 is also applied for this case study. Unlike for BC wood pellet LCI where the 38  damage category “Externality” was not part of the analysis, for the UBC district heating case study, externality is included in the analysis. Externality, also known as external cost, is the unaccounted and uncompensated impact on a group arising from the social or economic activities of other groups (European Commission, 2003). Therefore, externality reflects the impact on environment and human health. Table 3.4 lists three sets of reported external costs for air pollutants investigated in this study. The costs for biogenic CO2, CH4 and CO are estimated using the impact factors for different pollutants in IMPACT 2002+. The global warming factors listed in IMPACT 2002+ are mostly based on the IPCC 2001 report's 500year time horizon values. Since CO2 only has an effect on climate change and biogenic CO2 has no impact, biogenic CO2 has been given zero external cost. It is noted that the average external cost for CH4 in the literature is close to $0.23, which is equal to the cost of CO2 multiplied by the impact factor of CH4, a value of 7. The same observation is made for N2O where the calculated value based on its impact factor of 156 is $5.15. Based on these observations, the external cost of biogenic CH4 is estimated by multiplying its impact factor of 4.25 by the cost of CO2 to yield $0.14. This is plausible as CH4 only has effects on global warming according to IMPACT 2002+. For biogenic CO, it also has impact on human health, which is the total cost of CO minus the cost of climate change. With the cost of climate change for CO being estimated as the cost of CO2 multiplied by the climate change impact factor for CO in IMPACT 2002+, which is 1.57, the health cost for CO is found to be $0.67, which applies to CO from all sources. Since the climate change impact factor of biogenic CO is 0, the total cost of biogenic CO is equal to the health cost of CO. The emission reduction achieved from replacing natural gas and fuel oil with wood pellets can then be combined with external cost for each pollutant in Table 3.4 to derive the reduction in external costs. Table 3.4: Summary of External Costs from Literature and the Values Used in this Study  Pollutant  (CAD $/kg)  Average values from various a states in the US (Golay, 2005) (CAD $/kg)  CO2, fossil  0.04  0.03  (Bi & Wang, 2006)  CO2, biogenic  (Dones et al., 2005)  Values used in this analysis  (CAD $/kg)  (CAD $/kg)  0.03  0.03 0  Calculation and remarks  Average of all values Estimated using impact factors in IMPACT 2002+ method  39  (Bi & Wang, 2006) Pollutant  (CAD $/kg)  CH4  1.05  b  Average values from various a states in the US (Golay, 2005) (CAD $/kg) 0.25  (Dones et al., 2005)  Values used in this analysis  (CAD $/kg)  (CAD $/kg)  NA  0.25  CH4, biogenic  0.14 b  N2O  12.52  4.73  NA  4.73  CO  0.41  1.02  NA  0.72  CO, biogenic NMVOC  0.67  Calculation and remarks  State average value is used as they are not just estimations based on GWP Estimated using impact factors in IMPACT 2002+ method State average value is used as they are not just estimations based on GWP Average of all values Estimated using impact factors in IMPACT 2002+ method  NA  NA  1.78  1.78  VOC  NA  3.76  NA  3.76  NOX  5.23  6.41  4.59  5.41  Average of all values  SOX  5.46  2.30  4.64  4.14  Average of all values Average of all values  c  PM  14.70  3.14  18.5  12.12  PM2.5  NA  NA  30.87  30.87  a  Based on values from New York State Public Service Commission, Department of Public Utilities of Massachusetts, Public Service Commission of Nevada and California Public Utilities Commission and presented in Goley's lecture slides (Golay, 2005). b Estimated by source based on CO2 cost multiplied by specific pollutant's 100-years time horizon GWP (global warming potential) value from the 2007 IPCC report c Estimated by source based on typical PM2.5/PM ratio  Since health impact depends heavily on the proximity of location of emission to population, the health impact associated with end usage alone for all five scenarios are compared as the point of usage is at UBC campus, where the risk of exposure to pollutant is much higher compared to pellet plants in suburban areas. The end-stage health impact for all scenarios are normalized by the value from the base scenario as it is the relative, not the absolute, values of the health impact that are relevant for this comparison.  3.3  RESULTS AND DISCUSSION  Using values presented in Table 3.1, the current annual emissions from UBC boiler house are calculated and presented in Table 3.5, together with the emissions from the biomass gasification scenarios. The emission factor for PM instead of PM2.5 is provided for all processes in the life cycle except for steam generation, where the PM2.5 emission factor is provided instead. Due to this reason, there are both PM and PM2.5 emissions reported in 40  Table 3.5 but there is no overlapping between them as the emission factor for PM during steam generation was not used in the calculation.  41  Table 3.5: Annual Air Emissions from Current and Woody Biomass Gasification Scenarios Scenario  NG and oil  Uncontrolled woody biomass gasification Emissions for Reduction in Emissions for wood waste external cost wood pellet (t/yr) ($1,000 CAD) (t/yr)  Pollutant  Emissions (t/yr)  All CO2  55,997  155,839  1,506  CO2, fossil  55,911  10,252  CO2, biogenic  86.30  145,586  All CH4  Reduction in external cost ($1,000 CAD)  Controlled woody biomass gasification Emissions for Reduction in Emissions for wood waste external cost wood pellets (t/yr) ($1,000 CAD) (t/yr)  Reduction in external cost ($1,000 CAD)  121,552  1,552  155,839  1,506  121,552  1,552  1,506  8,877  1,552  10,252  1,506  8,877  1,552  0.00  112,676  0.00  145,586  0.00  112,676  0.00  75.70  29.55  13.23  17.52  14.79  29.55  13.23  17.52  14.79  CH4  75.70  15.22  15.24  16.36  14.96  15.22  15.24  16.36  14.96  CH4, biogenic  0.00  14.33  -2.01  1.17  -0.16  14.33  -2.01  1.17  -0.16  1.79  9.88  -38.23  4.63  -13.40  9.88  -38.23  4.63  -13.40  9.65  48.19  -26.30  47.60  -25.98  48.19  -26.30  47.60  -25.98  9.65  22.09  -8.92  23.43  -9.89  22.09  -8.92  23.43  -9.89  0.00  26.10  -17.38  24.17  -16.10  26.10  -17.38  24.17  -16.10  NMVOC  5.40  17.32  -21.17  11.79  -11.34  17.32  -21.17  11.79  -11.34  NOX  38.04  221  -987  203  -893  128.39  -489  137.56  -539  SOX  8.22  27.77  -80.84  11.64  -14.11  27.77  -80.84  11.64  -14.11  All PM  0.56  72.67  -883  43.55  -522  10.31  -127  24.63  -292  PM  0.56  72.18  -868  43.52  -521  9.81  -112  24.59  -291  c PM2.5  0.00  0.49  -15.20  0.03  -1.01  0.49  -15.20  0.03  -1.01  b  N2O All CO CO  b  CO, biogenic  Total changes in external cost  -518  87  737  671  a  SCR has a removal efficiency of 80% while ESP has a PM removal efficiency of 99% May include some biogenic emissions as well c From “steam generation” only as no PM emission factor was available for this process b  42  From Table 3.5 it is apparent that the estimated biogenic CO, NMVOC, NOX and PM emissions for pellet gasification are lower than wood waste gasification, as observed in pellet and wood waste combustion. It appears that the most obvious advantage of switching to woody biomass gasification is the drastic reduction of CO2 emissions of fossil fuel origin. However, this is coupled with a substantial increase in biogenic CO2 emission, particularly due to lower thermal efficiency for the biomass gasification system and the high carbon intensity of biomass energy. Another emission reduction lies in generic CH4. Even though there is a slight increase of biogenic CH4 emission, there is a net CH4 reduction of 61% and 77% when accounting CH4 from all origins for wood waste and pellet gasification, respectively. The high CH4 emission from the current scenario arises from the upstream processing of natural gas as well as the leakage and loss during pipeline transmission. This observation is more noticeable in Figure 3.1 where the stage-wise distribution of each pollutant for the current scenario is illustrated. It is evident from the same figure that natural gas burns very cleanly with most of the emissions produced during upstream processing, with the exception of fossil CO2, N2O and NMVOC. Despite that natural gas combustion and upstream operations seem to be contributing the most to the emissions and environmental impacts, it is important to note that more than 99% of the energy input was from natural gas thus Figure 3.1 does not suggest that fuel oil burning is cleaner than natural gas. However, it is noted that there is a significant SOX emission from oil combustion despite that only less than 1% of the energy input was from fuel oil. The numerical values used for the construction of Figure 3.1 are presented in the Appendix D.  43  100%  Oil combustion NG combustion Oil upstream NG upstream  80% 60% 40%  PM  SOX  NMVOC NOX  N2O  CH4 CH4, biogenic  CO2, biogenic  CO2, fossil  0%  CO CO, biogenic  20%  Figure 3.1: Stage-wise emission distribution for the current natural gas scenario Other than generic CH4 emission and CO2 emission of fossil origins, all other emissions would increase when the boiler is switched from natural gas to woody biomass gasification. The most significant increase, other than in biogenic CO2, is in PM emissions, reaching approximately 130 and 77 folds for wood waste and wood pellets, respectively. Even with an ESP unit, the increase would still be approximately 18 and 44 folds for wood waste and pellet, respectively. ESP appears to be less effective for the pellet scenario because a large portion of PM emission is released from the upstream fuel preparation process that is not controlled by the ESP installed for the gasification plant. For wood pellet scenario, approximately 31% of the total PM emission is from pellet plant where wood residue is burned for biomass drying. Thus, removing PM from gasification process alone would achieve a less significant PM reduction over the entire life cycle. However, it is important to point out that the zero emission of PM2.5 under current natural gas operation results from the fact that all emission factors related to base scenario are only for PM but not for PM2.5 specifically. With emission controls in place, the increase in other pollutant emissions 44  compared to the base scenario ranges from 221% (for NMOVC) to 452% (for N2O) for wood waste and 42% (for SOX) to 393% (for all CO), for wood pellets. In Figure 3.2, the stage-wise contributions to the total emissions are illustrated for wood waste gasification (Figure 3.2a), wood pellet gasification (Figure 3.2b), wood waste gasification with emission controls (Figure 3.2c) and wood pellet gasification with emission controls (Figure 3.2d), respectively. Figure 3.2 reveals that the top contributor to biogenic CO2 and N2O emissions is the gasification stage for all woody biomass gasification scenarios. For the uncontrolled wood waste scenario, more than 80% of the generic CO and approximately 50% of the NMVOC emissions are emitted during the harvesting stage. The gasification stage is the main contributor to the remaining pollutants except for fossil-origin CO2 and generic CH4 as more than 40% of each of these pollutants are emitted during transportation via HDV. For wood waste gasification with emission control units, the harvesting stage also becomes the main contributing stage for NOX and PM emissions throughout the life cycle while HDV transportation remains to be the main contributor for fossil-origin CO2 and generic CH4. The numerical values used for the construction of Figure 3.2 are presented in the Appendix D.  45  80%  80%  60%  60%  40%  40%  20%  20%  0%  0%  a  80%  80%  60%  60%  40%  40%  20%  20%  0%  0%  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  100%  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  b  100%  c  Transportation by Train Transportation by HDV Gasification Pellet plant operation Sawmill operation Harvesting operation  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  100%  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  100%  d  Figure 3.2: Stage-wise emission distribution for a) wood waste gasification, b) wood pellet gasification, c) wood waste gasification with SCR and ESP units with 80% NOX and 99% PM removal efficiency, respectively, and d) wood pellet gasification with identical emission control units For both uncontrolled and controlled wood pellet scenarios, the harvesting stage is the main contributor to fossil-origin CO2, generic CO, NMVOC, and SOX while pellet plant is where the majority of biogenic CH4 and CO is emitted due to the burning of wood residue within the mill. In the uncontrolled pellet scenario, 42% of the NOX emission in the life cycle is emitted in the harvesting stage and 40% from gasification. Moreover, gasification is responsible for 44% of the life cycle PM emission. However, with emission control, gasification stage’s 46  contribution to PM and NOX are reduced to 0.8% and 12%, respectively, with pellet plant becoming the new hot-spot for PM emission. Note that the PM category in both Figure 3.1 and Figure 3.2 refers to "All PM" in Table 3.5. The external costs from each scenario are also presented in Table 3.5. By switching to wood waste gasification, there is actually an increase of $518,000 CAD in external costs while wood pellet gasification would result in an $87,000 CAD saving. It was stated earlier that in order to satisfy the air emission limits in Vancouver for biomass boiler the NOX and PM emissions need to be reduced. With the installation of SCR and ESP units, the external costs can be reduced by 34% and 31% from the base case for wood waste and wood pellets, respectively. Note that no spatial variation of the external cost has been considered in the current analysis in which the emissions released in densely populated urban area and less populated remote area are given the same external cost for each gas pollutant. Since emission increased for all major pollutants when the boiler house is switched from natural gas to wood pellet gasification, it is hard to comprehend the relative overall impacts from each scenario based on emission inventories only. Figure 3.3 compares each of the five scenarios' impacts on human health, ecosystem quality and climate change, as well as a breakdown of these impacts into different stages to signal out hot-spots throughout their life cycles. The numeric values used for the construction of Figure 3.3 is included in the Appendix D.  47  . .  a  40 30 20 10  Climate change (kt CO2-equivalent)  0  60  Ecosystem quality (PDF m2 yr)  Human health (DALY)  50  1.4x106  Current Wood Wood Wood Wood waste pellet waste pellet with with control control  c  50 40 30 20  1.2x106  b  1.0x106 8.0x105 6.0x105 4.0x105 2.0x105 0.0  Current Wood Wood Wood Wood waste pellet waste pellet with with control control  Transportation by Train Transportation by HDV Gasification Pellet plant operation Sawmill operation Harvesting operation Oil comubstion NG combustion Oil upstream NG upstream  10 0  Current Wood Wood Wood Wood waste pellet waste pellet with with control control  Figure 3.3: Stage-wise impact analysis in terms of a) human health, b) ecosystem quality, and c) climate change for base and woody biomass gasification scenarios with and without emission control units By switching to woody biomass, both impacts on human health and ecosystem quality increase significantly. For human health, the current impact is 4 DALY and it would increase by 6.2 folds and 8.6 folds for wood pellets and wood waste, respectively. Even with emission control units, the increase would still be 3.3 folds on average for both woody biomass fuels. Since the parameters used in the impact assessment method for human health are based on Western Europe, care should be exercised in the interpretation of human health impact. 48  It is clear from Figure 3.3 that the harvesting of woody material and the gasification stage contribute greatly to human health impact. Also, by adding emission control units, the pellet scenario’s human health impact for the entire life cycle can be further reduced by 35% while the health impact associated with gasification alone can be further reduced by 87%. However, since wood waste requires little upstream processing, the addition of emission control can effectively reduce the overall health impact by 59% and the reduction in gasification stage alone would be 88%. The current impact on ecosystem quality is 2.26E5 ∙m PDF  2  ∙yr and it would increase by  around 4.7 and 4.2 times when switched from natural gas to wood waste and wood pellet gasification systems, respectively. With SCR and ESP, the increase can be lowered to an average of 2.5 folds for both fuel types. For the effect on ecosystem quality, the main contributions are from the harvesting and gasification stages as well. With emission control, gasification only contributes 20% and 12% to the entire life cycle’s impact on ecosystem quality for wood waste and pellet, respectively. Moreover, with emission controls the ecosystem quality impact for the entire pellet gasification life cycle can be further lowered by 32% while impacts associated with gasification alone can be reduced by 80% when compared to uncontrolled pellet scenario. Lastly, Figure 3.3 confirms that the key advantage associated with switching to woody biomass is the reduction in GHG emissions. Figure 3.3c clearly illustrates that impact on climate change can be reduced by 79% and 83% from the current 56.7 kt of CO2-equivalent per year when wood waste and wood pellets are used, respectively. Another scenario performance indicator is primary energy consumption. To generate 974 TJ of usable heat annually, the current scenario consumes 1,284 TJ of primary energy and this number is slightly higher for the pellet scenarios at 1,516 TJ and 1,748 TJ for wood waste scenarios. Primary energy takes into account the energy resource required to produce fuels, power or products. These include the heating value of raw materials such as harvested 49  wood and crude oil, energy required to produce fuels such as diesel, and energy required to convert different fuels, such as natural gas or diesel, to electricity. It is important to acknowledge that human health impact is more of local concern as compared to the global climate change impact. As the UBC district heating system is located in a densely populated area, the stack emissions from the boiler house will have the most significant impact on human health. The end usage contributions to human health impact for all five scenarios are normalized by the base case value and are compared in Figure 3.4. It is apparent that the human health impact linked directly to stack emissions increases substantially when switched from natural gas to woody biomass as it would be augmented by 19 and 8.7 folds for wood waste and pellet gasification, respectively. This value is lowered to a 133% increase for controlled wood waste scenario and a mere 12% increase for controlled wood pellet scenario. As a result, it is strongly recommended that both the PM and NOX emission control units be installed in biomass combustion/gasification district heating systems to prevent the deterioration of local air quality and drastic increase in local health impact, in addition to meeting the local emission standards.  Normalized end-stage health impact  20 15 10 5 0  Current  Wood waste  Wood pellet  Wood Wood waste pellet with with control control  Figure 3.4: Human health impacts associated with stack emissions only normalized by current scenario value 50  3.4  CONCLUSIONS  It is observed that compared to the base scenario with natural gas for UBC boiler house, woody biomass gasification has significant advantages in GHG reduction, ranging from 79% to 83%, and possible external cost savings of $87,000 CAD if wood pellets are utilized. However, these advantages are accompanied with higher human health impact, ecosystem quality impact and a slight increase in primary energy consumption. With emission control units installed, the life cycle impacts on both human health and ecosystem quality can be lowered by an average of 50% for wood waste and 34% for wood pellets but the impacts are still higher than the base case. With control units, external cost savings are estimated to be $737,000 and $671,000 CAD for wood waste and wood pellet scenarios. Despite higher emissions and impacts compared to the base case, both wood waste and wood pellet gasification with proper PM and NOX control units can meet the emission standards set for biomass boilers in Metro Vancouver. In all aspects the uncontrolled wood pellet scenario performs better than uncontrolled wood waste scenario. But when emission controls are installed, wood waste performs better than wood pellets in terms of external costs, ecosystem quality and human health impact over the entire life cycle. This is due to the fact that wood waste requires little upstream processing and has high stack emission while the opposite is true for wood pellets. Since the emission controls are only effective for controlling the end stage emission, the overall impact of the controlled wood waste scenario is lower than pellets. However, the main concern for biomass utilization in district heating systems is its impact on human health for residents in the proximity of the heating facility. By comparing human health impact linked directly to end usage alone, it is observed that controlled wood pellet gasification would result in only a 12% increase in health impact while controlled wood waste has a much greater increase at 133% from the natural gas base case. Replacing fossil fuels, especially clean ones such as natural gas, with biomass energy may not always be desirable and the decision would depend heavily on the priorities of the specific project. Although gasification already produces considerably less pollutants when 51  compared to direct combustion of biomass, natural gas combustion still outperforms wood pellet gasification in all impact categories considered other than climate change. Other factors that are not considered in this study include storage requirement for pellets, the noise and inconvenience associated with traffics for pellet delivery. In this study, the gasification plant produces only heat so the LCA study of a CHP plant in place of the existing boiler house might yield different results. As UBC also aims to become a net energy exporter by 2050, the CHP option is readily pursued as UBC has already decided to establish a CHP demonstration unit on campus using a system developed by Nexterra and GE to provide green heat and electricity while serving as a research facility.  52  4  EVALUATION OF WOOD PELLET APPLICATION FOR RESIDENTIAL HEATING IN BRITISH COLUMBIA BASED ON A STREAMLINED LIFE CYCLE ANALYSIS  4.1  INTRODUCTION  In 2007, the secondary energy consumption in Canada was 8,871 PJ with 16.3% attributed to the residential sector with 62.7% of the residential energy consumption in space heating (Natural Resources Canada's Office of Energy Efficiency, 2010; Natural Resources Canada’s Office of Energy Efficiency, 2010b). On a provincial level, 159.1 PJ of energy was consumed in 2007 in the residential sector in BC, of which 55.8% was for space heating, translating to 2.7 Mt of CO2-equvalent emitted (Natural Resources Canada’s Office of Energy Efficiency, 2010a). In 1990, the contribution of natural gas in residential heating was 57.3% and this number had increased to 63.5% around 1995 but had decreased back to approximately 60% since then. Electricity usage for this sector climbed up steadily from 18.5% in 1990 to 29.4% in 2007 while the contribution of wood was at 9.2% in 1990 and reached a low of 6.5% around 1995 but had been growing since then to 10.3% (Natural Resources Canada’s Office of Energy Efficiency, 2010a). Although the burning of biomass is considered to be carbon neutral, this does not mean biomass performs better in other categories, such as impact on human health and ecosystem quality, when compared to other types of fuels. As reported (Caserini et al., 2010; Pa et al., 2009), the health impact arising from biomass combustion or gasification in district and residential heating could be higher than natural gas combustion. There is a major health concern on emissions from biomass combustion in BC since 44% of the wood burning appliances in BC residences are conventional fireplaces and 19% are conventional wood stoves (British Columbia Ministry of Water, Land and Air Protection, 2005; Ipsos Reid, 2002). Conventional wood burning devices for residential heating have two main problems: low efficiency and high emissions. Typical efficiency of conventional fireplaces is lower than 10% and has high emissions due to incomplete combustion (Natural Resources Canada, 2009). Emissions from fireplaces not only pollute the environment but may also have serious health impacts on its users (Canada Mortgage and Housing 53  Corporation, 2008; Natural Resources Canada, 2009). There are also many studies on the effects of exhaust from residential biomass combustion on humans (Bellmann et al., 2009; Kocbach Bølling et al., 2009; Ramanakumar et al., 2007; Torres-Duque et al., 2008). A study in Portugal concluded that particulate matter (PM) emission from wood combustion for residential heating is a significant source of PM in the atmosphere (Borrego et al., 2010). The study further established that by implementing a policy for the conversion of traditional fireplaces to certified devices, the air quality, in terms of PM concentration, could be greatly improved. Luckily there are many wood-burning alternatives on the markets that offer higher efficiency and less emission. These include catalytic fireplaces, advanced fireplaces and fireplace inserts. Other than burning firewood directly, one can also burn wood pellets. Switching to wood pellets comes with many advantages such as higher efficiency (less fuel required), lower emissions due to cleaner burning (less health and environmental impacts), easier operation, easier storage of fuels and no need for further drying of the fuels (Canada Mortgage and Housing Corporation, 2008; Kocbach Bølling et al., 2009). Boman et al. (2003) in Sweden applied dispersion modeling to investigate the effects of biomass pellet combustion on residential air quality and recommended switching from fire log to wood pellets for residential heating as a method to improve local air quality. Another study on the chimney emissions of softwood pellet burning in residential settings also concluded that wood pellet is a favourable alternative for residential heating due to its low content of mineral matters, resulting in low emissions of NOX, SOX and PM (Olsson et al., 2003). It was also mentioned that pellets have been replacing firewood in residential heating in Sweden mainly due to convenience of automated pellet stoves (Olsson et al., 2003). Generally, devices using wood pellets have less emission than advanced wood combustion units (Canada Mortgage and Housing Corporation, 2008). Even when looking at the impact on climate change, pellets are superior to firewood as CH4, a much stronger GHG than CO2, is emitted substantially less from pellet burning units than wood burning units (Olsson et al., 2003). One important bonus for using locally produced BC wood pellets for residential 54  heating is the reduced fossil fuel content and GHG footprint. BC has the most number of pellet plants in Canada (Melin, 2008) but most of the wood pellets are being exported to Europe (Melin, 2008; Spelter & Toth, 2009), increasing the fossil fuel content of the pellets from 9% to 16% due to marine transportation (Pa, Craven et al., 2009). It would be beneficial to increase the local utilization of pellets to reduce emissions associated with transportation. For this study, the feasibility of replacing firewood in BC domestic heating by wood pellets is analyzed by using the in-house LCI database of exported BC pellets constructed in Chapter 2. In the analysis, the current residential firewood heating practice is the base scenario while the new scenario is the replacement of all wood-burning equipment by their pellet counterparts. The total amount of pellets to be consumed in the new scenario is the amount required to provide the same amount of heat as the base scenario. The overall reduction in impact categories such as climate change, human health, ecosystem quality and primary energy usage will be presented and discussed. The avoided external cost based on potential emission reductions is also calculated to illustrate how much externality can be saved for every tonne of pellets burnt to replace firewood. Lastly, a simple economic analysis is carried out to demonstrate whether or not switching to a pellet-equivalent residential heating unit is economically attractive for users. This analysis will also provide some basis for the development of future user-incentive programs.  4.2  METHODS AND CALCULATION  4.2.1 Data collection for Wood-based Residential Heating in British Columbia This case study involves two types of wood fuels and each fuel has its own life cycle and, for the ease of calculation, different functional units suitable for each scenario are first used. However the values that are shown in the result section are all in the functional unit of annual energy demand of the operation, which is equal to 11,066 TJ, for both scenarios. This functional unit is also equivalent to per unit of energy produced. 55  4.2.1.1 Base Scenario Data on the amount of fire logs utilized in residential heating in BC and the type of burning appliances are obtained from three surveys conducted in BC. BC Ministry of Water, Land and Air Protection (WLAP) commissioned a telephone survey in June 2003 after PM was identified as the air pollutant of most concern in terms of health threats in BC (British Columbia Ministry of Water, Land and Air Protection, 2005). This survey covers all of BC other than LFV (Lower Fraser Valley) and Kelowna. These two regions were covered by two separate surveys, the “Okanagan Indoor Wood Burning Appliance Inventory Survey” in 2001 and the “GVRD Residential Wood Burning Survey” in 2002, respectively. GVRD stands for Greater Vancouver Regional District, which is now known as Metro Vancouver. The result from the Okanagan Indoor Wood Burning Appliance Inventory Survey was included and presented in the 2003 survey report titled "Residential Wood Burning Emissions in British Columbia " while the 2002 GVRD survey data were not included (British Columbia Ministry of Water, Land and Air Protection, 2005). The 2003 BC report disclosed data on the quantity of different types of residential wood combustion units, the amount of firewood burnt in each type of unit annually, referred to as "base quality", and the average emission factors of each type of units. The data from the 2002 GVRD Residential Wood Burning Survey (Ipsos Reid, 2002) are used to fill the gap that is missing in the 2003 BC report. GVRD has commissioned Ipsos Reid to conduct the 2002 GVRD survey, covering both of GVRD and FVRD (Fraser Valley Regional District). However, the data presented in the Ipsos Reid report is not as detailed as the 2003 BC report, thus assumptions had to be made. In the Ipsos Reid report, single dwelling families who owned wood burning appliances were identified and the type of units owned were further specified. This information allows the calculation of the total number of wood burning appliances and the model distribution in GVRD and FVRD. The types of equipment considered in the surveys were fireplace, conventional wood stove, advanced technology stove (referred to as non-catalytic and non-traditional stove in survey), catalytic stove, masonry heater and pellet stove. Since there is no distinction between advanced technology fireplace and conventional fireplace for the Ipsos Reid survey, the ratio of the number of 56  conventional to advanced technology fireplaces based on the 2003 provincial survey, calculated to be 6.35:1, is also used for GVRD and FVRD. After obtaining the number of each type of appliance in GVRD and FVRD, the next step is to figure out how much wood is used in each unit per year. This information is derived from the section describing number of split firewood burnt on an average winter/fall and spring/summer day. The weight average value for number of split wood used per day is computed to be 6.2 and 0.92 for winter/fall season and spring/summer season, respectively. These numbers take into account families that own wood-burning equipment but do not use them. It is important to note that for the Ipsos Reid survey, the wood usage data were not specific to equipment type thus all units are assumed to have the same wood consumption rate. This is not the case for the BC and Kelowna surveys as the amount of wood used was specific to each type of equipment. Assuming a typical split wood is 15 inches (38 cm) in length and 5 inches (13 cm) in diameter with a moisture content of 18% wet basis, as required by the Canadian Standards Association stove testing procedure (British Columbia Ministry of Water, Land and Air Protection, 2005), and a density of 530 kg/m3, a simple average of all woods indigenous to BC (British Columbia Ministry of Water, Land and Air Protection, 2005), the total amount of wood used per year by all households are calculated to be 644,000 t and 70,000 t for GVRD and FVRD, respectively. With these values and the distribution of appliances in GVRD and FVRD, the base quality by appliances in these regions can be obtained. Table 4.1 shows the base quantity by appliances for BC, including Kelowna, GVRD and FVRD. Table 4.1: Summary of Each Appliance's Cost, Efficiency and Base Quality in both Firewood and Wood Pellets Current wood combustion unit Fireplace Furnace/central boiler  Advanced technology Conventional Indoor Outdoor Unspecified  Base quantity (kt)  Efficiency (%)  94.6  60  570 94.5 19.1 0.47  a a  10 b 85 c 43 a 50  Pellet-equivalent replacement Pellet fireplace insert Pellet Furnace and boiler  Base quantity (kt)  57.7 58.0 75.3 7.71 0.22  Efficiency (%) 83  Cost ($CAD)  i  3689  j  5085  90  k  l  57  Current wood combustion unit  Fireplace insert  Woodstove  Advanced technology Catalytic Conventional Advanced technology Catalytic Conventional  Masonry heater a  Pellet stove  b  Base quantity (kt)  Efficiency (%)  8.57  76  Pellet-equivalent replacement  d e  Pellet fireplace insert  e  Pellet stove  2.84 28.1  78.5 f 20  226  75  a  78.5 a 62.5  17.9  58  29.9  80  h  Efficiency (%)  6.65 2.27 5.72  Pellet fireplace insert Pellet stove c  58.5 205  3689  80  h  3275  i  3689  10.6  83  29.9  80  d  Cost ($CAD)  i  k  83  179  70.6 311  g  Base quantity (kt)  k  k  h  k  e  3275  (Natural Resources Canada, 2009) , (The Clean Energy Company, 2010), (Schreiber et al., 2005), (Quadra-Fire, 2010), (RJM Manufacturing, 2010), f (Nancy, 2009), g (U. S. Environmental Protection Agency, 1995), h (Natural Heat), i (Natural Heat), j (Harman Stove, 2009), k (Natural Heat), l (No Utility Bills Inc., 2010)  Using Table 4.1, the total amount of heat generated annually in the base scenario from firewood burnt in residential heating practices is calculated to be 10,602 TJ and another 464 TJ of heat is generated currently by wood pellets for residential heating in BC. 4.2.1.1 Wood Pellet Scenario Given the efficiencies of the different equipment and the HHV of 16.4 GJ per tonne of firewood at 18% moisture content, wet basis (Wright et al., 2009) and 19.4 GJ per tonne of wood pellets at 5.6% moisture content, wet basis (Accredited Laboratory, 2007), the equivalent base quantity by appliances in the unit of tonne of wood pellet can be calculated. Base quantities of wood pellets in pellet-equivalent equipment are presented in Table 4.1.  4.2.2 Life Cycle Inventory Data for the Production and Transportation of Fuels To calculate the various environmental impacts for both scenarios, both the upstream and combustion emissions need to be accounted for. The upstream processes of the firewood and wood pellets will be based on the BC wood pellet LCI database established. 4.2.2.1 Base Scenario For the firewood scenario, the harvesting process is taken into account. The value presented by Sambo (2002) is 134 MJ for the production of 1 m3 of green timber and this does not 58  include hauling to wood processing plants. This value is converted into 262 MJ required to produce 1 tonne of firewood at 18% moisture content, wet basis. The calculation required the assumptions that the density of harvested material is 840 kg/m3 green material and the green material has 50% moisture content, wet basis (British Columbia Ministry of Water, Land and Air Protection, 2005; Simpson, 1993). It is then assumed that the green lumber is harvested and delivered to the log processing location via HDV over a distance of 5 km. As transportation emission factors are in the unit of kg of pollutant emitted per tkm transported, it is important to take the mass difference of green wood (at 50% moisture content, wet basis) and seasoned firewood (at 18% moisture content, wet basis) into consideration since the functional unit for this part of the analysis is per tonne of firewood. For the chopping and natural drying of the green lumber, it is assumed that all green lumber is converted to firewood. The energy consumption of 3L of diesel and hourly wood output of 12.5 m3 of the commercial scale wood chopper are based on Whitlands Engineering’s figures (2009). The seasoned firewood is then delivered via MDV over an average distance of 75 km to the customers. Note that the travelling distance of the firewood from harvesting site is limited to 80 km as this is the recommended maximum distance to spread firewood to avoid spreading of pests (The Nature Conservancy). When the firewood arrives at the end user's home, it is combusted in various types of wood burning appliances and each type would have a different set of emission factors. 4.2.2.2 Wood Pellet Scenario The BC wood pellet LCI established previously is modified to accommodate for the inclusion of packaging and different logistics. The streamlined life cycle now consists of harvesting, transportation of harvested material to sawmill, sawmill processing, transportation of sawmill by-products to pellet plant, pellet plant operations, packaging, and lastly pellet transportation in bulk and packages via HDV and medium duty vehicles (MDV) to end users. Emissions from infrastructure and land changes are not included in the database and the analysis and allocations are mass-based.  59  For packaging, it is assumed that 50% of the pellets produced will be bagged into LLDPE bags each weighing 0.123 lbs (Trotzuk, 2010). Each bag would be able to hold 40 lbs, or 18.1 kg, of wood pellets (Melin, 2010). The energy required to produce these plastic bags are taken into account by using the LLDPE granulates and plastic film extrusion process data from the US-EI database, a database of Ecoinvent processes with all European electricity mix replaced by US electricity mix (Swiss Centre for Life Cycle Inventories et al., 2008). The other 50% of the pellets are delivered in bulk to the end user where the pellets are unloaded by either compressed air or a pneumatic conveyance system (Biomass Energy Resource Center, 2007). Currently, end users tend to receive bag delivery or make trips to retailers to purchase bagged pellets. However, in parts of Europe where wood pellets are a common fuel for residential heating, wood pellets are usually delivered in bulk to end users (Sikkema et al., 2010). The pellet delivery distance is broken down into two segments. The first segment is from the pellet plants to a central storage close to highly populated area via HDV while the second segment is the delivery of pellets to end users via MDV. Judging from the fact that over 50% of the BC households are located in the LFV (British Columbia Ministry of Water, Land and Air Protection, 2005), an average distance of 450 km from all pellet plants in BC to Vancouver, which is located in LFV, is used as a basis for distance estimation (Melin, 2010). The assumed distance used for the first segment via HDV is 400 km while the second segment via MDV is 50 km. Note that the total distance is much higher than the recommended 48 km for cost effectiveness (Biomass Energy Resource Center, 2007). Furthermore, more environmentally friendly transportation, such as train, for the 400 km traveled may be implemented if pellets were a popular fuel for residential heating and would result in much lower estimated emissions for the pellet scenario. However, HDV is chosen in the current study as it is the current practice and it provides a conservative estimation. Details regarding various transportation segments are also obtained from the surveys with the exception of the segment between harvesting and sawmill, which is based on Sambo's work (2002). 60  4.2.3 Inventory Data for the End Stage Combustion of Wood Fuels Table 4.2 and Table 4.3 summarize the combustion emission factors of the various types of combustion appliances and the sources of data for firewood and wood pellets, respectively. The sources of these emission factors are also listed. Moreover, the upstream (production and transportation of the wood fuel to end users) emission of firewood and wood pellets are presented as well. The emission factors for pellet stoves are applied for both pellet stove and pellet fireplace insert as emission factors for pellet fireplace inserts were not available. The emissions from the two scenarios are analyzed by the modified IMPACT 2002+ method using SimaPro.  4.2.4 Economic Analysis The economic analysis requires several assumptions. The pellet burning units to be purchased are first assumed to have a lifetime of 10 years. The assumed annual interest rate is 8% compounded annually. Pellet price is assumed to be $189 CAD per tonne for bulk based on $135 CAD at pellet plant gate, $25 CAD of transportation cost within BC, $20 markup and 5% tax (Melin, 2010). The bagged pellet price is assumed to be $329 CAD per tonne plus 5% tax, yielding $345.45 CAD (Melin, 2010). Since the economic analysis is conducted from the perspective of the end user, the bulk and bagged scenarios are performed separately instead of using an average pellet price. Seasoned firewood price including shipping is $314 CAD per tonne based on price list from BC firewood suppliers (Squamish Wood Fuel Supply Ltd.). The cost of various pellet appliances are listed in Table 4.1 and these values are obtained from various product catalogues accessible to the general public. First the average amount of firewood needed for a single appliance per year is calculated for each type of appliance by dividing the annual amount of firewood needed for a specific type of appliance in BC by the total number of that type of appliance in BC. The annual amount of pellets required in the pellet-equivalent appliances to produce the same amount of heat is then calculated. The annualized cost of a new pellet appliance is calculated based on an assumed 10 year lifetime. The total annualized cost for the pellet scenario is then compared 61  to the annualized cost for the firewood scenario. Switching to pellet-equivalent units, depending on the type of appliance currently owned, may or may not be an economical decision. To help demonstrate if the investment should be made, two indicators are presented. First, the payback period is calculated by dividing the pellet appliance's capital investment by the annualized savings between the firewood and pellet scenarios. Note that payback period does not consider the time value of money. Secondly, the net present value (NPV) of switching to pellet-equivalent appliances, taking into account the savings or losses on fuel cost, interest rate, equipment life time and initial capital investment, is also computed. Two wood pellet scenarios are analyzed as the bagged and bulk pellet prices vary quite substantially. The savings in external costs due to switching from firewood to wood pellet appliances can be computed using values in Table 3.4. It is also possible to show the externality, in $CAD, saved per tonne of pellets utilized to replace firewood. This value may give some insights to government policy-makers on determining the level of monetary incentives given to wood burning unit owners to encourage them to switch to pellet burning units.  62  Table 4.2: Upstream and Combustion Emission Factors for Firewood in Various Residential Heating Appliances CO2, CO2, a CH4 CH4, biogenic N2O fossil biogenic (kg/tonne of firewood delivered to user or combusted by user)  Fireplace Insert  Furnace/central boiler  Fireplace  Firewood 74.7 upstream Advanced 0 technology Conventional 0  Source  Indoor, outdoor and unspecified boilers  0  Source  0.52  0.11 0  5.4E-03  CO  a  CO, biogenic  0.13 0  NMVOC  VOC  0.064  b  c  PM  c  PM10  c  NOX  SOX  PM2.5  --  0.59  6.7E-02 4.3E-02 --  --  1503  4.12  0.15  70.4  14.93  7  1.4  0.2  5.1  4.8  4.8  1503 Based on carbon content and moisture content of fuel  4.12  0.15  77.7  14.93  6.5  1.4  0.2  19.3  18.5  18.4  (Schauer et al., 2001)  (U. S. Environmental Protection Agency, 1995). Based on fireplace in general  (British Columbia (Schauer et al., Ministry of 2001). Based on (British Columbia Ministry of Water, Land and Water, Land and fireplace in Air Protection, 2005) Air Protection, general 2005)  1503  10.50  0.11  68.5  Based on carbon content and moisture content of fuel  Based on logs burnt in 6kW wood heater (Johansson et al., (Swiss Centre for Life 2004) Cycle Inventories et al., 2008)  (British Columbia Ministry of (Johansson et Water, Land and al., 2004) Air Protection, 2005)  (British Columbia Ministry of Water, Land and Air Protection, 2005)  5.74  21.3  1.4  0.2  14.1  13.3  13.3  Advanced technology  0  1503  8  0.11  70.4  6  7  1.4  0.2  5.1  4.8  4.8  Catalytic  0  1503  5.8  0.11  70.4  7.5  7  1.4  0.2  5.1  4.8  4.8  Conventional 0  1503  15  0.11  115.4  26.5  21.3  1.4  0.2  14.4  13.6  13.6  63  CO2, CO2, a CH4 CH4, biogenic N2O fossil biogenic (kg/tonne of firewood delivered to user or combusted by user)  Wood Stove  Source  Advanced 0 technology Catalytic 0 Conventional 0  Source  Masonry  Source  a  0  CO  a  CO, biogenic  NMVOC  b  VOC  NOX  SOX  c  PM  c  PM10  c  PM2.5  Based on carbon content and moisture content of fuel  Based on nonSame as boiler as US catalytic, catalytic AP-42 suggests that and conventional stoves have lower N2O wood stoves (U. S. emission than Environmental fireplace so the wood Protection Agency, boiler emission is used 1995). Wood stove for both inserts and value is used as stoves (U. S. estimation since Environmental inserts are similar Protection Agency, to stoves 1995)  Total nonmethane organic compound (TNMOC) (British Columbia emissions for Ministry of non-catalytic, (British Columbia Ministry of Water, Land and Water, Land and catalytic and Air Protection, 2005) Air Protection, conventional 2005) wood stoves (U. S. Environmental Protection Agency, 1995)  1503  8  0.11  70.4  6  7  1.4  0.2  5.1  4.8  4.8  1503 1503 Based on carbon content and moisture content of fuel 1503  5.8 15  0.11 0.11  70.4 100  7.5 26.5  7 35.5  1.4 1.4  0.2 0.2  5.1 24.6  4.8 23.2  4.8 23.2  Based on carbon content and moisture content of fuel  (U. S. (Swiss Centre for Life Environmental Cycle Inventories et Protection Agency, al., 2008) 1995)  (British Columbia TNMOC Ministry of emissions (U. S. (British Columbia Ministry of Water, Land and Water, Land and Environmental Air Protection, 2005) Air Protection, Protection 2005) Agency, 1995)  0.58  74.5  (Tissari et al., 2008)  0.11 (Swiss Centre for Life Cycle Inventories et al., 2008). Same emission as stove since masonry is listed under the stove section in US AP-42 (U. S. Environmental Protection Agency, 1995)  (U. S. Environmental Protection Agency, 1995)  8.99  9.57  1.4  0.2  3.3  Calculated by subtracting CH4 from VOC  Assumed to be the same as (Fergus others in the (Ferguso on, survey as they n, 2008) 2008) appear not to be equipmentspecific  2.8  --  (U. S. Environ mental Protect ion Agency , 1995)  May contain biogenic emissions VOC emissions are not included in the analysis to avoid double accounting since CH4 and NMVOC are included already. VOC emissions are only included to show how CH4 and NMOVC emission are calculated in some cases c The definitions of PM is all particulate matter, which include both PM10 and PM2.5 while PM10 includes PM2.5. Due to these definitions, only PM2.5 is included in the impact analysis as PM2.5 is the only type of particulate matter that has an impact according to IMPACT 2002+. The impact factor for PM in IMPACT 2002+ is based on an average value of PM2.5 to PM ratio in air and used only when the emission for PM2.5 is not available b  64  Table 4.3: Upstream and Combustion Emission Factors for Wood Pellets in Various Residential Heating Appliances  Wood pellet upstream Pellet stove and insert  CO2, CO2, a a CH4 CH4, biogenic N2O CO fossil biogenic (kg/tonne of wood pellets delivered to user or combusted by user)  CO, biogenic  NMVOC  VOC  NOX  SOX  PM  PM10  PM2.5  208  130  0.35  0.19  --  1.73  0.22  0.38  --  --  0  1731  8.8  0.39  1.5  1.4  0.2  1.2  1.1  1.1  Based on carbon content and moisture content of fuel  Source  Pellet boiler  Source  a  0.38  0  1731 Based on carbon content and moisture content of fuel  0  1.2E-2  2.1E-02  1.11  0.058  Calculated by subtracting NMVOC from VOC  Based on pellets burned in 15kW furnace (Swiss Centre for Life Cycle Inventories et al., 2008)  0.078  0.058  Based on pellets burned in 15kW (Johansson et furnace (Swiss al., 2004) Centre for Life Cycle Inventories et al., 2008)  0.36  0  b  c  c  c  (UNECE/EMEP Task Force on Emission (British Inventories and Columbia Projections (TFEIP) Ministry of & European (British Columbia Ministry of Water, Land and Air Water, Land Protection, 2005) Environment and Air Information and Protection, Observation 2005) Network (Eionet), 2009) 8.50 0.19 -1.29 0.2 0.62 --Assumed to be the same as (Johanss others as (Johanss (Johansson (Johansson et al., N/A on et al., they on et al., et al., 2004) 2004) 2004) appear not 2004) to be equipment -specific  May contain biogenic emissions VOC emissions are not included in the analysis to avoid double accounting since CH4 and NMVOC are included already. VOC emissions are only included to show how CH4 and NMOVC emission are calculated in some cases c The definitions of PM is all particulate matter, which include both PM10 and PM2.5 while PM10 includes PM2.5. Due to these definitions, only PM2.5 is included in the impact analysis as PM2.5 is the only type of particulate matter that has an impact according to IMPACT 2002+. The impact factor for PM in IMPACT 2002+ is based on an average value of PM2.5 to PM ratio in air and used only when the emission for PM2.5 is not available b  65  4.3  RESULTS AND DISCUSSION  The emissions from the current firewood and the hypothetical wood pellet scenarios for BC residential heating are calculated and presented in Table 4.4. There is a 38% reduction in overall CO₂ emissions, contributed from the reduction in biogenic CO 2, due to the fact that pellet appliances have better efficiency and higher fuel quality such as low moisture content and uniform size. There is a 30% increase in CO2 from fossil origin, mostly resulting from the extra processing required for pellet production compared to only chopping for firewood. The same trend is observed for CH4 and CO. The emission of another important GHG N2O can be reduced by 72% by switching to wood pellets. In fact, total emissions of all major pollutants decreased by 27 to 98%. Pellet combustion creates substantially less PM compared to firewood combustion and this is reflected on the 95% total PM emission reduction. In Table 4.4, PM2.5 and PM are listed separately because they have different impact and associated external cost. Table 4.4: Annual Emissions from Current and Wood Pellet Scenarios and Possible Savings in External Costs and Emissions when Wood Pellets are Utilized Pollutant  Firewood scenario emissions (kt/yr)  Pellet scenario emissions (kt/yr)  Reduced externality under pellet scenario ($1,000 CAD/year)  Reduction in emission (%)  All CO2  2,338  1,441  -1,120  38  CO2, fossil  111  145  -1,120  -30  CO2, biogenic  2,226  1,296  0.00  42  All CH4  11.53  0.96  1,471  92  a CH4  0.16  0.26  -24.77  -60  CH4, biogenic  11.36  0.70  1,496  94  0.20  0.06  678  72  117  6.60  73,228  94  0.20  0.25  -37.61  -26  116  6.35  73,265  95  NMVOC  21.78  0.38  38,007  98  NOX  2.96  2.17  4,279  27  SOX  0.40  0.29  437  27  N2O All CO CO  a  CO, biogenic  All PM  21.69  0.99  642,614  95  PM  0.13  0.31  -2,209  -138  c PM2.5  21.56  0.68  644,823  97  b  Total external cost reduced ($1000 CAD/year)  759,594  66  Reduced external cost per additional t of pellets utilized ($CAD/yr/t of pellets)  1,140  a  CH4 and CO emissions listed here may contain a small fraction of biogenic emission. The distinction is not possible as upstream emission data provided by GHGenius does not segregate between biogenic and fossil emissions of CH4 and CO. The data used to calculate upstream emissions of firewood and wood pellet did not have a separate category for PM2.5 thus the amount of PM2.5 emitted during the production and transportation of firewood and pellets are included in PM c The data used to calculate emissions during end usage of wood pellets and firewood have values for all of PM, PM10 and PM2.5 emissions. To avoid double accounting, only the PM2.5 emissions are taken into account and reported here as they are the ones with impact according to the IMPACT 2002+ method. It is important to note that the values presented for PM2.5 here are only from end stage usage thus there is no double accounting issue with the PM emission reported in the same table. b  The amount of external costs saved annually due to emission reductions of each pollutant is also presented in Table 4.4. In the current analysis, it is assumed that all wood has neutral CO2 emission because the CO2 released is equal to the amount of CO2 captured during the growth of trees. Therefore, biogenic CO2 is assumed to have no external cost for a conservative estimation. However, since there is still a cost associated with biogenic CH4 and due to the drastic decrease in biogenic CH4, there is a net reduction in external cost of $1,471,000 CAD for all CH4 even though there is an increase in generic CH4 emission. The same trend is observed for CO and PM where there are net reductions in external cost due to the change in emissions of these pollutants. Overall, $759,594,000 CAD can be saved in externality per year if all firewood utilized in current BC residential heating practices is replaced with wood pellets. To generate the same amount of heat as currently generated with firewood, it is calculated that 667,000 tonnes of pellets are required in total. This means that for every tonne of additional pellet used annually, $1,140 CAD can be saved in external cost. Also, it is noted that the demand is much less than the current 1.2 million tonnes annual pellet production rate in BC.  67  80%  80%  60%  60%  40%  40%  20%  20%  0%  0%  a  Combustion Upstream  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  100%  CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O CO CO, biogenic NMVOC NOX SOX PM  100%  b  Figure 4.1: Stage-wise emission distribution for BC residential heating in the a) current firewood and b) wood pellet scenarios Figure 4.1 reveals how the fuel production, denoted as "Upstream", and fuel end usage, denoted as "Combustion", contribute to the emissions of each type of pollutant. Note that the PM columns in Figure 4.1 refer to "All PM" in Table 4.4. As expected, wood pellet has more upstream emissions when compared to firewood because of the need for electricity in sawmills and pellet plants. Furthermore, the use of wood residue in pellet plants adds to the biogenic emissions and PM emissions substantially. On the other hand, firewood only requires diesel to power the equipment for harvesting, chopping and transportation. Although according to GHGenius, some biogenic CO2 emissions do arise from the production of diesel but they ultimately contribute much less than 1% throughout the entire life cycle of the firewood burning scenario. Lastly, since both fuels are biomass, all the CO2, CH4 and CO emissions are considered biogenic during the end usage. The numeric values used for the graphing of Figure 4.1 are included in Appendix E. Moreover, the emission data categorized by appliance type instead of processing stages is also presented for both scenarios in the Appendix E.  68  1.4x10  4  1.2x10  4  1.0x10  8.0x103 6.0x103 4.0x103 2.0x103 0.0  Firewood  Climate change (kt CO2-equivalent)  1.4x107 1.2x107 1.0x107 8.0x106 6.0x106 4.0x106 2.0x106  Firewood  Pellets Combustion Upstream  250  c  200  150  100  50  0  b  1.6x107  0.0  Pellets  Firewood  Pellets  Primary energy consumption (TJ)  Human health (DALY)  4  . .  1.6x10  1.8x107  Ecosystem quality (PDF m2 yr)  a  4  d  2.5x104 2.0x104 1.5x104 1.0x104 5.0x103 0.0  Firewood  Pellets  Figure 4.2: Stage-wise impacts on a) human health, b) ecosystem quality, c) climate change, and d) primary energy consumption for the current and wood pellet scenarios of BC residential heating Figure 4.2 summarizes the impact of the firewood and pellet scenarios on human health, ecosystem quality and climate change. The sources of impacts, divided into "Upstream" and "Combustion", are also illustrated. Moreover, the primary energy consumption for both scenarios is also presented as Figure 4.2d. Replacing firewood with wood pellets proves to lower impacts on all aspects considered in this study. For human health, by switching to pellets there is a small increase in the upstream impact. However, the substantially lower impact 69  during the combustion stage, mainly due to the reduction in PM2.5 emission, results in an overall decrease of 95% in human health impact. Similar patterns can be detected in both ecosystem quality and climate change impacts where the upstream impact suffers a small increase but overall there is a decrease in impact due to emissions avoided in the combustion stage. Whereas the reduction of impact on human health and ecosystem quality can be attributed to lowered emissions, the reduction of impact on climate change and primary energy consumption is related to higher equipment efficiency. In order to generate 11,066 TJ of heat in the current scenario, 25,983 TJ of primary energy is required as compared to only 17,144 TJ for the pellet scenario. The numeric values used for the graphing of Figure 4.2 are included in Appendix E. Moreover, the impact data grouped by appliance type instead of processing stages is also presented for both scenarios in the Appendix E. In order to evaluate if it is economical from a BC resident's point of view to switch from a firewood-burning unit to its pellet counterpart, a simple economic analysis is performed. The economic analysis is performed for two cases. The first case is for an owner to purchase pellets by bulk while the second case is for the owner to purchase bagged pellets of approximately 18 kg each. Results from the economic analysis are summarized in Table 4.5 for a single unit of each type of appliance. In Table 4.5, the annual fuel costs for pellets are based on the current amount of heat produced from a single unit of the listed type of appliances. The percent increase on fuel cost indicates how the annual pellet cost compares to annual firewood cost. A positive value means that there is an increase in fuel cost by switching to wood pellets whereas a negative value indicates that the user saves on fuel cost when switching to wood pellets. From Table 4.5, it is apparent that all users will save on fuel cost by replacing firewood with wood pellets. The savings ranges from 50% to 94% when bulk pellets are used or 9% to 89% when bagged pellets are utilized. This is not a surprise since wood pellets burn much more efficiently, resulting in a reduction in fuel cost. Appliances with low efficiency, such as the conventional fireplace, would benefit the most from fuel cost saving when switched to wood pellets. 70  However, it is often required to have equipment replaced when a different fuel is to be used, which thus requires the inclusion of capital investment in the economic analysis. After taking into account the annualized capital cost of the pellet-equivalent unit, the total annualized cost for switching from firewood to wood pellets is obtained, as presented in Table 4.5. By comparing the annualized total cost between wood pellets scenario and the firewood scenario (assuming that the firewood burning unit was bought a long time ago thus its capital cost is neglected) one can see that switching to wood pellet would result in a lower annualized cost for all appliances except for the owners of fireplace inserts and unspecified boilers when pellets are to be bought in bulk. If bagged pellets are to be utilized, switching to wood pellets would only be economical for owners of conventional fireplaces, masonry heaters and outdoor boilers.  71  Bagged  Bulk  Fireplace Annual fuel cost ($CAD) Percent increase on fuel cost (%) Annual cost for unit and fuel ($CAD) Percent increase on annual cost (%) Payback period (year) Net present value ($CAD) Annual fuel cost ($CAD) Percent increase on fuel cost (%) Annual cost for unit and fuel ($CAD) Percent increase on annual cost (%) Payback period (year) Net present value ($CAD)  Central Furnace  Fireplace Insert  Conventional  Catalytic  Advanced  Conventional  Catalytic  Advanced  unspecified  Outdoor  Indoor  Masonry  Conventional  Advanced  Table 4.5: Summary of Simple Economic Analysis for Switching from Firewood to Wood Pellets Appliances Utilizing Bulk or Bagged Wood Pellets  Wood stove  $331  $50  $843  $727  $582  $298  $215  $284  $65  $509  $606  $416  -63  -94  -64  -52  -76  -72  -53  -52  -88  -52  -50  -60  $880  $600  $1,393  $1,485  $1,339  $1,055  $765  $834  $614  $997  $1,094  $904  -2  -27  -41  -2  -44  0  66  41  17  -7  -10  -14  6.48  4.79  2.41  6.46  2.80  6.72  15.04  12.00  7.98  5.85  5.37  5.19  $130  $1,479  $6,580  $200  $7,084  -$8  -$2,043  -$1,627  -$585  $481  $815  $962  $604  $92  $1,541  $1,329  $1,063  $544  $393  $520  $118  $931  $1,108  $760  -33  -89  -35  -12  -56  -48%  -15  -12  -78  -13  -9  -27  $1,154  $642  $2,090  $2,087  $1,821  $1,302  $943  $1,070  $668  $1,419  $1,596  $1,248  28  -22  -12  38  -24  23  105  81  27  33  31  19  12.48  5.06  4.43  27.37  3.82  9.97  54.87  51.35  9.02  23.73  30.45  11.40  -$1,706  $1,200  $1,898  -$3,838  $3,853  -$1,662  -$3,238  -$3,207  -$944  -$2,349  -$2,553  -$1,348  72  The NPV is also given in Table 4.5. Generally, the appliances with a negative "percent increase on annual cost" will have a positive NPV, indicating that the investment is economically viable. Furthermore, the NPV is directly correlated to the payback period, with a positive NPV for appliances with less than 6.7 years of payback period. It is important to explain how both indoor and outdoor boilers result in positive NPV for bulk pellets while unspecified boilers have a negative NPV. To understand this result, one must keep in mind that the economic analysis does not only rely on the type of appliances and its properties, such as efficiency and the cost of the pellet-equivalent units, but also on the usage pattern of the current appliance. For instance, if a type of unit is used very often and consumes a large amount of firewood then the fuel cost saving generated from switching to wood pellets would be greater and would pay back the capital investment faster. The usage patterns of the various types of appliances are provided in the survey data analyzed. This simple economic analysis reveals that for conventional fireplace, masonry heater and outdoor boiler, switching to wood pellet, whether bulk or bagged, would be a good choice from an economical point of view, while owners of any type of fireplace inserts and unspecified boilers may not consider switching to wood pellets, whether bulk or bagged, unless some incentives or subsidies are provided.  4.4  CONCLUSIONS  Replacement of firewood by wood pellets in BC residential heating will substantially reduce the impacts on human health, ecosystem quality, climate change and primary energy consumption. Although there is a slight increase of impact from upstream processing, more efficient and cleaner burning of wood pellets yield an overall decline in all impact categories. Annual human health impact dropped by 95% while ecosystem quality impact can be reduced by 27% and climate change impact can be lowered by 17%. As for primary energy consumption, 25,983 TJ of primary energy is required in the current scenario but only 17,144 TJ is needed for the pellet scenario. Savings in external costs per year are totalled at $759,594,000 CAD if all wood burning units in BC for residential heating are replaced by their pellet-counterparts. For every additional tonne 73  of pellets burned per year for residential heating in BC, $1,140 CAD in external cost can be avoided. The simple economic analysis performed indicated that current users of wood burning units will save from 50 to 94% or 9 to 89% on fuel cost for bulk or bagged pellets, respectively. However, when the capital investment for the pellet appliances is also considered, owners of any type of fireplace inserts and unspecified boilers may not want to switch to pellet appliances without additional incentives/subsidies. Furthermore, if users plan to purchase bagged pellets, only owners of conventional fireplaces, masonry heaters and outdoor boilers may consider switching to pellet appliances. Lastly, it is important to acknowledge that the economic analysis performed depends on not only the efficiency and cost of the appliances considered but also the average amount of fuel used in each type of appliance on a yearly basis. The latter information was extracted from the survey data used for this study and it consequently influences the result of the economic analysis as units that are used more often to generate more heat would require more fuel which results in greater savings in fuel costs. This study reveals that switching from firewood to wood pellets at BC holds great potential in lowering the impacts on human health, ecosystem quality, climate change and primary energy consumption. The external cost calculation also indicates that government incentives may be introduced to encourage local residents to switch to pellet appliances in order to make the switch economically attractive. Nonetheless, if wood pellets are to become a popular residential heating fuel, like they are in many European countries, their supply and distribution logistics need to be further improved, especially in terms of implementing bulk deliverance of pellets to residential users in order to avoid the expensive packaging operation.  74  5  CONCLUSIONS  BC wood pellets are exported to various countries such as the United Kingdom, Sweden, the Netherlands, and Japan in large amounts annually to be utilized in various energy applications. However, the environmental footprint of BC pellets, once arriving at its destination, is unclear. An in-house BC wood pellets LCI database was compiled to answer this question. The database was constructed using published energy consumption data on harvesting and sawmill processing practices in Western Canada and Canada, respectively. Transportation logistics, pellet plant processing and port operation data were collected from an industrial survey distributed in British Columbia. Compared to the currently available literature, this study refines the database and analysis by utilizing actual industrial data for the pellet plant processing stage and more updated emission factors. Other key improvements are the inclusion of primary energy consumption, more detailed logistic scheme, moisture content calculation and analysis, and a more extensive LCIA with the help of commercial LCA software. The in-house LCI database was able to quantify the energy quality, in terms of content and composition, and various impacts, including those on human health, ecosystem quality and climate change, of BC pellets that are exported to Rotterdam. Comparisons between exported BC pellets and BC pellets for domestic applications were also made. This database enables one to understand how sustainable exported wood pellets actually are. Although the life cycle of BC wood pellets combustion in Rotterdam emits only 15.9 kg of CO2-equivalent for every GJ utilized compared to 99.1, 87.3, 93.9 and 56.6 for coal, heavy fuel, diesel and natural gas combustion, respectively, BC pellet’s GHG emission can be further reduced to 7.9 kg of CO2equivalent if they stay in BC for domestic application. Furthermore, impacts associated with human health and ecosystem quality can also be reduced by at least 60% each. In light of this discovery, case studies on the domestic applications of BC wood pellets were performed to explore the possibility of future domestic applications of these pellets. Moreover, this LCI database allows for future analysis of different energy systems involving BC wood pellets, such as pellet and coal co-firing practices in UK or Japan for electricity generation or the utilization of BC wood pellets in other Canadian provinces. 75  The UBC district heating case study reveals that by switching from natural gas combustion to wood pellet gasification, the annual GHG emission can be reduced by 83% from the original 56.7 kt of CO2-equivalent per year. Moreover, if emission control units are used in the wood pellet gasification system, the savings in annual external costs would be $671,000 CAD and all emissions would be significantly lower than the Metro Vancouver air emission limits for biomass boilers. However, compared to the base scenario, the impacts in human health and ecosystem quality would increase by 3.7 and 2.5 fold respectively for controlled pellet gasification. Comparing between emission-controlled wood waste and wood pellet gasification systems, the wood waste gasification system has slightly lower external costs, human health and ecosystem quality impact over the entire life cycle since wood waste requires less processing. However, due to lower thermal efficiency, the overall primary energy consumption for wood waste scenario is higher. Moreover, when looking into end stage emissions only, as they are directly related to the air quality of the local community, controlled wood pellet gasification would result in a mere 12% increase in human health impact while the wood waste scenario would yield a 133% increase from the base scenario. This case study reveals that switching to woody biomass gasification is an effective way to reduce GHG emission -- an important goal of UBC, but it comes with the disadvantages of higher impacts on the ecosystem and human health. Comparing between wood pellet and wood waste, wood pellet is the better choice as the resultant increase in local air quality is significantly lower than that of wood waste gasification. Results from this case study provide some insights that should be considered when implementing a biomass gasification facility on UBC campus. The case study on BC residential heating looks into the effects of replacing current firewood combustions in residential heating by wood pellet combustions. The result of the study confirms that human health, ecosystem quality, and climate change impacts can be reduced by 95%, 27%, and 17%, respectively. The amount of primary energy consumption can also be reduced by 34%. Furthermore, the total possible savings in external costs would be $760,000,000 CAD annually, which is equivalent to $1,140 CAD in external costs saved for every additional tonne of pellets burned per year in place of firewood. The economic analysis performed also revealed that owners of any type of fireplace inserts and unspecified boilers 76  may not want to switch to pellet appliances without additional incentives/subsidies. Furthermore, if users plan to purchase bagged pellets, only owners of conventional fireplaces, masonry heaters and outdoor boilers should consider switching to pellet appliances. The results from this case study indicate that air quality can be improved significantly and GHG emissions can be reduced if wood pellets are used in place of firewood for BC residential heating. The external costs savings and the values from the economic analysis can provide a basis for an incentive program urging people to switch from firewood to wood pellets. The two case studies utilized the LCI database established to evaluate two possible domestic applications of BC wood pellets. The LCA result reveals that the UBC district heating system is an effective way to reduce GHG emissions but disadvantages associated with this reduction may make this application undesirable. The case study on wood pellet replacing firewood for BC residential heating shows that there will be a slight GHG reduction but significant reductions in human health impact and external costs. The economic analysis performed also indicates that switching to wood pellet is economical for end users in many cases. Replacing firewood with wood pellets for BC residential heating appears to be a desirable application and the economic analysis performed provides a basis for the planning of an incentive program. In terms of data collection for the BC wood pellet LCI database, currently only three sets of industrial survey data are incorporated in the LCI database. Inclusion of more data would be beneficial. A more detailed and recent harvesting energy consumption profile would also be an essential improvement as this study exposes the harvesting stage as the main contributor to all impact categories for non-exported BC pellets. For the first case study performed, the emission factors for pellet gasification were estimated based on literature values of the emission factors for wood waste, wood pellet combustion and the wood waste gasification emission factors from the industry. Measured wood pellet gasification emission factors would greatly improve the validity of the result. For the BC residential heating case study, the main limitations lie in the data collected. These include the age of the data and the assumption that all units consume the same amount of fuel 77  in GVRD and FVRD since appliance-specific fuel consumption data were not available in the “2002 GVRD Residential Wood Burning Survey”. In the methodology aspect, limitations of the current study include the exclusion of emissions and impacts associated with land usage and infrastructure in the LCI database. Land usage is not included because most of the forests in BC that are being harvested were previously forest as well while the inclusion of infrastructure would likely raise the emissions and impacts by roughly 5%. However, future projects looking into the burdens of land changes and infrastructure would make this LCI database more complete. Another major limitation lies in the method chosen for LCIA. The human health impact indicator in IMPACT 2002+ uses the unit of DALY and the parameters used for the compilation of the impact in this category are all calculated at a continental level for Western Europe. Therefore, the final values to be presented here only serve as indicators for scenario comparisons as the absolute values do not capture the geographical and ecological differences in Western Canada and Western Europe. Overall, all current impact assessment methods associated with human health contain more uncertainties than ideal thus the numbers presented should just be used for comparison on a relative basis. The methodology behind the derivation of the DALY unit itself also contains uncertainties and raises controversies. Lastly, the location and time frame of emissions were also not taken into account in the LCI database and the case studies. These should be considered in future projects as both of these factors are gaining awareness in recent LCA practices and should be accounted for if possible. Furthermore, if future LCA were to be performed for policy making, such as to promote pellet utilization in Canada, a consequential LCA, as opposed to an attributional LCA as performed in this study, should be carried out. Consequential LCA requires much more complex modeling which involves information such as demand and supply curve shifts that may be caused by policy implementation. Due to the greater amount of information built into a consequential LCA, indirect changes and effects can often be better captured with consequential LCA. However, it should be noted that presently, there is no strict guideline or solid framework for conducting a consequential LCA.  78  REFERENCES Accredited Laboratory. (2007). Certificate of analysis. Accredited Laboratory. Aldrete, G., Anderson, B., Durham, C., Kristiansson, J., Obluda, M., & Wells, S. (2005). Evaluation of low sulfur marine fuel availability – Pacific Rim. Starcrest Consulting Group, LLC. 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Environmental Science & Technology, 44(1), 538-544. doi:10.1021/es902555a  89  APPENDIX A – MODELING OF OFF-GAS EMISSIONS FROM WOOD PELLETS DURING MARINE TRANSPORTATION  90  91  92  93  94  95  96  97  98  APPENDIX B – EMISSION FACTORS AND PRIMARY ENERGY CONSUMPTIONS FOR VARIOUS ENERGY PRODUCTS Table B.1: Emission Factors for electricity generation and distribution Contributi on to BC electricity Fuel to electricity efficiency  Fuel oil  Natural gas (boiler)  Natural gas (turbine)  Biomass  Hydro  0.10%  3.66%  3.66%  1.44%  91.14%  45%  42%  42%  15.21%  100%  Upstream  Downstream  Total  Upstream  Downstream  Total  Upstream  DownUpDownTotal stream stream stream a (kg/ MJ of electricity distributed)  CO2, fossil  4.50E-2  1.94E-1  2.39E-1  1.03E-2  1.34E-1  1.44E-1  1.03E-2  1.21E-1  1.31E-1  2.12E-3  -  CO2, biogenic  1.39E-3  -  1.39E-3  1.89E-4  -  1.89E-4  1.89E-4  -  1.89E-4  3.54E-6  CH4 CH4, biogenic N2O  2.83E-4  2.19E-6  2.85E-4  1.71E-4  2.61E-6  1.73E-4  1.71E-4  8.93E-6  1.79E-4  -  -  -  -  -  -  -  -  2.18E-6  3.60E-8  2.22E-6  2.88E-7  9.43E-8  3.83E-7  2.88E-7  CO CO, biogenic NMVOC  3.03E-5  3.91E-5  6.94E-5  1.40E-5  9.52E-5  1.09E-4  -  -  -  -  -  2.22E-5  6.28E-6  2.85E-5  4.84E-6  NOX  1.13E-4  1.97E-4  3.10E-4  5.48E-5  SOX  7.95E-5  6.72E-4  7.51E-4  1.44E-5  Upstream  Downstream  Total  2.12E-3  -  1.51E-3  1.51E-3  1.17E-2  6.97E-1  6.97E-1  -  -  -  1.00E-2  2.33E-6  -  2.33E-6  -  9.05E-5  9.05E-5  9.57E-5  -  3.25E-9  3.51E-5  3.52E-5  -  -  -  5.05E-7  3.11E-6  3.40E-6  2.06E-7  1.56E-5  1.58E-5  -  -  -  3.67E-7  1.40E-5  8.51E-5  9.91E-5  8.32E-5  -  8.32E-5  -  -  -  8.89E-6  -  -  -  -  1.13E-9  1.00E-3  1.00E-3  -  -  -  1.44E-5  9.86E-6  1.47E-5  4.84E-6  1.58E-6  6.42E-6  3.53E-5  3.01E-5  6.54E-5  -  -  -  1.74E-6  1.78E-4  2.33E-4  5.48E-5  1.86E-4  2.41E-4  2.14E-5  3.68E-4  3.90E-4  -  -  -  2.32E-5  1.41E-6  1.58E-5  1.44E-5  1.27E-6  1.57E-5  4.15E-6  3.61E-4  3.65E-4  -  -  -  7.16E-6  1.23E-5 1.09E-4 1.21E-4 9.32E-7 1.09E-4 For the sources of these emission factors, please refer to Table 2.1  1.10E-4  9.32E-7  1.09E-4  1.10E-4  2.22E-6  1.09E-4  1.11E-4  -  1.09E-4  1.09E-4  1.09E-4  Pollutant  PM a  BC electric ity mix  Total  Table B.2: Emission Factors for Natural Gas Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO2, fossil  5.59E-02  4.35E-03  5.16E-02  CO2, biogenic  7.98E-05  7.98E-05  -  99  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CH4  7.32E-05  7.22E-05  9.89E-07  CH4, biogenic  -  -  -  N2O  1.07E-06  1.22E-07  9.46E-07  CO  5.93E-06  5.93E-06  0.00E+00  CO, biogenic  -  -  -  NMVOC  4.42E-06  2.05E-06  2.36E-06  NOX  2.32E-05  2.32E-05  0.00E+00  SOX  6.35E-06  6.09E-06  2.58E-07  PM  3.66E-06  3.95E-07  3.27E-06  Table B.3: Emission Factors for Heavy Fuel Oil Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO2, fossil  8.62E-02  1.57E-02  7.05E-02  CO2, biogenic  4.75E-04  4.75E-04  -  CH4  1.22E-04  1.20E-04  2.82E-06  CH4, biogenic  -  -  -  N2O  9.77E-07  6.67E-07  3.10E-07  CO  2.48E-05  1.07E-05  1.41E-05  CO, biogenic  -  -  -  NMVOC  8.62E-06  7.83E-06  7.89E-07  NOX  1.76E-04  4.39E-05  1.33E-04  SOX  4.78E-04  2.22E-05  4.56E-04  PM  3.87E-05  3.73E-06  3.50E-05  Table B.4: Emission Factors for Heavy Fuel Oil for Marine Transportation Pollutant  Total emissions (for transportation (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ output)  CO2, fossil  8.38E-02  1.57E-02  1.72E-01  Combustion emissions (kg/MJ input) 6.80E-02  CO2, biogenic  4.75E-04  4.75E-04  -  -  CH4  1.28E-04  1.20E-04  2.17E-05  8.56E-06  CH4, biogenic  -  -  -  -  100  Pollutant  Total emissions (for transportation (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ output)  N2O  2.64E-06  6.67E-07  5.00E-06  Combustion emissions (kg/MJ input) 1.98E-06  CO  1.64E-04  1.07E-05  3.89E-04  1.54E-04  CO, biogenic  -  -  -  -  NMVOC  7.37E-05  7.83E-06  1.67E-04  6.58E-05  NOX  2.03E-03  4.39E-05  5.03E-03  1.99E-03  SOX  4.83E-04  2.22E-05  1.17E-03  4.61E-04  PM  2.08E-04  3.73E-06  5.17E-04  2.04E-04  Table B.5: Emission Factors for Low sulphur Heavy Fuel Oil for Marine Transportation Pollutant  Total emissions (kg/tkm)  CO2, fossil  9.09E-03  1.71E-03  7.38E-03  Reduction during combustion compared to normal HFO (%) 0  CO2, biogenic  5.15E-05  5.15E-05  -  NA  CH4  1.39E-05  1.30E-05  9.28E-07  NA  CH4, biogenic  -  -  -  NA  N2O  2.87E-07  7.23E-08  2.14E-07  NA  a  Upstream emissions (kg/tkm)  a  Combustion emissions (kg/tkm)  a  CO  1.78E-05  1.16E-06  1.67E-05  NA  CO, biogenic  -  -  -  NA  NMVOC  7.99E-06  8.50E-07  7.14E-06  NA  NOX  2.20E-04  4.77E-06  2.15E-04  0  SOX  2.99E-05  2.41E-06  2.75E-05  45  PM  1.86E-05  4.05E-07  1.82E-05  18  a b  b  Fuel efficiency for marine vessel is 0.108 MJ HFO/tkm (Delucchi & Levelton, 2010) and dead weight tonnage, dwt, is 58,844 (The Chamber of Shipping, 2007) For PM10  Table B.6: Emission Factors for Middle Distillates Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO2, fossil  9.06E-02  2.01E-02  7.05E-02  CO2, biogenic  6.20E-04  6.20E-04  -  CH4  1.30E-04  1.26E-04  3.43E-06  CH4, biogenic  -  -  -  101  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  N2O  1.13E-05  9.73E-07  1.03E-05  CO  4.22E-04  1.35E-05  4.08E-04  CO, biogenic  -  -  -  NMVOC  1.95E-04  9.92E-06  1.85E-04  NOX  1.95E-03  5.04E-05  1.90E-03  SOX  1.60E-04  3.55E-05  1.25E-04  PM  1.39E-04  5.51E-06  1.33E-04  Table B.7: Emission Factors for Middle Distillates for Train a  Total emissions (kg/RTK)  CO2, fossil  2.03E-02  4.60E-03  1.57E-02  CO2, biogenic  1.42E-04  1.42E-04  -  CH4  2.98E-05  2.89E-05  8.86E-07  CH4, biogenic  -  -  -  N2O  6.72E-06  2.23E-07  6.49E-06  CO  3.48E-05  3.09E-06  3.17E-05  CO, biogenic  -  -  -  NMVOC  1.29E-05  2.27E-06  1.06E-05  NOX  2.83E-04  1.15E-05  2.71E-04  SOX  1.32E-05  8.13E-06  5.03E-06  PM  1.09E-05  1.26E-06  9.65E-06  a  Upstream emissions (kg/RTK)  a  Pollutant  Combustion emissions (kg/RTK)  a  Fuel efficiency for train is 0.229 MJ of diesel/RTK (total revenue tonne∙km) (Railway Association of Canada, 2008)  Table B.8: Emission Factors for Propane Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO2, fossil  7.53E-02  1.60E-02  5.94E-02  CO2, biogenic  4.29E-04  4.29E-04  -  CH4  1.21E-04  1.20E-04  9.50E-07  CH4, biogenic  -  -  -  N2O  4.98E-06  7.09E-07  4.28E-06  CO  2.62E-05  1.10E-05  1.52E-05  102  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO, biogenic  -  -  -  NMVOC  1.44E-05  1.21E-05  2.38E-06  NOX  1.38E-04  4.80E-05  9.03E-05  SOX  3.25E-05  3.21E-05  4.75E-07  PM  6.65E-06  3.80E-06  2.85E-06  Table B.9: Emission Factors for Wood Waste Combustion for Energy in Sawmill and Pellet plant a  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (kg/MJ)  CO2, fossil  -  -  -  CO2, biogenic  9.17E-02  -  9.17E-02  CH4  0.00E+00  -  -  CH4, biogenic  9.03E-06  -  9.03E-06  N2O  5.59E-06  -  5.59E-06  CO  0.00E+00  -  -  CO, biogenic  2.58E-04  -  2.58E-04  NMVOC  7.31E-06  -  7.31E-06  NOX  9.46E-05  -  9.46E-05  SOX  1.07E-05  -  1.07E-05  PM  1.42E-04  -  1.42E-04  a  Upstream emissions are already accounted for in the wood pellet LCI database itself since the bone dry tonne ratio of wood residue to pellet is greater than 1  Table B.10: Emission Factors for Gasoline  a  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (g/km)  CO2, fossil  7.13E-02  2.22E-02  207.63  Combustion emissions (kg/MJ) 4.91E-02  CO2, biogenic  6.38E-04  6.38E-04  -  -  CH4  1.35E-04  1.30E-04  0.021  5.07E-06  CH4, biogenic  -  -  -  -  N2O  3.74E-06  1.17E-06  0.011  2.57E-06  CO  2.58E-03  1.49E-05  10.86  2.57E-03  CO, biogenic  -  -  -  -  NMVOC  9.34E-05  3.56E-05  0.244  5.78E-05  103  a  Pollutant  Total emissions (kg/MJ)  Upstream emissions (kg/MJ)  Combustion emissions (g/km)  NOX  1.06E-04  5.39E-05  0.218  5.16E-05  SOX  5.15E-05  3.61E-05  0.065  1.53E-05  PM  9.90E-06  6.51E-06  0.014  3.39E-06  a  Combustion emissions (kg/MJ)  Source for combustion emission factors: GHGenius Version 3.17 LDV Summary Sheet (as it is for trucks driven by foreman and supervisor on site so light duty)  Table B.11: Emission Factors for Middle Distillate for HDV Operation Pollutant  Total emissions (kg/tkm)  Upstream emissions (kg/tkm)  Vehicle operation (kg/tkm)  CO2, fossil  1.91E-01  4.30E-02  1.48E-01  CO2, biogenic  1.33E-03  1.33E-03  -  CH4  2.80E-04  2.71E-04  9.31E-06  CH4, biogenic  -  -  -  N2O  8.49E-06  2.09E-06  6.40E-06  CO  5.46E-05  2.90E-05  2.57E-05  CO, biogenic  -  -  -  NMVOC  3.67E-05  2.13E-05  1.54E-05  NOX  1.64E-04  1.08E-04  5.60E-05  SOX  8.65E-05  7.61E-05  1.04E-05  PM  1.45E-05  1.18E-05  2.74E-06  Table B.12: Emission Factors for Steam Generated for Chemical Processes with US Electricity (from Ecoinvent) Pollutant  Total Emission (kg/MJ steam produced)  CO2, fossil  9.534E-02  CO2, biogenic  4.801E-05  CH4  1.926E-04  CH4, biogenic  1.411E-07  N2O  7.295E-07  CO  1.496E-05  CO, biogenic  4.093E-07  NMVOC  2.825E-05  NOX  8.077E-05  SOX  1.673E-04  104  Pollutant  Total Emission (kg/MJ steam produced)  PM  1.069E-05  Table B.13: Upstream Emission Factors for Wood Waste Used for Electricity Generation Pollutant  Upstream emissions (kg/MJ)  CO2, fossil  3.23E-04  CO2, biogenic  5.38E-07  CH4  3.54E-07  CH4, biogenic  4.94E-10  N2O  3.13E-08  CO  1.27E-05  CO, biogenic  1.71E-10  NMVOC  5.37E-06  NOX  3.26E-06  SOX  6.31E-07  PM  3.38E-07  Table B.14: Primary Energy Consumption of Different Fuels and Materials Substance  Unit  Gasoline  MJ  Non-renewable energy (MJ) 1.2998  Renewable energy (MJ)  Total (MJ)  0.0332  1.3330  Energy production efficiency 75%  HFO/low-S HFO  MJ  Middle distillate  MJ  1.2158  0.0251  1.2409  81%  1.2738  0.0316  1.3054  77%  Natural gas  MJ  1.2308  0.0015  1.2323  81%  Propane  MJ  1.0987  0.0011  1.0998  91%  Residual wood at forest road (for electricity generation)  MJ  0.0055  1.0026  1.0081  99%  Plastic pellet bag  1  5.651  3.3739  9.0249  --  105  APPENDIX C – NUMERICAL VALUES FOR FIGURES IN CHAPTER 2 Table C.1: Stage-wise Emissions from Exported BC Pellets Pollutant  Harvesting operation (kg/t)  Sawmill operation (kg/t)  Pellet plant operation (kg/t)  Port operation (kg/t)  HDV (sawmill to pellet plant) (kg/t)  HDV (pellet plant to railhead) (kg/t)  Train (railhead to port) (kg/t)  CO2, fossil  6.24E+01  1.97E+01  8.33E+00  7.60E-01  7.87E+00  1.90E+01  1.71E+01  Marine transportation (Vancouver to Rotterdam) (kg/t) 1.51E+02  CO2, biogenic  4.27E-01  2.67E+01  1.02E+02  1.16E-01  5.46E-02  1.32E-01  1.19E-01  8.59E-01  1.30E+02  CH4  8.94E-02  4.46E-02  5.06E-02  2.03E-03  1.15E-02  2.78E-02  2.50E-02  2.32E-01  4.83E-01  CH4, biogenic  -  2.55E-03  9.81E-03  5.61E-06  -  -  -  -  1.24E-02  Total (kg/t)  2.86E+02  N2O  7.77E-03  2.28E-03  6.40E-03  7.22E-05  3.49E-04  8.42E-04  5.64E-03  4.78E-03  2.81E-02  CO  2.91E-01  2.17E-02  1.44E-02  7.55E-03  2.24E-03  5.42E-03  2.92E-02  2.97E-01  6.68E-01  CO, biogenic  -  7.26E-02  2.80E-01  1.60E-04  -  -  -  -  3.53E-01  NMVOC  1.34E-01  1.28E-02  1.33E-02  1.25E-03  1.51E-03  3.64E-03  1.08E-02  1.33E-01  3.11E-01  NOX  1.34E+00  1.23E-01  1.58E-01  1.09E-02  6.74E-03  1.63E-02  2.38E-01  3.67E+00  5.56E+00  SOX  1.10E-01  2.70E-02  1.89E-02  1.04E-03  3.56E-03  8.58E-03  1.11E-02  4.98E-01  6.79E-01  PM  9.56E-02  6.57E-02  2.07E-01  1.98E-03  5.98E-04  1.44E-03  9.17E-03  3.09E-01  6.91E-01  PM2.5  -  5.08E-04  -  -  -  -  -  -  5.08E-04  Table C.2: Stage-wise Emissions from BC Pellets Delivered to Port in North Vancouver Pellet plant operation (kg/t) 8.33E+00  Port operation (kg/t)  HDV (pellet plant to railhead) (kg/t)  Train (railhead to port) (kg/t)  Total (kg/t)  6.24E+01  Sawmill operation (kg/t) 1.97E+01  7.87E+00  1.90E+01  1.71E+01  1.34E+02  CO2, biogenic  4.27E-01  2.67E+01  1.02E+02  5.46E-02  1.32E-01  1.19E-01  1.29E+02  CH4  8.94E-02  4.46E-02  5.06E-02  1.15E-02  2.78E-02  2.50E-02  2.49E-01  CH4, biogenic  -  2.55E-03  9.81E-03  -  -  -  1.24E-02  Pollutant  Harvesting operation (kg/t)  CO2, fossil  N2O  7.77E-03  2.28E-03  6.40E-03  3.49E-04  8.42E-04  5.64E-03  2.33E-02  CO  2.91E-01  2.17E-02  1.44E-02  2.24E-03  5.42E-03  2.92E-02  3.64E-01  CO, biogenic  -  7.26E-02  2.80E-01  -  -  -  3.53E-01  NMVOC  1.34E-01  1.28E-02  1.33E-02  1.51E-03  3.64E-03  1.08E-02  1.76E-01  106  1.34E+00  Sawmill operation (kg/t) 1.23E-01  Pellet plant operation (kg/t) 1.58E-01  SOX  1.10E-01  2.70E-02  PM  9.56E-02  6.57E-02  PM2.5  -  5.08E-04  Pollutant  Harvesting operation (kg/t)  NOX  Port operation (kg/t)  HDV (pellet plant to railhead) (kg/t)  Train (railhead to port) (kg/t)  Total (kg/t)  6.74E-03  1.63E-02  2.38E-01  1.88E+00  1.89E-02  3.56E-03  8.58E-03  1.11E-02  1.79E-01  2.07E-01  5.98E-04  1.44E-03  9.17E-03  3.79E-01  -  -  -  -  5.08E-04  Table C.3: Stage-wise Impacts from Exported and Non-exported BC Wood Pellets (impact/tonne of wood pellets) Impact Category  Export  Human Health (DALY) 2  Ecosystem Quality (PDF*m *yr) Climate Change (kg CO2-eqv) Primary Energy Consumption (MJ)  Harvesting operation  Sawmill operation  Pellet plant operation  Port operation  HDV (sawmill to pellet plant)  HDV (pellet plant to railhead)  Train (railhead to port)  1.48E-04  2.81E-05  6.32E-05  1.49E-06  9.36E-07  2.26E-06  2.39E-05  Marine transportati on (North Vancouver to Rotterdam) 4.26E-04  Local  1.48E-04  2.81E-05  6.32E-05  -  9.36E-07  2.26E-06  2.39E-05  -  Export  7.76  0.73  0.92  6.34E-02  4.22E-02  1.02E-01  1.37  21.46  Local  7.76  0.73  0.92  -  4.22E-02  1.02E-01  1.37  -  Export  64.67  20.37  9.75  7.97E-01  8.00  19.31  18.17  154.28  Local  64.67  20.37  9.75  -  8.00  19.31  18.17  -  Export  20325  837  1725  24  115  277  251  2243  Local  20325  837  1725  -  115  277  251  -  107  APPENDIX D – NUMERICAL VALUES FOR FIGURES IN CHAPTER 3 Table D.1: Upstream Emission Factors of Wood Waste and Wood Pellets Delivered to UBC Pollutant  Wood waste at 60% moisture content, wet basis (kg/tonne)  Wood pellet (kg/tonne)  CO₂, fossil  8.14E+01  1.38E+02  CO₂, biogenic  9.48E+00  1.30E+02  CH₄  1.21E-01  2.55E-01  CH₄, biogenic  8.58E-04  1.24E-02  N₂O  8.55E-03  2.34E-02  CO  1.75E-01  3.65E-01  CO, biogenic  2.44E-02  3.53E-01  NMVOC  8.37E-02  1.77E-01  NOₓ  8.36E-01  1.89E+00  SOₓ  8.60E-02  1.81E-01  PM  7.29E-02  3.80E-01  PM2.5  3.91E-03  5.08E-04  Table D.2: UBC Boiler House Current Emissions Pollutant  NG upstream (kg/yr)  Oil upstream (kg/yr)  NG combustion (kg/yr)  Oil combustion (kg/yr)  Total (kg/yr)  CO₂, fossil  4.50E+06  1.23E+05  5.07E+07  5.71E+05  5.59E+07  CO₂, biogenic  8.26E+04  3.73E+03  -  -  8.63E+04  CH₄  7.47E+04  938  103  -  7.57E+04  CH₄, biogenic  -  -  -  -  -  N₂O  126  5.23  1.60E+03  57  1.79E+03  CO  6.13E+03  83.8  3.32E+03  121  9.65E+03  CO, biogenic  -  -  -  -  -  NMVOC  2.12E+03  61.4  3.10E+03  118  5.40E+03  NOₓ  2.40E+04  345  1.33E+04  360  3.80E+04  SOₓ  6.30E+03  175  -  1.75E+03  8.22E+03  PM  408  29  103  16  557  108  Table D.3: Stage-wise Emissions for Uncontrolled Wood Waste Gasification Scenario CO₂, fossil  Harvest operation (kg/yr) 4.04E+06  Sawmill operation (kg/yr) 8.32E+05  CO₂, biogenic  2.50E+04  1.13E+06  1.44E+08  3.07E+04  6.74E+03  1.46E+08  CH₄  5.45E+03  1.89E+03  -  6.47E+03  1.42E+03  1.52E+04  CH₄, biogenic  -  108  1.42E+04  -  -  1.43E+04  N₂O  466  96  8.81E+03  196  319  9.88E+03  CO  1.83E+04  919  -  1.26E+03  1.65E+03  2.21E+04  CO, biogenic  -  3.07E+03  2.30E+04  -  -  2.61E+04  NMVOC  8.55E+03  541  6.77E+03  847  612  1.73E+04  NOₓ  8.29E+04  5.23E+03  1.15E+05  3.79E+03  1.34E+04  2.21E+05  SOₓ  7.07E+03  1.14E+03  1.69E+04  2.00E+03  625  2.78E+04  PM  5.55E+03  2.78E+03  6.30E+04  336  518  7.22E+04  PM2.5  471  22  -  -  -  492  Pollutants  Gasification (kg/yr) -  HDV transportation (kg/yr) 4.42E+06  Train transportation (kg/yr) 9.65E+05  Table D.4: Stage-wise Emissions for Uncontrolled Wood Pellet Gasification Scenario Sawmill operation (kg/yr)  Pellet plant operation (kg/yr)  Gasification (kg/yr)  HDV transportation (kg/yr)  CO₂, fossil  Harvest operation (kg/yr) 4.01E+06  1.26E+06  5.35E+05  -  CO₂, biogenic  2.74E+04  1.72E+06  6.56E+06  CH₄  5.74E+03  2.86E+03  CH₄, biogenic  -  N₂O CO  Total (kg/yr) 1.03E+07  1.97E+06  Train transportation (kg/yr) 1.10E+06  8.88E+06  1.04E+08  1.37E+04  7.66E+03  1.13E+08  3.25E+03  -  2.89E+03  1.61E+03  1.64E+04  164  630  374  -  -  1.17E+03  499  146  411  3.12E+03  88  363  4.63E+03  1.87E+04  1.39E+03  927  -  563  1.88E+03  2.34E+04  CO, biogenic  -  4.66E+03  1.80E+04  1.50E+03  -  -  2.42E+04  NMVOC  8.62E+03  820  852  424  378  696  1.18E+04  NOₓ  8.61E+04  7.93E+03  1.02E+04  1.64E+04  1.69E+03  1.53E+04  1.38E+05  SOₓ  7.09E+03  1.73E+03  1.21E+03  -  892  710  1.16E+04  PM  6.14E+03  4.22E+03  1.33E+04  191  150  589  2.46E+04  PM2.5  -  33  -  -  -  -  33  Pollutant  Total (kg/yr)  109  Table D.5: Stage-wise Emissions for Controlled Wood Waste Gasification Scenario CO₂, fossil  Harvest operation (kg/yr) 4.04E+06  Sawmill operation (kg/yr) 8.32E+05  -  CO₂, biogenic  2.50E+04  1.13E+06  1.44E+08  3.07E+04  6.74E+03  1.46E+08  CH₄  5.45E+03  1.89E+03  -  6.47E+03  1.42E+03  1.52E+04  CH₄, biogenic  -  108  1.42E+04  -  -  1.43E+04  N₂O  466  96  8.81E+03  196  319  9.88E+03  CO  1.83E+04  919  -  1.26E+03  1.65E+03  2.21E+04  CO, biogenic  -  3.07E+03  2.30E+04  -  -  2.61E+04  NMVOC  8.55E+03  541  6.77E+03  847  612  1.73E+04  NOₓ  8.29E+04  5.23E+03  2.30E+04  3.79E+03  1.34E+04  1.28E+05  SOₓ  7.07E+03  1.14E+03  1.69E+04  2.00E+03  625  2.78E+04  PM  5.55E+03  2.78E+03  630  336  518  9.81E+03  PM2.5  471  22  -  -  -  492  Pollutant  Gasification (kg/yr)  HDV transportation (kg/yr) 4.42E+06  Train transportation (kg/yr) 9.65E+05  Total (kg/yr) 1.03E+07  Table D.6: Stage-wise Emissions for Controlled Wood Pellet Gasification Scenario Sawmill operation (kg/yr)  Pellet plant operation (kg/yr)  Gasification (kg/yr)  HDV transportation (kg/yr)  Train transportation (kg/yr)  Total (kg/yr)  CO₂, fossil  Harvest operation (kg/yr) 4.01E+06  1.26E+06  5.35E+05  -  1.97E+06  1.10E+06  8.88E+06  CO₂, biogenic  2.74E+04  1.72E+06  6.56E+06  1.04E+08  1.37E+04  7.66E+03  1.13E+08  CH₄  5.74E+03  2.86E+03  3.25E+03  -  2.89E+03  1.61E+03  1.64E+04  CH₄, biogenic  -  164  630  374  -  -  1.17E+03  N₂O  499  146  411  3.12E+03  88  363  4.63E+03  CO  1.87E+04  1.39E+03  927  -  563  1.88E+03  2.34E+04  CO, biogenic  -  4.66E+03  1.80E+04  1.50E+03  -  -  2.42E+04  NMVOC  8.62E+03  820  852  424  378  696  1.18E+04  NOₓ  8.61E+04  7.93E+03  1.02E+04  1.64E+04  1.69E+03  1.53E+04  1.38E+05  SOₓ  7.09E+03  1.73E+03  1.21E+03  -  892  710  1.16E+04  PM  6.14E+03  4.22E+03  1.33E+04  191  150  589  2.46E+04  PM2.5  -  33  -  -  -  -  33  Pollutant  110  Table D.7: Annual Impacts Associated with Base Scenario Natural gas upstream emission 2.59  Damage category Human health (DALY) 2  Oil upstream emission  Natural gas combustion  Oil combustion  Total  0.05  1.22  0.13  3.98  Ecosystem quality (PDF∙m ∙yr)  1.44E+05  2.15E+03  7.61E+04  3.87E+03  2.26E+05  Climate change (kg CO2-eqv)  5.05E+06  1.31E+05  5.10E+07  5.81E+05  5.67E+07  Primary energy consumption (MJ)  1.27E+09  9.73E+06  -  -  1.28E+09  External cost ($ CAD)  3.37E+05  7.45E+03  1.76E+06  2.88E+04  2.14E+06  Table D.8: Annual Impacts Associated with Uncontrolled Wood Waste Gasification Scenario Damage category  Harvest operation  Human health (DALY)  Sawmill operation  Gasification  HDV  Train  Total  9.41  1.19  25.76  0.53  1.35  38.24  Ecosystem quality (PDF∙m ∙yr)  4.81E+05  3.10E+04  6.75E+05  2.37E+04  7.73E+04  1.29E+06  Climate change (kg CO2-eqv)  4.18E+06  8.62E+05  1.43E+06  4.50E+06  1.03E+06  1.20E+07  2  Primary energy consumption (MJ)  1.63E+09  3.54E+07  -  6.46E+07  1.42E+07  1.75E+09  External cost ($ CAD)  7.25E+05  9.95E+04  1.53E+06  1.84E+05  1.18E+05  2.65E+06  Table D.9: Annual Impacts Associated with Uncontrolled Wood Pellet Gasification Scenario Harvest operation 9.50  Sawmill operation 1.81  Pellet plant operation 4.06  Ecosystem quality (PDF∙m ∙yr)  4.99E+05  4.71E+04  Climate change (kg CO2-eqv)  4.16E+06  Primary energy consumption (MJ)  1.31E+09  External cost ($ CAD)  7.34E+05  Damage category Human health (DALY) 2  Gasification  HDV  Train  Total  11.72  0.23  1.54  28.86  5.93E+04  4.68E+05  1.06E+04  8.79E+04  1.17E+06  1.31E+06  6.26E+05  4.88E+05  2.01E+06  1.17E+06  9.75E+06  5.38E+07  1.11E+08  -  2.88E+07  1.61E+07  1.52E+09  1.51E+05  2.56E+05  6.92E+05  8.20E+04  1.34E+05  2.05E+06  Table D.10: Annual Impacts Associated with Controlled Wood Waste Gasification Scenario Damage category Human health (DALY) 2  Harvest operation  Sawmill operation  Gasification  HDV  Train  Total  9.41  1.19  3.15  0.53  1.35  15.63  Ecosystem quality (PDF∙m ∙yr)  4.81E+05  3.10E+04  1.49E+05  2.37E+04  7.73E+04  7.62E+05  Climate change (kg CO2-eqv)  4.18E+06  8.62E+05  1.43E+06  4.50E+06  1.03E+06  1.20E+07  Primary energy consumption (MJ)  1.63E+09  3.54E+07  -  6.46E+07  1.42E+07  1.75E+09  External cost ($ CAD)  7.25E+05  9.95E+04  2.73E+05  1.84E+05  1.18E+05  1.40E+06  111  Table D.11: Annual Impacts Associated with Controlled Wood Pellet Gasification Scenario Damage category Human health (DALY) 2  Harvest operation  Sawmill operation  Pellet plant operation  Gasification  HDV  Train  Total  9.50  1.81  4.06  1.51  0.23  1.54  18.65  Ecosystem quality (PDF∙m ∙yr)  4.99E+05  4.71E+04  5.93E+04  9.35E+04  1.06E+04  8.79E+04  7.97E+05  Climate change (kg CO2-eqv)  4.16E+06  1.31E+06  6.26E+05  4.88E+05  2.01E+06  1.17E+06  9.75E+06  Primary energy consumption (MJ)  1.31E+09  5.38E+07  1.11E+08  -  2.88E+07  1.61E+07  1.52E+09  External cost ($ CAD)  7.34E+05  1.51E+05  2.56E+05  1.08E+05  8.20E+04  1.34E+05  1.46E+06  112  APPENDIX E – NUMERICAL VALUES FOR FIGURES IN CHAPTER 4 Table E.1: Emissions in Current (Firewood) Scenario by Appliance Types Fireplace (kg/yr) Adv. Convent tech. ional  Pollutant CO2, fossil CO2, biogenic CH4 CH4, biogenic N2O  Central furnace (kg/yr) Boiler Boiler Boiler (inside) (outside)  Fireplace insert (kg/yr) Adv. Convent Catalytic tech. ional  Wood stove (kg/yr) Adv. Convent Catalytic tech. ional  Masonry (kg/yr)  Pellet stove (kg/yr)  Total (kg/yr)  6.90E+6  4.16E+7  6.89E+6  3.45E+4  1.39E+6  6.25E+5  2.07E+5  2.05E+6  1.65E+7  5.15E+6  2.26E+7  1.31E+6  6.24E+6  1.11E+8  1.42E+8  8.58E+8  1.42E+8  7.12E+5  2.88E+7  1.29E+7  4.28E+6  4.23E+7  3.40E+8  1.06E+8  4.67E+8  2.70E+7  5.56E+7  2.23E+9  1.00E+4  6.04E+4  1.00E+4  5.01E+1  2.03E+3  9.07E+2  3.01E+2  2.98E+3  2.39E+4  7.47E+3  3.29E+4  1.90E+3  1.13E+4  1.64E+5  3.90E+5  2.35E+6  9.92E+5  4.97E+3  2.01E+5  6.86E+4  1.65E+4  4.22E+5  1.81E+6  4.09E+5  4.66E+6  1.04E+4  3.36E+4  1.14E+7  1.47E+4  8.85E+4  1.13E+4  5.68E+1  2.30E+3  1.03E+3  3.42E+2  3.38E+3  2.71E+4  8.48E+3  3.73E+4  2.15E+3  2.39E+3  1.99E+5  CO CO, biogenic NMVOC  1.25E+4  7.51E+4  1.24E+4  6.23E+1  2.52E+3  1.13E+3  3.74E+2  3.70E+3  2.98E+4  9.29E+3  4.09E+4  2.36E+3  1.09E+4  2.01E+5  6.66E+6  4.43E+7  6.47E+6  3.24E+4  1.31E+6  6.03E+5  2.00E+5  3.24E+6  1.59E+7  4.97E+6  3.11E+7  1.34E+6  2.73E+5  1.16E+8  1.42E+6  8.55E+6  5.48E+5  2.75E+3  1.11E+5  5.20E+4  2.15E+4  7.47E+5  1.37E+6  5.34E+5  8.25E+6  1.62E+5  1.72E+4  2.18E+7  NOX  1.88E+5  1.13E+6  1.88E+5  9.40E+2  3.80E+4  1.70E+4  5.65E+3  5.58E+4  4.49E+5  1.40E+5  6.17E+5  3.56E+4  9.34E+4  2.96E+6  SOX  2.52E+4  1.52E+5  2.52E+4  1.26E+2  5.09E+3  2.28E+3  7.58E+2  7.49E+3  6.02E+4  1.88E+4  8.27E+4  4.78E+3  1.25E+4  3.97E+5  PM  4.02E+3  2.42E+4  4.01E+3  2.01E+1  8.12E+2  3.64E+2  1.21E+2  1.19E+3  9.59E+3  3.00E+3  1.32E+4  6.00E+4  1.13E+4  1.32E+5  PM2.5  4.54E+5  1.05E+7  1.26E+6  6.30E+3  2.54E+5  4.11E+4  1.37E+4  3.82E+5  1.08E+6  3.39E+5  7.21E+6  -  3.29E+4  2.16E+7  Table E.2: Emissions in Current (Firewood) Scenario by Life Cycle Stages Pollutant  Upstream emission (kg/year)  Combustion emission (kg/yr)  Total (kg/yr)  CO2, fossil  1.11E+08  -  1.11E+08  CO2, biogenic  4.61E+06  2.22E+09  2.23E+09  CH4  1.64E+05  -  1.64E+05  CH4, biogenic  3.71E+02  1.14E+07  1.14E+07  N2O  8.25E+03  1.91E+05  1.99E+05  CO  2.01E+05  -  2.01E+05  CO, biogenic  1.05E+04  1.16E+08  1.16E+08  NMVOC  9.74E+04  2.17E+07  2.18E+07  113  Pollutant  Upstream emission (kg/year)  Combustion emission (kg/yr)  Total (kg/yr)  NOX  8.97E+05  2.06E+06  2.96E+06  SOX  1.02E+05  2.95E+05  3.97E+05  PM  7.25E+04  5.92E+04  1.32E+05  PM2.5  3.13E+01  2.16E+07  2.16E+07  Table E.3: Emissions in Wood Pellet Scenario by Appliance Types Pollutant  Pellet boiler (kg/yr)  CO2, fossil  1.74E+07  Pellet fireplace insert (kg/yr) 2.94E+07  9.24E+07  Existing pellet stove (kg/yr) 6.24E+06  CO2, biogenic  1.55E+08  2.62E+08  8.23E+08  5.56E+07  1.30E+09  CH4 CH4, biogenic  3.14E+04  5.31E+04  1.67E+05  1.13E+04  2.62E+05  7.54E+03  1.58E+05  4.97E+05  3.36E+04  6.97E+05  N2O  6.65E+03  1.13E+04  3.53E+04  2.39E+03  5.56E+04  Pellet stove (kg/yr)  Total (kg/yr) 1.45E+08  CO  3.03E+04  5.13E+04  1.61E+05  1.09E+04  2.53E+05  CO, biogenic  7.37E+05  1.29E+06  4.05E+06  2.73E+05  6.35E+06  NMVOC  3.14E+04  7.71E+04  2.55E+05  1.72E+04  3.80E+05  NOX  2.51E+05  4.41E+05  1.38E+06  9.34E+04  2.17E+06  SOX  3.48E+04  5.90E+04  1.85E+05  1.25E+04  2.91E+05  PM  8.28E+04  5.32E+04  1.67E+05  1.13E+04  3.14E+05  PM2.5  8.72E+01  1.55E+05  4.87E+05  3.29E+04  6.75E+05  Table E.4: Emissions in Wood Pellet Scenario by Life Cycle Stages Pollutant  Upstream emission (kg/year)  Combustion emission (kg/yr)  Total (kg/yr)  CO2, fossil  1.45E+08  -  1.45E+08  CO2, biogenic  9.05E+07  1.21E+09  1.30E+09  CH4  2.62E+05  -  2.62E+05  CH4, biogenic  8.66E+03  6.88E+05  6.97E+05  N2O  1.50E+04  4.06E+04  5.56E+04  CO  2.53E+05  -  2.53E+05  CO, biogenic  2.46E+05  6.10E+06  6.35E+06  NMVOC  1.30E+05  2.50E+05  3.80E+05  114  Pollutant  Upstream emission (kg/year)  Combustion emission (kg/yr)  Total (kg/yr)  NOX  1.20E+06  9.66E+05  2.17E+06  SOX  1.52E+05  1.39E+05  2.91E+05  PM  2.63E+05  5.14E+04  3.14E+05  PM2.5  7.29E+02  6.74E+05  6.75E+05  Table E.5: Annual Impacts Grouped by Appliance Types for Current (Firewood) Scenario Damage category  Human health (DALY) Ecosystem quality 2 (PDF∙m ∙yr) Climate change (kg CO2-eqv) Primary energy consumption (MJ) External cost ($ CAD)  Fireplace Advanc ed technol ogy 3.44E+0 2 1.10E+0 6 1.09E+0 7 1.65E+0 9 2.25E+0 7  Central furnace convent ional  Indoor  Unspeci fied  Outdoo r  7.50E+0 3 6.62E+0 6 6.59E+0 7 9.96E+0 9 3.78E+0 8  9.04E+0 2 1.10E+0 6 1.30E+0 7 1.65E+0 9 4.57E+0 7  4.53E+0 0 5.50E+0 3 6.50E+0 4 8.27E+0 6 2.29E+0 5  1.83E+0 2 2.22E+0 5 2.62E+0 6 3.34E+0 8 9.25E+0 6  Fireplace insert Advanc ed Catalyti technol c ogy 3.10E+0 1.03E+0 1 1 9.95E+0 3.30E+0 4 4 1.08E+0 3.34E+0 6 5 1.50E+0 4.97E+0 8 7 1.91E+0 6.39E+0 6 5  Convent ional 2.77E+0 2 3.26E+0 5 4.40E+0 6 4.91E+0 8 1.58E+0 7  Wood stove Advanc ed Catalyti technol c ogy 8.18E+0 2.56E+0 2 2 2.62E+0 8.19E+0 6 5 2.86E+0 8.27E+0 7 6 3.95E+0 1.23E+0 9 9 5.03E+0 1.59E+0 7 7  convent ional 5.14E+0 3 3.61E+0 6 4.86E+0 7 5.42E+0 9 2.63E+0 8  Masonr y  Pellet stove  Total  1.85E+0 1 2.08E+0 5 1.70E+0 6 3.13E+0 8 2.17E+0 6  3.49E+0 1 5.46E+0 5 6.85E+0 6 7.38E+0 8 2.15E+0 6  1.55E+0 4 1.73E+0 7 1.92E+0 8 2.59E+1 0 8.07E+0 8  Table E.6: Annual Impacts Grouped by Life Cycle Stages for Current (Firewood) Scenario Damage category  Upstream  Combustion  Total  1.03E+02  1.54E+04  1.55E+04  Ecosystem quality (PDF∙m ∙yr)  5.22E+06  1.21E+07  1.73E+07  Climate change (kg CO2-eqv)  1.14E+08  7.81E+07  1.92E+08  Primary energy consumption (MJ)  2.59E+10  -  2.59E+10  External cost ($ CAD)  1.02E+07  7.97E+08  8.07E+08  Human health (DALY) 2  Table E.7: Annual Impacts Grouped by Appliance Types for Wood Pellet Scenario Damage category  Pellet boiler  Human health (DALY) 2  Ecosystem quality (PDF∙m ∙yr)  Pellet fireplace insert  Pellet stove  Existing pellet stove  Total  4.41E+01  1.65E+02  5.16E+02  3.49E+01  7.60E+02  1.47E+06  2.58E+06  8.09E+06  5.46E+05  1.27E+07  115  Damage category  Pellet boiler  Pellet fireplace insert  Pellet stove  Existing pellet stove  Total  Climate change (kg CO2-eqv)  1.87E+07  3.23E+07  1.01E+08  6.85E+06  1.59E+08  Primary energy consumption (MJ)  2.06E+09  3.48E+09  1.09E+10  7.38E+08  1.72E+10  External cost ($ CAD)  3.69E+06  1.02E+07  3.19E+07  2.15E+06  4.79E+07  Table E.8: Annual Impacts Grouped by Life Cycle Stages for Wood Pellet Scenario Damage category  Upstream  Human health (DALY)  Combustion  Total  1.77E+02  5.82E+02  7.60E+02  Ecosystem quality (PDF∙m ∙yr)  7.02E+06  5.66E+06  1.27E+07  Climate change (kg CO2-eqv)  1.50E+08  9.26E+06  1.59E+08  Primary energy consumption (MJ)  1.72E+10  0.00E+00  1.72E+10  External cost ($ CAD)  1.59E+07  3.20E+07  4.79E+07  2  116  

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