GREENHOUSE GAS LIFECYCLE ASSESSMENT OF BIOCHAR AND BIOCOAL APPLICATIONS IN BRITISH COLUMBIA by Geoff de Ruiter, B.Sc., University of Northern British Columbia, 2006 M.Sc, University of Victoria, 2009 DISSERTATION SUBMITTED IN PARITAL FULFILLMENT OF THE REQUIRMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN NATURAL RESOURCES AND ENVIRONMENTAL STUDIES UNIVERSITY OF NORTHERN BRITISH COLUMBIA December 2018 © Geoff de Ruiter, 2018 ABSTRACT Biochar, a form of black carbon produced from pyrolyzed biomass, has been touted as a product that may suppress agricultural soil emissions while also sequestering carbon. BC Biocarbon LTD, a recently established company in McBride, BC, has developed a method of producing a new product called biocoal. This biocoal is produced from a combination of crushed biochar and an organic-based binder also made from the original biomass feedstock. As their biocoal contains similar properties to fossil coal or petroleum coke, its use to reduce emissions as an energy fuel or sequestration method may be favourable to biochar’s use as a soil additive. Additionally, this biocoal may present a method of long-term carbon sequestration if buried. This dissertation assessed the greenhouse gas emissions from the production of biocoal from BC Biocarbon’s system and compared the results to wood pellet production and delivery (Project 1), coal and petroleum coke displacement (Project 2), landfilling for carbon sequestration, while also assessing biochar’s potential soil greenhouse gas reductions with added carbon sequestration (Project 3), and a regional and province-wide assessment for reducing emissions in BC using available sawmill and roadside slash residues (Project 4). Project 1 showed that when comparing biocoal made from sawmill residues to locally produced wood pellets, transportation emissions may be decreased 64% due to biocoal’s higher heating value. When comparing emissions produced for biocoal or wood pellets at gate, biocoal may show a 42% reduction in emissions or up to a 51% increase in emissions, however this is largely dependent on the data-sourced scenarios and their underlying assumptions of emissions allocation. Project 2 showed that displacing petroleum coke in cement kilns offered the largest reduction potential compared to coal applications such as electricity generation, or lead smelting. Project 3 showed that under 2 average conditions, sequestering biocoal offered greater emission reduction potential than soil applied biochar. Finally, Project 4 showed that an estimated GHG emission reduction or carbon sequestration of 28,000,00 Mg CO2e/year from current available residues, and 20,006,000 Mg CO2e/year in 10 years’ time, BC has the potential to reduce its current emissions by around 46%, and 33% in 10 years. This research has implications on the optimal use of BC’s biomass for greenhouse gas reductions, and the broader field of biochar as a climate change mitigation strategy. Government and industry would benefit from these findings as to best approach the provinces bioenergy industry direction and path towards mitigating our contribution to anthropogenic climate change. 3 TABLE OF CONTENTS LIST OF TABLES ........................................................................................................................ 7 LIST OF EQUATIONS ............................................................................................................. 11 LIST OF ACRONYMS AND ABBREVIATIONS .................................................................. 12 LIST OF KEY DEFINITIONS ................................................................................................. 13 ACKNOWLEDGMENTS ......................................................................................................... 15 STATEMENT OF RESEARCH FUNDING ............................................................................ 15 DEDICATION ........................................................................................................................... 15 CHAPTER 1 - Introduction ................................................................................................. 16 1.1 1.2 1.3 1.4 1.5 1.6 1.7 2 Background ........................................................................................................................ 16 Statement of the problem .............................................................................................. 16 BC relevant context ......................................................................................................... 17 Objectives ........................................................................................................................... 18 Scientific contribution and relevance ....................................................................... 19 Dissertation layout .......................................................................................................... 20 References .......................................................................................................................... 21 CHAPTER 2 - Literature Review .............................................................................. 23 2.1 BC biochar and biocoal industry background ........................................................ 23 2.2 Overview of products & co-products from biomass pyrolysis .......................... 25 2.3 Physical and chemical properties of biochar and biocoal.................................. 26 2.4 Potential applications of biochar and biocoal in BC............................................. 28 2.4.1 Energy applications ....................................................................................................................... 29 2.4.2 Soil application of biochar .......................................................................................................... 30 2.4.3 Biochar application impacts on greenhouse gas emissions (CO2, N2O and CH4) .... 30 2.4.4 Filtration and other applications of biochar ........................................................................... 34 2.5 BC carbon market ............................................................................................................ 34 2.6 Including biochar into biomass resource planning in BC................................... 36 2.7 Lifecycle assessment of biochar systems ................................................................. 38 2.8 Biochar related lifecycle assessments ...................................................................... 41 2.9 Need for biochar and biocoal assessment in BC .................................................... 44 2.10 References .......................................................................................................................... 45 3 CHAPTER 3 – Project 1: Greenhouse gas assessment of a novel pyrolysis retort kiln producing wood-based synthetic coal from sawmill residues, roadside slash, and hybrid poplar feedstocks. .............................................................................................. 55 3.1 Abstract ............................................................................................................................... 55 3.2 Introduction ....................................................................................................................... 56 3.3 Methods ............................................................................................................................... 58 3.3.1 Goal and scope ................................................................................................................................ 58 3.3.2 Inventory data collection (Databases, sources, and analysis tools) ............................... 60 3.3.3 BC Biocarbon pyrolysis system and biocoal product. ....................................................... 60 3.3.4 Biocoal feedstocks ......................................................................................................................... 63 3.3.5 Biomass and Biocoal transportation......................................................................................... 68 3.3.6 GHG assessment ............................................................................................................................. 69 4 3.4 Results.................................................................................................................................. 70 3.4.1 Sawmill residue feedstock ........................................................................................................... 70 3.4.2 Roadside slash ................................................................................................................................. 72 3.4.3 Hybrid poplar feedstock ............................................................................................................... 75 3.5 Discussion ........................................................................................................................... 78 3.5.1 Comparison of feedstock types to biocoal ............................................................................. 78 3.5.2 Sawmill residue feedstock ........................................................................................................... 80 3.5.3 Roadside slash ................................................................................................................................. 84 3.5.4 Hybrid poplar feedstock ............................................................................................................... 86 3.5.5 Other points and limitations ........................................................................................................ 87 3.5.6 Conclusions and future research................................................................................................ 89 3.6 References .......................................................................................................................... 89 4 CHAPTER 4 – Project 2: Carbon displacement factors of wood-based biocoal in cement, smelting, and electrical power production ........................................................ 97 4.1 Abstract ............................................................................................................................... 97 4.2 Introduction ....................................................................................................................... 98 4.3 Methods ............................................................................................................................... 99 4.3.1 Goal and scope ................................................................................................................................ 99 4.3.2 Inventory data collection (databases, sources, and analysis tools) ............................. 100 4.3.3 BC Biocarbon pyrolysis system and biocoal product ..................................................... 100 4.3.4 Biocoal application scenarios .................................................................................................. 101 4.3.5 Lifecycle impact and GHG assessment ............................................................................... 105 4.4 Results................................................................................................................................106 4.5 Discussion .........................................................................................................................108 4.5.1 Biocoal application scenarios .................................................................................................. 108 4.5.2 Other factors and limitations of this study .......................................................................... 111 4.5.3 Conclusions and future research............................................................................................. 113 4.6 References ........................................................................................................................113 5 CHAPTER 5 – Project 3: Greenhouse gas assessment and carbon displacement factors of soil and carbon sequestration applications of biochar, biocoal and wood wastes in BC ........................................................................................................................... 118 5.1 Abstract .............................................................................................................................118 5.2 Introduction .....................................................................................................................119 5.3 Methods .............................................................................................................................122 5.3.1 Goal and scope ............................................................................................................................ 122 5.3.2 Inventory data collection (Databases, sources, and analysis tools) .................... 123 5.3.3 BC Biocarbon pyrolysis system and products............................................................... 123 5.3.4 Biocoal, biochar and wood characteristics ..................................................................... 124 5.3.5 Application scenarios .............................................................................................................. 128 5.3.6 Lifecycle impact and GHG assessment ............................................................................. 135 5.4 Results................................................................................................................................137 5.5 Discussion .........................................................................................................................139 5.5.1 Interpretation of results ......................................................................................................... 139 5.5.2 Biocoal, biochar and wood waste for landfill carbon sequestration ................... 140 5.5.3 Implications of results ............................................................................................................. 151 5.5.4 Factors to consider and limitations of the project ...................................................... 152 5.5.5 Conclusions .................................................................................................................................. 153 5.6 References ........................................................................................................................154 5 6 CHAPTER 6 – Project 4: BC-wide assessment of biocoal industrial emission reduction potentials from wood-based sawmill and roadside slash residues. ........ 164 6.1 Abstract .............................................................................................................................164 6.2 Introduction .....................................................................................................................165 6.3 Methods .............................................................................................................................166 6.3.1 Goal and scope ............................................................................................................................ 166 6.3.2 Inventory data collection (Databases, sources, and analysis tools) .................... 166 6.3.3 BC Biocarbon pyrolysis system and products............................................................... 166 6.3.4 Wood residue supply availability ....................................................................................... 167 6.3.5 Application scenarios .............................................................................................................. 170 6.3.6 Lifecycle impact and GHG assessment ............................................................................. 175 6.4 Results................................................................................................................................175 6.5 Discussion .........................................................................................................................177 6.5.1 Biomass residue availability ................................................................................................. 178 6.5.2 Application scenarios .............................................................................................................. 180 6.5.3 Other GHG factors...................................................................................................................... 182 6.5.4 Limitations, considerations, and conclusions ............................................................... 183 6.6 References ........................................................................................................................185 Appendix 1 Supplementary Information ................................................................... 189 Appendix 2 Supplementary Information ................................................................... 193 Appendix 3 Supplementary Information ................................................................... 198 Appendix 4 Supplementary Information ................................................................... 206 6 LIST OF TABLES Table 2.1 List of biochar and biocoal companies that had been or are based in BC as of September 2018. ....................................................................................................... 25 Table 2.2 Average product yields (dry wood basis) obtained through different methods of feedstock pyrolysis. (Modified from IEA 2007). ..................................................... 26 Table 2.3 Summary of key characteristics from carbon-based energy sources. Pine, Spruce, and Fir are averages of harvested species in BC without bark (Spruce: Picea sitchensis, Pine: Pinus contorta and Pinus ponderosa, Fir: Abies amabilis and Pseudotsuga menziesii). ............................................................................................ 26 Table 2.4 Modeled biochar biotic degradation parameters for half-life and percent loss in 100 years (table reproduced from Zimmerman 2010). ............................................. 31 Table 2.5 A non-exhaustive list of percent greenhouse gas reductions found from application of biochar to soil. Increases in emissions are denoted by ‘+’. ............... 33 Table 2.6 Overview of biochar lifecycle assessments with primary investigated attributes. Blank spaces indicate not mentioned or performed. ................................................. 42 Table 3.1 Original product emissions taken from sources, applied percent allocation, and resulting values used for this assessment. ................................................................. 65 Table 3.2 Assumed hybrid poplar 4-year yield set for this project, and showing referenced values drawn upon. ................................................................................. 67 Table 4.1. Biocoal application factors included in each scenario or not. ....................... 102 Table 4.2 Cement production values used to calculate the carbon displacement factor by displacing petroleum coke (petcoke) with biocoal. ................................................ 103 Table 4.3 Electricity production values used to calculate the carbon displacement factor by displacing coal with biocoal. ............................................................................. 104 Table 4.4 Lead production values used to calculate the carbon displacement factor by displacing coal with biocoal. .................................................................................. 105 Table 5.1 Biocoal, biochar and wood characteristics used in this project. ..................... 124 Table 5.2 Table of factors used within the BC Landfill Gas Generation Assessment Procedure Guidelines and Landfill Gas Generation Estimation Tool (BCMOE 2017) for biocoal, biochar, and wood wastes. ................................................................... 129 Table 5.3 Research performed on soil applied biochar with results that are comparable with units analyzed. ................................................................................................ 146 7 Table 5.4. Summary of included or excluded factors used for calculating net carbon reductions seen from high temperature biochar when applied to soils. .................. 150 Table 6.1 Base case GHG reductions and sequestration factors were imported from Research Project 2 and 3 and converted to a wood residue basis (Mg CO2e/Mg wood residue).................................................................................................................... 172 Table 6.2 Total residue requirements at Lehigh Cement, Lafarge Canada Inc. and Teck Resources based on their energy requirements and fuel type ................................. 172 Table 6.3 Emission factors for various methods of biocoal transportation. ................... 174 Table 6.4 Total calculated residues in each Natural Resource Region calculated for current and in 10 year’s-time. ................................................................................. 176 Table 6.5 Transportation distance emission allowance for various modes of biocoal transportation. ......................................................................................................... 177 8 LIST OF FIGURES Figure 2.1 Image of bituminous coal (left) (Wikipedia.com 2015), and Author’s images of biochar (middle) and biocoal (right). Biocoal shown was made by BC Biocarbon LTD of McBride, BC. ............................................................................................... 27 Figure 2.2 Conceptual comparison of product revenue and greenhouse gas reduction potential for biochar relative to other forms of bioenergy.. ...................................... 38 Figure 2.3 Procedure flow diagram of a lifecycle inventory analysis (ISOb 2006). ....... 40 Figure 3.1 GHG assessment scope of this project includes all processes within solid boundary are to be accounted for the GHG lifecycle CO2-equivalent emissions. 1 . 60 Figure 3.2 Calculated net biocoal GHG emission scenarios in kg CO2e/GJ biocoal at gate (Kamloops, BC) and at Rotterdam............................................................................ 70 Figure 3.3 Percent allocation of biocoal GHG emissions for sawmill residue emissions within the Sambo (2002) and Nyboer (2008) derived results. .................................. 71 Figure 3.4 Sensitivity analysis of biocoal GHG emissions made from sawmill residue feedstock from within the Sambo (2002) and Nyboer (2008) derived results. ......... 72 Figure 3.5 Calculated net biocoal GHGs in kg CO2e/GJ biocoal from roadside slash feedstock, at gate, at Rotterdam, and contrasting varying feedstock recovery distances. ................................................................................................................... 73 Figure 3.6 Percent allocation of biocoal GHG emissions made from roadside slash. Both scenarios are relative to their own results and are based on a 200-km residue recovery distance. ..................................................................................................... 74 Figure 3.7 Sensitivity analysis of biocoal GHGs made from roadside slash feedstock delivered to Rotterdam.............................................................................................. 75 Figure 3.8 Estimated net biocoal GHG emissions in kg CO2e/GJ from hybrid poplar feedstock at gate (Kamloops, BC) and at Rotterdam with and without land use change. ...................................................................................................................... 76 Figure 3.9 Percent allocation of biocoal GHG emissions from hybrid poplar. ................ 77 Figure 3.10 Sensitivity analysis of biocoal GHG emissions made from hybrid poplar feedstock delivered to Rotterdam.. ........................................................................... 78 Figure 3.11 Comparison graph of the most likely scenarios of biocoal production emissions at gate (kg CO2e/GJ biocoal), and comparison to wood pellets production from Pa et al. (2012) (kg CO2e/GJ wood pellets) (further discussed below in section ‘3.5.2 Sawmill Residue Feedstock’). ........................................................................ 79 9 Figure 4.1 Lifecycle scope included all processes within the solid boundary boxes are to be accounted for lifecycle CO2-equivalent emissions. ........................................... 100 Figure 4.2 Carbon displacement factors of cement, electricity, and lead produced at Lafarge, Kamloops BC, HR Milner power station, Grande Cache AB, and Teck Resources, Trail BC, respectively (product GHG emissions normalized to 1 GJ biocoal minus biocoal production and transportation emissions). Numbers are presented in kg CO2e/GJ biocoal. .......................................................................... 107 Figure 4.3 Sensitivity analysis of the carbon displacement factor from cement production base case analysis.. .................................................................................................. 108 Figure 5.1 GHG Lifecycle scope of research project 3 with research work in white. .... 122 Figure 5.2 Thermogravimetric thermograms for wood residue (hog fuel) a) biochar and b) biocoal made by BC Biocarbon. R50 values are corrected for moisture and ash content. R50 calculated from graphite reference temperature of 886 °C (Harvey et al. 2012); e.g. a) 471.92/886=0.53=R50. ...................................................................... 127 Figure 5.3 Carbon sequestration/offset factors for biocoal, biochar and wood waste along with the business as usual (BAU) cases currently performed for reference. .......... 138 Figure 5.4 Percent breakdown of GHG contribution emissions from soil applied biochar made from a) Low N2O emission reduction scenario (biochar soil effects for 3 years and 40 kg N/10,000 m2), and b) High N2O emission reduction scenario (biochar soil effects for 100 years and 120 kg N/10,000 m2). ..................................................... 139 Figure 6.1 Natural resource regions used for quantifying wood residues and associated GHG reductions through the use of biocoal across BC. ......................................... 171 Figure 6.2 Total BC GHG emission reduction potential in the 9 natural resource regions (NRRs) through the use of biocoal for cement production and carbon sequestration applications. Values are presented in Mg CO2e/year.............................................. 177 10 LIST OF EQUATIONS Equation 4.1 Sample net carbon displacement factor calculation for cement. ............... 106 Equation 5.1 Percent carbon loss equation from Zimmerman 2010. Slope (m=-5.419) and intercept (b=-0.556) were obtained from Zimmerman’s supplementary information Table S5, from course biochar produced from pine feedstock at 525°C. ............... 131 Equation 5.2 Sample net carbon sequestration/offset factor for biochar. Biocoal and wood waste carbon sequestration/offset factors are also similarly calculated.................. 136 Equation 6.1 Rail transportation distance emission allowance of biocoal cement use versus biocoal sequestration. .................................................................................. 174 11 LIST OF ACRONYMS AND ABBREVIATIONS AAC Annual allowable cut AUD Australian Dollar BAU Business as usual BC British Columbia C Carbon CDF Carbon Displacement Factor CSF Carbon Sequestration Factor CH4 Methane CO2 Carbon dioxide CO2e Carbon dioxide equivalent CFI Carbon Farming Initiative EPA Environmental Protection Agency g Gram GBR Great Bear Rainforest Gg Gigagrams GHG Greenhouse gases GJ Gigajoule H Hydrogen HHV Higher heating value IPCC Intergovernmental Panel on Climate Change ISO International Organization for Standardization km Kilometers LCA Lifecycle assessment 12 LHV Lower heating value LTD Limited m Meter Mg Megagram MOE Ministry of Environment MRT Mean residence time MW Megawatt MWh Megawatt-hour N Nitrogen NL Netherlands N 2O Dinitrogen monoxide NOx Nitrogen oxides NRR Natural Resource Region O Oxygen ODMg Oven dried Mega grams PCT Pacific Carbon Trust Petcoke Petroleum coke TBD To be determined THLB Timber Harvest Land Base TSA Timber Supply Area UNBC University of Northern British Columbia LIST OF KEY DEFINITIONS 13 Biochar Biochar is a form of crystalline black carbon that is chemically and physically similar to wood charcoal, activated carbon, and graphite. Biochar, if produced from woody biomass and with slow pyrolysis, will encompass approximately 35% of the initial biomass. Biochar is of low density, high porosity, and brittle. The name biochar is usually applied to a product used as a soil additive, however this term is also broadly adopted into the bioenergy and carbon industries. Biocoal Biocoal is chemically and physically similar to fossil coal. In this dissertation, biocoal is made from pulverized biochar mixed with a tarry binder also created from the original feedstock. If produced from woody biomass, as assumed in this dissertation, it will encompass approximately 65% of the initial biomass. The final biocoal product is water impermeable and solid, and resists crushing to a larger extent than biochar. 14 ACKNOWLEDGMENTS To be completed upon final completion of dissertation. STATEMENT OF RESEARCH FUNDING I received PhD fellowship funding from the Pacific Institute for Climate Solutions and the UNBC Bioenergy Scholarship, and Westcana Electric Inc. Award through the University of Northern British Columbia. I also received employment funding through the British Columbia Innovation Council’s Venture Acceleration Program in order to expand the transportation scope of this project on behalf of BC Biocarbon. DEDICATION This dissertation is dedicated to the effort and advancement of science and the future generations that may benefit from this produced collection of knowledge. Climate change is real, it is an impending threat to our Earth’s current biosphere, and I deeply hope my efforts in this dissertation will help navigate our uncertain future. 15 CHAPTER 1 - Introduction 1.1 Background Biochar is a form of black carbon produced from fibrous or high cellulose-based substances such as wood, straw, nutshells, or general biomass through a high temperature low-oxygen process called pyrolysis. Biochar has been used for generations as a cooking fuel and is proposed to be responsible for high productivity soils in the Amazon (Glaser 2007). Due to the physical and chemical properties of biochar, it has the potential to be used in the production of metals as a chemically and energetically similar coal substitute (Bianco et al. 2013, Fick et al. 2013; and Suopajärvi and Fabritius 2013), as a filter medium such as traditional activated carbon (Azargohar and Dalai 2006), as a potential soil amendment (reviewed in Ali et al. 2017; and Wu et al. 2017), as a long-term carbon storage mechanism (Lehmann 2007; and Woolf et al. 2010), and even a potential source of carbon for supercapacitors (Dehkhoda et al. 2013; Jiang et al. 2013; and Jin et al. 2013). Biocoal, another form of thermally decomposed biomass, has commonly been related to the production method of torrefaction or roasting (NCE 2015). However, a recent company, BC Biocarbon LTD, McBride BC, has developed a method of producing pyrolyzed biocoal with properties even closer to fossil coal. As presented in this dissertation, this form of biocoal has the opportunity to displace the quantified emissions of fossil coal and petroleum coke, while also acting as a long-term carbon storage mechanism with possibly greater carbon sequestration potential than biochar. 1.2 Statement of the problem In British Columbia (BC) there is a potential burgeoning bioenergy industry regarding the production and sale of biochar and biocoal. Limited discussion and limited 16 analyses have been performed regarding the direction or progression of the industry, and subsequently, the optimal uses of BCs biomass resources (de Ruiter et al. 2014). As there are stages of development for biochar and biocoal, ranging from fully demonstrated to theoretical, these applications may eventually compete for feedstock with other established industries, that is, if biochar and biocoal become significant players in the bioenergy, carbon, and agricultural sectors. Additionally, there is an informational gap in applications of biochar and biocoal as they have not been compared from a climate mitigation standpoint. This research aimed to elucidate optimal uses of biochar and biocoal through BC specific case studies involving cradle-to-grave greenhouse gas (GHG) assessments. Biochar and biocoal applications were investigated and compared for CO2-equivalent emission reductions and carbon sequestration potential. These results were then crossreferenced with a BC-wide assessment of biomass availability. Overall, this assessment will situate biocoal within the literature and compare it to soil applications of biochar. Eventually, this information may help to inform policy-making and industry to where biochar and biocoal products could be applied locally, and BC-wide, in order to help best mitigate climate change. 1.3 BC relevant context BC’s unique policy, geography, energy, and industry factors present an opportunity for investigation. Particularly, unique aspects in BC include our greenhouse gas reduction targets of 40% by 2030, $35/Mg CO2 carbon tax, abundance of cheap low-carbon hydroelectricity, diverse industry including mining and metal smelting, forestry and energy, relative abundance of wood fibre resources; large geographic distances and physical barriers such as lakes, mountains, and ocean; diverse climates from temperate rainforests, 17 to dry desert-like regions in the Okanagan, to cold Northern and mountainous ranges. Thus, it is due to these factors that a BC relevant greenhouse gas assessment of biochar and biocoal opportunities is needed to best guide the potential industry, and provide the optimal opportunity within this industry to reduce greenhouse gas emissions for climate change mitigation. 1.4 Objectives This research aimed to identify optimal carbon abatement within the potential BC biochar and biocoal industry. The research objectives of this dissertation were to: a) Perform a greenhouse gas lifecycle assessment for biocoal production from a novel pyrolysis retort kiln owned by BC Biocarbon. b) Use the BC Biocarbon biochar results to perform a case study of GHG assessments of biochar and related co-products for combustion applications with primary focus on CO2-equivalent emission reductions. c) Use the BC Biocarbon biochar results to perform a case study of GHG assessments of biochar, including landfill carbon sequestration and as a soil amendment with co-current carbon sequestration. d) Integrate BC wood biomass resource data and case study GHG assessments from the two prior projects into a province and regional-wide assessment for possible emission reductions. Combustion and non-combustion case study comparisons across various biochar and biocoal applications were modeled through greenhouse gas assessments. The research then cross-referenced BC regional biomass availability to assess total possible provincial emission reductions. 18 The focus of this research was to examine the priority of carbon abatement for climate change mitigation and not examine economic or social factors. It is deemed that social factors of carbon abatement are outside the skillset boundaries of this author and that economics and revenue potential of biochar and biocoal applications will already be assessed by industry. It is estimated that these proposed works will thus dovetail with the knowledge of industry and the social benefits planned by local and provincial governments. 1.5 Scientific contribution and relevance This proposed research will initially develop a greenhouse gas lifecycle assessment for biocoal from a novel pyrolysis retort kiln. This retort kiln is unique for its high percent carbon recovery and process that produces a biochar product almost exactly identical to coal. The greenhouse gas assessment for this biocoal product holds great potential if the predicted low emission product can be compared favourably to other existing bioenergy products. This dissertation also investigates and compares the combustion of biocoal to non-combustion uses for biocoal as well as biochar applications within the BC context. Primarily, it will be investigated which applications best assist local goals for climate change mitigation through CO2-equivalent emission reductions/carbon sequestration. From these greenhouse gas assessments, a range of biochar applications will be compared between combustion, and landfill applications. Additionally, at this time, no known GHG assessments have examined newly alternative applications for biochar and this unique biocoal, such as in cement production or landfill carbon sequestration. Thus, this dissertation also aims to investigate these new opportunities for climate change mitigation. Overall, this dissertation aimed to examine the possible current and future 19 applications of biochar and biocoal and to provide a broader assessment of applications and guidance for climate change mitigation. The target audience of this dissertation is not only the scientific community, but also the bioenergy industry and interested government institutions. 1.6 Dissertation layout This dissertation took a manuscript approach to organize and display these works, i.e. each of the research chapters (3, 4, 5, and 6) were presented as a publishable journal article. Chapter 2 of this dissertation is a literature review that covers the biochar and biocoal industry in BC and existing lifecycle assessment research associated with biochar and biocoal applications. Specific topics covered are: Situating the current economic, social, and environmental state of the BC biochar and biocoal industry, characteristics, potential products and applications, and the necessity for biomass planning, whether used for pyrolyzed energy streams or for other combustion or non-combustion applications. Chapters 3, 4, and 5 addressed objectives a, b, and c of this dissertation. Each subsequent project/chapter assessed certain steps in the progression to find and compared biochar and biocoal lifecycle CO2-equivalent emission reductions/carbon sequestration potential, whether for combustion applications, such as with biocoal, or soil and landfill applications with biochar and biocoal. Chapter 6 will cross-reference the results of chapters 4 and 5 (objectives b and c) with available BC sawmill and roadside slash residue feedstock. This aimed to provide a province and regional-wide assessment of possible emission reductions and present the findings as recommendations for BC policymakers and industry. 20 1.7 References Ali, S., Rizwan, M., Qayyum, M.F., Ok, Y.S., Ibrahim, M., Riaz, M., Arif, M.S., Hafeez, F., Al-Wabel, M.I., and Shahzad, A.N. (2017). Biochar soil amendment on alleviation of drought and salt stress in plants: a critical review. Environ Sci Pollut Res 24, 12700–12712. BC Hydro. (2013) Appendix 6 – Wood Based Biomass Potential Report. 2013 Resource Options Report Update. Last accessed May 11, 2014 at http://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/regulatory-planning-documents/integrated-resourceplans/current-plan/ror-update-appx-6-20130802.pdf. Bianco, L., G. Baracchini, F. Cirilli, L. Di Sante, A. Moriconi, E. Moriconi, M. M. Agorio, H. Pfeifer, T Echterhof, T. Demus, HP. Jung, C. Beiler, HJ. Krassnig. (2013). Sustainable Electric Arc Furnace Steel Production: GREENEAF, BHM Bergund Hüttenmännische Monatshefte, Vol 158(1), pp. 17-23. Dehkhoda, A.M., N. Ellis, and E. Gyenge. (2013) Activated Biochar: a green and lowcost electrode material for capacitor applications. Abstract #611, 244th Electrochemical Society. de Ruiter, G., S. Helle, M. Rutherford., B. (2014). Industrial and Market Development of Biochar in BC. Pacific Institute for Climate Solutions Whitepaper. Last accessed March 8, 2014 http://pics.uvic.ca/research/publications/white-papers Fick, G., Mirgaux, O., Neau, P., Patisson, F. Using Biomass for Pig Iron Production: A Technical, Environmental and Economical Assessment Waste and Biomass Valorization. March 2013. Glaser, B. (2007). Prehistorically modified soils of central Amazonia: a model for sustainable agriculture in the twenty-first century. Philosophical Transactions of the Royal Society B., Vol. 362(1478), pp. 187-196. Jiang, J., Zhang, L., Wang, X., Holm, N., Rajagopalan, K., Chen, F., and Ma, S. (2013). Highly ordered macroporous woody biochar with ultra-high carbon content as supercapacitor electrodes. Electrochimica Acta, Vol. 113, pp. 481–489. Jin, H, X. Wang, Z. Gu, J. Polin. (2013). Carbon materials from high ash biochar for supercapacitor and improvement of capacitance with HNO3 surface oxidation. Journal of Power Sources, Vol. 236(15), pp. 285-292. 21 Lehmann, L. (2007). A Handful of carbon. Nature, Vol. 447, pp. 143-144 Suopajärvi, H., and Fabritius, T. (2013). Towards More Sustainable Ironmaking- An Analysis of Energy Wood Availability in Finland and the Economics of Charcoal Production. Sustainability, Vol. 5 (3), pp. 1188-1207. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications 1, 56. Wu, H., Lai, C., Zeng, G., Liang, J., Chen, J., Xu, J., Dai, J., Li, X., Liu, J., Chen, M., et al. (2017). The interactions of composting and biochar and their implications for soil amendment and pollution remediation: a review. Critical Reviews in Biotechnology 37, 754–764. 22 2 CHAPTER 2 - Literature Review Some sections of this literature review, and co-written by this author, appear in a Pacific Institute for Climate Solutions’ white paper titled “Industrial and Market Development of Biochar in BC” (de Ruiter et al. 2014). 2.1 BC biochar and biocoal industry background The BC bioenergy industry has developed and refined itself in recent years. Industrial-scale electricity and heating projects have been built around the province, such as a wood gasification and district-heating system at the University of Northern BC in Prince George. Bioenergy systems can be used to make electricity, heat, and bioproducts including ethanol, synthetic natural gas, activated carbon or biochar for soil application, and a coal-like product known as biocoal. This dissertation focuses on the products of biochar and biocoal. Briefly, and expanded upon later in section 2.3 ‘Physical and chemical properties of biochar and biocoal’, biochar is a form of crystalline black carbon, which is chemically and physically similar to activated carbon, graphite, whereas biocoal is chemically and physically similar to fossil coal. Biochar and biocoal are made on an industrial scale through a high temperature process called pyrolysis. Pyrolysis is the thermal decomposition of organic matter in oxygen-limited environments. Biochar and biocoal may be produced from fibrous or high cellulose-based substances such as nutshells, straw, manure, or wood wastes. The name biochar is usually applied to a product used as a soil additive, however this term is also broadly adopted into the bioenergy and carbon industries. In this dissertation, biocoal is made from pulverized biochar mixed with a tarry binder also created from the original feedstock. When the mixture cools the biocoal product solidifies. 23 Because of their chemical similarities to coal, such as lower ash and potentially higher carbon content (laid out later in Table 1.3 below), biochar and biocoal can be used as a fuel substitute. Additionally, biochar may be used as a soil amendment (Biederman and Harpole 2013) and indirectly as a method of carbon sequestration because of its long residence periods (Zimmerman 2010; Matovic 2011; and Singh et al. 2012). Biocoal also has potential to act as a dedicated carbon sequestration product because of its similarities to coal and carbon recalcitrance similar to biochar. It is because of its multiple options for utilization that biochar has become increasingly studied for industrial applications and seen as a potential option for mitigating the effects of climate change, whereas biocoal as outline in this dissertation needs to be investigated. As BC is a major producer of lumber and pulp and paper, it is also a large producer of wood residues in the form of hog fuel/sawmill residues and roadside slash. It is because of the large volumes of lower cost wood residues that the biochar and biocoal industry had begun to develop in recent years. As of September 2018, 10 companies that have aimed to produce biochar, biocoal, and associated co-products are known to have been founded within BC (Table 2.1). Some companies were focused on pyrolysis oils, such as Dynamotive Energy Systems, while others, such as Out of Ashes Bioenergy, were focused on biochar as a soil amendment. 24 Table 2.1 List of biochar and biocoal companies that had been or are based in BC as of September 2018. Companies that have announced projects but no current information are listed as ‘To Be Determined’ (TBD). If the company has seemingly suspended operations they are noted as ‘Suspended’. Company Biochar/pyrolysis-oil/syngas Canadian Biocoal Diacarbon Energy Dynamotive Energy Systems Out of Ashes Bioenergy Poncho Wilcox Pytrade Canada Canadian Agrichar Biocoal or torrified wood BC Biocarbon Global Bio-coal Energy Nations Energy Corporation Headquarters Known or Planned Operations Vancouver Burnaby Richmond Quesnel Prince George Vancouver Maple Ridge TBD or Suspended Suspended Suspended Suspended Suspended Suspended Maple Ridge McBride Vancouver Vancouver McBride TBD or Suspended Suspended Because the biochar and biocoal industry has grown and filtered numerous companies, further research into key opportunities can still guide policy and direct specific uses to optimize local priorities, whether being for revenue potential or GHG reductions, or both. Additionally, biomass residue limitations may become a concern if the BC bioenergy industry continues to expand (explained later). Hence the focus of this dissertation will be to perform multiple GHG assessments in order to compare optimal applications of biochar and biocoal in BC and see their potential for reducing GHGs with considerations to total available wood waste residues in BC. 2.2 Overview of products & co-products from biomass pyrolysis Many products can be produced through the process of pyrolysis. They vary in proportions due to production parameters and method of pyrolysis (see Table 2.1), but include pyrolysis oil and tars, condensable and non-condensable gases, and biochar. Each of these products may serve as inputs for other processes, such as transportation fuels (Reviewed in Czernik and Bridgewater 2004) or combusted for heat and or electricity 25 (Ahrenfeldt et al. 2013; and de Miranda et al. 2013). Table 1.2 shows the average proportions of pyrolysis products obtained from various production methods (IEA 2007). Table 2.2 Average product yields (dry wood basis) obtained through different methods of feedstock pyrolysis. (Modified from IEA 2007). Pyrolysis Fast Intermediate Slow Gasification 2.3 Conditions Moderate temperature, around 500°C, short hot vapour residence time ~ 1 second. Moderate temperature, around 500°C, moderate hot vapour residence time ~ 10-20 seconds. Low temperature, around 400°C, very long solids residence time. High temperature, around 800°C, long vapour residence time. Biochar (Solid) 12% Producer gas/syngas (Gas) 13% Pyrolysis oil (Liquid) 75% 20% 30% 50% 35% 35% 30% 10% 85% 5% Physical and chemical properties of biochar and biocoal Charred carbon is the major constituent of biochar and biocoal (Table 2.3). Other elements are also present in biochar, and are mainly oxygen, hydrogen, and nitrogen, but other inorganic elements are found such as, silicon, potassium, sodium, calcium, iron and others to a lesser extent (Mohanty et al. 2013; and Lee et al. 2013). Table 2.3 compares key characteristics of related carbon-based materials including BC harvested wood, wood biochar and biocoal, coal, petroleum coke, and graphite. Table 2.3 Summary of key characteristics from carbon-based energy sources. Pine, Spruce, and Fir are averages of harvested species in BC without bark (Spruce: Picea 26 sitchensis, Pine: Pinus contorta and Pinus ponderosa, Fir: Abies amabilis and Pseudotsuga menziesii). Material Spruce wood Pine wood Fir wood Biochar Biocoal Bituminous Coal Petroleum Coke Graphite Sources 1 (BC MOE 2008) 2 (Lamlom and Savidge 2003) 3 (IGCL 2014) % Carbon Content 502 512 502 22 - 958 819 69 - 86 4 88 - 9111 70 - 997 % Ash 31 0.21 0.1 - 0.81 0.4 - 618 2.29 3.3 - 11.75 0.2 - 0.311 0.00056 4 (ASTM 2008) 5 (Engineering Toolbox 2014) 6 (Entegris 2013) 7 (Asbury 2014) Energy Content GJ/Mg % Volatiles ~191 75-8010 15 - 338 29.69 19.3 - 32.6 4 28.9911 32.76 1.3 - 888 N/A9 14 - 31 4 8 - 1111 8 (Reviewed in Nanda et al. 2016) 9 (BC Biocarbon 2015*) 10 (Baker 1983) 11 (Indian Oil. 2016) *Values quoted within BC Biocarbon (2015) are sourced from independent work such as ultimate analyses performed by Loring Laboratories ltd, Calgary, AB and a characteristic report by James Butler through partnership with National Research Council Canada. Biochar and biocoal appear similar to fossil coal (Figure 2.1), however coal and biocoal are less brittle than biochar and less prone to being crushed. Figure 2.1 Image of bituminous coal (left) (Wikipedia.com 2015), and Author’s images of biochar (middle) and biocoal (right). Biocoal shown was made by BC Biocarbon LTD of McBride, BC. It is made from crushed biochar and an organic-based binder made from the pyrolysis co-products. Varying biochar properties can be achieved through modifying the production process (Brownsort 2009). Variations can be made during pyrolysis by altering production parameters (Fletcher et al. 2014), but are particularly due to highest treatment temperature and time (Zhao et al. 2013), and feedstock (Fungai et al. 2013). Thus, biochar may be tailored to meet specific requirements for physical properties such as specific surface area, porosity, pH, water-holding capacity, and surface exchange 27 properties, and chemical structure when referring to energy applications. See Lehmann and Joseph (2009) for an extensive description of biochar characteristics and properties. The chemical composition of biochar and biocoal directly relates to their ability to act as a substitute for coal or other high carbon molecules such as graphite or activated carbon. Carbon content, volatile organic compounds, and ash content are three main chemical compositions that are affected by feedstock type, highest treatment temperature, length or intensity of treatment time and relating to either fast, intermediate, or slow pyrolysis (Brewer et al. 2011, Mohanty et al. 2013; Chen et al. 2014; and Zhao et al. 2013). An example comparison of high grade coal for blast furnaces show compositions of 7-9% for ash, 0.65-0.85% for sulfur (Wozek and Ricketts 1994), whereas biochar ash content from wood and wood wastes can range from 1-8% (reviewed in Nanda et al. 2016), and very low sulfur contents less than 0.02% (Emmerich and Luengo 1996; and Malone 2010). This indicates that wood biochar from BC may be good for coal displacement and would rank as low ash and low sulfur under the US Geological Survey standard for coking coal. Research and test trials have also confirmed biochar’s suitability as a coal substitute (Huang et al. 2013 and Bianco et al. 2013). Energy content per volume will be lower in biochar compared to coal because of its lower density, however this can be partially remedied through pelletizing for ease of shipment. This is also where biocoal, as defined in this dissertation, can fill in the gaps with organic based binders, or when torrefied in other methods of making biocoal and pelletized. 2.4 Potential applications of biochar and biocoal in BC As stated, biochar is not a single uniform product, and biocoal contains more energy because it is a solid mix of biochar and organic-based binder. Both are able to be produced 28 with some specific physical characteristics by varying the production conditions and as a result of this, many applications of biochar and biocoal are seen. Below are descriptions of the various potential uses for biochar and biocoal and a brief discussion of the current associated feasibilities for implementation. 2.4.1 Energy applications Energy applications of biochar and biocoal can be as simple as coal substitution or as complex as a feedstock for chemical conversion to other products in a biorefinery, such as liquid transportation fuels (modeled in Shabbir et al. 2012). Biochar and biocoal can be used as a bioenergy feedstock for electricity production, industrial co-generation for heat and electricity, heating for buildings or greenhouses, or for export as pellets. As a fuel substitute biochar and biocoal have approximately the same energy density of coal (Table 2.3), and can be used as a complete substitute, as opposed to wood pellets where only around 10-20% coal can be displaced (Koppejan and van Loo 2012). This is due to the higher combustion temperature of the higher carbon content biochar and biocoal. However, biocoal has the added benefit of being denser than biochar and so more energy can be transported in the same volume of space. In BC, it is estimated that 1.8 million Mg of coal is combusted annually (BC production minus export; Statistics Canada 2012), which equates to 3.9 million Mg of CO2 (Environment Canada, 2013). This coal use is primarily by the cement industry. Locations in BC are Lafarge Canada Inc, in Richmond, and Lehigh Cement in Delta, however there are others in surrounding jurisdictions such as Washington State and Alberta that also use coal for various applications such as quicklime and cement production, and electricity generation. 29 2.4.2 Soil application of biochar Biochar’s impact as a soil amendment has been covered in many papers and reviews over the past decade (Shackley et al 2010; Soi et al. 2010; Spokas et al. 2012; Biederman and Harpole 2013; Cayuela et al. 2015; and He et al. 2017) and text books (Gaunt and Lehmann 2008; Lehmann and Joseph 2015) including effects on water holding capacity, bulk density, net primary production, soil biological properties, nutrient retention, soil chemial properties, and GHG fluxes. Factors such as soil type, climate, application levels, biochar production methods, associated physical properties, and co-application with fertilizers all show varying benefits, or in some cases, drawbacks to soil productivity. A meta-analysis performed by Biederman and Harpole (2013) on 371 independent studies showed an average increase in aboveground crop productivity, yield, soil microbe and rhizobia biomass, some plant and soil nutrient benefits, and greater total soil carbon content. However, there was no relationship found between concentration of biochar applied and aboveground productivity. An earlier meta-analysis was also performed by Jeffery et al. (2011) and found similar positive results to that of Biederman and Harpole (2013). Overall, they found a 10% increase in crop productivity. This was mainly linked to changes in soils that were neutral to acidic and medium to coarse texture. This will be of particular importance if biochar is to be used as a carbon sequestration mechanism as well. 2.4.3 Biochar application impacts on greenhouse gas emissions (CO2, N2O and CH4) Climate change mitigation is one of the main rationales for applying biochar to soils (Reviewed in Lorenz and Lal 2014; and Lehmann and Joseph 2015 – Chapter 18). As a carbon storage and GHG reduction mechanism, biochar needs to be predictable and quantifiable if it is to be adopted by the carbon-offset industry. Although biochar is a very stable form of carbon, slow rates of decomposition are still seen when applied to soils. These 30 rates depend on many factors such as the feedstock of biochar, how it was produced, and environmental conditions (reviewed in Lehmann and Joseph 2015 – Chapter 11), with recalcitrance predicted by the molar ratio of O:C (Spokas, 2010). From reviewing biochar recalcitrance papers that also reported chemical analyses, Spokas (2010) found that biochars with O:C ratios less than 0.2 were the most stable with a half-life typically greater than 1000 years, biochars with a half-life of 100-1000 years were associated with O:C ratios of 0.2-0.6, and biochars with half-lives less than 100 years associated with ratios greater than 0.6. A comprehensive analysis of biochar decomposition modeling was performed by Zimmerman (2010) where various feedstocks (oak, pine, cedar, bubinga, grass, and sugar cane) were examined over a 1-year period while measuring the levels of released CO2. Results were calculated and modeled, and carbon losses were found to be from 3 to 26% over a 100year period, with overall half-life increasing with higher peak heating temperatures. It was found that the majority of decomposition occurred earlier, whereas over time, reduced amounts of carbon were released, and eventually stabilizing with very low levels of carbon loss. Table 2.4 summarizes results from Zimmerman (2010) for the percent loss for the first 100 years and half-life periods for 3 types of wood found in BC: Oak, pine, and cedar. Results found in this study are based on 32°C temperatures and would be much higher than average yearly temperatures in BC and possibly conservative for lost CO2. Table 2.4 Modeled biochar biotic degradation parameters for half-life and percent loss in 100 years (table reproduced from Zimmerman 2010). Wood species below were selected from Zimmerman (2010) because of applicability to BC fibre supplies. 100-year Clost stands for percent loss of carbon in the first 100 years, while ‘NP’ stands for “not performed in experiment”. Temperatures represent the peak heating temperature during pyrolysis. 250 °C 400 °C 525 °C 650 °C 72 h at 650 °C 31 Feedstock Half-life Oak 840 years Pine Could not calc. 730 years Cedar 100year Clost 20% 7% Halflife 1,020 years 990 years 16% 23,800 years 100year Clost 18% 14% 7% Halflife 9,590 years 6,790 years 12,800 years 100year Clost 7% 8% 7% Halflife 96,200 years 17,000 years 20 million years 100year Clost 6% 6% 3% Halflife 40 million years 71,800 years NP 100year Clost 1.9 % 3.2 % NP Other papers have examined the decay rates of wood-based biochar in soils (Baldock and Smernik 2002; Cheng et al. 2006; Hamer et al. 2004; Spokas and Reicosky 2009; Zavalloni et al. 2011; Zimmerman et al. 2011). These papers show decay rates comparable to Zimmerman (2010), but were only run for one year. A recent analysis was performed to investigate carbon sequestration in charcoal hearths in Northern Italy from the 1800’s (Criscuoli et al. 2014). The experiment was performed because the scenario was analogous to current proposals for biochar carbon sequestration in soils. Results found a mean residence time of 650 ±139 years, which are congruent with biochar’s long-term stability in soil and appropriateness as a carbon storage mechanism. The longest biochar degradation study was performed by Singh et al. (2012). Their study examined 5-years of incubation and biochar made from a woody biomass, Eucalyptus saligna and at peak heating temperatures of 400 °C and 550 °C, along with other feedstocks. Wood biochar incubated at 550 °C without steam activation showed a mean residence time of 1616 ±252 years and a half-life of 1120 ±174 years. The results of the study strongly indicated biochar represents a long-term storage mechanism for carbon with regards to climate mitigation. 32 Evolution of nitrous oxide and methane has shown to be suppressed following biochar application to soil. Table 2.5 shows the results of recent papers exploring nitrous oxide and methane reductions from biochar applications to soil. No data were found on long-term studies past one year of N2O and CH4 reductions and thus is an information gap at this time. Additionally, the exact mechanisms have not yet been fully elucidated, however it is thought that microbial inhibition (e.g. of denitrifying bacteria), altered soil properties and possible increases in soil aeration status may explain the effects. Cayuela et al. (2013) performed a meta-analysis examining N2O production in laboratory and field trials with application of biochar. They found an overall effect of N2O being reduced by 54%. They also attempted to correlate key attributes of biochar and its application to the observed reduction in N2O, and found that greater reductions were positively correlated with higher application rates. Although they were able to identify some related factors affecting N2O (feedstock, pyrolysis conditions, and C/N ratios) they concluded there is still a lack of understanding regarding key mechanisms that lead to N2O reductions. Table 2.5 A non-exhaustive list of percent greenhouse gas reductions found from application of biochar to soil. Increases in emissions are denoted by ‘+’. Author Malghani et al., 2013 Augustenborg et al., 2012 Felber et al., 2012 Kammann et al., 2012 Yoo and Kang, 2011 Singh et al., 2010 Nitrous oxide % reductions ~80% 10 - 91% 60% 56% 29% 14 - 73% Methane % reductions ~60% 0 - +17% 0% 33 van Zwieten et al., 2010 Spokas et al., 2009 Spokas and Reicosky, 2009 Yanai et al., 2007 Rondon et al., 2006 2.4.4 46 - 49% 0% 100% 89% 80% 48 - 65% 99, +83, +89% 100% Filtration and other applications of biochar Biochar possesses variable but high specific surface area due to its porosity, typically around 400 m2/g, and possesses chemically activated surfaces for binding other molecules (Reviewed in Lehmann and Joseph 2015 – Chapters 2 and 3). These properties make biochar, and more specifically activated carbon made from biochar/wood, a good filter/sorption medium (Azargohar and Dalai 2006). This can be applied to air pollution control (Klassen et al. 2010, and Klassen et al. 2014), and water and soil sorption of molecules (Inyang et al. 2012; Hina 2013; and discussed in Lehmann and Joseph 2015 – Chapters 15 and 16). Application of biochar for filtration can provide a dual service as it can also be used as a carbon storage mechanism due to its end disposal in a landfill. Carbon stability and storage is discussed in the “Biochar application impacts on greenhouse gas emissions” section. Research into non-thermal products with very high percentages of carbon made from biomass/biochar is still in its infancy. With that said, this field of research could drive longterm uses if production costs are not insurmountable. Some of these applications include supercapacitors (Dehkhoda et al. 2013; Jiang et al. 2013; and Jin et al. 2013), carbon electrodes (Huggins et al. 2014), and, hypothetically, due to the similarities of high carbon feedstocks used, synthetic graphite. Similar to biochar filtration applications, these products also store carbon as a secondary service at the end of their life, if not combusted. 2.5 BC carbon market The policy environment affecting development of the biochar and biocoal market in BC 34 relates to either the private carbon market or the public carbon market. At this time, there are no known carbon offset companies in the private carbon market that sell biochar credits as a viable carbon sequestration or fuel replacement option. As of 2010, BC has legislated that all public institutions, such as universities and government offices, must be carbon neutral either through zero CO2 emissions or from the purchase of carbon offsets. These offsets were purchased through a BC Crown corporation called the Pacific Carbon Trust (PCT), at $25 per Mg CO2e (CO2 equivalent) (PCTa 2012). These offsets are then bid upon by businesses and organizations to partially pay for the implementation of carbon reduction activities. On March 31, 2014, the PCT was dissolved and its mandate was transitioned into the operations of the BC Climate Action Secretariat (PCTb 2013). Biochar and biocoal has large potential in helping to advance carbon neutrality and expand the BC green economy. The former PCT opened a request for proposals, from June 12th, 2012 to May 31, 2013, for the sale of offsets involved in the fuel switching from coal to BC biochar (referred to as biocoal by the PCT and also including torrefied/roasted wood) (PCTc 2012). This ultimately aims to facilitate the sale of biochar or biocoal and help build a potential market for the product. The operations of the PCT represented a very unique public carbon market in North America, and perhaps even the world. The only other market for biochar offsets at this time is located in Australia through a program called the Carbon Farming Initiative (CFI, 2013), however this is a government-run program and not a private market. Farmers may add biochar to their soils as an amendment leading to potential greater productivity, and more importantly carbon sequestration. The price of carbon offsets started in 2012/2013 at a fixed price of $23 AUD/Mg (1 AUD =1.05 CAD at the time of writing), and shifted to a flexible market cap and trade price in 2015/2016. 35 One stipulation of the CFI is that the carbon must be sequestered for 100 years. Given the discussed stability of biochar in soils, sequestration times should easily be maintained for the majority of biochar applied, with the highest loss being 20% and the lowest at 3% over the first 100 years. Therefore, a carbon offset price should develop for the sale of biochar, as it is a reliable, stable, and relatively easy to quantify offset. Peters-Stanley and Hamilton (2012) discussed the average cost of voluntary market biomass/biochar offset prices in 2011 at $4/Mg CO2, however this is far below the $13/Mg CO2 found in clean cook stoves, or $12/Mg CO2 for forest management, thus making biomass/biochar offset projects less competitive and profitable than other biomass related offsets. The report did not state where the carbon market was purchasing the biochar offsets, but it can be assumed the price reflected general biomass combustion projects and not biochar sequestration because none are currently known to exist for dedicated biochar sequestration. It should be noted that, currently, carbon sequestered from the atmosphere would allow us to get closer to carbon neutrality. Ultimately, carbon sequestration projects have the potential to be carbon negative if global GHG emissions stabilize. At this time however, direct biochar or biocoal sequestration may not be the optimal use for reducing GHGs. Depending on local priorities, opportunities and resources, alternative options for reducing carbon emissions, such as a coal replacement, may provide better carbon reduction potentials. 2.6 Including biochar into biomass resource planning in BC There is a necessity for planning any development of the BC biochar and biocoal industry. This is because of potential hurdles in the production of biochar, future and possible feedstock limitations, and optimization of revenue and/or carbon emission reductions, depending on priorities. 36 Greenhouse gases may be reduced through the implementation of bioenergy for substitution of fossil fuels, however these reductions depend on the carbon intensity of the fuel, i.e. coal has increased carbon intensity versus natural gas. In Figure 2.2, electricity generation from low carbon sources, such as hydro or wind could be considered a relatively poor choice for bioenergy or biomass applications versus coal substitution in a power plant, when prioritizing carbon reduction potentials. It should be noted that even though coal has a higher carbon intensity and thus carbon reduction potential, shipping biochar or other coal substitutes longer distances reduces the offset potential because energy and most likely fossil fuels are used for transport. Alternately, soil applications or pure sequestration of biochar may (Ibarrola et al. 2012; and Gaunt and Lehmann 2008)) or may not (Pourhashem et al. 2013; and Woolf et al. 2010) result in equal or greater reductions in carbon emissions as a coal substitute. Therefore, more research is needed, with attention to local use and conditions and is targeted in this dissertation. Liquid fuel production from bioenergy may be more challenging from an economic and technological use versus that of coal substitution or as a soil amendment. Additionally, liquid fuel production may not yield substantial carbon emission reductions if a combination of low GHG displacements and high production emissions are seen. Ultimately the best use of our bioenergy resources will optimize various priorities while also providing an easy technological entry into specific markets. In time, technological improvements should be pursued to rapidly shift to higher value carbon products so that the industry can increase revenue while also offsetting carbon emissions (Concept is displayed in Figure 2.2). 37 Figure 2.2 Conceptual comparison of product revenue and greenhouse gas reduction potential for biochar relative to other forms of bioenergy. Large gray arrows show the impact of increasing carbon tax on potential revenue (greater impact with increasing greenhouse gas emission reductions). Because of discussed residue feedstock limitations, a growing BC bioenergy economy, and uncertain current and future applications of biomass resources, including biochar and biocoal, there is a need for investigation into optimal uses through lifecycle GHG assessments. 2.7 Lifecycle assessment of biochar systems Lifecycle assessment (LCA) is a method of analysis to determine environmental performance of a product (ISOa 2006). It helps to examine the product’s various points or phases during its life, and helps to inform and provide guidance to governments and policy makers, non-government organizations, and industry. LCA’s have four phases: i) Goals and scope definition ii) Inventory analysis iii) Impact assessment 38 iv) Interpretation Defining the goals and scope of the project help to set the investigation boundaries and intent/outcome of the LCA. This phase establishes the foundation to the research and provides a clear framework for analysis. The second phase of an LCA (inventory analysis) inventories the existing information and literature within the system boundaries and categorizes it into input and output data. Figure 2.3 demonstrates a simplified procedural flow diagram for an inventory analysis, including the goal and scope definition. The third phase of an LCA, the lifecycle impact assessment, uses the information from the inventory analysis to calculate and assess potential environmental impacts. This is done through developing the assessment framework, assigning the inventory analysis data into the assessment framework, and then calculating the impact results. The final stage of LCA is the interpretation of the results. This provides conclusions, recommendations, and discusses limitations to the study. 39 Figure 2.3 Procedure flow diagram of a lifecycle inventory analysis (ISOb 2006). A subcategory of the lifecycle assessment protocol is a GHG assessment. The primary steps are similar, however only GHGs are assessed instead of other metrics applicable to the product, such as energy use, water use, or air toxicity. Many lifecycle assessments will include GHG assessments as various programs and databases such as GaBi or SimaPro make it easy to choose various metrics. Greenhouse gas assessments, also known as carbon footprint analyses, are categorized into 3 levels of detail: Scope 1, 2 and 3 (UN Environment 2018). Scope 1 assessments include only direct emissions produced by an organization, such as vehicles, furnaces, or release of other GHGs such as methane from site operations. Scope 2 assessments include indirect electricity and heat emissions (upstream generation), while scope 3 assessments include the production of indirect emissions from the extraction, purchase or used of materials or services linked to an organization’s activities. These can be the emissions from the production of the building leased, paper purchased, or transportation of fuel consumed. 40 2.8 Biochar related lifecycle assessments Multiple papers have researched lifecycle assessments of biochar applications. These have focused on different scopes such as, location, feedstock source, pyrolysis production system, application, carbon and GHGs, and economics. Table 2.6 provides a summary of major investigative scopes. 41 Table 2.6 Overview of biochar lifecycle assessments with primary investigated attributes. Blank spaces indicate not mentioned or performed. Experiment reference Feedstock Production Application Carbon/GHGs Teichmann (2014) Various for tested scenarios including: Cereal straw, forestry residues, industrial wood wastes, green wastes, shortrotation coppice, sewage sludge, manures, and farm biomass residues Virgin or plantation forest Maize cobs Slow pyrolysis Soil sequestration for biochar; co-products used for electricity production. CO2, CH4 and N2O Coal offset CO2-eq Production of biochar: CH4, NOX, N2O, SO2 Wang et al., (2013) Corn stover Fast and slow pyrolysis Pourhashem et al. (2013) Corn stover Huang et al. (2013) Rice straw Norgate et al. (2012)* Mallee eucalypts, forestry or logging residues Soil sequestration in: conventional farming; conservation farming with biochar from earth-mound kilns; conservation farming with biochar from retort kilns, and conservation farming with biochar from micro top-lit updraft gasifier stoves. Soil sequestration; Biochar electricity cogeneration; pyrolysis oil gasoline Biochar soil sequestration; biochar electricity co-firing with bituminous; pyrolysis oil electricity co-firing with heavy oil Electricity co-firing with sub-bituminous, 10 and 20% Fuel and reductant in ironmaking and steelmaking Vadenbo et al. (2013) Sparrevik et al. (2013) Traditional earth-mound kilns, improved retort kilns, and micro top-lit updraft gasifier stoves Slow pyrolysis Soil: CO2, Soil organic carbon, N2O, and CH4; Pyrolysis oil gasoline, CO2 Soil: CO2, N2O; Fossil Fuel: CO2, N2O, and CH4. Coal: CO2, N2O, and CH4. CO2 42 Ibarrola et al. (2012) Sewage sludge, green waste, food waste, wood waste, urban wood, used cardboard digestates, dense refuse, whisky draff, and poultry litter Soil sequestration; biochar combustion; non-charred land spreading Rousset et al. (2011) Hammond et al. (2011) Eucalyptus wood and babaçu nut pulp Wheat straw, barley straw, oilseed rape straw, sawmill residues, forestry residue chips, small round wood chips, short rotation coppice chips, short rotation forestry chips, miscanthus, and imported Canadian forestry residue chips Fossil fuel displacement overseas Soil sequestration; fossil fuel displacement Woolf et al. (2010) Rice, other cereals, sugar cane, manures, biomass crops, forestry residues, agroforestry, green/wood waste Crops: switchgrass. Wastes: corn stover and yard wastes. Mallee eucalypts Roberts et al. (2010) Norgate and Langberg (2009)* Gaunt and Lehmann (2008) Crops: miscanthus, switchgrass, and corn. Wastes: corn stover and winter wheat straw. Pyrolysis cogeneration with biochar plus electricity; Slow Pyrolysis, fast pyrolysis, gasification, and combustion; Large, medium, and small scale Fast pyrolysis Soil: CO2, N2O, and CH4; Fossil Fuel: CO2, and CH4 Soil: CO2, N2O, and CH4; Fossil Fuel: CO2, and CH4 Soil sequestration; fossil fuel displacement compared (gas, oil, coal) Soil: CO2, N2O, and CH4; Fossil Fuel: CO2, and CH4 Soil sequestration Soil: CO2, N2O, and CH4 Fuel and reductant in ironmaking and steelmaking CO2 Soil sequestration; and sub-bituminous coal and natural gas substitution Soil: CO2, N2O; Fossil Fuel: CO2, N2O, and CH4. *Norgate and Landberg, (2009) and Norgate et al. (2012) possess very similar methods and overall analysis due to the similar researchers. The papers reviewed in Table 2.6 show varying results from the different goals and 43 scopes sought by each assessment. It can be seen that various lifecycle assessments focus on different scopes whether it being feedstock, biochar production, application of biochar, carbon/GHGs, economics, or other. Within each individual scope, different comparisons are set. An example of this is with feedstocks. Feedstocks can vary tremendously from wood products to sewage sludge, with the most commonly examined being corn stover, likely due to the extent of global corn production. Given the varying scopes and goals, and ultimate applications, it makes comparing exact results more challenging. Therefore, research case studies and local applications based on local parameters are further desired. 2.9 Need for biochar and biocoal assessment in BC Like any jurisdiction, BC has unique political, social, economic and environmental attributes that necessitate the need for a location specific lifecycle assessment of biochar and biocoal use. Primarily, there is an abundant, although limited, wood residue supply that may benefit BC, whether that being economically, socially, or environmentally. Second to this, BC possesses an abundance of low cost fossil fuels such as coal and natural gas, which can out compete biochar, biocoal, and other biomass applications with ease of implementation, technological deployability, and when not in proximity to abundant wood residues, fuel cost. Additionally, BC has a provincial $35/Mg CO2 carbon tax and public-sector carbon offset price of $25/Mg CO2, which has not been directly assessed. Finally, there still remains informational gaps in the literature with regard to alternative/new applications of biochar and biochar-derived products, as well as GHG comparisons of thermal or non-thermal applications of biocoal to biochar soil sequestration applications. Therefore, this research dissertation aims to address and add to information and context in the biochar and biocoal GHG literature, as well as providing a BC-oriented assessment for optimally implementing biochar and biocoal. 44 2.10 References Ahrenfeldt, J., Thomsen, T.P., Henriksen, U., and Clausen, L.R. (2013). Biomass gasification cogeneration – A review of state of the art technology and near future perspectives. Applied Thermal Engineering 50, 1407–1417. Alibaba.com. (2014). Product and price search for “carbon electrode”. Last accessed Jan 13, 2014 at http://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchT ext=carbon+electrode Amazon.ca (2014) Nature's Way Activated Charcoal (100 Capsules). Last accessed March 12, 2014 at http://www.amazon.ca/Natures-Way-Activated-CharcoalCapsules/dp/B0006LCQ4Q/ref=sr_1_cc_2?s=aps&ie=UTF8&qid=1395051222&sr=12-catcorr&keywords=Activated+Charcoal Wikipedia.com. (2015). Bituminous Coal. Photograph taken by Amcyrus2012. Last accessed Dec 26, 2018 at https://commons.wikimedia.org/wiki/File:Bituminous_Coal.JPG#/media/File:Bitumino us_Coal.JPG Antal, M.J., and Grønli, M. (2003). The Art, Science, and Technology of Charcoal Production. Industrial & Engineering Chemistry Research 42, 1619–1640. Asbury. (2014). The World’s carbon and graphite source. Asbury Carbons, Last accessed Feb 27, 2014 at http://asbury.com/homepage_pdf/Brochure.pdf ASTM. (2008). Gaseous fuels; coals and coke. ASTM International. Vol. 5.06. Augustenborg, C.A., S. Hepp, C. Kammann, D. Hagan, O. Schmidt, and C. Müller. (2012). Biochar and earthworm effects on soil nitrous oxide and carbon dioxide emissions. Journal of Environmental Quality, Vol. 41, pp. 1203–1209. Azargohar R, and K.A. Dalai (2006) Biochar as a precursor of activated carbon. Applied Biochemistry and Biotechnology, Vol. 131(1-3), pp. 762-773. Baker, A. J. (1983). Wood fuel properties and fuel products from woods. In: Fuelwood management and utilization seminar: Proceedings. East Lansing, MI; 1982 November 911. East Lansing. MI: Michigan State University; 1983: 14-25. 45 Baldock, J.A., and R.J. Smernik (2002) Chemical composition and bioavailability of thermally altered Pinus resinosa (Red Pine) wood. Organic Geochemistry, Vol. 33, pp. 1093−1109. BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. BC Hydro. (2012). Integrated Resource Plan 2012, Appendix 3A-25. 2010 Resource Options Report Wood Based Biomass Potential Report. Last accessed Dec 18, 2012 at https://www.bchydro.com/content/dam/hydro/medialib/internet/documents/planning_re gulatory/iep_ltap/2012q2/draft_2012_irp_appx_3A_25.pdf. BC Hydro. (2013). Appendix 6 – Wood Based Biomass Potential Report. 2013 Resource Options Report Update. Last accessed May 11, 2014 at http://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/regulatory-planning-documents/integrated-resourceplans/current-plan/ror-update-appx-6-20130802.pdf. BC MOE. (2008). Emissions from Wood-Fired Combustion Equipment. BC Ministry of environment. Last accessed March 11, 2014 at http://www.env.gov.bc.ca/epd/industrial/pulp_paper_lumber/pdf/emissions_report_08.p df. Bianco, L., Baracchini, G., Cirilli, F., Sante, L.D., Moriconi, A., Moriconi, E., Agorio, M.M., Pfeifer, H., Echterhof, T., Demus, T., et al. (2013). Sustainable Electric Arc Furnace Steel Production: GREENEAF. Berg Huettenmaenn Monatsh, Vol. 158, pp. 17–23. Biederman, L.A., and Harpole, W.S. (2013). Biochar and its effects on plant productivity and nutrient cycling: a meta-analysis. GCB Bioenergy 5, 202–214. Brewer, C.W., R. Unger, K. Schmidt-Rohr, and RC. Brown. (2011). Criteria to Select Biochars for Field Studies based on Biochar Chemical Properties. BioEnergy Research, Vol. 4,(4), pp 312-323. Brownsort, P.A. (2009). Biomass Pyrolysis Processes: Review of Scope, Control and Variability. UKBRC Working Paper 5. Last accessed Jan 5, 2013 at http://www.biochar.org.uk/abstract.php?id=16 Cayuela, M.L., Jeffery, S., and van Zwieten, L. (2015). The molar H:Corg ratio of biochar is a key factor in mitigating N2O emissions from soil. Agriculture, Ecosystems & Environment 202, 135–138. 46 Chen, D., Zhou, J., and Zhang, Q. (2014). Effects of heating rate on slow pyrolysis behavior, kinetic parameters and products properties of moso bamboo. Bioresource Technology 169, 313–319. Cheng, C.H., J. Lehmann, J.E. Thies, S.D. Burton, M.H. Engelhard. (2006). Oxidation of black carbon by biotic and abiotic processes. Organic Geochemistry, Vol. 37, pp. 1477– 1488. CFI. (2013). Carbon Farming Initiative, Department of Climate Change and Energy Efficiency, Australian Government. Last accessed Feb 10, 2013 at http://www.climatechange.gov.au/government/initiatives/carbon-farminginitiative/activities-eligible-excluded/additional-activities-positive-list/application-ofbiochar.aspx Criscuoli, I., Alberti, G., Baronti, S., Favilli, F., Martinez, C., Calzolari, C., Pusceddu, E., Rumpel, C., Viola, R., and Miglietta, F. (2014). Carbon Sequestration and Fertility after Centennial Time Scale Incorporation of Charcoal into Soil. PLoS ONE, Vol. 9, e91114. Czernik, S. and Bridgewater, A.V. (2004) Overview of Applications of Biomass Fast Pyrolysis Oil. Energy Fuels, Vol. 18(2), pp. 590–598. Dehkhoda, A.M., N. Ellis, and E. Gyenge. (2013) Activated Biochar: a green and low-cost electrode material for capacitor applications. Abstract #611, 244th Electrochemical Society. de Ruiter, G., S. Helle, M. Rutherford., B. (2014). Industrial and Market Development of Biochar in BC. Pacific Institute for Climate Solutions Whitepaper. Last accessed March 8, 2014 http://pics.uvic.ca/research/publications/white-papers de Miranda, R.C., Bailis, R., and Vilela, A. de O. (2013). Cogenerating electricity from charcoaling: A promising new advanced technology. Energy for Sustainable Development 17, 171–176. Dymond, C.C., B.D. Titus, G. Stinson, W.A. Kurz. (2010). Future quantities and spatial distribution of harvesting residue and dead wood from natural disturbances in Canada. Forest Ecology and Management, Vol. 260, pp. 181–192. Emmerich, F.G. and CA. Luengo. (1996). Babassu charcoal: A sulfurless renewable thermoreducing feedstock for steelmaking. Biomass and Bioenergy, Vol. 10, pp. 41–44. Engineering Toolbox. (2014) Classification of Coal. Engineeringtoolbox.com. Last accessed March 8, 2014 at http://www.engineeringtoolbox.com/classification-coal-d_164.html 47 Entegris. (2013). Properties and characteristics of graphite. Entegris.com, Last accessed March 8, 2014 at http://www.engineeringtoolbox.com/classification-coal-d_164.html https://www.entegris.com/resources/assets/6205-7329-0513.pdf Environment Canada. (2013). GHG Emissions Quantification Guidance, Fuel Combustion. Last accessed April 8, 2014 http://www.ec.gc.ca/gesghg/default.asp?lang=En&n=AC2B7641-1. Felber, R., R. Hüppi, J. Leifeld, and A. Neftel. (2012). Nitrous oxide emission reduction in temperate biochar-amended soils. Biogeosciences Discussions, Vol. 9, pp. 151-189. Fletcher, A., Smith, M., Heinemeyer, A., Lord, R., Ennis, C., Hodgson, E., and Farrar, K. (2014). Production Factors Controlling the Physical Characteristics of Biochar Derived from Phytoremediation Willow for Agricultural Applications. Bioenerg. Res. Vol. 7, pp. 371–380. Gaunt, J.L., and Lehmann, J. (2008). Energy Balance and Emissions Associated with Biochar Sequestration and Pyrolysis Bioenergy Production. Environmental Science & Technology, Vol. 42, pp. 4152–4158. Hamer, U., B. Marschner, S. Brodowski, W. Amelung. (2004). Interactive priming of black carbon and glucose mineralization. Organic Geochemistry, Vol. 35, pp. 823–830. Hammond, J., Shackley, S., Sohi, S., and Brownsort, P. (2011). Prospective lifecycle carbon abatement for pyrolysis biochar systems in the UK. Energy Policy, Vol. 39, pp. 2646– 2655. He, Y., Zhou, X., Jiang, L., Li, M., Du, Z., Zhou, G., Shao, J., Wang, X., Xu, Z., Hosseini Bai, S., et al. (2017). Effects of biochar application on soil greenhouse gas fluxes: a meta-analysis. GCB Bioenergy 9, 743–755. Hina, K. (2013) Application of Biochar Technologies to Wastewater Treatment. PhD dissertation, Massy University, Palmerston North, New Zealand. Huang, Y.-F., Syu, F.-S., Chiueh, P.-T., and Lo, S.-L. (2013). Lifecycle assessment of biochar cofiring with coal. Bioresource Technology, Vol. 131, pp. 166–171. Huggins, T., Wang, H., Kearns, J., Jenkins, P., and Ren, Z.J. (2014). Biochar as a sustainable electrode material for electricity production in microbial fuel cells. Bioresource Technology, Vol. 157, pp. 114–119. 48 Ibarrola, R., Shackley, S., and Hammond, J. (2012). Pyrolysis biochar systems for recovering biodegradable materials: A lifecycle carbon assessment. Waste Management, Vol. 32, pp. 859–868. IEA. (2007). IEA Bioenergy Annual Report (2006). International Energy Agency, Paris. Last accessed Dec 24, 2015 at http://www.globalbioenergy.org/uploads/media/0707_IEA__Bioenergy_annual_report.pdf IGCL (2014). Activated Carbon. Indo Germans carbon limited. Online resource, last accessed Feb 10, 2014 at http://www.igcl.com/php/activated_carbon.php Indian Oil. (2016). Raw Petroleum Coke (RPC). Last accessed September 15, 2018 at https://www.iocl.com/Products/RawPetroleumCokeSpecifications.pdf Inyang, M., Gao, B., Yao, Y., Xue, Y., Zimmerman, A.R., Pullammanappallil, P., and Cao, X. (2012). Removal of heavy metals from aqueous solution by biochars derived from anaerobically digested biomass. Bioresource Technology, Vol. 110, pp. 50–56. ISOa. (2006) ISO 14040:2006 Environmental management - Lifecycle assessment - Principles and framework. International organization for standardization, Geneva, Switzerland. ISOb. (2006) ISO 14044:2006 Environmental management - Lifecycle assessment Requirements and guidelines International organization for standardization, Geneva, Switzerland. Jeffery, S., Verheijen, F.G.A., van der Velde, M., and Bastos, A.C. (2011). A quantitative review of the effects of biochar application to soils on crop productivity using metaanalysis. Agriculture, Ecosystems & Environment, Vol. 144, pp. 175–187. Jiang, J., Zhang, L., Wang, X., Holm, N., Rajagopalan, K., Chen, F., and Ma, S. (2013). Highly ordered macroporous woody biochar with ultra-high carbon content as supercapacitor electrodes. Electrochimica Acta, Vol. 113, pp. 481–489. Jin, H., Wang, X., Gu, Z., and Polin, J. (2013). Carbon materials from high ash biochar for supercapacitor and improvement of capacitance with HNO3 surface oxidation. Journal of Power Sources, Vol. 236(15), pp. 285–292. Kammann, C., S. Ratering, C. Eckhard, and C. Müller. (2012). Biochar and hydrochar effects on greenhouse gas (carbon dioxide, nitrous oxide, methane) fluxes from soils. Journal of Environmental Quality, Vol. 41, pp. 1052–1066. 49 Klasson, K.T., Lima, I.M., Boihem, L.L., and Wartelle, L.H. (2010). Feasibility of mercury removal from simulated flue gas by activated chars made from poultry manures. Journal of Environmental Management, Vol. 91, pp. 2466–2470. Klasson, K.T., Boihem, L.L., Uchimiya, M., and Lima, I.M. (2014). Influence of biochar pyrolysis temperature and post-treatment on the uptake of mercury from flue gas. Fuel Processing Technology, Vol. 123, pp. 27–33. Koppejan, J. and S. van Loo. (2012) The Handbook of Biomass Combustion and Co-firing. Earthscan Ltd, Published by Taylor & Francis Ltd, London, UK. Kumarappan, S. S. Joshi, and H.L. MacLean. (2009). Biomass Supply for Biofuel Production: Estimates for The United States and Canada. BioResources, Vol. 4(3), pp. 1070-1087. Lamlom, S.H., and Savidge, R.A. (2003). A reassessment of carbon content in wood: variation within and between 41 North American species. Biomass and Bioenergy, Vol. 25, pp. 381–388. Lee, Y., Park, J., Ryu, C., Gang, K.S., Yang, W., Park, Y.-K., Jung, J., and Hyun, S. (2013). Comparison of biochar properties from biomass residues produced by slow pyrolysis at 500°C. Bioresource Technology 148, 196–201. Lehmann, L. and S. Joseph (Eds.). (2009). Biochar for Environmental Management: Science and Technology, Earthscan Ltd, London, UK. pp. 76-77. Lehmann, L. and S. Joseph (Eds.). (2015). Biochar for Environmental Management: science, technology and implementation, Routledge, New York, NY. UN Environment. (2018). Carbon Footprint. Life Cycle Initiative, Paris France, Last accessed January 11, 2018 at https://www.lifecycleinitiative.org/starting-life-cycle-thinking/lifecycle-approaches/carbon-footprint/. Lorenz, K., and Lal, R. (2014). Biochar application to soil for climate change mitigation by soil organic carbon sequestration. J. Plant Nutr. Soil Sci. 177, 651–670. Malghani, S., Gleixner, G., and Trumbore, S.E. (2013). Chars produced by slow pyrolysis and hydrothermal carbonization vary in carbon sequestration potential and greenhouse gases emissions. Soil Biology and Biochemistry Vol. 62, pp.137–146. Malone, S. (2010). Characterization of sulfur in biochar. University of Colorado at Boulder, Poster presentation. Last accessed May 1, 2013 at http://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1008&context=star. 50 Matovic, D. (2011). Biochar as a viable carbon sequestration option: Global and Canadian perspective. Energy, Vol. 36, pp. 2011–2016. Mohanty, P., Nanda, S., Pant, K.K., Naik, S., Kozinski, J.A., and Dalai, A.K. (2013). Evaluation of the physiochemical development of biochars obtained from pyrolysis of wheat straw, timothy grass and pinewood: Effects of heating rate. Journal of Analytical and Applied Pyrolysis 104, 485–493. Mukome, F.N.D., X. Zhang, LCR. Silva, J. Six, and SJ. Parikh. (2013). Use of Chemical and Physical Characteristics To Investigate Trends in Biochar Feedstocks Journal of Agricultural and Food Chemistry, Vol. 61(9), pp. 2196-2204. Nanda, S., Dalai, A.K., Berruti, F., and Kozinski, J.A. (2016). Biochar as an Exceptional Bioresource for Energy, Agronomy, Carbon Sequestration, Activated Carbon and Specialty Materials. Waste Biomass Valor 7, 201–235. NCE. (2015). Turning Canadian Wood Waste into Green Bio-coal. Networks of Centres of Excellence. Last accessed Sept 18, 2016 at http://www.nce-rce.gc.ca/ResearchRecherche/Stories-Articles/2015/GreenBioCoal-BiocharbonVert_eng.asp. Norgate, T., Haque, N., Somerville, M., and Jahanshahi, S. (2012). Biomass as a Source of Renewable Carbon for Iron and Steelmaking. ISIJ International 52, 1472–1481. PCTa. (2012). What we do, Pacific Carbon Trust. Last accessed Dec 18, 2012 at http://www.pacificcarbontrust.com/what-we-do/ PCTb. (2013). November 19, 2013 News Release: First Core Review decisions announced. Last accessed Dec 20, 2013 at http://pacificcarbontrust.com/newsroom/newsreleases/first-core-review-decisions-announced/. PCTc. (2012). Bio-coal’s Potential for BC’s Economy and Environment, Pacific Carbon Trust. Last accessed Dec 18, 2012 at http://www.pacificcarbontrust.com/newsroom/news-releases/bio-coal-s-potential-forbc-s-economy-and-environment/. Peters-Stanley, M., and K., Hamilton. (2012). Developing Dimension: State of the Voluntary Carbon Markets 2012, Ecosystem Marketplace and Bloomberg New Energy Finance. Last accessed Feb 14, 2013 at http://www.foresttrends.org/publication_details.php?publicationID=3164. 51 Pourhashem, G., Spatari, S., Boateng, A.A., McAloon, A.J., and Mullen, C.A. (2013). Lifecycle Environmental and Economic Tradeoffs of Using Fast Pyrolysis Products for Power Generation. Energy & Fuels, Vol. 27, pp. 2578–2587. Ralevic, P. and D.B. Layzell. (2006). An Inventory of the Bioenergy Potential of British Columbia. BIOCAP Canada Foundation. Last accessed Feb 9, 2012 at www.biocap.ca/images/pdfs/BC_Inventory_Final-06Nov15.pdf. Roberts, K.G., Gloy, B.A., Joseph, S., Scott, N.R., and Lehmann, J. (2010). Lifecycle Assessment of Biochar Systems: Estimating the energetic, economic, and climate change potential. Environmental Science & Technology, Vol. 44, pp. 827–833. Rondon, M.A., D. Molina, M. Hurtado, J. Ramirez, J. Lehmann, J. Major, E. Amezquita. (2006). Enhancing the productivity of crops and grasses while reducing green-house gas emissions through biochar amendments to unfertile tropical soils. Proceedings of the 18th World Congress of Soil Science, July 9–15, Philadelphia, PA, USA, pp. 138–168. Rousset, P., Caldeira-Pires, A., Sablowski, A., and Rodrigues, T. (2011). LCA of eucalyptus wood charcoal briquettes. Journal of Cleaner Production, Vol. 19, pp. 1647-1653. Shabbir, Z. T.H.S. Douglas, K.S. Denny, A. Ng. (2012). Hybrid optimisation model for the synthesis of sustainable gasification-based integrated biorefinery, Chemical Engineering Research and Design, Vol. 90(10), pp. 1568-1581. Shackley, S., Sohi, S., Brownsort, P., Carter, S., Cook, J., Cunningham, C., Gaunt, J., Hammond, J., Ibarrola, R., and Mašek, O. (2010). An assessment of the benefits and issues associated with the application of biochar to soil. Department for Environment, Food and Rural Affairs, UK Government, London. Last accessed May 16, 2014 at http://www.geos.ed.ac.uk/homes/sshackle/SP0576_final_report.pdf. Singh, B.P., B.J. Hatton, B Singh, and A.L. Cowie. (2010). The role of biochar in reducing nitrous oxide emissions and nitrogen leaching from soil. 19th World Congress of Soil Science, Soil Solutions for a Changing World. Brisbane, Australia. Published on DVD. Singh, B.P., Cowie, A.L., and Smernik, R.J. (2012). Biochar Carbon Stability in a Clayey Soil as a Function of Feedstock and Pyrolysis Temperature. Environ. Sci. Technol. 46, 11770–11778. Sohi, S.P., Krull, E., Lopez-Capel, E., and Bol, R. (2010). Chapter 2 - A Review of Biochar and Its Use and Function in Soil. In Advances in Agronomy, (Academic Press), pp. 47– 82. 52 Sohi, S.P., Loez-Capel, E., Krull, E., and Bol, R. (2009). Biochar's roles in soil and climate change: A review of research needs. CSIRO Land and Water Science Report. Newcastle University. Last accessed Mar 10, 2013 at www.csiro.au/files/files/poei.pdf Sparrevik, M., Field, J.L., Martinsen, V., Breedveld, G.D., and Cornelissen, G. (2013). Lifecycle Assessment to Evaluate the Environmental Impact of Biochar Implementation in Conservation Agriculture in Zambia. Environmental Science & Technology, Vol. 47(3), pp. 1206–1215. Spokas, K.A., W.C. Koskinen, J.M. Baker, D.C. Reicosky. (2009). Impacts of woodchip biochar additions on greenhouse gas production and sorption/degradation of two herbicides in a Minnesota soil. Chemosphere, Vol. 77, pp. 574-581. Spokas, K.A. (2010). Review of the stability of biochar in soils: predictability of O:C molar ratios. Carbon Management Vol. 1, pp. 289–303. Spokas, K.A. (2012). Impact of biochar field aging on laboratory greenhouse gas production potentials. GCB Bioenergy 5, 165–176. Spokas, K.A., DC. Reicosky. (2009). Impacts of sixteen different biochars on soil greenhouse gas production. Annals of Environmental Science, Vol. 3, pp. 179-193. Statistics Canada. (2012). Table 7.2-1 Coal production by province and Table 7.1 Coal exports by province. Energy Statistics Handbook. Last accessed Jan 20, 2012 at www.statcan.gc.ca/pub/57-601-x/2012001/tablelist-listetableaux7-eng.htm. Vadenbo, C.O., Boesch, M.E., and Hellweg, S. (2013). Lifecycle Assessment Model for the Use of Alternative Resources in Ironmaking: LCA Model for Use of Alternative Resources in Ironmaking. Journal of Industrial Ecology, Vol. 17, pp. 363–374. van Zwieten, L., S. Kimber, S. Morris, A. Downie, E. Berger, J. Rust, C. Scheer. (2010). Influence of biochars on flux of N2O and CO2 from Ferrosol. Soil Research, Vol. 48(7), pp. 555–568. Wang, Z., Dunn, JB., Han, J., Wang, M. (2013). Effects of coproduced biochar on lifecycle greenhouse gas emissions of pyrolysis derived renewable fuels. Biofuels, Bioproducts, and Biorefining, Vol. 8(2), pp. 189–204. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications Vol. 1, pp. 1–9. 53 Wozek J.S. and JA. Ricketts. (1994). Metallurgical coal quality - a customer’s perspective. OneMine.org. Last accessed May 1, 2013 at http://www.onemine.org/search/summary.cfm/Metallurgical-Coal-Quality-ACustomersPerspective?d=C7E4AB1E060AEF0B52F1B78595368DFF22AFADFD938E5536A42 D1EAC4B25B625176367&fullText=purpose%20of%20%20quality Yanai, Y., K. Toyota, M. Okazaki. (2007). Effects of charcoal addition on N2O emissions from soil resulting from rewetting air-dried soil in short-term laboratory experiments. Soil Science and Plant Nutrition, Vol. 53, pp.181−188. Yemshanov, D. and D. McKenney. (2008). Fast-growing poplar plantations as a bioenergy supply source for Canada. Biomass and Bioenergy, Vol. 32, pp. 185–197. Yoo, G. and H. Kang. (2011). Effects of Biochar Addition on Greenhouse Gas Emissions and Microbial Responses in a Short-Term Laboratory Experiment. Journal of Environmental Quality, Vol. 41, pp. 1193-1202. Zavalloni, C.G., Alberti, S. Biasiol, G. Delle Vedove, F. Fornasier, J. Liu, A. Peressottia. (2011). Microbial mineralization of biochar and wheat straw mixture in soil: A shortterm study. Applied Soil Ecology, Vol. 50, pp. 45–51. Zhao, L., X. Cao, O. Mašek, A. Zimmerman. (2013). Heterogeneity of biochar properties as a function of feedstock sources and production temperatures. Journal of Hazardous Materials, Vol. 256–257, pp. 1-9. Zimmerman, A. (2010). Abiotic and microbial oxidation of laboratory-produced black carbon (biochar). Environmental Science & Technology, Vol. 44, pp. 1295–1301. Zimmerman, A., B. Gao and M. Ahn. (2011). Positive and negative carbon mineralization priming effects among a variety of biochar-amended soils. Soil Biology and Biochemistry, Vol. 43, pp. 1169–1179. 54 3 CHAPTER 3 – Project 1: Greenhouse gas assessment of a novel pyrolysis retort kiln producing wood-based synthetic coal from sawmill residues, roadside slash, and hybrid poplar feedstocks. 3.1 Abstract A novel pyrolysis retort kiln design was examined for the production of biocoal. This biocoal has similar energetic, chemical, and physical characteristics to fossil coal and petroleum coke, and can be used for substitution. Due to the production novelty, and carbon mitigation potential of this biocoal product, a cradle-to-gate greenhouse gas assessment was performed. Lifecycle assessment methods were applied in compliance with ISO standards and scope-3 carbon accounting. Greenhouse gas emissions of kilograms CO2-equivalent per GJ of energy (kg CO2e/GJ) were quantified for the novel pyrolysis system drawing from the Ecoinvent lifecycle inventory database and calculated in the lifecycle accounting program OpenLCA. Biocoal was examined from three bioenergy feedstock scenarios: roadside slash, sawmill residues, and hybrid poplar crops. A sensitivity analysis was performed to elucidate the most impactful factors. Roadside slash derived biocoal yielded the lowest at gate emissions at -2.1 kg CO2e/GJ for the average case 200 km recovery scenario, while at gate emissions averaged 7.5 kg CO2e/GJ for biocoal derived from sawmill residues, but where data-sourced scenario dependent. Emissions were 4.9 kg CO2e/GJ for hybrid poplar derived biocoal. When comparing biocoal made from sawmill residues to locally produced wood pellets, transportation emissions may be decreased 64% due to biocoal’s higher heating value. When comparing emissions produced for biocoal or wood pellets at gate, biocoal may show a 42% reduction in emissions or up to a 51% increase in emissions, however this is largely dependent on the data-sourced scenarios and their underlying assumptions of emissions allocation. 55 Overall, sourcing feedstock from roadside slash will achieve the greatest reduction in GHGs when methane and nitrous oxide combustion emission-offsets are applied. When sourcing sawmill residues or hybrid poplar for biocoal production, maximizing the lowerheating value will make the largest impact in reducing overall GHG emissions and thus should be a priority. Biocoal has the potential to substantially reduce GHGs compared to wood pellets, especially when transported overseas. 3.2 Introduction Bioenergy is becoming an important alternative to fossil fuels. Bioenergy can produce electricity, domestic and industrial heat, and more specialized products like renewable liquid fuels. Pyrolysis derived bioenergy products such as biochar and biocoal are gaining popularity due to their multiple applications (Lehmann and Joseph 2009 – Chapters 12 – 16; and Nanda et al. 2016). Recently, biochar has seen attention as a bioenergy product because of its chemical and combustion similarities to coal (Bianco 2013; Fick et al. 2013; Suopajärvi and Fabritius 2013; and de Ruiter et al. 2014). For the purpose of this paper’s terminology, biochar, synthetic coal, charcoal, and biocoal are all treated as similar products. It is acknowledged that variation exists with in all of these products, however they all represent a solid charred biomass product. Biochar, commonly related to soil applications, is made from wood residues and is known to be porous and brittle with high crushability (Lehmann and Joseph 2009 – Chapter 2), whereas fossil coal is more solid and resilient to being crushed. With these characteristic differences, both can still possess similar energy content per unit mass. Investigations into biochar as a coal substitute have shown potential, however with common pyrolysis methods, much of the original feedstock carbon is not recovered in the biochar, and contained in the pyrolysis oils and gasses (Nanda et al. 2016). 56 Biochar’s use as a bioenergy fuel will, in part, be determined through its greenhouse gas (GHG) offset potential, and this is dependent on many factors including feedstock (Woolf et al. 2010; Roberts et al. 2010; Hammond et al. 2011; Ibarrola et al. 2012; and Teichmann 2014), byproduct use (Peters et al. 2015; and Dutta and Raghavan 2014), pyrolysis type (Hammond et al. 2011; and Wang et al. 2013) and general parameters such as product and byproduct yields, carbon pricing, and final application. Feedstock sources are an important factor in the production of biochar. They limit production volume through their availability and they can influence biochar’s GHGs and carbon reduction potential. Many biochar GHG assessments and lifecycle assessments have examined numerous feedstock sources (Woolf et al. 2010; Roberts et al. 2010; Hammond et al. 2011; Ibarrola et al. 2012; and Teichmann 2014) and they typically relate to the regional feedstock availability. This research is no different and will examine 3 feedstocks: sawmill residues, roadside slash, and hybrid poplar in the province of British Columbia, Canada. Sawmill residues (including hog fuel) are commonly produced around the province because of a well-established forestry industry, however residues may be fully committed or even stranded in areas without economical access to market. Roadside slash residues are an underrecovered resource that are commonly burned in the field with potential impacts on air quality, and hybrid poplar represents a potential high yielding bioenergy crop that could provide additional, dedicated, and stable feedstocks for biochar producers. Many biochar GHG assessments use pre-existing data for biochar production yields (Fick et al. 2013; Dutta and Raghavan 2014; Chan et al. 2015; Suopajärvi et al. 2014; and Peters et al. 2014) and some have analyzed actual kilns (Harsono et al. 2013; Clare et al. 2014; Sparrevik et al. 2015; Rosas et al. 2015). Some research has been performed on novel pyrolysis retort kilns, however the majority of research has analyzed batch kilns (Iribarren 57 et al. 2012; Rosas et al. 2015) and earth-mound kilns (Sparrevik et al. 2012; Sparrevik et al. 2015). Norgate et al. (2012) modeled their research from a novel pyrolysis retort kiln designed by the Commonwealth Scientific and Industrial Research Organisation of Australia, with the intention of maximizing biochar production with slow pyrolysis. Related to this study, a similar goal has been sought by a Canadian startup company called BC Biocarbon. Their novel pyrolysis system produces a biocoal product that is essentially a synthetic coal with similar energy density and physical characteristics. Their biocoal product recovers approximately 75% of the energy content from the initial feedstock, starting with an average 45% moisture content, and increasing the bulk density from feedstock at 240 kg/m3 to 700 kg/m3 for the biocoal. BC Biocarbon aims to target coal substitution applications while eventually competing with the wood pellet industry for bioenergy exports. This research aims to compare the GHG emissions from BC Biocarbon’s biocoal product, made from sawmill residues, roadside slash and hybrid poplar. Additionally, biocoal GHGs will be compared to wood pellets produced at gate in Kamloops, BC, Canada, and shipped to Rotterdam, Netherlands (NL). Finally, a sensitivity analysis will be performed to assess the factors that most influence these results. 3.3 Methods 3.3.1 Goal and scope ISO 14040 protocol was adapted for this GHG assessment as similarly performed by Norgate and Langberg (2009), Hammond et al. (2011), Rousset et al. (2011), Norgate et al. (2012), and Pourhashem et al. (2013). Greenhouse gas assessments were outlined in four phases similar to the International Association for Standardization ISO 14040 and ISO 14044 protocols (ISOa 2006; and ISOb 2006). These standards are equivalent to ‘Scope 3’ GHG 58 assessment protocols, which include value chain (input and output) emissions from direct and indirect upstream and down sources. The primary goal of this research was to assess the cradle-to-gate lifecycle GHG emissions of BC Biocarbon’s biocoal product, which could then be used to assess the GHGs of biochar for Project 3, through the application of GHG emissions by mass allocation. The primary scope of this project is shown in Figure 3.1 and begins with the collection of feedstocks and ends at the plant gate. Comparison of biocoal GHGs to BC produced wood pellets was also performed. This was done to examine the potential carbon reduction advantage of biocoal, at gate (Kamloops) and delivered to Rotterdam, NL. Rotterdam is a major port destination for BC wood pellets and was previously used in Pa et al. (2012) for a wood pellet GHG lifecycle assessment. The functional unit of this study was defined as the CO2-equivelent (CO2e) emissions per gigajoule (GJ) of biocoal produced by BC Biocarbon and emissions are allocated on a mass basis. 59 Figure 3.1 GHG assessment scope of this project includes all processes within solid boundary are to be accounted for the GHG lifecycle CO2-equivalent emissions. 1 BC Biocarbon reserves intellectual property, including visual representations of the pyrolysis system. 3.3.2 Inventory data collection (Databases, sources, and analysis tools) Identifying all factors that affect the defined scope was performed in the inventory analysis. The analysis collected all relevant information in order to assess biocoal CO2e emissions. 3.3.3 BC Biocarbon pyrolysis system and biocoal product. The pyrolysis system examined in this study was designed by BC Biocarbon and is patent pending for the process and product. The proprietary process primarily produces biocoal, with only biogenic CO2 and water vapor as byproducts/wastes from the system. This contrasts with typical pyrolysis systems that produce large proportions of pyrolysis oils as a co-product to biochar production (IEA 2007), and in other studies, the co-products have been underutilized or considered a waste product with no economic or application value (Harsono et al. 2013; Feliciano-Bruzual 2014; Galgani et al. 2014; and Miller-Robbie et al. 2015). The 60 system investigated reforms and integrates the pyrolysis oils into the final biocoal product, thus increasing the carbon recovery percent compared to biochar production alone. This is a key point of differentiation compared to other biochar production GHG analyses and the first known characterization of this type of biocoal. This is opposed to more commonly thought of torrefied (roasted) biomass made into a different type of biocoal (Agar and Wihersaari 2012). Process details presented are presented in such a manner to protect the intellectual property of BC Biocarbon, but providing independent information to validate. Data for the pyrolysis system was obtained from the BC Biocarbon process flow diagram which showed the engineered mass, energy, and carbon balance. The pyrolysis system and facility was developed in SolidWorks (2010) by BC Biocarbon and modeled as a large-scale plant based off the workings of a pilot and demonstration facility previously built. This research was performed using Ecoinvent LCA database (Ecoinvent 2014), personal communication/industry research, and published data/research, and was modeled within OpenLCA (2015). Items quantified from BC Biocarbon (2015) and included in the GHG assessment were: Materials such as rubber, steel, concrete (Ecoinvent 2014 (GHG values)), construction of buildings (TheStructuralEngineer 2012), production and use of an onsite skidder/loader (Ecoinvent 2014 (GHG values)), electricity from the British Columbia power grid (Ecoinvent 2014 (GHG values)), feedstock driers (Ecoinvent 2014 (GHG values); and Stummer 2015 (Personal communication for system size)), and electric motors (Ecoinvent 2014 (GHG values); Inverterdrive.com 2015a; and Inverterdrive.com 2015b (sizes and mass)). All items were ascribed on either a mass basis in SolidWorks or usage basis, such as for electricity or the skidder/loader. Jungmrirt et al. (2002) concluded mass basis the most appropriate allocation method in wood-based products. All aspects of the biocoal facility and system were assumed to be amortized over a 20-year timeframe (BC Biocarbon 2015). This 61 was set because major retrofits or rebuilds were deemed to be required after 20 years and thus would need to reassess GHG emissions for biocoal production. The large-scale pyrolysis system modelled uses 47 Mg of feedstock at 45% moisture content (25.85 oven dried Mg (ODMg)) to produce 12.2 Mg biocoal product per hour (equaling 0.47 Mg of biocoal per Mg original oven dried feedstock). The biocoal is produced from 50% biochar on a mass basis, while the organic bio-based binder made from the pyrolysis co-products makes up the other 50% of the biocoal. The system is designed around the use of sawmill residues such as hog fuel (a mix of chips, bark and sawdust), however alternative feedstocks such as roadside slash and hybrid poplar are assumed to function in BC Biocarbon’s pyrolysis system in a similar manner. The biocoal produced by BC Biocarbon is chemically and structurally similar to that of coal and contains a mixture of a biochar (wood charcoal) and an organic-based binder made from the same initial feedstock. Characteristics of biocoal made by BC Biocarbon are derived from independent test evaluations. These were an ultimate chemical analysis performed by Loring Laboratories ltd, Calgary, AB and a physical characteristics analysis of varying biocoal samples by James Butler through partnership with National Research Council Canada in Vancouver, BC. And as previously indicated, performance data relating to BC Biocarbon’s pyrolysis system is based on the modelled large-scale system. Therefore, when referring to any biocoal production or characteristics BC Biocarbon (2015) is cited. Biocoal bulk density was set at 800 kg/m3 (BC Biocarbon 2015) and the 3rd party analysis performed by the National Research Council Canada found a carbon content recovery of 75.7% by dry weight. This being energetically condensed approximately 45-50%, and containing 27-39% volatiles; however, both carbon and volatiles can slightly depend on the feedstock and biocoal design parameters. The energy density was found to be 30.0 GJ/Mg 62 higher heating value (HHV) and 29.6 GJ/Mg lower heating value (LHV) (BC Biocarbon 2015). Anthracite coal has an HHV of 32.6 GJ/Mg and bituminous coal ranges from 19.3 32.6 GJ/Mg (ASTM 2008). The biocoal product has an approximate ash content of 3-7% if made from a sawdust, wood trimmings, chips, or hog fuel (BC Biocarbon 2015; and supported by BCMOE 2008). 3.3.4 Biocoal feedstocks The Kamloops region (50.715298, -120.444142) was chosen as the case study location because of its diverse agriculture, energy, and forestry industries, and its geographical proximity to rail lines and the Trans-Canada Highway. Three feedstock scenarios were examined: sawmill residues, roadside slash/slash piles (referred herein as roadside slash), and hybrid poplar as a bioenergy crop. All feedstocks are assumed to be limited in green material, such as leaves and needles, as they are known to contain higher ash content. This is especially true in biochar and biocoal, where ash contents proportionally rise with increasing pyrolysis temperatures as more carbon is lost, leaving behind the ash residues (Crombie et al. 2013). Forest products and combusted forest residues are considered carbon neutral in the British Columbia Greenhouse Gas Inventory. However other activities, such as permanent road construction, harvesting, silviculture practices, and general fossil fuel combustion are accounted in total GHGs (BC MOE 2012). These production emissions are defined as anthropogenic and are thus quantified in this assessment. Ecosystem emissions, the emissions released or sequestered through the natural cycle of our forests, were not included in this assessment. The primary source of biomass feedstock reported in this paper is from sawmill waste and mainly considered to be hog fuel. However, depending on the facility, differing proportions of sawdust, wood trimmings, chips, and bark is acknowledge and may impact 63 overall system performance to an unknown amount. Greenhouse gas values for sawmill residues were obtained from Western Canada GHG assessments that sourced upstream GHG values from the feedstock supply chain from pre-harvest operations to delivery at mill (Sambo 2002). Emissions accounted were from silviculture, camp work, and diesel-powered machinery for falling, onsite processing (trimming), skidding, and transportation. Sawmill operation emissions were obtained from (Nyboer 2008). This was similar to methods found in Pa et al. (2012) and is used as a primary comparison paper for bioenergy shipments to Europe. To better test the variability of GHG emissions for the biocoal product, a second source was used for emissions from sawmill residues. Athena (2018) quantified the GHG emissions of the Canadian softwood supply chain from fifteen softwood lumber production facilities, while also presenting a co-current breakdown of all sawmill wood residues, including bark, planer shavings, sawdust, pulp chips, trim ends, chipper fines, and wood waste. These residues were allocated by mass and percent usable amounts. The value of GHGs were presented and used as CO2e based on the IPCC (2006) protocol. Allocation of sawmill residue emissions were needed to be derived from Sambo (2002), Nyboer (2008), and Athena (2018). Each paper or report presented values in m3 wood product and not in Mg residues but was translated to Mg through 428 kg/m3 derived from Athena (2018). Emissions reported in Nyboer (2008) were ascribed to finished lumber with no reference to already partitioned residue emissions. Because of this, finished lumber emissions were assumed to represent the total mass of both finished lumber and residues from the original whole logs. Emissions were then divided as shown in Table 3.1 but allocated to 1.57 Mg of sawmill residues. Table 3.1 shows the sawmill residue allocation and values for each data source. 64 Table 3.1 Original product emissions taken from sources, applied percent allocation, and resulting values used for this assessments sawmill residues. All m3 values are translated to kg through 428 kg/m3 derived from Athena (2018) mass basis for inputs, outputs, and residues. Source Original product emissions Sambo 2002 9.37 kg CO2e / m3 harvested wood logs. 0.0008 kg CH4 / m3 harvested wood logs. 0.0021 kg N2O / m3 harvested wood logs. Nyboer 2008 Athena 2018 9.35 kg CO2e / m3 finished wood output2 43.35 kg CO2e / m3 surfaced dried lumber Percent allocated to sawmill residues 66%1 (34% applied for roadside slash residues) 61%3 Value and unit measurement for value used 14.45 kg CO2 / Mg harvested wood 0.0012 kg CH4 / Mg harvested wood 0.0032 kg N2O / Mg harvested wood 8.52 kg CO2e / Mg sawmill residues 61%3 159.3 kg CO2e / Mg sawmill feedstock residues 61% minus 34% 105.4 kg CO2e / Mg sawmill feedstock from roadside residues with forestry residues estimate slash residues removed 1Mass allocation of 66% is based on the harvested logs proportion from original stand biomass (MacDonald 2006). 2Allocation of emissions were reported as, but were assumed to represent all lumber and residues based on Nyboer (2008) methods. 3Mass allocation of 61% is based on percent residues from harvested logs as calculated from Athena (2018). Athena (2018) and Nyboer (2012) presented values only in CO2e. This simplifies the comparison, however it limited the specificity of the analysis, as non-CO2 GHGs were not able to be updated to 2013 IPCC values like was able in Sambo (2002). Forestry harvest emissions were ascribed based on BC specific data in Sambo (2002) (pre-harvest, logging, camp and silviculture operations minus transportation, which was included in sawmill residues), and similarly supported by Johnson et al. (2007) in the Pacific Northwest. Emissions used from Sambo (2002) were based on a mass allocation of 34% average roadside residual proportion from original stand biomass (MacDonald 2006). Roadside slash recovery was applied in OpenLCA (2015) using the Ecoinvent database (Ecoinvent 2014) from Lindroos et al. (2011). Lindroos et al. examined GHG emissions for 3 recovery distance scenarios (100 km, 200 km, and 300 km) for roadside slash recovery. The assessment examined the use of industrial machinery, including grapple loader, mobile grinder, front-end wheel loader, subsequent relocation of mobile machinery, and feedstock transport trucks. This research focused on the data presented for ‘hog fuel’ as it is 65 the method currently employed by BC forestry companies for roadside slash recovery. Additional categories of varying transport distances were examined and data from cutblocks of 50-10,000 m2 (10,000 m2 = 1 hectare) were used. Fifty-10,000 m2 data was deemed most suitable due to the examination of cutblock sizes measured from satellite imagery surrounding the Kamloops region (measured in Google Maps 2015). In BC, roadside slash is usually combusted in the field as waste. The resulting combustion and smoldering releases high levels of tars (BC MOE 2012) and releases N2O, and CH4 from incomplete combustion (Lee et al. 2010; and EPA 1996). Emission reduction offsets were applied to the model based on roadside slash on-site combustion emission factors per Mg biomass, and subsequently converted per GJ (Lee et al. 2010; and supported by EPA 1996). Global warming potentials used for emission reductions, included methane (CH4) and nitrous oxide (N2O), and were updated from IPCC 1996 to IPCC (2013) guidelines. Hybrid poplar feedstock GHG values were obtained from an LCA for bioenergy crops from Hillier et al. (2009) and modified to better represent the estimated yield performance in Kamloops for the common hybrid poplar species Populus trichocarpa x deltoides. GHG emissions included all aspects of crop production from plantation to harvest and including harvest machinery. Fertilizers were modeled at 100 kg/10,000 m2/year of synthetic nitrogen as similar to Hillier et al. (2009) and emissions from soil N are modeled from IPCC Tier 1 land use where 1% of nitrogen applied is converted and emitted as N2O. Nitrogen fertilizer production (urea ammonium nitrate; 32% nitrogen content) and nitrous oxide emissions were applied in OpenLCA per ODMg biomass (Ecoinvent 2014). Fertilizing by broadcast spreader was also modeled per ODMg (Ecoinvent 2014). Similar to Hillier et al. (2009) no irrigation was assumed. This was for three reasons. Primarily the region that is proposed for Hybrid poplar plantation is on the banks of the 66 Thompson River and should have access to ground water and the river ground water system. Secondly, poplar trees readily grow wild in the proposed areas. And third, if irrigated, water pumped with electricity provided by BC Hydro would be very low carbon intensity. This is because the primary source of power is provided by hydroelectricity (11 kg CO2/MWh; BC Hydro 2016). Hybrid poplar yield was set at 14.44 oven dried Mg (ODMg)/10,000 m2/year reflecting the average of sourced data and personal feedback from Hillier (2015), shown in Table 3.2. Yields were also based on a crop cycle of 20 years, and 4-year harvest cycle (5 harvests) before full replanting is needed (Van Oosten 2015 (Personal communication; BC hybrid poplar industry researcher)). Table 3.2 Assumed hybrid poplar 4-year yield set for this project, and showing referenced values drawn upon. Hybrid poplar yield set in this paper Oven dried Mg (ODMg)/10,000 m2/year 14.44 Hybrid poplar yield average in the United States Pacific Northwest (Berguson et al. 2010) Oven dried Mg (ODMg)/10,000 m2/year 7.61-21.28 Hybrid poplar yield range in Southern Sweden (DeBell et al. 1996) Oven dried Mg (ODMg)/10,000 m2/year 5-20 Hybrid poplar yield range in the UK (Hillier et al. 2009) Range and (average) Oven dried Mg (ODMg)/10,000 m2/year 5-16 (9 ±3.0) Land use change for hybrid poplar was examined by use of the land transformation data in Ecoinvent (2014) rather than from Hillier et al. (2009). This was done on recommendation through personal communication with Hillier (2015). Land use was scenario tested and changed from human-made pasture to forest intensive, short-cycle. 67 3.3.5 Biomass and Biocoal transportation Transportation was segmented into three sections, from feedstock source including sawmill, forest roadside, and hybrid poplar plantation to the assumed Kamloops biocoal facility, biocoal facility to Delta, BC (GCT Deltaport Terminal), and from Delta to Rotterdam, NL. The biocoal facility is assumed to be adjacent to an existing rail line in North Kamloops and assumed to not have emissions associated. This is similar to many existing BC pellet plants, including Pinnacle Renewable Energy Inc in Armstrong, Williams Lake, Meadowbank, Premium Pellets in Vanderhoof, and Pacific BioEnergy in Prince George. Sawmill residue transport distances were set at 212 km round trip based on values determined by Sambo (2002) and industry feedback (Cooper 2015 (Personal communication); and Buker 2015 (Personal communication)). Distances were applied in OpenLCA as a >32 metric Mg freight lorry with EURO4 emissions standards (Ecoinvent 2014) as this reflected the closest fleet performance of North American freight lorries. Sambo (2002) did assess their own emissions for transportation, however for consistency with roadside slash and other freight lorry transportation their emission values were not used, but distances were. Road freight includes allocations for road construction and maintenance, diesel combustion, truck and trailer manufacturing and maintenance. Forest roadside and hybrid poplar plantation feedstocks were similarly modeled for freight lorry transport, although they were tested at 100, 200, 300 km for roadside slash, and 160 km on average for hybrid poplar. Hybrid poplar distances were set at 160 km round trip because all major agricultural regions surrounding Kamloops can be reached within an average 80 km distance. Given the similar physical characteristics to coal, biocoal was assumed transported by rail and ocean in the same manner as thermal and metallurgical coal mined in BC. Rail freight transportation of biocoal to GCT Deltaport, Delta, BC was digitally measured with Google 68 Maps (2015) along existing active rail lines and found to be 436 km (when measured with major roads the distance was negligibly different at 441 km). Rail freight includes allocations for track construction and maintenance, diesel combustion, train and car manufacturing and maintenance based per Mg-km US rail shipping for a goods-train with a weight of 1,000,000 Mg (Ecoinvent 2014). Marine transportation was found to be 16,471 km from GCT Deltaport (international coal and cargo port), Delta, BC to Rotterdam (Searates.com 2015), and calculated per Mg-km. Marine transportation was calculated based on a diesel transoceanic tanker of 150,000 dead weight tonnage (similar to coal tankers at GCT Deltaport), and includes its construction and maintenance of the port (Ecoinvent 2014). 3.3.6 GHG assessment This GHG assessment used information and assumptions collected in the inventory analysis and synthesized the lifecycle assessment GHG analysis in OpenLCA (OpenLCA, 2014). Greenhouse gas emissions were quantified and compared in a 100-year global warming potential (GWP) in kg CO2e/GJ biocoal based on the IPCC 2013 report. IPCC metrics were previously used for GHG assessments (Rousset et al. (2011); Pourhashem et al. (2013); Wang et al. (2013); Vadenbo el al. 2013; and others). A sensitivity analysis was performed to address variability in lifecycle factors that constituted more than 1% of total emissions, and was explored with ±25% change to each factor. Graphs were created in and exported from Microsoft Excel (2011). Sample calculations and key data are presented in Appendix 1 Supplementary Information. 69 3.4 Results Results are organized into the three different feedstocks, with sawmill residues representing the primary in-depth analysis. 3.4.1 Sawmill residue feedstock Figure 3.2 shows the net GHG in kg CO2e/GJ for biocoal produced at gate and Rotterdam from sawmill residues. The largest emissions were seen with data sourced from Athena (2018) and the smallest from Sambo (2002) and Nyboer (2008). At Gate Biocoal GHGs from Sawmill Residues (kg CO2e/GJ) At Rotterdam 16.0 14.0 13.4 11.7 12.0 9.6 10.0 7.8 8.0 6.0 4.3 4.0 2.5 2.0 0.0 Athena 2018 Athena 2018 with Removed Forestry Residues Sambo 2002 and Nyboer 2008 Athena 2018 Athena 2018 with Removed Forestry Residues Sambo 2002 and Nyboer 2008 Referenced data sources for feedstock Figure 3.2 Calculated net biocoal GHG emission scenarios in kg CO2e/GJ biocoal at gate (Kamloops, BC) and at Rotterdam. Scenarios are marked with the corresponding data sources. Percent allocation of biocoal GHG emissions delivered to Rotterdam is shown in Figure 3.3. The primary source of emissions comes from the production of sawmill residues and specifically the upstream forestry activity and harvest. Second to this is the emissions associated with sawmill activities, and transportation via transoceanic tanker from Delta, BC 70 to Rotterdam, NL. The lowest emissions were contributed from the biocoal production facility Biocoal GHG Breakdown from Sawmill residues (based on Pa et al. 2012) and electricity. 26 14 9 1 17 Sawmill Residues - Upstream forestry and harvest 24 Sawmill Residues - Sawmill activities 2 44 Transportation, Freight Lorry Forest to Sawmill to Biocoal plant 24 20 2 Infrastructure, Biocoal Plant Electricity, BC Grid 3 0% 10% 20% 30% 40% 50% 60% 70% 80% Percent allocation of GHGs 90% 100% Transportation, Train, Kamloops to GCT DeltaPort, Delta Transportation, Tanker, DeltaPort, Delta to Rotterdam, NL Figure 3.3 Percent allocation of biocoal GHG emissions for sawmill residue emissions within the Sambo (2002) and Nyboer (2008) derived results. A sensitivity analysis across various factors affecting biocoal GHG emissions is shown in Figure 3.4. The most influential factor was changes to the biocoal GJ lower heating value (LHV) followed by emissions released from the production of sawmill residues associated to upstream forestry activities and harvest. The lowest sensitive factor was electricity use and biocoal production infrastructure. 71 10% Sawmill Residues - Upstream forestry and harvest Output Percent Change of Biocoal GHGs 8% Sawmill Residues - Sawmill activities 6% 4% Transportation, Freight Lorry Forest to Sawmill to Biocoal plant 2% Transportation, Freight Train Kamloops to GCT DeltaPort, Delta 0% -2% Transportation, Freight Tanker, DeltaPort, Delta to Rotterdam, NL -4% Infrastructure, Biocoal plant -6% -8% Electricity, BC Grid -10% -25% Biocoal GJ LHV adjustment Input Percent Change (±25% from base case) Figure 3.4 Sensitivity analysis of biocoal GHG emissions made from sawmill residue feedstock from within the Sambo (2002) and Nyboer (2008) derived results. Values presented at 0% are rounded down. Input factors were adjusted by ±25% to derive the output percent change. 3.4.2 Roadside slash Figure 3.5 represents the net effect on GHGs for biocoal produced from roadside slash feedstock. Net GHGs shown, and particularly negative values, represent the emissions savings (reductions) from reduced CH4 and N2O from not combusting roadside slash and subtracting that from the production and transportation emissions of biocoal (release of emissions). The single positive value is still a low GHG value, however it is a net release of emissions rather than a net reduction in emissions like the other scenarios. 72 Net biocoal GHGs from Roadside Slash (kg CO2e/GJ) 2.00 1.00 Net CO2e/GJ biocoal At Rotterdam 1.31 Net CO2e/GJ biocoal At Gate 0.00 -0.31 -0.44 -1.00 -2.00 -1.94 -2.06 -3.00 -4.00 -3.69 100 km 200 km 300 km Roadside Slash Recovery Distance Figure 3.5 Calculated net biocoal GHGs in kg CO2e/GJ biocoal from roadside slash feedstock, at gate, at Rotterdam, and contrasting varying feedstock recovery distances. Example calculation can be found in Appendix 1 Supplementary Information Figure SI1-6. Percent allocation of biocoal GHGs at gate and delivered to Rotterdam are shown in Figure 3.6. The emissions offset of roadside slash is the largest factor regarding the emissions associated with roadside slash residues, while second to this, the recovery and delivery of residues to the biocoal plant. Similar to sawmill residues, biocoal plant infrastructure and electricity play minor roles in both scenarios. 73 Biocoal GHG Breakdown from Roadside Slash Roadside slash combustion emissions offset At Gate -6 0% 4 -58 37 Roadside slash preharvest activity emissions 1 At Rotterdam 4 -51 33 5 Roadside slash collection and transportation emissions to Biocoal facility 7 Infrastructure, Biocoal plant Transportation, Train, Kamloops to GCT DeltaPort, Delta 0 -4 0% -2 0% 0% 20% Percent allocation of GHGs 40% 60% Transportation, Tanker, DeltaPort, Delta to Rotterdam, NL Figure 3.6 Percent allocation of biocoal GHG emissions made from roadside slash. Both scenarios are relative to their own results and are based on a 200-km residue recovery distance. Negative values indicate the emissions savings or reductions from current business as unusual combustion of roadside slash residues, while positive values indicate an increase of emissions. A sensitivity analysis across various factors affecting biocoal GHGs is shown in Figure 3.7. The most influential factor was changes to the slash pile combustion emissions offset, followed by emissions released from roadside slash recovery. The lowest sensitive factor was electricity use and then BC Biocarbon plant infrastructure. 74 Slash Pile Combustion Emissions offset (N2O, CH4) Output Percent Change of Biocoal GHGs 30% Roadside slash collection and transportation emissions to Biocoal plant 20% Roadside slash preharvest activity emissions 10% Transportation, Train Kamloops to GCT DeltaPort, Delta 0% Transportation, Tanker, DeltaPort, Delta to Rotterdam, NL -10% Infrastructure, Biocoal plant -20% Electricity, BC Grid -30% -130% Biocoal GJ LHV adjustment Input Percent Change (±25% from base case) Figure 3.7 Sensitivity analysis of biocoal GHGs made from roadside slash feedstock delivered to Rotterdam. Input factors were adjusted by ±25% to derive the output percent change. Lines slash pile combustion emission offsets have been truncated, and output percent change noted for better visualization of other factors. 3.4.3 Hybrid poplar feedstock Estimated GHG emissions for biocoal produced from hybrid poplar feedstock are shown in Figure 3.8. Emissions were the same between biocoal with and without land use change delivered to Rotterdam, whereas the lowest emissions came from biocoal at gate and without land use change. 75 Biocoal GHGs from Hybrid Poplar (kg CO2e/GJ) 7.00 6.70 6.70 6.00 4.94 5.00 4.00 3.00 2.00 1.00 0.00 Without Land Use Change (At Rotterdam) With Land Use Change (At Rotterdam) Without Land Use Change (At Gate) Figure 3.8 Estimated net biocoal GHG emissions in kg CO2e/GJ from hybrid poplar feedstock at gate (Kamloops, BC) and at Rotterdam with and without land use change. Percent allocation of biocoal GHG emissions at gate (Kamloops), and delivered to Rotterdam, are shown in Figure 3.9. Primary emissions from each scenario come from production and application of N fertilizer in the form of urea ammonium nitrate, while infrastructure and electricity play minor roles in both scenarios. 76 Biocoal GHG Breakdown from Hybrid Poplar At gate with harvest emissions 1 52 Infrastructure, BC Biocarbon Plant 18 Electricity, BC Grid 26 Broadcast Spreader for FerDlizer 11 1 At RoPerdam with harvest emissions 38 14 18 ProducDon of Ammonium Nitrate 11 ProducDon of Urea 15 TransportaDon, Lorry, Field to BC Biocarbon 11 0% 20% 40% 60% 80% Percent alloca+on of GHGs 100% TransportaDon, Train, Kamloops to GCT DeltaPort, Delta TransportaDon, Tanker, DeltaPort, Delta to RoPerdam, NL Figure 3.9 Percent allocation of biocoal GHG emissions from hybrid poplar. Both scenarios are relative to their own results and emissions may not add to 100% due to rounding. A sensitivity analysis across various factors affecting biocoal GHG emissions is shown in Figure 3.10. The most influential factor was changes to the LHV of biocoal followed by hybrid poplar yield adjustments and then production of the ammonium nitrate fraction of fertilizer. The lowest sensitive factors were electricity use, BC Biocarbon plant infrastructure, and broadcast spreading of fertilizer. 77 Output Percent Change of Biocoal GHGs 25% N2O Soil Emissions 20% Hybrid Poplar Land Use Change 15% Broadcast spreading of FerElizer 10% ProducEon of Ammonium Nitrate FerElizer 5% ProducEon of Urea FerElizer 0% TransportaEon, Freight Lorry Field to BC Biocarbon -5% TransportaEon, Train Kamloops to GCT DeltaPort, Delta -10% TransportaEon, Tanker, DeltaPort, Delta to RoPerdam, NL -15% Infrastructure, BC Biocarbon Plant -20% Electricity, BC Grid -25% Biocoal GJ LHV adjustment Input Percent Change (±25% from base case) Hybrid Poplar Yield Adjustment Figure 3.10 Sensitivity analysis of biocoal GHG emissions made from hybrid poplar feedstock delivered to Rotterdam. Input factors were adjusted by ±25% to derive the output percent change. 3.5 Discussion 3.5.1 Comparison of feedstock types to biocoal Comparing the results across all three feedstocks in Figure 3.11, the lowest emissions were found with the use of roadside slash for biocoal production, with sawmill residue sourced biocoal drawing from Sambo (2002) and Nyboer (2008) being the next lowest and closely followed by sawmill residues. Values from Athena (2018) for sawmill residuederived biocoal are shown to be higher than all other scenarios and feedstock sources. The average value of biocoal derived from sawmill residue feedstocks is calculated to be 7.5 kg CO2e / GJ biocoal. This places it above all other feedstock sources and possibly due to the increased steps of processing and transportation. 78 Without the roadside slash emissions offset from the prevention of field combustion, roadside slash emissions would be more similar to the average of other two feedstocks. A comparison to wood pellets is show in Figure 3.11 and further discussed in section ‘3.5.2 Sawmill Residue Feedstock’. Sawmill residues scenarios At Gate Biocoal or wood pellet Produciton Emissions (kg CO2e/GJ) 14 12 Roadside slash scenarios Hybrid poplar scenario Wood pellet comparison scenarios 11.7 10 8 7.8 5.5 6 4 4.9 5.6 6.1 6.9 2.9 2 0 -2.1 Sawmill Athena 2018 Sawmill Roadside slash Roadside slash Hybrid poplar Pa et al. (2012) Pa et al. (2012) Pa et al. (2012) with harvest without land use wood pellet wood pellet wood pellet -2 residues Athena with emissions residues Sambo with harvest 2018 from roadside (2002) and emissions at 200 emissions at 200 change assesment assesment assesment slash residues Nyboer (2008) km recovery km recovery 0% feedstock 8% feedstock 21% feedstock -4 removed without with emissions adjustment adjustment adjustment emissions offset offset Figure 3.11 Comparison graph of the most likely scenarios of biocoal production emissions at gate (kg CO2e/GJ biocoal), and comparison to wood pellets production from Pa et al. (2012) (kg CO2e/GJ wood pellets) (further discussed below in section ‘3.5.2 Sawmill Residue Feedstock’). For roadside slash scenarios, emissions offset represents the reduction of CH4 and N2O by not combusting slash piles in the field. Of the three sensitivity analyses performed, adjustments to the LHV of biocoal had the greatest impact on GHG emissions, except within roadside slash where the field combustion offset was the greatest impacting. This is understandable because the unit process is set in GJ and any increase in energy content will directly change the resulting emissions. Supporting research performed on behalf of BC Biocarbon by National Research Council Canada showed that there was an effect on pelletizing pressure on the final biocoal density. This means that biocoal energy density could be increased with higher pressure when briquetting. Additionally, within the independent analysis, higher fractions of biocoal binder 79 used led to higher LHV, as similarly shown in Prasityousil and Muenjina (2013). Optimizing both the LHV and energy density will ultimately increase efficiencies for energy transportation and decrease proportional GHG emissions; this is most clearly evident in comparison to wood pellets where the biocoal is 1.64 times more energy dense, with similar assumptions of bulk and specific density for the two products. 3.5.2 Sawmill residue feedstock Aside from LHV adjustments, biocoal GHG emissions were most influenced by the production emissions of sawmill residues. This showed about equal contributions from upstream forestry and harvest emissions, and sawmill operations within the scenario sourcing emissions from Sambo (2002) and Nyboer (2008). The two scenarios from Athena likely represents the higher end of feedstock residues, and being around 3 to 4 times higher than the Sambo and Nyboer scenarios. A possible difference is that Athena (2018) was more oriented towards Eastern Canada where tree size may be smaller than in Western Canada. Additionally the difference could also be due to different tree species, and possibly less efficient processing with more fossil fuel use. These all would translate to greater GHGs to recover equivalent amounts of timber, however these are speculative and not definitively known. Emissions are also dependent on the allocated amount of GHGs from the total lifecycle of harvesting forest lumber. In total, approximately 39% of raw logs end up as finished lumber, while the remaining 61% ends up as residues (Athena 2018). This helps to partially explain the high emissions associated to sawmill residues because 61% of all emissions from silviculture to harvest to transportation are allocated to sawmill wastes. However, this would be different in the alternative Athena scenario, where roadside slash residues were removed because their inclusion or exclusion was not mentioned, and therefore was tested as a separate scenario. 80 Values by Athena (2018) represent the most up to date information, however they are not peer-reviewed and the data sources are kept proprietary. On the other hand only Sambo (2002) is peer-reviewed, while Nyboer (2008), like Athena, are institutional reports prepared for industries. Ultimately these papers provide a range of values that can be averaged to try represent the actual value of biocoal production GHGs. In order to compare these findings to another prominent bioenergy product, Pa et al. (2012) was used as a comparison paper for production emissions and delivery overseas. Pa et al. assessed the production GHGs from wood pellets at gate and delivered Rotterdam, NL, and also derived their findings from Sambo (2002) and Nyboer (2008). As shown in Figure 3.11, three scenarios derived from Pa et al.’s finding were developed and represented the feedstock efficiency of the pellet plant. In electricity generation, this is known as the parasitic load. In this case however, feedstock to final product efficiency relates to the throughput of the pellet plant system and was used to reflect proper GHG emission allocations per GJ product, thus could be compared to biocoal. Therefore, in order to supply feedstock with accurate impacts, and compare to Pa et al., they were adjusted back through the pellet production system. That includes the use of some feedstock for fibre drying purposes in order to determine the Mg dried feedstock in to dried product (pellets) out. As introduced above, this was called the ‘Feedstock Efficiency Adjustment”. From personal communication with (Pa 2015), additional non-published supplementary information from Pa et al. (2012) and industry communication, GHG results were tested for 3 feedstock efficiency adjustments: 1.22 (Pa et al. 2012), 1.08 (Reitsma 2015 (Personal communication)), and 1.00 Mg dried feedstock in to dried product out. In the 1.00 Mg case, this was used as a control for Pa et al. (2012) in case the values were already adjusted previously and because some pellet plants in BC do not require onsite feedstock drying because their sawmill residues are at the appropriate moisture content when 81 delivered (such as the Pinnacle Renewable Energy Inc., Armstrong, BC (Author’s first-hand knowledge). The 1.08 feedstock efficiency scenario is the most likely scenario because it was sourced from the President and Chief Operations Officer at Pinnacle Renewable Energy Inc. (Reitsma 2015). Greenhouse gas emissions factors were updated from Pa et al.’s (2012) use of IMPACT 2002+ and IPCC 2001 to the current IPCC (2013) and GHGs were assessed for one Mg dried pellets in Pa et al. (2012) by being backtracked through an LHV of 18 GJ/tonne wood pellets. The feedstock efficiency adjustment used had a linear impact on the assessment of pellet GHGs. This is understandable because it was a proportional impact on the input GHG emissions for sawmill residues. The values found in Pa et al. showed that pellet production emissions at gate sat between the ranges of data found in this project (Figure 3.11). Therefore, depending on which sawmill residue scenario was used for comparing the production of biocoal to pellets, pellets could have a higher or lower production emission. However, with an average of 7.5 kg CO2e/GJ biocoal and an average of 6.2 kg CO2e/GJ wood pellets, biocoal has on average 20% more emissions at gate. However, again, this depends on which data source is compared. Another paper, Magelli et al. (2009), also used residue data from Sambo (2002) and Nyboer (2008) for the production of wood pellets. Their assessment put wood pellet production at 3.6 kg CO2e/GJ wood pellets, which was close to this assessment’s biocoal production scenario based on Sambo and Nyboer at 2.9 kg CO2e/GJ. From Magelli et al.’s brief mention of emissions allocation, it seems that they were more similar to this assessment – appropriately allocating all products and co-products - than to that of Pa et al., at least for upstream forestry and harvest emissions, but unknown for sawmill residue allocations. Transportation use in Pa et al. (2012) was almost identical to what was explored in this analysis. Pa et al. (2012) used 198 km round trip vs 212 km round trip, and seaport to seaport 82 (16,668 km in Pa et al. versus 16,471 km here). For product shipped from railhead to seaport Pa et al. used 840 km versus 436 km here. This transportation difference primarily reflected the selection of bioenergy production plant location, and this was presumably set in Prince George, BC for Pa et al. (2012) versus Kamloops in this assessment. Comparing the 8% feedstock adjustment scenario from Pa et al. (2012) and when equalized for transportation distances to port and to Rotterdam, biocoal can offer an approximate 42% GHG reduction compared to pellets when sourcing emissions from Sambo (2002) and Nyboer (2008). When comparing to Athena (2018) sourced values biocoal would show an approximate 51% increase in emissions, and on average across the three scenarios determined in this assessment, there would be a 7% increase in emissions versus wood pellets. Regardless of the scenario comparisons, which are based on differing assumptions, if one assumes similar residue to product production emissions, the higher LHV of biocoal would allow for reduced shipping emissions and thus more efficient energy transportation to Rotterdam. Lower heating values of wood pellets tend to range from an international minimum standard of 16.5 GJ/Mg (ISO 2013), to 17.0-17.92 GJ/Mg for pure white wood (Strauss 2014; and Melin 2008), and up to 18.0-18.3 GJ/Mg (Buker 2015, industry reported; and Lee et al. 2015). Comparisons for the interpreted results from Pa et al. (2012) were based on high end of 18.1 GJ/Mg versus 29.6 GJ/Mg for biocoal. This means that with a simple comparison based on transportation emissions, biocoal will release 64% fewer emissions per GJ, however as the transportation distances of products reduce, the percent reduction of GHG emissions versus pellets diminishes down to at gate production. As concluded in Pa et al. (2012), and reflected in this assessment, local usage would greatly reduce the total emissions of biomass used for energy. When comparing the use of pellets versus biocoal, pellets may be 83 better suited for local combustion and biocoal for long-distance transportation due to its higher energy density and thus transportation efficiency. 3.5.3 Roadside slash Biocoal (or any biofuel made from roadside slash) greatly benefits from combustion emission-offsets. This is due to the reduction of anthropogenic N2O, and CH4 released from incomplete combustion of forestry slash (Lee et al. 2010; and EPA 1996). One caveat exists within the findings of this research. At this time, and given BC’s policy for GHG accounting of roadside slash combustion, emissions from N2O, and CH4 are not accounted in carbon accounting procedures. These disregards actual emissions being release in the form of N2O, and CH4, and is being subsidized, as BC’s $35/Mg CO2 carbon tax is not recovering the climate change and health costs associated with these emissions. This means that for every 19.5 GJ/Mg roadside slash (Lindroos et al. 2010 higher heating value), or approximately 2 m3 green pine or Douglas fir, the province is not recovering approximately $3 in climate change impact costs (based on roadside slash emission from Lee et al. 2010 and at 5.56 kg CO2e/GJ roadside slash N2O, and CH4 emissions). Combustion emission offsets, applied with the roadside slash investigation, are a product of business as usual activities. Similarly, combustion emission offsets could have been ascribed to sawmill residues, as they used to be combusted in beehive burners, however beehive burners were prohibited in BC in a phase-out process in 2010 (BC Government 2011). Reducing incomplete combustion and smoldering of biomass through legislation is beneficial for the climate because of the decrease in GHGs and other air pollutants. However, when prohibited, this reduces the theoretical carbon accounting emissions potential for sawmill residues and roadside slash because the legally permitted business as usual case would be either non-combustion or combustion that is clean without smoke or other produced 84 GHG, such as the examined N2O, and CH4. As shown in Figure 3.11, excluding combustion emissions offsets showed biocoal from roadside slash to be in line with average sawmill residues or hybrid poplar produced biocoal. On a provincial scale, roadside slash combustion released 8,144 Gg of CO2e emissions in 2013 and 8,408 Gg CO2e per year based on a 10-year average (BC MOE 2012). It is a question to explore whether or not biogenic (carbon neutral) CO2 should be included in these numbers or not, as they likely are due to the annual harvest quantities reported by the province and the associated quantities of wastes. Ultimately, slash pile combustion emission offsets are an important factor in assessing bioenergy’s GHG emissions and thus warrants further investigation, quantification, and policy evaluation by the province, however this topic is outside the scope of this assessment. The recovery of roadside slash was the second main factor determining GHG emissions. This is most likely due to the added diesel-powered machinery (4 types in total) and transportation of machinery between sites (Lindroos et al. 2011). Lindroos et al. modeled roadside slash recovery concurrently during log harvesting and it is possible that the grapple loader was inappropriately counted in their LCA. Grapple loaders typically pile forestry slash for later combustion but in Lindroos et al. it was used to load in to the grinder/chipper. This process should be either shared equally (halved in Lindroos et al. (2011)) or left out entirely. In either case this would reduce the total GHG emissions of roadside slash recovery. Based on roadside slash residue recovery rates ranging from 40 to 19 ODMg/10,000 m2 (BC Gov 2019), BC Biocarbon’s system would need approximately 5,700 to 14,200 * 10,000 m2 (5,700 to 14,200 hectares) of logged forest per year to maintain operations (25.85 ODMg Feedstock required/hour / 19 to 40 ODMg/10,000 m2 * 24 hours per day * 365 days 85 per year). A resource and economic analysis would need to be performed to see if this amount of residue distribution would be viable, however this is beyond the scope of this project. 3.5.4 Hybrid poplar feedstock Aside from the already noted LHV adjustments and resulting impact on GHG emissions, production and application of N fertilizer was the other main determinant of GHG emissions. Hillier et al. (2009) originally used pig slurry for fertilization however the substitution of pig slurry for synthetic N fertilizer was briefly explored. One hundred kg synthetic N fertilizer per 10,000 m2 was used in this research, reflecting the application noted in Hillier et al., and was updated for current GHG emission factors. Updated emission factors, and possibly upstream emissions not accounted for in Hillier et al. but accounted for in the Ecoinvent database, led to greater GHG emissions in this research. The total GHG emissions for fertilizer application and soil emissions from Hiller et al. was noted at 700 kg CO2e/10,000 m2, whereas in this research it was equivalent to emissions of 1,067 kg CO2e/10,000 m2 per year. In both Hillier et al. and this research, it is determined that N fertilizer and associated soil emissions are important factors to consider for bioenergy crop feedstocks. Hillier’s (2015) recommendation, and estimation, that land use change would be minimal or similar between transitioning grasslands to short rotation crops was justified as the application of land use change in Ecoinvent did not differ results found in this study. Many factors go into accounting for carbon fluxes from land use change, particularly after afforestation (reviewed in Laganière et al. (2010)), however highly specified research would be needed to examine the exact changes in soil carbon and was beyond the scope of this study. Given that BC Biocarbon would require approximately 10,800 x 10,000 m2 of hybrid poplar production per year, or approximately 12.3 km by 12.3 km (25.9 ODMg Feedstock 86 required/hour * 24 hours per day * 251.25 days per year / 14.44 ODMg/10,000 m2), existing managed grasslands in the Kamloops region would be sufficient, however it would be unlikely that much land would be converted. Regardless, this hybrid poplar investigation aimed to assess the theoretical GHG implications of full bioenergy crop feedstock supply, and not the entire feasibility of hybrid poplar production. 3.5.5 Other points and limitations The main novelty of BC Biocarbon’s pyrolysis system compared to other systems is the higher carbon and energy recovery from the original feedstock in to a single final product. The mass recovery of biochar/biocoal for energy use range depends on the pyrolysis type (fast, intermediate, slow) but typically recovers around 35% by mass, with another 35% producer gas and 30% pyrolysis oil (IEA 2007). Some research has modelled or examined other pyrolysis system’s GHGs, but has only accounted for the recovery of biochar/biocoal (Harsono et al. 2013; Feliciano-Bruzual 2014; Galgani et al. 2014; and Miller-Robbie et al 2015). In these cases, this effectively reduces the final energy recovery to 45%. Whereas the system examined in this research recovers approximately 75% of the energy in making the final biocoal. Other research has commonly applied the producer gas and pyrolysis oil for other processes, such as electricity production (Suopajärvi and Fabritius 2013; Teichmann 2014; Dutta and Raghavan 2014; and Wang et al. 2013) or to run the pyrolysis system (Suopajärvi and Fabritius 2013; Peters et al. 2015; Iribarren et al. 2015; Galgani et al. 2014, and Hsu 2012). However, as a general example and thought experiment, when pyrolysis oil and producer gas is applied to the production of electricity, most modern electricity grids are far below the GHG emissions of a 100% coal power grid, therefore the carbon mitigation potential would be lower than if the biocoal, with 75% energy recovery, was used entirely for coal displacement. 87 From 1990, when carbon accounting records began, to 2013, BC forest growth was on average a net carbon sink, sequestering 19,107 Gg CO2e annually. However, since 2003, BC forests have become a net GHG source (BC MOE 2012). It could be argued that these recent and current GHG emissions should be allocated to sawmill residues and roadside slash burning emissions; however, this change is partly related to the recent outbreak of the mountain pine beetle, and thus a relatively short-term period. The timeframe of greenhouse gas accounting is important to consider in forest carbon management, however as stated in the methods section, ecosystem emissions were excluded from this analysis. One limitation that occurred in this study was the occasional inability to trace published CO2e emissions back to their constituents, such as N2O and CH4, and this occurred when using data from Athena (2018) and Lindroos et al. (2011). Additionally, Lindroos et al. was reported in CO2, and presumably meant CO2e. This had the implication of not being able to update emission factors from older IPCC guidelines to current ones. Because Athena (2018) is built from a proprietary dataset, the values provided did not allow for comparisons through normalization. One example is that freight lorry recovery transportation for raw logs was set at 212 km when applying Sambo (2002) emissions, however recovery transportation distances were not provided in Athena (2018). Given that Athena’s dataset is proprietary and their values for sawmill residues were showed to be around double of the other feedstocks and values presented in Pa et al. (2012), it does bring into question the validity of their values. Moving forward this should be taken into consideration, and hopefully, with new analyses the value of emissions for sawmill residues and finished lumber can be more accurately assessed or distilled out. Finally, as the pyrolysis system in this study is currently only modeled, changes to the final size or performance may occur. Additionally, alternative feedstocks, such as roadside 88 slash and hybrid poplar are assumed to function in the BC Biocarbon system in a similar manner as sawmill residues (hog fuel), even though carbon content, moisture content and potential ash content may modify the system output. 3.5.6 Conclusions and future research From this initial assessment, biocoal has the potential to reduce greenhouse gases compared to wood pellets, depending on the comparing data sets, but especially when transported overseas. Sourcing feedstock from roadside slash will achieve the greatest offset of GHG emissions when roadside combustion emission offsets are applied. When sourcing sawmill residues or hybrid poplar for biocoal production, maximizing the LHV of biocoal will make the largest impact in reducing overall GHG emissions and thus should be a priority. This research is a starting point for future work to determine which local or international combustion applications of biocoal can most greatly reduce GHG emissions. This may include applications for metallurgy, coal substitution in power plants, cement production, and industrial or commercial heating. 3.6 References Antal, MJ., Grønli, M. (2003). The Art, Science, and Technology of Charcoal Production †. Industrial & Engineering Chemistry Research 42:1619–1640. doi: 10.1021/ie0207919. ASTM. (2008). Gaseous fuels; coals and coke. ASTM International. Vol. 5.06. Athena. (2018). A Cradle-to-Gate Life Cycle Assessment of Canadian Surfaced Dry Softwood Lumber. Athena Sustainable Materials Institute. Last accessed Feb 05, 2019 at http://www.athenasmi.org/resources/publications/. BC Biocarbon. (2015). Company reports and files. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer. BC Biocarbon LTD. 22 May - 31 December 2015 BC Government. (2011). Environmental Management Act - Wood Residue Burner and 89 Incinerator Regulation B.C. Reg. 519/95, O.C. 1488/95. Last accessed October 17, 2018 at http://www.bclaws.ca/EPLibraries/bclaws_new/document/ID/freeside/51_519_95. BC Hydro. (2014). Greenhouse Gas intensities. Last accessed May 29, 2016 at https://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/environment-sustainability/environmental-reports/ghgintensities-2004-2014.pdf. BC Government. (2019). Estimates of residual fibre, Residual Fibre Recovery. FPinnovations reports. BC Government. Last accessed January 19, 2019 at https://www2.gov.bc.ca/gov/content/industry/forestry/forest-tenures/forest-tenureadministration/residual-fibre-recovery. BC MOE. (2008). Emissions from Wood-Fired Combustion Equipment. British Columbia Ministry of Environment. Last accessed June 25, 2016 at http://www2.gov.bc.ca/assets/gov/environment/waste-management/industrialwaste/industrial-waste/pulp-paper-wood/emissions_report_08.pdf. BC MOE. (2012). British Columbia Greenhouse Gas Inventory. British Columbia Ministry of Environment. Last accessed December 24 2015 at http://www2.gov.bc.ca/gov/content/environment/climate-change/reportsdata/provincial-ghg-inventory-report-bc-s-pir. Bianco, L., Baracchini ,G., Cirilli, F., Sante, L.D., Moriconi, A., Moriconi, E., Agorio, M.M., Pfeifer, H., Echterhof, T., Demus, T., Jung, H.P., Beiler, C., Krassnig, H-J. (2013). Sustainable Electric Arc Furnace Steel Production: GREENEAF. BHM Berg- und Hüttenmännische Monatshefte 158:17–23. doi: 10.1007/s00501-012-0101-0. Berguson, B., Eaton, J., Stanton, B. (2010). Development of hybrid poplar for commercial production in the United States: The Pacific Northwest and Minnesota experience. Sustainable Alternative Fuel Feedstock Opportunities, Challenges and Roadmaps for Six US Regions. Soil Cons Soc 282–299. Buker, C. (2015). Personal email communication. Sales & Logistics Coordinator, Pinnacle Renewable Energy Inc. 26 August - 30 November 2015. Chan, Y.H., Yusup, S., Quitain, A.T., Tan, R.R., Sasaki, M., Lam, H.L., and Uemura, Y. (2015). Effect of process parameters on hydrothermal liquefaction of oil palm biomass for bio-oil production and its lifecycle assessment. Energy Conversion and Management. 104:180-188. 90 Clare, A., Shackley, S., Joseph, S., Hammond, J., Pan, G., Bloom, A. (2014). Competing uses for China’s straw: the economic and carbon abatement potential of biochar. GCB Bioenerg n/a-n/a. doi: 10.1111/gcbb.12220. Cooper, R. (2015). Personal email and phone communication. General Manager, Fibre Supply, Canfor Pulp LTD. 15 October 2015. Crombie, K., Mašek, O., Sohi, S.P., Brownsort, P., and Cross, A. (2013). The effect of pyrolysis conditions on biochar stability as determined by three methods. GCB Bioenergy 5, 122–131. DeBell, D.S., Clendenen, G.W., Harrington, C.A., Zasada, J.C. (1996). Tree growth and stand development in short-rotation Populus plantings: 7-year results for two clones at three spacings. Biomass Bioenerg 11:253–269. doi: 10.1016/0961-9534(96)00020-7. de Ruiter, G., Helle, S., Rutherford, P.M. (2014). Industrial and Market Development of Biochar in BC. Pacific Institute for Climate Solutions Whitepaper. Last accessed March 8, 2014 at http://pics.uvic.ca/research/publications/white-papers. Dutta, B., Raghavan, V. (2014). A life cycle assessment of environmental and economic balance of biochar systems in Quebec. Int J of Energ and Environ Eng 5:1–11. doi: 10.1007/s40095-014-0106-4. Ecoinvent. (2014). The ecoinvent database: Overview and methodology, Data quality guideline for the ecoinvent database version 3, developed by Weidema, B.P., Bauer, C., Hischier, R., Mutel, C., Nemecek, T., Reinhard, J., Vadenbo, C.O., Wernet, G. Last accessed July 9, 2014 at www.ecoinvent.org. EPA. (1996). Wildfires And Prescribed Burning. US Environmental Protection Agency. Last accessed December 8, 2015 at http://www3.epa.gov/ttnchie1/ap42/ch13/final/c13s01.pdf. Feliciano-Bruzual, C. (2014). Charcoal injection in blast furnaces (Bio-PCI): CO2 reduction potential and economic prospects. J Mater Res Tech 3:233–243. doi:10.1016/j.jmrt.2014.06.001. Fick, G., Mirgaux, O., Neau, P., Patisson, F. (2013). Using Biomass for Pig Iron Production: A Technical, Environmental and Economical Assessment. Waste Biomass Valor 5:43– 55. doi: 10.1007/s12649-013-9223-1. Galgani, P., van der Voet, E., Korevaar, G. (2014). Composting, anaerobic digestion and biochar production in Ghana. Environmental–economic assessment in the context of 91 voluntary carbon markets. Waste Manage 34:2454–2465. doi: 10.1016/j.wasman.2014.07.027. Google Maps. (2015). Desktop web mapping service. Google Inc. Last accessed Dec 24 2015 at https://www.google.ca/maps/. Hammond, J., Shackley, S., Sohi, S., Brownsort, P. (2011). Prospective life cycle carbon abatement for pyrolysis biochar systems in the UK. Energ Policy 39:2646–2655. doi: 10.1016/j.enpol.2011.02.033. Harsono, S.S., Grundman, P., Lau, L.H., Hansen, A., Salleh, M.A.M., Meyer-Aurich, A., Idris, A., and Ghazi, T.I.M. (2013). Energy balances, greenhouse gas emissions and economics of biochar production from palm oil empty fruit bunches. Resources, Conservation and Recycling 77, 108–115. Hillier, J. (2015). Personal email communication. PhD researcher in Lifecycle assessment of bioenergy crops, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen. 04 December 2015. Hillier, J., Whittaker, C., Dailey, G., Aylott, M., Casella, E., Richter, G.M., Riche, A., Murphy, R., Taylor, G., and Smith, P. (2009). Greenhouse gas emissions from four bioenergy crops in England and Wales: Integrating spatial estimates of yield and soil carbon balance in life cycle analyses. GCB Bioenergy 1, 267–281. Hsu, D.D. (2012). Life cycle assessment of gasoline and diesel produced via fast pyrolysis and hydroprocessing, Biomass and Bioenergy. 45, 41–47. doi:10.1016/j.biombioe.2012.05.019. Ibarrola, R., Shackley, S., and Hammond, J. (2012). Pyrolysis biochar systems for recovering biodegradable materials: A life cycle carbon assessment. Waste Management 32, 859– 868. IEA. (2007). IEA Bioenergy Annual Report (2006). International Energy Agency, Paris. Last accessed December 24, 2015 at http://www.globalbioenergy.org/uploads/media/0707_IEA__Bioenergy_annual_report.pdf. Inverterdrive.com. (2015a). TEC Electric – IE2 30kW (40HP) 4 Pole AC Induction Motor 400V B3 Foot Mount - 200L Frame. Last accessed December 24, 2015 at https://www.inverterdrive.com/group/Motors-AC/TECA2-200L-4-Pole-B3-HighEfficiency-AC-Motor-200/. 92 Inverterdrive.com. (2015b). ECA Series IE1 Efficiency Motors Technical Data (at 50Hz), 4-6. Last accessed December 24, 2015 at https://www.inverterdrive.com/file/TEC-ACMotor-Technical-Catalogue-IE1-IE2-v3. IPCC. (2006). IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4, Agriculture, Forestry and Other Land Use. Last accessed May 5, 2014 at http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.html. IPCC. (2013). Climate Change 2007: Working Group I: The Physical Science Basis. 2.10.2 Direct Global Warming Potentials. Intergovernmental Panel on Climate Change. Last accessed Sept 19, 2017 at https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-10-2.html Iribarren, D., Peters, J.F., and Dufour, J. (2012). Life cycle assessment of transportation fuels from biomass pyrolysis. Fuel 97, 812–821. ISO. (2013). Solid biofuels - Fuel specifications and classes – Part 2: Graded wood pellets. ISO FDIS 17225-2. International Organization for Standardization. Last accessed November 30, 2015 at infostore.saiglobal.com/store/PreviewDoc.aspx?saleItemID=2660875. Johnson, L.R., Lippke, B., Marshall, J.D., and Comnick, J. (2007). Life-cycle impacts of forest resource activities in the Pacific Northwest and Southeast United States. Wood and Fiber Science 37, 30–46. Jolliet, O., Margni, M., Charles, R., Humbert, S., Payet, J., Rebitzer, G., Rosenbaum, R. (2003). IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Ass 8: 324-330. Jungmrirt, G., Werner, F., Jarnehammar, A., Hohenthal, C., Richter, K. (2002). LCA case studies: allocation in LCA of wood-based products experiences of cost action E9; part II. Examples. Int J Life Cycle Ass 7(6), 369–375. doi:10.1007/BF02978686. Laganière, J., Angers, D.A., Paré, D. (2010). Carbon accumulation in agricultural soils after afforestation: a meta-analysis. Glob Change Biol 16, 439-453. doi/10.1111/j.13652486.2009.01930.x/full. Lee, C., Erickson, P., Lazarus, M., and Smith, G. (2010). Greenhouse gas and air pollutant emissions of alternatives for woody biomass residues-FINAL DRAFT Version 2.0 (Stockholm Environment Institute). Last accessed December 29, 2015 at http://seius.org/Publications_PDF/SEI-WoodyBiomassEmissions-11.pdf. 93 Lee, J., Sokhansanj, S., Lau, A., Lim, J., Bi, X., Basset, V., Yazdanpanah, F. Melin, S.O. (2015). The effects of storage on the net calorific value of wood pellets. Can Biosyst Eng 57, 8.5–8.12. doi: 10.7451/CBE.2015.57.8.5. Lehmann, L., Joseph, S. (Eds.). (2009). Biochar for Environmental Management: Science and Technology, Earthscan Ltd, London, UK. 76-77. Lindroos, O., Nilsson, B., Sowlati, T. (2011). Costs, CO2 emissions, and energy balances of applying Nordic slash recovery methods in British Columbia. West J Appl For 26:30– 36. MacDonald, A.J. (2006). Estimated Costs for Harvesting, Comminuting, and Transporting Beetle-killed Pine in the Quesnel/Nazko Area of Central British Columbia. Report for BC Ministry of Forests and Range, BC Ministry of Energy, Mines, and Petroleum Resources, and BC Hydro. Forest Engineering Research Institute of Canada Advantage Report 7(16). Magelli, F., Boucher, K., Bi, X.T., Melin, S., Bonoli, A. (2009). An environmental impact assessment of exported wood pellets from Canada to Europe. Biomass Bioenerg 33:434–441. doi: 10.1016/j.biombioe.2008.08.016. Melin, S. (2008). Bark as feedstock for production of wood pellets. Wood Pellet Association Of Canada. Last accessed December 01, 2015 at http://www.pellet.org/images/2008-1211_Bark_as_feedstock_for_Production_of_Wood_Pellets_Report_December_2008.pdf. Microsoft Excel (2011) Microsoft Excel® for Mac 2011 Version 14.0.0. Miller-Robbie, L., Ulrich, B.A., Ramey, D.F., Spencer, K.S., Herzog, S.P., Cath, T.Y., Stokes, J.R., and Higgins, C.P. (2015). Life cycle energy and greenhouse gas assessment of the co-production of biosolids and biochar for land application. Journal of Cleaner Production 91, 118–127. Nanda, S., Dalai, A.K., Berruti, F., and Kozinski, J.A. (2016). Biochar as an Exceptional Bioresource for Energy, Agronomy, Carbon Sequestration, Activated Carbon and Specialty Materials. Waste Biomass Valor 7, 201–235. Norgate, T., Langberg, D. (2009). Environmental and Economic Aspects of Charcoal Use in Steelmaking. ISIJ Int 49:587–595. doi: 10.2355/isijinternational.49.587. Norgate, T., Haque, N., Somerville, M., and Jahanshahi, S. (2012). Biomass as a Source of Renewable Carbon for Iron and Steelmaking. ISIJ International 52, 1472–1481. 94 Nyboer, J. (2008). A review of energy consumption and related data in the Canadian Wood Products Industry: 1990, 1995 to 2006. Last accessed December 30, 2015 at http://www2.cieedac.sfu.ca/media/publications/Wood%20Products%20Report%202007 %20_2006%20data_%20Final.pdf. OpenLCA. (2015). Green Delta. OpenLCA version 1.4. http://www.openlca.org. Released 20 February 2015. Pa, A. (2015). Email communication. Anna Pa, MSc. November 21. Pa, A., Craven, J.S., Bi, X.T., Melin, S., and Sokhansanj, S. (2012). Environmental footprints of British Columbia wood pellets from a simplified life cycle analysis. The International Journal of Life Cycle Assessment 17, 220–231. Prasityousil, J., and Muenjina, A. (2013). Properties of Solid Fuel Briquettes Produced from Rejected Material of Municipal Waste Composting. Procedia Environmental Sciences 17, 603–610. https://doi.org/10.1016/j.proenv.2013.02.076. Peters, J.F., Iribarren, D., Dufour, J. (2014). Life cycle assessment of pyrolysis oil applications. Biomass Convers Biorefin 5:1–19. doi: 10.1007/s13399-014-0120-z. Peters, J.F., Iribarren, D., Dufour, J. (2015). Biomass Pyrolysis for Biochar or Energy Applications? A Life Cycle Assessment. Environ Sci Technol 49:5195–5202. doi: 10.1021/es5060786. Reitsma, L. (2015) Personal phone communication. President & Chief Operating Officer, Pinnacle Renewable Energy Inc. 14 October 2015. Roberts, K.G., Gloy, B.A., Joseph, S., Scott, N.R., and Lehmann, J. (2010). Life Cycle Assessment of Biochar Systems: Estimating the Energetic, Economic, and Climate Change Potential. Environ. Sci. Technol. 44, 827–833. Rosas, J.G., Gómez, N., Cara, J., Ubalde, J., Sort, X., and Sánchez, M.E. (2015). Assessment of sustainable biochar production for carbon abatement from vineyard residues. Journal of Analytical and Applied Pyrolysis 113, 239–247. Sambo, S. (2002). Fuel consumption for ground-based harvesting systems in western Canada. FERIC Advantage Report 3:1–12. SolidWorks. (2010). Dassault Systèmes SolidWorks Corp. www.solidworks.com. Released 09 Dec 2009 Sparrevik, M., Field, J.L., Martinsen, V., Breedveld, G.D., and Cornelissen, G. (2013). Life Cycle Assessment to Evaluate the Environmental Impact of Biochar Implementation in 95 Conservation Agriculture in Zambia. Environmental Science & Technology 130116073805003. Sparrevik, M., Adam, C., Martinsen, V., Jubaedah, and Cornelissen, G. (2015). Emissions of gases and particles from charcoal/biochar production in rural areas using medium-sized traditional and improved “retort” kilns. Biomass and Bioenergy 72, 65–73. Strauss, W. (2014). “Black Pellets” - A Financial Analysis of Costs and Benefits: Can they provide cheaper energy than white pellets? Future Metrics LLC, Bethel, ME. Last accessed Dec 01, 2015 at http://futuremetrics.info/wpcontent/uploads/2014/07/Black_Pellets__An_Analysis_of_Costs_and_Benefits.pdf. Stummer, B. (2015). Personal email communication. Belt dryer sales manager, stela Laxhuber GmbH. 15 Sept 2015. Suopajärvi, H., Pongrácz, E., and Fabritius, T. (2014). Bioreducer use in Finnish blast furnace ironmaking – Analysis of CO2 emission reduction potential and mitigation cost. Applied Energy 124, 82–93. Teichmann, I. (2014). Technical Greenhouse-Gas Mitigation Potentials of Biochar Soil Incorporation in Germany. Social Science Research Network. August 2014. Last accessed November 15, 2015 at http://dx.doi.org/10.2139/ssrn.2487765. TheStructuralEngineer. (2012). A comparative embodied carbon assessment of commercial buildings. Last accessed December 24, 2015 at http://www.steelsci.com/SCIContentPDF/Target-Zero-Structural-Engineer.pdf. Vadenbo, C.O., Boesch, M.E., and Hellweg, S. (2013). Life Cycle Assessment Model for the Use of Alternative Resources in Ironmaking. Journal of Industrial Ecology 17, 363–374. Van Oosten, C. (2015). Personal email and phone communication. Silviculture Consultant with specialty in Hybrid poplar, SilviConsult Woody Crops Technology Inc. 02 - 22 Sept 2015. Wang, Z., Dunn, J.B., Han, J., and Wang, M.Q. (2013). Effects of co-produced biochar on life cycle greenhouse gas emissions of pyrolysis-derived renewable fuels. Biofuels, Bioprod. Bioref. 8, 189–204. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications 1, 1–9. 96 4 CHAPTER 4 – Project 2: Carbon displacement factors of wood-based biocoal in cement, smelting, and electrical power production 4.1 Abstract In previous work, a synthetic coal product, called ‘biocoal’, similar to biochar and charcoal was examined for at-gate lifecycle greenhouse gas (GHG) emissions. This current work extended said research into GHG emissions for Biocoal combustion applications. This project will perform a lifecycle greenhouse gas assessment in order to determine the optimal use of biocoal in 3 scenarios: cement, electricity, and lead production applications. Information collected and assumptions made in the inventory analysis were used to calculate the carbon displacement factors (GHG reduction potential) of each combustion application scenario for each product examined: cement, electricity, and lead. Carbon displacement factors were calculated as product lifecycle emissions normalized to 1 GJ Biocoal. A sensitivity analysis was performed in order to address variability in various lifecycle factors. Results of this assessment showed biocoal used for cement production possessed the largest carbon displacement factor while lead production was the lowest. This was confirmed through various scenarios. Sensitivity analysis demonstrated that the amount of GHG emissions from petcoke or coal combustion showed the next most influence and closely followed by energy density of biocoal. This project demonstrated that, given current information and within the case study scenarios described, biocoal should be applied to cement production to obtain the largest carbon displacement factor per GJ biocoal. Project 3 will assess the carbon reduction potential of non-combustion applications of biocoal and compare them across both combustion and non-combustion applications. 97 4.2 Introduction In the previous Project 1, a synthetic coal product, called biocoal, similar to biochar and charcoal, was examined for at-gate lifecycle greenhouse gas (GHG) emissions. This work extends research into GHG emissions for biooal combustion applications, including cement production, lead smelting, and electricity production. As described in Project 1, biocoal is energetically and physically similar to coal, and has the potential to replace other fossil fuels. Studies have examined biochar/biocoal (charred wood-derived product) as a coal substitute in metallurgy and have shown promising results for its technical feasibility (da Costa and Morais 2006; Bianco et al. 2013; Fick et al. 2013; and Suopajärvi and Fabritius 2013). Biochar/biocoal as a heating fuel is well documented and was previously supported through a carbon-offset request for proposals through the BC Pacific Carbon Trust (PCT 2012), however the substitution for petroleum coke (petcoke) has not been explored in the literature and the potential emission reductions are not known. Kamloops, BC is proposed as the primary case study to represent BC’s opportunities for biocoal applications. This is due to its proximity to sawmills and waste feedstock, mines and smelters, major road and rail lines for transportation. The potential for biocoal to enter key markets will depend, in part, on its ability to reduce GHGs. Therefore, this project will perform a lifecycle greenhouse gas assessment in order to determine the optimal use of biocoal in 3 scenarios: cement, electricity, and lead production applications. This lifecycle GHG assessment will examine and compare emission reduction potentials (displacement factors) for biocoal in replacing coke and coal for cement, electricity, and lead smelting. 98 4.3 Methods 4.3.1 Goal and scope GHG assessments were adapted from ISO 14040 protocol, and similar to (Norgate and Langberg, 2009; Hammond et al., 2011; Rousset et al., 2011; Norgate et al., 2012; and Pourhashem et al., 2013). International Association for Standardization ISO 14040 and ISO 14044 protocols (ISOa, 2006; and ISOb, 2006) were used to assess greenhouse gas equivalent to scope 3 GHG assessment protocols. The goal of this research was to assess the carbon displacement factors of the combustion applications of biocoal as defined in the previous chapter. The assessment was based on a case study production plant situated in Kamloops, BC. The project scope is shown in Figure 4.1 and begins after the production of biocoal and at the gate. Analysis for transportation to combustion site, potential combustion characteristic differences, combustion emissions, and ash/waste disposal were examined for GHG impacts. The functional unit of this study is defined as the displacement factor CO2-equivelent (CO2e) emissions per gigajoule (GJ) of biocoal. 99 Assessed in Project 1 1 Biocoal Assessed in this project Figure 4.1 Lifecycle scope included all processes within the solid boundary boxes are to be accounted for lifecycle CO2-equivalent emissions. All steps up to ‘biocoal’ production was investigated in Project 1 of this dissertation, while Project 2 assesses the product application and ash/waste disposal for combustion applications. 1 From image BC Biocarbon reserves intellectual property, including visual representations of the pyrolysis system. 4.3.2 Inventory data collection (databases, sources, and analysis tools) Identifying all factors that affect the defined scope for biocoal was performed in the inventory analysis in Project 1. Relevant fossil fuel GHG information for cement, electricity, and lead production were collected in this project’s inventory analysis and used for comparison to biocoal (Details presented in section 4.3.4 Biocoal application scenarios). 4.3.3 BC Biocarbon pyrolysis system and biocoal product Information pertaining to BC Biocarbon’s pyrolysis system and biocoal product characteristics are described in Project 1. No modifications to BC Biocarbon’s system were assumed in this assessment. Biocoal emissions were obtained from Project 1 but modified through the addition of transportation and combustion substitution in each of the application 100 scenarios investigated. Biocoal is assumed to originate in Kamloops, BC and transported to the various locations by either freight lorry for cement production or rail freight (described further in the ‘Biocoal applications scenarios’ section). Freight lorry and rail freight are applied in OpenLCA as described in Project 1 (Ecoinvent 2014). Similar to Project 1, allocation of emissions were ascribed on a mass basis for the production and distribution of biocoal (Jungmrirt et al. 2002). Biocoal production and characteristics were maintained from Project 1, however only sawmill residue feedstock numbers were used in this analysis. This is due to sawmill residues representing the most likely feedstock source for BC Biocarbon (2015). 4.3.4 Biocoal application scenarios Application scenarios were chosen due to the fuel similarities of biocoal to that of coal and petcoke (discussed in Project 1). Applications within British Columbia were initially chosen but were expanded to include one coal fired electrical power plant in the neighbouring province of Alberta. The application scenarios investigated were Lafarge Canada Inc., a cement production facility in Kamloops, BC, HR Milner coal-fired electrical power plant in Grande Cache, AB, operated by Maxim Power Corp., and Teck Resources Ltd., a zinc and lead smelting plant in Trail, BC. Each company was contacted by either phone or email to obtain GHG emissions data for their facility and product (Lafarge 2016; Maxim 2016; and Teck 2016). Additional publicly published data and datasets from Ecoinvent were included to complete or support information. These values were used to calculate an accurate assessment of GHG emissions in kg CO2-equivalent (CO2e) per unit of cement (Mg), electricity (MWh), and lead (Mg) product. 101 Two main scenarios were investigated within each application to explore the certainty and range of results. These were a base case scenario where produced biocoal is transported 100 km round trip for local application (‘100 km biocoal freight lorry to application’), and a second scenario of the ‘full scenario to actual conditions’. For the ‘full scenarios’, biocoal was assumed to be shipped to the end-use destination from Kamloops (described further below). The ‘full scenarios’ also included extraction/production emissions from fossil fuels, their transportation, and combustion emission reductions. Table 4.1 outlines the biocoal application scenarios and the various GHG factors that were included or not, and are discussed further below. Table 4.1. Biocoal application factors included in each scenario or not. Scenario GHG factor Biocoal production emissions Biocoal 100 km transportation to end use application site Biocoal transportation from Kamloops to actual end use application site Fossil fuel combustion emission reductions Fossil fuel transportation to combustion plant Fossil fuel extraction/production ‘100 km biocoal freight lorry to application’ Included Included Not included Included Included Included ‘Full scenario to actual conditions’ Included Not included Included Included Included Included 4.3.4.1 Cement Data obtained from Lafarge Canada Inc. for cement production is shown in Table 4.2. Petcoke was primarily assumed to be offset by biocoal rather than coal. This was due to petcoke being the primary solid fuel referenced by Lafarge (2016), however coal scenarios are included for comparison. Local wood waste, averaging 10% of the energy content while burning petcoke is also burned for heat at Lafarge Richmond and was proportionally removed from emissions counting (Lafarge 2016). In other words, the overall energy needed and supplied by biocoal is only offsetting petcoke coal, and the assumed wood waste combustion of 10% was maintained. For the alternative data scenario Petcoke production emissions were 102 obtained from Ecoinvent (2013) was supported by New Fuels Alliance (2009) which looked at the “Assessment of Direct and Indirect GHG Emissions Associated with Petroleum Fuels”. Coal production emissions were also obtained from Ecoinvent (2013). Table 4.2 Cement production values used to calculate the carbon displacement factor by displacing petroleum coke (petcoke) with biocoal. Mg of petcoke per Mg of cement (Lafarge 2016) (Mg / Mg) 13 GJ petcoke required per Mg cement (Lafarge 2016) Production emissions for petcoke (Ecoinvent 2014) Combustion emissions for petcoke (CRS 2013) (GJ / Mg) (kg CO2e / GJ) 2.544 3.84 Petcoke assumed lower heating value from assumed 10% moisture content (kg CO2e / GJ) Petcoke assumed higher heating value (Indian Oil 2016; and supported by CRS 2013) (GJ / Mg) (GJ / Mg) Rail transportation of petcoke from Lloydminster, SK to Richmond, BC. Google Maps (2016) (km) 111.3 33.04 28.99 1116 Transportation of fossil fuels were assumed to be by rail and emissions similarly applied as outlined in Project 1 from Ecoinvent (2013). Combustion emissions for petcoke were set from CRS (2013), while the alternative scenario with coal sourced combustion emissions from EPA (2014). In both scenarios petcoke and coal were assumed to have lower heating values adjusted from the reported higher heating value due to an assumed 10% moisture content. Transportation of biocoal to the Lafarge cement plant from Kamloops was set at 439 km and by rail, similar to petcoke (Ecoinvent 2014). Onsite handling and combustion of biocoal was assumed to be similar to that of petcoke and thus no changes were made to the cement operations or plant efficiency. Ash disposal (in addition to being incorporated into the cement) was found to be of minor GHG impact (<1%) and thus omitted from the analysis. 4.3.4.2 Electricity 103 Data obtained from Maxim Power Corp. regarding operations at HR Milner power station is shown in Table 4.3. Coal was primarily assumed to be offset by biocoal due to coal being the primary solid fuel referenced by Maxim (2016). HR Milner onsite emissions data were supported by public GHG disclosure data from the Alberta Ministry of Energy (AB MOE 2011). Table 4.3 Electricity production values used to calculate the carbon displacement factor by displacing coal with biocoal. GJ heat energy per MWh (Maxim 2016) (GJ / MWh) 14 Electricity emissions per MWh (Maxim 2016) (kg CO2 per MWh) Coal assumed higher heating value (Maxim 2016) (GJ / Mg) Electricity emissions per MWh (EPA 2014) (kg CO2 per Mg coal) Applied rail transportation of coal from mine to power plant. Google Maps (2016) (km) 1400 24 2,586 284 A second scenario was developed to use coal combustion emissions from the US Environmental Protection Agency (EPA 2014) and compare to the cement production scenario above and lead production scenario below. The origin of coal for HR Milner was not provided by Maxim power; however, the two most proximal coalfields, which mine equivalent grade coal as listed used from EPA (2014), were assumed to be HR Milner’s source. These fields were Obed Mountain and Coal Valley Mine, both operated by Westmoreland Coal Company. The average distance to HR Milner power station from both mines was found by use of Google Maps (2016) measurement and used for rail GHG emissions. Rail GHG emissions were similarly applied as rail transported biocoal and as in Project 1. Upstream GHG emissions for coal mining/production were ascribed from ‘Hard coal mine operation, alloc. default U’ (Ecoinvent 2014) and equated to 6.61 kg CO2/GJ coal. This value was also used for the cement production scenario above and lead production scenario below. 104 From best-known information, waste ash is landfilled at a nearby site to HR Milner and was deemed to be less than 1% of total emissions and thus excluded from this analysis. Additionally, no changes to plant operations were assumed due to the fuel substitution similarities of coal and biocoal. 4.3.4.3 Lead Teck Resources Ltd was contacted for information relating to their onsite coal use for lead smelting and values for the calculation lead carbon displacement factors, and are shown in Table 4.4. Each Mg of lead produced was calculated from 300 Mg of coal used for 234.93 Mg lead produce daily (Teck 2016). Emissions for coal production were again applied from Ecoinvent (2014), however Teck’s coal is obtained from their East Kootenay Coal Mountain mine located 475 km away. Rail GHG emissions for biocoal transportation were similarly applied as for electricity generation, however they were transported 891 km from Kamloops to Trail, BC. Table 4.4 Lead production values used to calculate the carbon displacement factor by displacing coal with biocoal. Mg of Eastern Kootenay bituminous coal daily used at Teck (Teck 2016) Mg lead produce daily (Teck 2016) Calculated Mg of Eastern Kootenay bituminous coal per Mg of lead produced (Teck 2016) (Mg) (Mg) 300 234.93 4.3.5 Eastern Kootenay bituminous coal assumed lower heating value from assumed 10% moisture content (MEM 2014) (GJ / Mg) Calculated GJ heat energy per Mg lead produced (Maxim 2016) Applied rail transportation of coal from East Kootenay Coal Mountain mine to Trail, BC. Google Maps (2016) (Mg / Mg) Eastern Kootenay bituminous coal assumed higher heating value (MEM 2014) [Calculated lower heating value] (GJ / Mg) (GJ / Mg) (km) 1.277 34 [29.85] 29.85 0.0428 475 Lifecycle impact and GHG assessment Information collected and assumptions made in the inventory analysis were used to calculate the lifecycle GHG assessment. IPCC (2013) report for 100-year global warming 105 potential was used for greenhouse gas emissions and biocoal emissions were quantified in kg CO2e/GJ biocoal. Biocoal production emissions were obtained from Project 1 and from the average 3 at gate scenarios equalling 7.34 kg CO2e/GJ biocoal. IPCC metrics have previously been used for GHG assessments in Rousset et al., (2011), Pourhashem et al., (2013), Wang et al. (2013), Vadenbo el al. 2013, and others. As for ash use or disposal, GHG emissions were not included in the analysis for inventory items if constituting less than 1% of total. Biocoal GHGs were used to calculate the net carbon displacement factors in each combustion scenario for each product: cement, electricity, and lead (Equation 4.1). 34 56789:6 34 ;6<6=7 :4;CD6 𝑁𝑒𝑡 𝑐𝑎𝑟𝑏𝑜𝑛 𝑑𝑖𝑠𝑝𝑙𝑎𝑐𝑚𝑒𝑛𝑡 𝑓𝑎𝑐𝑡𝑜𝑟 = 34 ;6<6=7 ∗ 34 ?@989AB ∗ 34 56789:6 − :4 ;CD6 34 ?@989AB (GH9IJ87@9= A=I 7HA=KG9H7A7@9= 6<@KK@9=K) = MNM O6IJ87@9= :4 ;CD6 34 ?@989AB Equation 4.1 Sample net carbon displacement factor calculation for cement. Carbon displacement factors were calculated as product lifecycle emissions normalized to 1 Mg biocoal minus biocoal production and transportation emissions. Values presented in this project are presented as per GJ biocoal but were derived from per Mg biocoal. Appendix 2 Supplementary Information outlines a sample calculation and background values for results of this project. A sensitivity analysis was performed in order to address variability in various lifecycle factors. 4.4 Results Results of this assessment showed biocoal used to offset petcoke for cement production possessed the largest carbon displacement factor while coal offset for lead production was the lowest (Figure 4.2), however, there was little variation between the two main scenarios examined across all applications. The carbon displacement factor for cement 106 production was 18.9 kg CO2e/GJ biocoal (21%) greater when offsetting petcoke versus that of coal. Results for carbon displacement factors between HR Milner derived values and EPA (2014) values were 7.8 kg CO2e/GJ biocoal and represent approximately 8% increase from HR Milner derived values. EPA derived results for electricity production were very similar to petcoke carbon displacement factors. The sensitivity analysis presented in Figure 4.3 shows changes to petcoke combustion GHGs caused the greatest change in carbon displacement factor, although this was very close to the energy density of biocoal. The least impacting factors were the production emissions from both biocoal and petcoke. Full scenario to actual conditions - Coal displacement 78.8 100 km biocoal freight lorry to application - Coal displacement 80.0 Lead Production EPA-sourced values Full scenario to actual conditions - Coal displacement 106.0 100 km biocoal freight lorry to application - Coal displacement 108.0 Full scenario to actual conditions - Coal displacement 98.3 100 km biocoal freight lorry to application - Coal displacement Electricity Production HR Milner-sourced values 100.2 Full scenario to actual conditions - Coal displacement 89.5 100 km biocoal freight lorry to application - Coal displacement 90.0 Cement Production EPA-sourced values Full scenario to actual conditions - Petcoke displacement 108.4 100 km biocoal freight lorry to application - Petcoke displacement 108.9 0.0 20.0 40.0 60.0 80.0 100.0 Electricity Production EPA-sourced values Cement Production CRS-sourced values 120.0 Displacement factor (kg CO2e/GJ Biocoal) Figure 4.2 Carbon displacement factors of cement, electricity, and lead produced at Lafarge, Kamloops BC, HR Milner power station, Grande Cache AB, and Teck Resources, Trail BC, respectively (product GHG emissions normalized to 1 GJ biocoal minus biocoal production and transportation emissions). Numbers are presented in kg CO2e/GJ biocoal. 107 Output Percent Change of Carbon dislplacement factor 30% 20% Biocoal GJ/Mg 10% Petcoke transportation Petcoke production emissions 0% Petcoke combustion emissions -10% Biocoal production emissions Petcoke GJ/Mg -20% -30% Input Percent Change from Base Case Figure 4.3 Sensitivity analysis of the carbon displacement factor from cement production base case analysis. Input factors were adjusted by ±25% to derive the output percent change, with exception of Ecoinvent LCA data where input percent change reflected the percent difference from base case to Ecoinvent case. Similar results were seen between cement, electricity, and lead production; thus, the cement base case scenario was chosen to represent all three. 4.5 Discussion 4.5.1 Biocoal application scenarios The various scenarios investigated for biocoal application showed that use in cement production would yield the highest carbon displacement factor, likely due to the higher production emissions associated with petcoke production, less transportation than coal, and higher carbon content relating to higher CO2 from combustion. Results for electricity production derived from EPA (2014) values were very close to cement production carbon displacement however. Exploring the different scenarios within each product (cement, electricity, lead) also helped to provide a level of certainty for which use was optimal for biocoal usage and GHG reductions. 108 Biochar or biocoal products have previously been considered for coal offset in various industries (Vadenbo et al. 2013; Norgate et al. 2012; Ibarrola et al. 2012; Norgate and Langberg 2009; Gaunt and Lehmann 2008), however this analysis is the first that is known to quantify and compare the potential carbon displacement factors between various applications in a defined region and with specific companies. This analysis was also the first that is known to assess a fully charred product that included the use of pyrolysis oils, gases, and solid carbon into one finished product. Many analyses have explored separate applications for biochar - typically soil applications - and pyrolysis oils for electricity production or transportation fuels (Wang et al. 2013; Pourhashem et al. 2013; Ibarrola et al. 2012; Hammond et al. 2011; Woolf et al. 2010; Norgate and Langberg 2009; Gaunt and Lehmann 2008), while some analyses have only used the solid biochar product and considering the others as wastes (Harsono et al. 2013; Feliciano-Bruzual 2014; Galgani et al. 2014; and Miller-Robbie et al. 2015). Ultimately in both these situations, the potential for optimal efficiency of feedstock use can lead to greater reductions in carbon displacement factors and especially if co-products are used. Results seen in the sensitivity analyses were very similar between cement, electricity, and lead production, thus the cement base case scenario was chosen to represent all three cases. Hence, GHG emissions from coal combustion in the electricity and lead production scenarios showed the most influence on results, closely followed by energy density of biocoal. 4.5.1.1 Cement This analysis is the first that is known to assess the use of a biochar or biocoal product in the production of cement and for the purpose of demonstrating carbon displacement factors. The idea of using biocoal, through either pyrolysis or a lower temperature process known at torrefaction, is not new. In 2012 the now dissolved Pacific Carbon Trust issued an 109 RFP for biocoal to be used as a coal replacement. It is unknown what the outcome of that RFP was due to the fate of the organization, however the technical feasibility still stands to displace coal with biocoal. Lafarge Canada Inc. currently uses 10% unmodified local wood waste in their cement manufacturing (Lafarge 2016). This fuel, and associated GJ contribution for heat, was removed from the Lafarge plant for the carbon displacement factor calculation. Although Lafarge Canada Inc. is limited in the amount of unmodified wood waste they can use (Lafarge 2016), the carbon displacement factor for petcoke remains the same if they were to increase or decrease the wood waste use. The only impact is the total GHG’s reduced per Mg of cement produced. From a GHG perspective and based on the results shown petcoke would be a better fossil fuel to offset with biocoal due to its higher carbon displacement factor. Of course, cost considerations are important, and that would need to be evaluated by the company, however an increase carbon displacement factor of 21% is substantial and could greatly help reduce emissions if there were a choice to displace coal or petcoke on a provincial policy level. 4.5.1.2 Electricity The information obtained from HR Milner indicated a 27% plant efficiency in terms of coal-to-electricity (MWh) output. This was the reasoning for including a separate analysis from the EPA coal fired power lifecycle GHGs. From Maxim Power Corp., the onsite emissions at HR Milner power plant operated at 1,400 kg CO2/MWh, where as other literature has shown values from 1,247-1,037 kg CO2/MWh (Burnham et al. 2012), 1,250-950 kg CO2/MWh (Reviewed in Weisser 2007), 1,124 kg CO2/MWh (NETL 2014), 1,022-941 kg CO2/MWh (Spath et al. 1999), 955 kg CO2/MWh (Jaramillo et al. 2007), and 703 kg CO2/MWh in Ecoinvent (2014). Ultimately, HR Milner’s lower plant efficiency (higher 110 GHGs per MWh) could have resulted in the higher carbon displacement factor than would likely be seen at other coal-fired power plants. As a point of reference, a single currently modelled BC Biocarbon facility would be able to provide 26 MW of power (12.2 Mgs biocoal/hour * 29.6 GJ/Mg biocoal * 1 MWh / 14 GJ). HR Milner runs at 144 MW and would thus require a BC Biocarbon facility 5.5 times larger than the current modelled plant, plus the available feedstock. This has implications on the amounts of feedstock that could be sourced locally and the likelihood of fully reducing the power plant combusion emissions in efforts to help mitigate climate change. 4.5.1.3 Lead This analysis is the first to assess the potential carbon displacement factor from the use of a biochar or biocoal product in the production of lead. Other analyses have focused on steel production (Feliciano-Bruzual 2014; Suopajärvi et al. 2014; Vadenbo et al. 2013; Fick et al 2013), however no steel is produced in either British Columbia or Alberta and thus was deemed to be outside the scope of this assessment. Similar to the cement assessment, Ecoinvent also possessed GHG emissions for the production of lead, however the production data were linked and divided between the production of lead and zinc. This is because lead and zinc are commonly produced in the same refining process because they share the same ore. The information was unable to be confidently decoupled for only lead as they existed in separate data sets but shared emissions. At the Teck refinery, zinc is refined and produced with electricity while coal is used for the smelting process of lead (Teck 2016). 4.5.2 Other factors and limitations of this study Scenarios for natural gas displacement and BC electricity production were not compared in this analysis due to their commonly known low emission factors. Natural gas 111 electricity generation is found to have an average lifecycle emissions factor of 488 kg CO2/MWh (NETL 2014), which is assessed at around half of that of coal-fired electricity. Even more so BC Hydro electricity generation is self-reported at 11 kg CO2/MWh (BC Hydro 2014). Based on HR Milner energy requirements per MWh (14 GJ/MWh), and only based on biocoal production, transportation, and combustion emissions, a power plant running 100% biocoal would emit approximately 120 kg CO2e/MWh (at 8.57 kg CO2e GJ biocoal). Ultimately, before natural gas is to be displaced with biomass or biocoal combustion, cement, coal-fired electricity and even lead smelting should be targeted for their higher carbon displacement factors. Results from Project 1 indicate that varying the feedstock for biocoal production would have a relatively small net change to the carbon displacement factors seen in this analysis, as the emissions released from coal and petcoke combustion are so large in comparison. For example, production and combustion emissions from petcoke were set at 114 kg CO2e/GJ, whereas biocoal production and combustions emissions were 7.34 kg CO2e/GJ. The largest change, and increase in carbon displacement factor would be seen with the use of roadside slash, however. This is because of its carbon reduction potential through offsetting nitrous oxides and methane. The primary limitation of the study was the limited values and numbers obtained from each company, with Teck Resources Limited being relied upon on the greatest number of assumptions and supporting information to complete the carbon displacement factors. Therefore, this assessment makes for a good starting point for future research to refine if more accurate information can be obtained from the lead smelting industry. 112 4.5.3 Conclusions and future research This project demonstrates that, given current information and within the case study scenarios described, biocoal should be applied to cement production to obtain the largest carbon displacement factor per GJ biocoal and depending on the date sources, electricity production should be a very close second. Other biocoal combustion applications could be added to this comparison and demonstrate a larger carbon displacement factor however at this time the results of this analysis give some assistance to policy makers and industry in where to pursue carbon mitigation strategies or incentives. The next two chapters of this work will include assessing the carbon reduction potential of non-combustion applications of biocoal and compare them across both combustion and non-combustion applications in Project 4. 4.6 References AB MOE. (2011). Specified Gas Reporting Regulation Annual Reports. Alberta Ministry of Energy. Last accessed May 15, 2016 at http://aep.alberta.ca/climate-change/reports-anddata/default.aspx Agar, D., and Wihersaari, M. (2012). Bio-coal, torrefied lignocellulosic resources – Key properties for its use in co-firing with fossil coal – Their status. Biomass and Bioenergy 44, 107–111. BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. BC Hydro (2014) Greenhouse Gas intensities. Last accessed May 29, 2016 at https://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/environment-sustainability/environmental-reports/ghgintensities-2004-2014.pdf Bianco, L., G. Baracchini, F. Cirilli, L. Di Sante, A. Moriconi, E. Moriconi, M. M. Agorio, H. Pfeifer, T Echterhof, T. Demus, HP. Jung, C. Beiler, HJ. Krassnig. 2013. Sustainable Electric Arc Furnace Steel Production: GREENEAF, BHM Bergund Hüttenmännische Monatshefte, Vol 158(1), pp. 17-23. 113 Burnham, A., Han, J., Clark, C.E., Wang, M., Dunn, J.B., and Palou-Rivera, I. (2012). LifeCycle Greenhouse Gas Emissions of Shale Gas, Natural Gas, Coal, and Petroleum. Environmental Science & Technology. Vol. 46, 619–627. CRS (2013). Petroleum Coke: Industry and Environmental. Petroleum Coke: Industry and Environmental Issues. Congressional Research Service. Authored by Andrews, A. and Lattanzio, R.K. October 29, 2013. Last accessed June 1, 2016 at http://www.nam.org/CRSreport/. da Costa, R.T., and Morais, F.M. (2006). Charcoal, renewable energy source for steelmaking process. Revue de Métallurgie, Vol. 103, pp. 203–209. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications Vol. 1, pp. 1–9. Ecoinvent. (2014). The ecoinvent database: Overview and methodology, Data quality guideline for the ecoinvent database version 3, developed by Weidema, B.P., Bauer, Ch., Hischier, R., Mutel, Ch., Nemecek, T., Reinhard, J., Vadenbo, C.O., Wernet, G. www.ecoinvent.org. Released July 08, 2014. EPA (2014). Emission Factors for Greenhouse Gas Inventories. Last accessed March 15, 2016 at https://www.epa.gov/sites/production/files/2015-07/documents/emissionfactors_2014.pdf. Feliciano-Bruzual, C. (2014). Charcoal injection in blast furnaces (Bio-PCI): CO2 reduction potential and economic prospects. Journal of Materials Research and Technology 3, 233–243. Fick, G., Mirgaux, O., Neau, P., and Patisson, F. (2013). Using Biomass for Pig Iron Production: A Technical, Environmental and Economical Assessment. Waste and Biomass Valorization, March, pp. 1–13. Finnveden, G., Hauschild, M., Ekvall, T., Guinee, J., Heijungs R, Hellweg S, Koehler A, Pennington D, Suh S., 2009. Recent developments in lifecycle assessment. Journal of Environmental Management 91 (1), 1–21. Galgani, P., van der Voet, E., and Korevaar, G. (2014). Composting, anaerobic digestion and biochar production in Ghana. Environmental–economic assessment in the context of voluntary carbon markets. Waste Management 34, 2454–2465. 114 Gaunt, J.L., and Lehmann, J. (2008). Energy Balance and Emissions Associated with Biochar Sequestration and Pyrolysis Bioenergy Production. Environmental Science & Technology, Vol. 42, pp. 4152–4158. Google Maps (2015). Desktop web mapping service. Google Inc. Last accessed Dec 24, 2015 at https://www.google.ca/maps/ Hammond, J., Shackley, S., Sohi, S., and Brownsort, P. (2011). Prospective lifecycle carbon abatement for pyrolysis biochar systems in the UK. Energy Policy, Vol. 39, pp. 2646– 2655. Harsono, S.S., Grundman, P., Lau, L.H., Hansen, A., Salleh, M.A.M., Meyer-Aurich, A., Idris, A., and Ghazi, T.I.M. (2013). Energy balances, greenhouse gas emissions and economics of biochar production from palm oil empty fruit bunches. Resources, Conservation and Recycling 77, 108–115. Ibarrola, R., Shackley, S., and Hammond, J. (2012). Pyrolysis biochar systems for recovering biodegradable materials: A lifecycle carbon assessment. Waste Management, Vol. 32, pp. 859–868. Indian Oil. (2016). Raw Petroleum Coke (RPC). Last accessed May 5, 2016 at https://www.iocl.com/Products/RawPetroleumCokeSpecifications.pdf IPCC. (2006). IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4, Agriculture, Forestry and Other Land Use. Last accessed May 5, 2014 at http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.html. ISOa. (2006) ISO 14040:2006 Environmental management - Lifecycle assessment - Principles and framework. International organization for standardization, Geneva, Switzerland. ISOb. (2006) ISO 14044:2006 Environmental management - Lifecycle assessment Requirements and guidelines International organization for standardization, Geneva, Switzerland. Jaramillo, P., Griffin, W.M., and Matthews, H.S. (2007). Comparative Life-Cycle Air Emissions of Coal, Domestic Natural Gas, LNG, and SNG for Electricity Generation. Environmental Science & Technology, Vol. 41, 6290–6296. Jungmrirt G., Werner F., Jarnehammar A., Hohenthal C., Richter K. (2002). LCA case studies: allocation in LCA of wood-based products experiences of cost action E9; part II. Examples. International Journal of Life Cycle Assessment 7(6), 369–375. 115 Lafarge (2016). Personal email communication. Eric Isenor, Plant Manager, Kamloops Cement Plant, Lafarge Canada Inc. Feb 15, 216. Maxim (2016). Personal email communication. Chris Devasahayam, Director – Asset Management, Maxim Power Corp., March 10, 2016. MEM. (2014). British Columbia Coal Industry Overview 2014: British Columbia Geological Survey. Ministry of Energy and Mines. Last accessed May 15, 2016 at http://www.empr.gov.bc.ca/Mining/Geoscience/PublicationsCatalogue/InformationCirc ulars/Documents/IC_2015-03.pdf Miller-Robbie, L., Ulrich, B.A., Ramey, D.F., Spencer, K.S., Herzog, S.P., Cath, T.Y., Stokes, J.R., and Higgins, C.P. (2014). Life cycle energy and greenhouse gas assessment of the co-production of biosolids and biochar for land application. Journal of Cleaner Production. Journal of Cleaner Production. Vol. 91, 118–127. New Fuels Alliance (2009). Assessment of Direct and Indirect GHG Emissions Associated with Petroleum Fuels. February 2009. Last accessed May 18, 2016 at http://www.newfuelsalliance.org/NFA_PImpacts_v35.pdf NETL (2014). Life Cycle Analysis of Natural Gas Extraction and Power Generation National Energy Technology Laboratory, United States Department of Energy. Last accessed May 20, 2016 at http://www.netl.doe.gov/File%20Library/Research/Energy%20Analysis/Life%20Cycle %20Analysis/NETL-NG-Power-LCA-29May2014.pdf Norgate, T., Haque, N., Somerville, M., and Jahanshahi, S. (2012). Biomass as a Source of Renewable Carbon for Iron and Steelmaking. ISIJ International, Vol. 52, pp. 1472– 1481. Norgate, T., and Langberg, D. (2009). Environmental and Economic Aspects of Charcoal Use in Steelmaking. The Iron and Steel Institute of Japan International, Vol. 49, pp. 587– 595. OpenLCA. (2014) GreenDelta GmbH. Last accessed March 18, 2014 at http://www.openlca.org/ PCT (2012). Bio-coal’s Potential for BC’s Economy and Environment, Pacific Carbon Trust. Last accessed May 18, 2016 at http://www.pacificcarbontrust.com/newsroom/newsreleases/bio-coal-s-potential-for-bc-s-economy-and-environment/ 116 Pourhashem, G., Spatari, S., Boateng, A.A., McAloon, A.J., and Mullen, C.A. (2013). Lifecycle Environmental and Economic Tradeoffs of Using Fast Pyrolysis Products for Power Generation. Energy & Fuels Vol. 27, pp. 2578–2587. Rousset, P., Caldeira-Pires, A., Sablowski, A., and Rodrigues, T. (2011). LCA of eucalyptus wood charcoal briquettes. Journal of Cleaner Production, Vol. 19, pp. 1647-1653. Spath, P.M., Mann, M.K., and Kerr, D.R. (1999). Life cycle assessment of coal-fired power production. National Renewable Energy Laboratory. Last accessed May 18, 2016 at http://www.nrel.gov/docs/fy99osti/25119.pdf Suopajärvi, H., Pongrácz, E., and Fabritius, T. (2013). The potential of using biomass-based reducing agents in the blast furnace: A review of thermochemical conversion technologies and assessments related to sustainability. Renewable and Sustainable Energy Reviews, Vol. 25, pp. 511–528. Suopajärvi, H. and T. Fabritius. (2013). Towards More Sustainable Ironmaking- An Analysis of Energy Wood Availability in Finland and the Economics of Charcoal Production. Sustainability, Vol. 5(3), pp. 1188-1207. Teck (2016). Personal email communication. Dave Reynolds, Trail Chief Metallurgist Teck Metals Ltd. March 28, 2016. Vadenbo, C.O., Boesch, M.E., and Hellweg, S. (2013). Lifecycle Assessment Model for the Use of Alternative Resources in Ironmaking: LCA Model for Use of Alternative Resources in Ironmaking. Journal of Industrial Ecology, Vol. 17, pp. 363–374. Weisser, D. (2007). A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy, 32, 1543–1559. Wang, Z., Dunn, JB., Han, J., Wang, M. (2013) Effects of coproduced biochar on lifecycle greenhouse gas emissions of pyrolysis derived renewable fuels. Biofuels, Bioproducts, and Biorefining, Vol. 8(2), pp. 189–204. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications 1, 1–9. 117 5 CHAPTER 5 – Project 3: Greenhouse gas assessment and carbon displacement factors of soil and carbon sequestration applications of biochar, biocoal and wood wastes in BC 5.1 Abstract In recent years biochar has been promoted as an effective soil amendment and carbon sequestration method to help mitigate climate change. Alternatively, a related product, referred to as biocoal, can be made with biochar and an organic bio-based binder, and has shown potential as another carbon sequestration/offset option. Additionally, simply burying wood waste may show equivalent or greater carbon sequestration/offset potential compared to the two previous options. This project presented a new method of carbon sequestration/offsetting through the landfilling of biocoal, biochar, and wood wastes and compared them to a detailed case study of soil applied biochar. Biocoal and wood waste landfilling scenarios produced the largest potential for carbon sequestration/offsetting at a likely range of 1.29 to 1.42 Mg CO2e / Mg original feedstock and a likely range 1.24 to 1.49 Mg CO2e / Mg original feedstock respectively, however biocoal showed the most consistency across scenarios. Biochar applied to soils were shown to have lower carbon sequestration/offset potential than existing literature, ranging from 0.66 to 1.34 Mg CO2e / Mg original feedstock, and can partially be explained by the assumed use, or not, of pyrolysis oils. Aside from the carbon retention of biochar, N2O emission suppression from N-fertilizer application rates were the second main influence of soil biochar carbon sequestration/offsets. Further research in the field of biochar degradation in soils will help to elucidate and or refine parameters that are not yet clear or fleshed out, such as moisture impacts on biochar degradation and environmental temperature differences. 118 This project will add a new comparison of carbon sequestration/offsetting to existing soil biochar and biocoal literature, and initiate a discussion about the potential use of biomass as a carbon sequestration method, when either thermally reformed into biocoal or directly used and buried. These results can be compared to combustion options of biomass and biocoal options, as well as technologically based air CO2 capture systems for climate change mitigation. 5.2 Introduction In recent years, biochar has been promoted as an effective soil amendment and method of carbon sequestration to help mitigate climate change (Nanda et al. 2016). In 2012 the Pacific Carbon Trust developed a biocoal offset request for proposals in BC (PCT 2012), however this did not include options for carbon storage in soils such as the Australian Carbon Farming Initiative (CFI 2013), which included biochar soil application. In this project biochar is referred to a product that is used for soil addition and amendment, whereas biocoal is a synthetic coal-like product typically used for energy applications; however, in much of the literature biochar is also named and used as a fuel (Gaunt and Lehmann 2008; Woolf et al. 2010; Hammond et al. 2011; Ibarrola et al. 2012; Pourhashem et al. 2013). Current research is somewhat conflicted in which application, combustion or noncombustion applications, results in greater greenhouse gas (GHG) reductions, however these results are dependent on project assumptions, pyrolysis process, co-product use, GHG intensities, feedstock, as well as others. Pourhashem et al. (2013) and Woolf et al. (2010) found that the carbon abatement of biochar for electrical energy production was greater with fossil fuels compared to land application, but depended on the fossil fuel’s carbon intensity, while Hammond et al. (2011), Ibarrola et al. (2012) and Gaunt and Lehmann (2008) found 119 land application of biochar to sequester carbon, or offset emissions, reduced emissions to a greater extent. Project 2 of this dissertation assessed the GHG mitigation potential of combustion uses of biocoal made from a novel pyrolysis system, whereas this chapter examines noncombustion uses. At this time, there is no research that has assessed the GHG reductions and carbon sequestration potential of landfilling biochar or biocoal, in other words, re-depositing coal-like products back into the earth. Only one short discussion paper has outline biochar’s role as a carbon sequestration method (Dufour 2013), and no research as looked at biocoal for the same application. Ultimately, this may add a new option for carbon sequestration that doesn’t require large external energy inputs as does current air carbon capture and storage methods (Leung et al. 2014). Landfilling, or geologically sequestering, biochar or biocoal has a potentially lower exposure to biotic and abiotic factors compared to biochar integrated into soils. These factors are known to influence biochar degradation and carbon mineralization to CO2 (Spokas 2010; Gurwick et al. 2013; Lorenze and Lal 2014; and reviewed in Lehmann and Joseph 2015 – Chapter 10). This is particularly applicable to the water resistant biocoal product previously modelled in Project 1 of this dissertation. In addition, the carbon percent recovery from the original wood feedstock is higher in the biocoal than it is in the biochar, thus leading to potentially greater carbon sequestration potential than biochar, which has been greatly researched and discussed for its carbon sequestration potential in soil application scenarios (Gaunt and Lehmann 2008; Woolf et al. 2010; Hammond et al. 2011; Ibarrola et al. 2012; Gurwick et al. 2013; Pourhashem et al. 2013; Nanda et al. 2016; and others). Related to this, research and discussion has occurred on the landfilling of wood and wood wastes as a carbon sequestration method (Zeng et al. 2013; Micales and Skog 1997; Kreysa 2009; Wang et al 120 2011; and countered by Köhl and Frühwald 2009). In fact, industry guidelines in British Columbia already exist for the landfilling of woody material, commonly from construction and deconstruction of buildings (BCMOE 2011) but they do not extend to the roll of carbon sequestration, only GHG mitigation from decomposition. The impact of biochar on soil properties has been extensively covered in many reviews (Shackley et al 2010; Soi et al. 2010; Spokas et al. 2012; Biederman and Harpole 2013; Cayuela et al. 2015; and He et al. 2017) and text books (Gaunt and Lehmann 2008; Lehmann and Joseph 2015) including effects on water holding capacity, bulk density, net primary production, soil biota, and biogeochemical processes, nutrient retention and GHG fluxes. Climate change mitigation is one of the main rationales for applying biochar to soils (Woolf et al. 2010; and Lorenz and Lal 2014;). Therefore a more encompasing GHG assessment is needed to understand its ability to offset climate change, and then, be placed in context to other carbon offsetting options, such as biocoal and wood waste landfill carbon sequestration. This project aims to expand on previous GHG assessment research in this dissertation, and detail a new method of carbon sequestration with biocoal, while comparing it to wood waste sequestration and the summated GHG impact of soil applied biochar. This research will be performed through a case study scenario, based in the region of Kamloops, BC. It is because of the regional emphasis on agriculture, proximity to mines and local landfill locations for carbon sequestration, and comparison to the previous chapters’ results that this location was maintained. Therefore, this study aims to assess GHG reductions/carbon sequestration of biochar as a soil amendment, and biocoal, biochar, and wood waste as a longterm carbon sequestration mechanism. 121 5.3 Methods 5.3.1 Goal and scope As similar to previous chapters, this investigation drew upon the ISO 14040 and ISO 14044 protocols in this GHG assessment (ISOa, 2006; and ISOb, 2006). Identified major scopes for this project are shown in Figure 5.1. This project aimed to research and compare the GHGs of non-combustion options for biocoal and biochar, as a landfill carbon sequestration mechanism and soil amendment. The boundaries of this research reflect common methods from existing biochar GHG assessments (Wang et al. 2013; Pourhashem et al. 2013; Huang et al. 2013; Ibarrola et al. 2012; Hammond et al. 2011; Woolf et al. 2010; and Gaunt and Lehmann 2008) and included stages from feedstock production to soil and landfill application, including the GHG effects of biochar application to soil. Assessed in Project 1 Assessed in this project Figure 5.1 GHG Lifecycle scope of research project 3 with research work in white. 122 5.3.2 Inventory data collection (Databases, sources, and analysis tools) All factors that affect the assessed GHGs for biocoal production were performed in the inventory analysis in Project 1, and subsequently used to generate values for biochar in this chapter. Relevant fossil fuel GHGs applicable to this project, including biocoal, biochar, and wood waste degradation values from biotic and abiotic factors, were collected in this project’s inventory analysis and used for comparison over a 100-year time frame (further discussed in the section 5.3.6 Lifecycle impact and GHG assessment). 5.3.3 BC Biocarbon pyrolysis system and products Information regarding BC Biocarbon’s pyrolysis system is described in Project 1 and originates from BC Biocarbon (2015). Similar to Projects 1 and 2, this case study was set in Kamloops, BC and was used as the central point for modelling aspects of the project, such as transportation and climate. No modifications to BC Biocarbon’s system were assumed for the assessment of the biocoal. The biocoal made by BC Biocarbon is made from a mixture of 50% biochar and 50% organic-based binder made from the pyrolysis co-products. Thus, biochar GHG production emissions are 50% of the original at gate emissions for biocoal as emissions were allocated on a mass basis. Mass allocation of emissions is congruent with the two previous chapters and supported by Jungmrirt et al. (2002) for bioenergy products. Emissions for biochar and biocoal were calculated with the addition of transportation, biotic, abiotic, and environmental effects leading to changes in GHGs. End use of biocoal, biochar, and wood were modelled for delivery transportation at 100 km to landfill or field application, and via freight lorry. Freight lorry emissions were sourced from the Ecoinvent database, and as applied in OpenLCA as in Project 1. 123 Biocoal production results from Project 1 were used as the GHG production emissions basis; however, sawmill residue feedstocks and roadside slash feedstock numbers were used in this analysis, excluding hybrid poplar feedstocks due to their current limited applicability in British Columbia. This is due to sawmill residues representing the most likely feedstock source for BC Biocarbon (BC Biocarbon 2015), while roadside slash feedstocks present a substantial opportunity for reducing GHG emissions and sequestering carbon. The three scenarios from Project 1 that represented the average production emissions at gate for biocoal and biochar produced from sawmill residue feedstocks were used in this project and were based on the work of Athena (2018), Sambo (2002), and Nyboer (2008). The same sources were used to source emission values for wood sequestration based on sawmill residues. Roadside slash feedstock for biocoal and biochar production, and wood sequestration use emissions were based off the Project 1 200-km roadside slash recoverydistance scenario from Lindroos et al. (2011), along with upstream emissions provided by Sambo (2002). 5.3.4 Biocoal, biochar and wood characteristics Biocoal, biochar, and wood characteristics were used to assess the various modelling scenarios for carbon sequestration/offsets and to qualify the most likely scenarios of GHG emissions and are shown in Table 5.1. Added examples of biochar are to support the ultimate analyses of biochar samples performed by Loring Laboratories ltd, Calgary, AB on behalf of BC Biocarbon (2015). Table 5.1 Biocoal, biochar and wood characteristics used in this project. C H O Ash % dry basis % dry basis % dry basis % dry basis Heating Value (LHV) (HHV) Bulk Density Specific Particle Density GJ/Mg kg/m^3 kg/m^3 O:C Molar Ratio H:C Molar Ratio R50 124 Biocoal 80.91 3.691 12.941 2.171 29.61 8001 11104 0.211 0.541 0.543 Biochar 92.531 0.941 3.381 2.751 27.81 2755 18505 0.051 0.121 0.533 6 6 6 6 6 6 6 Other 81.4 3.0 15.3 4.6 29.2 0.1 0.4 N/A biochar 89.317 2.577 7.347 2.287 N/A 0.117 0.347 N/A examples 84.847 3.137 10.27 12.847 N/A 0.167 0.447 N/A Wood 50.72 6.0632 41.22 1.102 19.82 2682 4152 0.6112 1.4222 N/A waste 1 Values were obtained from BC Biocarbon (2015) from an ultimate analysis independently performed by Loring Laboratories ltd, Calgary, AB. 2 Value were obtained from an amalgamation average of various wood wastes including: wood chips, softwood, sprucewood, hybrid popular, pine chips. 3 Values obtained by thermogravimetric analysis for this project, performed by Naoko Ellis' Lab in the department of Chemical and Biological Engineering. 4 Values were obtained from BC Biocarbon (2015) and sourced from an independently performed analysis by James Butler through partnership with National Research Council Canada. 5 Value sourced from Santín et al. 2017, biochars made from dead wood at highest heating temperatures of 500 and 600 °C. 6 Values were obtained from Mohanty et al. 2013. SPWB: slow heating rate pinewood biochar at 400-500 °C. 7 Values were obtained from Lee et al. 2013 and represent wood stem (first value) and wood bark (second value) biochar at highest heating temperatures of 500 °C. O/C and H/O ratios were calculated from given data. Physical characteristics of the biocoal and biochar produced by BC Biocarbon are different even though the biocoal is made from the 50/50 mixture of biochar and binder. The biochar, like many wood-based biochars, is a charred, brittle, crystalline carbon product that is essentially identical to wood charcoal, just with a different name and more commonly known in the research field for soil integration. It is also highly porous and with a low density as indicated with its bulk density in Table 5.1. Physical characteristics of the biocoal are the same as described in Project 1. Biochar, binder and biocoal were thermogravimetrically analyzed at the University of British Columbia to quantify their R50 values. R50 values have been used in multiple studies to quantify and compare the recalcitrance of charred biomass products (Harvey et al. 2012; Zhao et al 2013; Windeatt et al. 2014; Gomez et al. 2016). The R50 value is defined as the temperature point at which 50% of the charred material’s mass is lost through combustion, excluding the initially assumed moisture and final ash content, then compared to the same value of pure graphite (Harvey et al. 2012). In this project, the R50 is used to qualify the most likely recalcitrance scenarios for both the carbon sequestration and soil applications. The 125 method for the thermogravimetric analysis was developed as the average method used in Harvey et al. (2012), Zhao et al (2013), Windeatt et al. (2014), and Gomez et al. 2016 with a starting temperature at 21°C, a temperature ramp rate of 10°C/min, a temperature cut off at 1000°C, and reacted in air. R50 values found are shown in Table 4.1, and thermogravimentric graphs are shown in Figure 5.2. 126 a) 16 Assumed moisture loss under 100°C (starting mass 14.86 mg) 13.91 mg average higher plateau 14 Mass (mg) 12 10 R50 = 0.53 8 (50% Mass loss at 7.13 mg; 471.92°C) 6 4 Assumed remaining ash 0.36 mg average lower plateau 2 0 0 100 200 300 400 500 600 700 800 900 1000 Temperature (°C) b) Assumed moisture loss under 100°C (starting mass 31.42 mg) 30.82 mg average higher plateau 35 30 Mass (mg) 25 20 R50 = 0.54 (50% Mass loss at 16.40 mg; 475.72°C) 15 10 Assumed remaining ash 1.97 mg average lower plateau 5 0 0 100 200 300 400 500 600 700 800 900 1000 Temperature (°C) Figure 5.2 Thermogravimetric thermograms for wood residue (hog fuel) a) biochar and b) biocoal made by BC Biocarbon. R50 values are corrected for moisture and ash content. R50 calculated from graphite reference temperature of 886 °C (Harvey et al. 2012); e.g. a) 471.92/886=0.53=R50. 127 5.3.5 Application scenarios 5.3.5.1 Biocoal, biochar and wood waste for carbon sequestration As mentioned above, biocoal was modelled from emissions presented in Project 1, and in this project, the transportation from Kamloops, BC, degradation emissions, and emissions associated with landfill creation and operations were added from the Ecoinvent 3.1 database in OpenLCA (OpenLCA 2014; and Ecoinvent 2014) and exported to Microsoft Excel. Biocoal and biochar for carbon sequestration were similar, however the landfilling of biochar is assumed to be a simplified scenario of the production and disposal of activated charcoal. Additionally, the scenario could also represent a scenario where the biochar is landfilled directly and the co-product pyrolysis oils or tars are targeted, such as in a fast pyrolysis system for liquid fuels production (reviewed in Carpenter et al. 2014 and Perkins et al. 2018). Because the degradation of biocoal and biochar has not been assessed for carbon sequestration in a landfill scenario, 5 degradation scenarios were developed for this assessment and modelled to test potential differing quantities of CO2 and CH4 loss. This assessment is based on a physical-chemical quantification of the available atoms of oxygen available to react with carbon, either through a biotic and abiotic mechanism, and thus form CO2. Additionally, wood waste landfill sequestration was also tested under these scenarios. They were: 1) No degradation; 2) Limited CO2 release based on macropore O2; 3) Full CO2 based on embedded O2 and macropore O2; 4) Full CH4 burned and equal CO2; and 5) Full CH4 release. The ‘no degradation scenario’ assumed no CO2 would be lost from the landfilled material and represents the most conservative estimate. ‘Limited CO2 release based on macropore O2’ assumed that 100% of O2 contained in the macropore space around the landfilled materials (biocoal, biochar, wood waste) would react either biotically or abiotically with carbon to form CO2, and be released to the atmosphere. ‘Full CO2 based on embedded 128 O2 and macropore O2’ expands on the previous scenario by adding the molecular bound O2 from the landfilled material to the pool of available O2, which could react to form and release CO2. ‘Full CH4 burned and equal CO2’ was modelled through BC’s Landfill Gas Generation Assessment Procedure Guidelines and Landfill Gas Generation Estimation Tool (BCMOE 2017). The Landfill Gas Generation Estimation Tool categorizes various common landfilled materials and moisture contents and estimates the amount of anaerobic CH4 produced over a set period of time. BC’s Landfill Gas Assessment is a ministry applied legal requirement for landfills receiving over 10,000 Mg per year or over 100,000 Mg capacity, and assumes that at these levels CH4 is combusted in a flair-stack or used for energy purposes; at the least being fully combusted to CO2 and water. Although the Landfill Gas Generation Estimation Tool is limited in scope and does not include materials such as biochar and biocoal, their release of CO2 and CH4 are in line with other items that are available in the model such as asphalt and tar. Exponential decay values were extrapolated from the model output (R2 value of 1) and projected to 100 years. Table of factors used within the Estimation Tool are shown in Table 5.2. Table 5.2 Table of factors used within the BC Landfill Gas Generation Assessment Procedure Guidelines and Landfill Gas Generation Estimation Tool (BCMOE 2017) for biocoal, biochar, and wood wastes. Inert level 1 2 Biocoal Biochar Wood wastes Relatively Inert1 Relatively Inert1 Moderately Decomposable Annual precipitation factor for Kamloops region 0.01 0.01 0.01 Approximated due to chemical similarities to asphalt/tar. Represent water infiltration and addition to the landfill. Water Addition Factor2 1 1 1 Equal molecules of CO2 and CH4 were also modelled due to the chemical pathway of CH4 production where approximately one molecule of CO2 is produced for every molecule of CH4. In this scenario, produced CH4 was assumed to be flared and burned to CO2 to reduce its 129 global warming potential. ‘Full CH4 release’ scenario used the same anaerobic CH4 production emissions from the BC Landfill Gas Assessment, but did not assume the CH4 to be combusted. The one to one release of CO2 was also assumed for each molecule of CH4 produced and released. 5.3.5.2 Biochar for soil application The overall method for estimating greenhouse gas emissions and carbon sequestration/offset potential was to elucidate the most applicable literature values for biochar applied to agricultural soils. This is akin to using lifecycle assessment software/databases and applying factors that best fit a model and adjusting for defined circumstances. Five factors were assessed for their net biochar GHG impacts: biochar degradation/stability, soil texture effects on biochar degradation, non-CO2 emissions, biochar priming/carbon flush effect and environmental temperature impacts, all of which are discussed further below. A literature review was performed and then assessed for inclusion in the analysis best related to the biochar characterized in this project. Biochar degradation was primarily quantified through the use of incubation research and qualified through the above mentioned R50 analysis and below discussed H:C molar ratios within the context of environmental temperatures. Leng et al. 2019 reviewed the methods for quantifying biochar stability and concluded three general types: 1) incubation and mineralization modelling, 2) determination of resistance to oxidation, and 3) carbon structure analyses. The methods employed in this assessment mentioned above touch on each of the 3 biochar stability types outlined by Leng et al. respectively. Ideally this aims to provide a broad check on the quantification and qualification of this assessment’s results. 130 Research of biochar degradation tend to present findings in Mean Residence Time (MRT), and can be inversed (1/MRT) and adjusted from years to days to equal the percent daily degradation. These degradation rates were then projected to 100-years. Singh et al. (2012) was chosen as the most applicable literature to draw from because their results described the longest study to date, of 5-years, and examine biochar made from a woody biomass, Eucalyptus saligna and at peak heating temperature of 550°C, which is assumed to be similar to the feedstock and biochar and biocoal peak heating temperatures from BC Biocarbon (2015). Biochar degradation/stability was qualified from an equation presented by Zimmerman 2010 (Equation 5.1). The equation was used to qualify and support the soil degradation values found in Singh et al. (2012). The first order equation predicts the 100-year degradation of biochar incorporated into soils and is based off a detailed biochar degradation study performed by Zimmerman. Clost = (Co*eb/m+1)tm+1 Equation 5.1 Percent carbon loss equation from Zimmerman 2010. Slope (m=-5.419) and intercept (b=-0.556) were obtained from Zimmerman’s supplementary information Table S5, from course biochar produced from pine feedstock at 525°C. Where Co is the initial biochar mass, t is the time frame set at 100 years, b and m are the intercept and slope from supplementary information Table S5 Zimmerman (2010) for course biochar produced from pine feedstock at 525°C, respectively. Soil texture has been examined to determine how it may play a role in biochar degradation rates in soils (Qayyum et al. 2011; Bruun et al. 2013; Bamminger et al. 2014; Kuzyakov et al. 2014; Fang et al. 2015; Singh et al. 2015; Malghani et al. 2015; and Gronwald et al. 2016). However, it was determined through a literature review that at this 131 time there is insufficient data to apply biochar soil texture specific degradation rates. This was because of the limited number of experiments that clearly differentiated particle size distribution of studied soils, i.e. soils presented were similarly classified under the Canadian soil classification system (Fang et al. 2014; Fang et al. 2015), limited and/or recent field trials (Singh et al. 2015; Malghani et al. 2015; and Gronwald et al. 2016), and showed no clear significant differences in soil degradation rates (Singh et al. 2015). Non-CO2 GHG emissions were included in the literature review that investigated the potential impacts of biochar addition to soils. These non-CO2 sources included methane (CH4) and nitrous oxide (N2O). He et al. (2016) and Cayuela et al. (2015) performed separate metaanalyses and were both chosen to source data from, as each of the meta-analyses had detailed specialties relating to either CH4 or N2O. Cayuela et al. (2015) was most applicable for predicting N2O emissions in the current study because the paper was subdivided into field studies (most relevant to this study), whereas in He et al. (2016) incubation, greenhouse, and field experiments were pooled together. Overall, Cayuela et al. found biochar addition to soil reduced N2O by 28%, based on an average application rate of 24 Mg / 10,000 m2 (1.16 w/w%) found from the field trial data in their supplementary information. The temporal effect of biochar-related N2O suppression has been infrequently reported in the literature, and this has led to methodological assumptions for this project. Low-end and high-end scenarios were applied and were based off the range of available research and highest possible N2O offset potential. Research from Spokas (2012) and Hagemann et al. (2017) indirectly and directly indicate that the suppression of N2O occurs for at least 3 years after biochar application, and was thus used for the low-end scenario of this research. 132 In the high-end scenario, suppression of N2O was extended for 100-years to determine the highest possible emission reduction potential. The high scenario was rationalized because biochar’s persistence in the soil and its physical and chemical composition will stay relatively constant once surface hydrogen and carbon groups are oxidized to form carboxylic, carbonyl, and hydroxyl functional groups (Hilscher et al. 2009; and Mukherjee et al. 2011). It is the opinion of the author that this chemical and physical consistency could translate to a 100-year timeframe and was thus used. In order to estimate N2O emissions from soils in the Kamloops region 3 typical crops of the region, timothy grass, carrots, and bush beans, were modelled to represent high (120 kg/10,000 m2 N applied), medium (70 kg/10,000 m2 N applied) and low (40 kg/10,000 m2 N applied) N-fertilizer requirement examples, respectively, however only the high and low scenarios were presented in order to show the high-end range and low-end range of emissions. Emissions factors for N2O were included for N-fertilizers as per IPCC (2013) and equated to 1% of N applied fertilizers being released as N2O with an uncertainty range of 0.3 – 3.0%. For CH4 production effects from biochar applied to soils, He et al. (2016) showed through their meta-analysis that biochars made from woody material, and applied to field experiments, did not show a significant effect in fertilized soils. Therefore, no changes in CH4 production was used in this project. In their meta-analysis scenario breakdown, wood-based biochars showed an average, but non-significant, decrease in CH4, and when in fertilized soils biochar on average increased CH4 production, but again was not significantly different from no change. Essentially, this shows that the application of biochar to soils has differing effects on CH4, and is dependent on the application scenario. The most recent meta-analysis on the impact of biochar on soil carbon priming/carbon flush effects was performed by Wang et al. (2016). Soil carbon priming/carbon flush effect is 133 the process of an increased rate of soil carbon release, primarily as CO2 through the addition of a new substance/substrate to the soil or environmental change. This effect can be through chemical, or more commonly, biological degradation of the original biomass feedstock, however priming can also be a negative effect where less carbon is released from the soil than normal. The meta-analysis by Wang et al. (2016) showed that biochars that are similarly categorized in this project - meaning produced by slow pyrolysis, high temperatures of approximately 600°C, and made from woody materials - did not show statistical differences from zero, therefore this factor was not applicable for inclusion in this paper as it did not impact GHG emissions. Cation exchange capacity/fertilization-use-efficiency literature was reviewed to assess whether biochar has the potential to reduce the need for N-fertilizers by reducing the leaching of ammonium and/or nitrate. The most recent and applicable multi-year field experiments showed that there is a statistical effect on ammonium and nitrate leachate (and commonly reductions), however, there was no effect translating to reduced application requirements of N-fertilizers (Ventura et al. 2013; Guerena et al. 2013; and Goa et al. 2016). This was shown in comparisons where no differences were seen between biochar and non-biochar treatments and yield of plants (Ventura et al. 2013; Guerena et al. 2013; and Keith et al. 2016), and/or no change in N uptake by the plants (Keith et al. 2016). Environmental temperature impacts on biochar degradation was assessed from the literature. Most literature has described the Q10 temperature coefficient, which relates the change in reaction rate of a molecular or biological process to a 10 ºC change in environmental temperature (reviewed in Lehmann and Joseph 2015 - Chapter 10). Two factors indicate that the role of environmental temperature on biochar degradation was chosen not to be applied given this project’s parameters: H:C molar ratio and experimental research 134 limitations. The H:C molar ratio for the biochar assessed in this project (Table 4.1) situated it below the range of data presented in Lehmann and Joseph (2015) (Chapter 10 – Figure 10.5) with respects to differing 100-year degradation rates between 10 ºC and 20 ºC (H:C range 0.2 – 1.2). This indicated that the biochar assessed here represents a more recalcitrant carbon based on a lower H:C ratio than the literature interpreted by Lehmann and Joseph. Additionally, the r2 value from Lehmann and Joseph for the two linear regressions was 0.45 representing a mid-range coefficient of determination. 5.3.5.3 Roadside slash business as usual scenarios A brief comparison to business as usual scenarios was added to show context around roadside slash and possibly leaving woody debris in the forest. Roadside slash pile combustion emissions are offset and sourced from Lee et al. (2010). Scenarios of roadside slash and sawmill residues cleanly combusted in a boiler – indicating without appreciable CH4 or N2O emissions or smoke - are also shown for comparison, and are assumed to be additive capacity and not replacing or offsetting natural gas or other fossil fuels. Emissions from roadside slash combusted cleanly in a boiler included emissions for collection and transportation 200 km to combustion facility (as outlined in Lindroos et al. 2011), and roadside slash combustion offsets (Lee et al. 2010) and as used previously in Projects 1 and 2 of this dissertation. Sawmill residues cleanly burned (without smoke) only included the allocated emissions of the feedstock supply chain from sawmill operations (Nyboer 2008) and harvest operations (Sambo 2002). 5.3.6 Lifecycle impact and GHG assessment Information collected and assumptions made in the inventory analysis were used to calculate the lifecycle assessment GHG analysis in OpenLCA from Ecoinvent data (OpenLCA 2015; and Ecoinvent 2014). Applicable values were then exported to Microsoft 135 Excel for further GHG assessment scenarios with additional values and factors. All GHG values were reported for 100-year global warming potentials from the IPCC (2013) report. IPCC metrics have previously been used for GHG assessments (Rousset et al. 2011; Pourhashem et al. 2013; Wang et al. 2014; Vadenbo el al. 2013; and others). The net GHG emissions describe the sum of CO2 equivalent (CO2e) emissions and are referred to as the Net Carbon Sequestration/Offset Factor. Net carbon sequestration/offset factors seen in this project are analogous to the displacement factors calculated in Project 2, however the results are now expressed in Mg CO2e/Mg original feedstock for appropriate comparison to wood waste. In all scenarios modelled, the CO2 released from any oxidative degradation or combustion of wood wastes and biochar were considered carbon neutral as referenced in the British Columbia Greenhouse Gas Inventory (BC MOE 2012). Any carbon that is lost to the atmosphere, reported in the form of CO2e, then corresponds to a smaller carbon sequestration factor, and is represented in Equation 5.2. Net Carbon Sequestration or offset factor = Net Mg CO2e Mg Original feedstock = carbon sequestered after 100 years − Biochar production emissions − biochar impact emsssions Equation 5.2 Sample carbon sequestration/offset factor for biochar. Biocoal and wood waste carbon sequestration/offset factors are also similarly calculated. Net sequestration/offset factors values were reported for, and projected, to 100-year time frames, for example the total degradation of biochar in soil was modelled at the 100th year after 100 years of carbon loss in the form of CO2e. Sample calculations and key data are presented in Appendix 3 Supplementary Information. 136 5.4 Results Figure 5.3 displays the net carbon sequestration/offset factors for biochar, biocoal and wood waste. Depending on the sub-scenarios, either landfill sequestration of biocoal or wood waste demonstrate the largest opportunity for net carbon sequestration/offset per Mg original feedstock. Variation in sub-scenario results are least in biocoal and biochar landfill sequestration and greatest in wood waste sequestration. Products and applications from the use of roadside slash had larger net carbon sequestration/offset factors. 137 138 2 C ll r o O 2 n se ba on d r ac O2 CH 4 r bu O d an 2 9 1.2 d ne re o op 2 1.4 r ac m ll Fu nd 2 9 1.2 O a e or op 2 1.4 6 1.1 e as le re 0 1.4 9 1.2 a ad gr de n tio re o op 0.8 Ⓛ 0 4 0.7 O 2 4 0.7 re o op 0 0.8 O 2 4 0.7 3 0.7 O2 lC ua eq 0 0.8 7 0.6 e as le re 9 0.7 Biochar Landfill Sequestration Scenarios Feedstock from roadside slash Feedstock from sawmill wood waste Legend 4 0.7 1 -0.1 0.0 9 0 -0.1 3 0.0 Roadside Slash Business as Usual Scenarios 3 1.7 6 1.8 3 1.7 6 1.8 6 1.1 Ⓛ 9 1.2 6 1.3 Ⓛ 9 1.4 3 -0.6 Ⓛ 0 -0.5 0 0.7 Ⓛ 6 0.7 4 1.2 Ⓛ 0 1.3 Biochar Soil Sequestration/Offset Scenarios e 2 2 n n s) s) ot i ler il er O2 as tio tio dl as an eO eO le gr lC us oo bo n bo da be or or re a a b y n p p r w i u h i 4 4 4 h m in g r ro r ro y y eq us ot de co nl nl CH CH CH ac ac ac ac d d (B o o im ll ll ll m m ld e red lea l ea M M an an o T e N N u u u i ( d d i c t c r n n F F F f t a o o ed ed io an an m sca ted t ed rn rn en ar ed ed sc O2 O2 fro eft bus bus bu bu as as en t c d d b b 0 4 4 e L e e m m 2 e e ts H H fs N b - Co Co dd dd as as of fse lC lC le be be n/ nd U1 a - b ele ul ul of a re r o m m / i F F 2 2 t e e n 4 BA U 2 2 U io tra on on CH CO CO at es BA BA d d d d 2, str qu se se e te O e a a it e i s b b qu m m -C 2 2 w se Li Li a O h Lo CO g i U1 ll C l l H Fu BA Fu 7 1.2 O2 lC ua eq 2 1.4 Biocoal Landfill Sequestration Scenarios de ed M n tio 1.2 9 Ⓛ b em d se ba o -0.70 d e as ele N a ad -0.20 gr de 0.30 0.80 1.30 1.80 Figure 5.3 Carbon sequestration/offset factors for biocoal, biochar and wood waste along with the business as usual (BAU) cases currently performed for reference. Negative numbers equate to a net GHG increase/loss of carbon to the atmosphere. Ⓛ symbol indicates the most likely scenarios and explained in the discussion. Fu d it e m i L CO Mg CO2e Sequestered/offset after 100 years/Mg of original wood feedstock Wood Waste Landfill Sequestration Scenarios Ⓛ The percent breakdown of GHG contributions from soil applied biochar showed biochar carbon sequestration had the greatest reduction on GHG emissions in both low and high N2O emission reduction scenarios (Figure 5.4a and b). In the ‘low N2O emission reduction scenario’, N2O emissions did not affect the results of the overall GHG analysis. In the high N2O emission reduction scenario, the second highest GHG emission contribution was from N2O emission reduction. Soil Biochar % GHG Breakdown a) Low N20 emission reduction scenario Low N20 emission reduction scenario Sawmill residues Roadside slash emissions offset 0% 6% -86% 9% Roadside slash residues Loss of biochar from degradation 0% -100% -76% -80% -11% -60% -40% -20% 5% 0% 8% 20% Sequestration of biochar in soil Biochar production emissions Percent allocation of GHGs Soil Biochar % GHG Breakdown b) High N20 emission reduction scenario Roadside slash emissions offset Sawmill residues -38% -53% Loss of biochar from degradation 3% 5% Roadside slash residues Sequestration of biochar in soil -49% -36% -100% -80% -60% -40% Percent allocation of GHGs -7% 3% 5% -20% 0% 20% High N20 emission reduction scenario Biochar production emissions Figure 5.4 Percent breakdown of GHG contribution emissions from soil applied biochar made from a) Low N2O emission reduction scenario (biochar soil effects for 3 years and 40 kg N/10,000 m2), and b) High N2O emission reduction scenario (biochar soil effects for 100 years and 120 kg N/10,000 m2). For the ‘Low N2O emission reduction scenario’, 0% was rounded down from 0.02%, but still shown for direct image and scenario comparison. Negative values denote a reduction in GHGs from business as usual scenarios. 5.5 Discussion 5.5.1 Interpretation of results Biochar’s importance in potentially sequestering large amounts of carbon in surface soils (e.g. agricultural topsoils) has led to the examination of its recalcitrance and 139 decomposition (rate and extent) in soils as primary biochar research topics (Harvey et al. 2012; Zhao et al 2013; Windeatt et al. 2014; and Gomez et al. 2016), while biochar, and indirectly biocoal, have only recently been proposed as a direct carbon sequestration method from a geological or landfill storage context (Dufour 2013). Therefore, the results presented in this work provide a first known assessment on the comparative opportunity of using biocoal, biochar, and wood wastes as carbon sequestration methods (i.e. non-soil storage). With that said, results presented in this project depend on the interpretation and likelihood of the various scenarios presented in Figure 5.3, and additionally the assumptions made within. Key assumptions that should be noted before interpretation of the results are: (i) the biocoal and biochar modelled in this assessment is based on a manufactured product made by BC Biocarbon, that is produced in a high temperature pyrolysis system, around 550 to 600°C, and (ii) these materials are made from common wood wastes such as sawmill residues and roadside slash. Along with this, the characteristics of the biocoal and biochar presented in Table 5.1 characterize the products as highly recalcitrant, whereas other biochars made from grasses or manures, and at low temperatures around 350 to 450°C, are known to be less recalcitrant (Harvey et al. 2010; and reviewed in Lehmann and Joseph 2015). Therefore, the results of this assessment, particularly with respect to biochar in applications to soil, is only perceived to be relevant to the type of biochar described. Further analyses and research will need to expand this project to assess other biochars as their characteristics and performance in soil will be different. 5.5.2 Biocoal, biochar and wood waste for landfill carbon sequestration 5.5.2.1 Wood waste scenarios Wood waste landfill sequestration scenarios presented the most variability due to the potential release of CH4 and full potential to sequester all original carbon. However, the most 140 likely scenarios are ‘Full CH4 burned and equal CO2’, ‘Full CO2 based on embedded O2 and macropore O2’ and ‘Full Methane release’. The most likely scenario ‘Full CH4 burned and equal CO2’ is based on BC’s Landfill Gas Generation Assessment Tool (BCMOE 2017). This is the official and business as usual assessment protocol for modelling GHGs from the degradation of woody material in a landfill, and likely represents an accurate assessment of emissions from landfilling wood for carbon sequestration. Supporting the results of the ‘Full CO2 based on embedded O2 and macropore O2’ scenario is at least partially backed by literature that has examined the degradation of wood in landfills (Micales and Skog 1997; and Wang et al. 2011). These papers demonstrated that degradation of wood material is often slower than typically described in landfill gas models, however in this project a lower carbon sequestration/offset potential was shown versus the BC’s Landfill Gas Generation Assessment Tool scenario ‘Full Methane burned and equal CO2’. Woody material persists in landfills primarily due to the lignin content being known to inhibit degradation of cellulose and hemicellulose and as well as being a more recalcitrant form of carbon (Reviewed in Barlaz 2006). Barlaz estimated that 0.195 kg of carbon would be stored in the form of lignin, cellulose, and hemicellulose per kg of dry wood waste and would translate to 0.715 kg of CO2 per kg. This would be approximately equivalent to the ‘Full CO2 based on embedded O2 and macropore O2’ scenario in this project. However, the time period for carbon sequestration was not discussed in Barlaz and could be a longer projection beyond 100 years, being explained by further time leading to further decay. Interestingly, the scenario of ‘Full CO2 based on embedded O2 and macropore O2’ represents the theoretical limit of carbon decay from woody material because the scenario allocates all oxygen, in the macropore space and molecular makeup of the wood, and converts it to CO2. No further 141 oxidation would be capable because no freely available oxygen would be available in the landfill system, unless introduced. Reservation is warranted when inferring wood sequestration because of the variability in the scenarios. If the landfill is below the threshold of receiving over 10,000 Mg per year or over 100,000 Mg capacity, as per the estimation tool, no CH4 flaring is legally required (BCMOE 2017). Similar to this, even if landfill CH4 is being collected and flared, leaks are still known to occur even under the best-case landfill gas recovery systems (Thompson et al. 2009; Spokas 2006; and Lee et al. 2017). Lee et al. (2017) showed that even with wood landfill sites under updated values proposed in their research, approximately 3% of carbon’s fate is lost in the form of non-collected CH4 (value estimated from Figure 4). In this case, each carbon atom lost to CH4 equals 34 times 3% of carbon essentially equaling 112% loss of carbon sequestration value over 100 years based on the IPCC (2013) CH4 global warming potential. Thus, due to the methane’s high global warming potential this would essentially nullify the potential of the wood sequestration, plus being a net release of carbon, and risk any evaluated and purchased carbon sequestration project. If added oxygen was introduced into the landfill it would further the carbon degradation and CO2 loss, along with increasing CH4 production, again, reducing the carbon sequestration/offset potential and ultimately being a net emitter. The methods employed in this assessment do encompass a range of possible scenarios, however they do not accurately reflect the risk of CH4 release. The risk of CH4 release makes wood sequestration less predictable and therefore unlikely to be validatable as a carbon sequestration method, unless wood degradation could be entirely prevented somehow. 5.5.2.2 Biochar landfill scenarios 142 The quantification of CO2 and CH4 released from biochar landfilling did not take into consideration the reported indicators of high carbon recalcitrance, such as: high production temperatures (Singh et al. 2012), low O:C ratio (Spokas et al. 2010; and Enders et al. 2012), low H:C ratio (Enders et al. 2012) and low R50 value (Harvey et al. 2012; Zhao et al. 2013; Windeatt et al. 2014; and Gomez et al. 2016), however the results impact was negligible. Based on these metrics the most likely scenario was the ‘No degradation’. If considering no additional input of oxygen to the landfill the ‘Full CH4 burned and equal CO2’ scenario was very similar to ‘No degradation’ because the biochar was modelled as “relatively inert” in the BC Landfill Gas Generation Assessment Tool. Asphalt and tar were other similar compounds listed as relatively inert and are broadly chemically similar to biochar, and biocoal (discussed later). Biochar for landfill sequestration, and applied to soils (discussed later), has one caveat for their potential carbon sequestration/offset factor. That is, what is done with the remaining pyrolysis oils and binder that are also derived from the original feedstock. Depending if these co-products are sequestered as well, but in a recalcitrance form, this can increase the carbon sequestration/offset factor by approximately 40%, being similar to biocoal in this project. If the co-products are combusted cleanly without CH4 or N2O emissions, then that fraction of the wood waste is considered carbon neutral as per the British Columbia Greenhouse Gas Inventory (BC MOE 2012). If the co-products are left to biodegrade and CH4 is produced and not controlled for, then this would start to lower the overall carbon sequestration/offset factor for the biochar because of the increase in GHG emissions. 5.5.2.3 Biocoal landfill scenarios Biocoal landfilling for carbon sequestration had, like the biochar, a very low level of variation between the scenarios and can be inferred to have the most likely certainty for the 143 modelled 100-year time period. Similarly, to biochar, the most likely scenario was “No degradation” because of its high production temperature, low O:C Ratio, low H:C Ratio, and low R50 value, albeit slightly higher than biochar for the O:C Ratio, H:C Ratio, and R50 values. Additionally, biocoal’s characteristics are a solid water impermeable product similar to fossil coal, and thus helps increase the likelihood of certainty for the scenarios, as it would seemingly act as coal while being buried underground. The kind of biocoal product described in this project, as far as we know, has not been investigated as a carbon sequestration option before and thus represents an entirely new method for climate change mitigation. Dufour (2013) is the only paper that has discussed biochar as a dedicated landfill carbon sequestration product, but again, biochar does not contain the approximate additional 40% of carbon from the original feedstock as does the BC Biocarbon biocoal. Given that this is the very first known attempt at quantifying the carbon sequestration/offset factors for biochar and biocoal, the physical-chemical methods employed here, along with the validation of scenarios using supplementary information, is a novel approach. Ultimately however long-term in situ experiments of biocoal and biochar landfill sequestration would need to be performed to refine or validate the theoretical findings in this assessment. 5.5.2.4 Biochar soil scenarios Results for biochar applied to soils was presented by demonstrating the high and low scenarios of two different crops commonly found in the Kamloops region: Timothy grass, and bush beans, respectively. Through reviewing existing literature, it seems that the methods employed in this assessment are the most intensive in attempting to quantify the lifecycle GHG emissions and potential for carbon sequestration with soil applied biochar. Many theoretical, lab and field experiments, and reviews have performed analyses based on various 144 individual factors such as feedstock type (Woolf et al. 2010; Ibarrola et al. 2012; and McBeath et al. 2015), production temperatures (Ibarrola et al. 2012; and Malghani et al 2013) and environmental temperatures (Nguyen et al. 2010; Fang et al. 2013b; Singh et al. 2012; and Cheng et al. 2008), soil types (Singh et al. 2012; Fang et al. 2014; and Malghani et al. 2015), non-CO2 GHG emissions (reviewed in Cayuela et al. 2015 and He et al. 2017), cation exchange capacity and its effect on fertilization use efficiency (Ventura et al. 2012; Angst et al. 2013; Hardie et al. 2015; and reiewed in Jeffery et al. 2014) biochar and soil carbon priming/carbon flush effects (reviewed in Wang et al. 2016) and of course biochar degradation (Reviewed in Spokas 2010 and Lehmann and Joseph 2015 – Chapter 10). Some papers have looked at multiple scenarios together, typically biochar degradation and another factor (Harvey et al. 2010; Singh et al. 2010; Hammond et al. 2011; Fang et al. 2013b; and Keith et al. 2016), but few have attempted to examine the entire body of literature based on a specific biochar type to assess the complete carbon sequestration/offset factor in such a specific case study. Additionally, any comparisons of carbon sequestration/offset factors between research projects presents challenges due to the various factors involved and assumptions made. For example, Woolf et al. (2010) performed a very high-level analysis for biochar application to soils and included factors such as soil CH4, while also including biochar decomposition as increasing atmospheric carbon levels. Whereas in this project and based on He et al. (2016), biochar was assumed to not have an effect on CH4, and CO2 was deemed to be carbon neutral. Some assessments have also allocated pyrolysis oils from biochar production as a source for heat or electricity systems (Roberts et al. 2010; Hammond et al. 2011; Ibarrola et al. 2012), thus increasing the assessment’s GHG reduction or offset potential. However, pyrolysis oils are not ideal for combustion because of their high-water content, corrosive nature, low heating values, and are generally considered a low-grade liquid 145 fuel (Oasmaa and Czernik 1999; and Lu et al. 2009). Additionally, there is extremely limited implementation of pyrolysis oils for heat and electricity production, if any. Therefore, the assumption that this percent pyrolysis oil allocation for GHG reductions is hard to justify and exaggerates the carbon sequestration/offset factor. Harsono et al. (2013) and Miller-Robbie et al. (2015), however, excluded pyrolysis oils from their accounting and considered them as waste or outside the scope of their research, respectively. With that said, pyrolysis oils may have value to reduce emissions in offsetting natural gas or coal, or be thermochemically transformed into a more recalcitrant form of carbon for sequestration; it is simply the likelihood of use is deemed to be very low at this time, and thus it was assumed to be waste in this project in this assessment. Comparable research has investigated the lifecycle emissions and carbon sequestration/offset potential of biochar for soil application and ones with similar unit output results are shown in Table 5.3. Results indicate that including pyrolysis oils seemingly presents a higher carbon sequestration/offset factor than what was found in this project. However, these projects used differing feedstocks, pyrolysis temperatures, degradation and carbon storage assumptions, and GHG accounting methods. Table 5.3 Research performed on soil applied biochar with results that are comparable with units analyzed. Positive values indicate the amount of sequestered or offset GHGs through use of biochar. Cited values are presented in Mg CO2e / Mg original feedstock for ease of comparison as cited values did not always have product energy density to convert. Sawmill wood waste sourced values found in this paper are shown for comparison. Wood waste landfill sequestration most likely scenarios are noted as S1 and S2 and correspond back to Figure 5.3. Biochar GHG papers Peters et al. 2015 Kung et al. 2015 Clare et al. 2014 Carbon sequestration / offset factor Mg CO2e / Mg original feedstock 1.22 2.438 1.06 Use of pyrolysis oils and co-products to offset emissions Yes, Pyrolysis oils to run process Yes, Pyrolysis oils for electricity Yes, Pyrolysis oils for electricity 146 Wang et al. 2013 0.8 - 1.0 Yes, pyrolysis oils for gasoline 1.29 0.74 1.16 1.36 0.70 1.24 Yes, for biocoal binder No N/A N/A No No Values found in this paper Biocoal landfill sequestration Biochar landfill sequestration Wood waste landfill sequestration S1 Wood waste landfill sequestration S2 Biochar soil low scenario Biochar soil high scenario Percent allocation analysis of this project showed the largest contributor to soil biochar’s carbon sequestration/offset factor was the carbon stored in the biochar followed by the nitrogen N2O emission reduction range in both the high and low N2O scenarios (Figure 5.4). The carbon stored in the biochar was primarily assessed through degradation findings of Singh et al. (2012) and Fang et al. (2014a) and ranged from 3.8 up to 8.6 % across the 3 soil types examined. These results were generally supported by the developed degradation equation (Equation 5.1) found in Zimmerman (2010) and calculated a 100-year biochar degradation rate of 7.7%. This is admittedly on the low end of our findings. Increased environmental temperatures can show greater degradation of biochars in soils (Cheng et al. 2008; Nguyen et al. 2010; Fang et al. 2014b; and Fang et al. 2015). However, Q10 values which have been used to equate degradation rates do not appropriately reflect the recalcitrant nature and degradation scenarios of a particular biochar. For example, a high temperature biochar, made from oak at 600°C in Nguyen et al. (2010), will have a particularly low level of degradation at lower environmental temperatures, and with that, a tripling or quadrupling of degradation at an increase of 10°C thus leading to a large Q10; however, that rate will still reflect a low level of degradation compared to a low temperature biochar that has similar rates of degradation across increases of temperature, leading to a lower Q10. 147 Secondly, there has been a limited amount of research that has investigated the influence of environmental temperature on degradation of biochar in field trials. One study by Cheng et al. (2008), which represents the closest field trial of biochar degradation at differing temperatures to this study, however not directly, found a negative degradation relationship of charcoals from blast furnaces compared to mean annual temperatures (lower mean annual temperatures allowed more carbon to be retained). Overall, the temperature sensitive degradation results of their incubation study, performed at 30°C, were linked to their original regional environmental temperatures from varying US regions. Another incubation study by Fang et al. (2014b) examined an environmental temperature range of 20, 40 and 60°C between 450 and 550°C temperature-produced biochars. Biochar produced at high temperature (550°C) showed significant sensitivity to temperature differences for 2-year Q10 values, based on average mineralization rates between 20 and 40°C, but these significant scenarios decreased when comparing Q10 values based on cumulative mineralization; the more applicable metric for quantifying biochar stability in situ. Additionally, there were less statistical differences between soils in the cumulative Q10 values than the average scenario Q10 values, and with the higher temperature biochars. Overall the results of Fang et al. (2014b), and following up study Fang et al. 2015, do show there is an effect of environmental temperature on biochar, along with an effect of soil type, however these details need further investigation to elucidate more clarity in any trends or biochar types for use in temperature dependent degradation modelling. Acknowledging that environmental temperature likely does have a broad effect on biochar degradation in some cases, it is likely specific to certain biochars and under certain soil environments. Therefore, it is from the interpreted information above and limited overall studies that environmental temperature impacts on biochar degradation was determined, at 148 this time, to be unreliable or not sufficiently researched to include in this project’s analysis. Additionally, given that lower temperatures are widely believed to reduce reaction rates and thus degradation rates, results found for biochar applied to soils in the project are assumed to be conservative given that most studies and field experiments are performed at 20°C, whereas the mean annual temperature in Kamloops BC is 9.3°C (Government of Canada 2017). Ultimately, the ability to quantify to what extent the degradation rates will be reduced is an unknown at this time, given the limited data for low temperature scenarios and the factor of high C:H ratio biochars, as described in Lehmann and Joseph 2015 – Chapter 10. The N2O emission reduction range represents the range between maximum and minimum emissions but are largely related to the N-fertilizer applied to the specified crop and the percent N2O suppression. In this case, timothy grass on the high end and bush beans on the low end. The biochar application rate assessed for this project was set at 24 Mg/10,000 m2 (1.16% by weight) from Cayuela et al. (2015), which corresponded to a suppression rate of 28% in applicable field studies. However, in some lab circumstances, that were not as directly relatable to this project, Cayuela found N2O suppression percentages of 73 ± 7% when H:C molar ratios were < 0.3. Given that the biochar modelled in this project has a H:C molar ratio of 0.121, N2O suppression could have a much larger impact on overall emission suppressions, if these results can be replicated in field trials rather than in lab experiments. Biochar application rates have been found to correspond to differing reductions in N2O emissions (reviewed in Cayuela et al. 2015 He et al. 2016), their contributions were shown to be low in explaining GHG flux variation given an R2 value of 0.09. Therefore, the impact of N-fertilizer application will have a larger impact on biochar carbon sequestration/offset factor, as demonstrated between the timothy grass and bush beans 149 scenarios. This indicates that targeting specific crops with high N fertilizer requirements will benefit goals in climate mitigation. One factor of soil biochar degradation that was not explicitly examined was the impact of moisture. This is mainly due to the very limited research that has been performed in field trials. Soil moisture has shown an effect on biochar degradation under certain lab scenarios (alternating moisture and lower temperature biochars (discussed in Lehmann and Joseph 2015 - Chapter 10)), however, Nguyen and Lehmann (2009) also found moisture did not impact degradation for high temperature biochars, as well with charcoal (biochar) from historic blast furnaces (Cheng et al. 2008). The last factor of radiative forcing by biochar was not accounted for due to a dearth of research on the topic. Radiative forcing would reduce the carbon sequestration/offset factor because of increased radiation adsorption. Radiative forcing has not likely been researched due the difficulty of establishing experimental protocols in field studies. Finally, Table 5.4 summarizes the 7 factors that were included and assessed in this project for biochar application to soils, or excluded, with a brief reason why. Table 5.4. Summary of included or excluded factors used for calculating net carbon reductions seen from high temperature biochar when applied to soils. Biochar factor effecting soil GHGs Carbon depredation/ stability Non-CO2 emissions (N2O and CH4) Factor included or excluded due to lack of information or certainty Included Author’s reason for exclusion Included Soil texture effect Cation exchange capacity/fertilization retention and reuse efficiency Excluded Excluded Insufficient data Effect not validated from research Mean annual temperature Excluded Insufficient data 150 Priming effect (carbon flush effect) Moisture levels on degradation Excluded Effect not applicable Excluded Insufficient data 5.5.2.5 Business as usual scenarios Roadside slash and sawmill residue business as usual scenarios were shown to be, on average, unfavorable for carbon sequestration/offsets compared to all other scenarios, aside from the worst case full CH4 release scenario for wood wastes. However, these results still compare favorably to the emissions of fossil fuels (BCMOE 2016). Roadside slash that is left in the forest, either scattered or piled will very likely degrade before 100 years, however there is still a delay factor and this type of temporal degradation analysis will need further investigation. 5.5.3 Implications of results Implications of this research indicate that of the scenarios examined, landfilling biocoal indicates the most consistent option and possibly highest amount of carbon sequestration/offset, with burial of wood waste potential being similar if certain parameters, like water infiltration, can be controlled for. It is the author’s opinion that the collection and burial of carbon as solid products derived, or used directly, from wood wastes, could perform favourably in its overall ease of carbon management compared to gaseous carbon capture and storage techniques, such as those proposed and tested by Switzerland’s Climeworks, Canada’s Carbon Engineering, US’s Global Thermostat, and employed at the Boundary Dam Carbon Capture Project in Saskatchewan, Canada. If this does further demonstrate with further research, biocoal or wood 151 waste carbon storage could become a major strategy for carbon sequestration in the near future. Comparing these determined carbon sequestration/offset results for soil applied biochar are, in most cases and scenarios, below other literature findings shown in Table 5.3. This has implications in questioning or reassessing which factors are and are not, accounted for in current literature, and future work. One of the most evident differences were the use of pyrolysis oil in the assumption that they will also reduce GHG emissions; however, from the discussion, there may now be a precedent to acknowledge this limitation in other papers in order to better model carbon sequestration/offset emissions in soil biochar. This report may also act as a rubric for modelling or testing different types of biochar for soil application and their impact on carbon sequestration/offsets because of the vast differences in various environmental and physical characteristics that are possibly impactful. 5.5.4 Factors to consider and limitations of the project As presented above, different methods of biochar degradation modelling were used for landfill carbon sequestration and soil applied biochar. At this time, no research is known to examine the carbon degradation difference between aerobic versus anaerobic environments and thus as a limitation of this project. From degradation results modelled from Singh et al. (2012) there showed a 6.2% loss of carbon from the soil applied biochar applied over a 100year timeframe, whereas in the landfill carbon sequestration scenario there was assumed to be no net loss of carbon. This is a notable difference, but influenced by many other factors such as differences in non-GHG emissions or the end use of any co-products. The majority of wood sequestration scenarios are presented as ideal circumstances based on physical and chemical calculations and thus have limits when translating that information to biological systems. The landfill gas model, although based on in situ biological 152 research, is also ideal in that it doesn’t take into consideration the leakage of methane and its impact on GHGs. It is this uncertainty that would reduce the viability of wood-based carbon sequestration. If the burial of biocoal, biochar, or wood waste becomes a substantial industry for carbon sequestration/offsetting, landfill space will need to be appropriately managed. In the short term this would be less of a concern. In the long-term it is acknowledged that dedicated regional carbon sequestration landfills would need to be created, or the use of shuttered coal mines to deposit biocoal will need to be arranged. With these scenarios, appropriate GHG accounting would be needed in order to ensure accurate carbon sequestration/offsets, especially if products would need to be shipped much further distances for landfilling or from different feedstocks not examined here. Ultimately, the analysis performed in this project is established upon literature that is subject to refinement or correction in future years, or fundamental differences in accounting because of the biochar type or scenario described. Additionally, many reviews have nuanced details that were not initially apparent within their main findings; meaning that applicable research and values used were needing to be drawn from supplementary information or adapted from research, such as in the case of N2O emission reduction potential in Cayuela et al. (2015). 5.5.5 Conclusions This project presented a new method of carbon sequestration/offset through the landfilling of biocoal, biochar, and wood wastes and compared them to a detailed case study of soil applied biochar. Biocoal and wood waste landfilling scenarios produced the largest potential for carbon sequestration/offset, however biocoal showed the most consistency across scenarios. Biochar applied to soils were shown to have lower carbon sequestration/offset 153 potential than existing literature and this is at least partially explained by the assumed use, or not, of pyrolysis oils. Further research in the field of biochar degradation in soils will help to elucidate and or refine parameters that are not yet clear or fleshed out, such as moisture impacts on biochar degradation and environmental temperature differences. This project will add a new comparison of carbon sequestration/offsetting to existing soil biochar literature and initiate a discussion about the potential use of biomass as a carbon sequestration method when either pyrolyzed into biocoal or directly used and buried. These results can be compared to combustion options of biomass and biocoal options as well as technologically based air CO2 capture systems for climate change mitigation. 5.6 References Angst, T.E., Patterson, C.J., Reay, D.S., Anderson, P., Peshkur, T.A., and Sohi, S.P. (2013). Biochar Diminishes Nitrous Oxide and Nitrate Leaching from Diverse Nutrient Sources. Journal of Environmental Quality 42, 672–682. Athena. (2018). A Cradle-to-Gate Life Cycle Assessment of Canadian Surfaced Dry Softwood Lumber. Athena Sustainable Materials Institute. Last accessed Feb 05, 2019 at http://www.athenasmi.org/resources/publications/. Bamminger, C., Marschner, B., and Jüschke, E. (2014). An incubation study on the stability and biological effects of pyrogenic and hydrothermal biochar in two soils. Eur J Soil Sci 65, 72–82. Barlaz, M.A. (2006). Forest products decomposition in municipal solid waste landfills. Waste Management 26, 321–333. BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. BCMOE. (2011). Wood waste landfills guideline. British Columbia Ministry of Environment. Last accessed Feb 10, 2013 at 154 http://www2.gov.bc.ca/assets/gov/environment/waste-management/industrialwaste/industrial-waste/pulp-paper-wood/woodwastelandfillguideline.pdf. BCMOE. (2012). British Columbia Greenhouse Gas Inventory. British Columbia Ministry of Environment. Online resource, last accessed Dec 24, 2015 at http://www2.gov.bc.ca/gov/content/environment/climate-change/reportsdata/provincial-ghg-inventory-report-bc-s-pir. BCMOE. (2016). B.C. Best Practices Methodology for Quantifying Greenhouse Gas Emissions. British Columbia Ministry of Environment. Last accessed Nov 15, 2017 https://www2.gov.bc.ca/assets/gov/environment/climatechange/cng/methodology/2016-17-pso-methodology.pdf. BCMOE. (2017). Landfill gas generation assessment procedure guidelines and Landfill Gas Generation Estimation Tool. British Columbia Ministry of Environment. Last accessed Oct 15, 2017 at https://www2.gov.bc.ca/gov/content/environment/wastemanagement/garbage/landfills. BCMOA. (2017). British Columbia Soil Information Finder. British Columbia Ministry of Agriculture. Online resource, last accessed Oct 01,2017 at Toolhttp://bcgov03.maps.arcgis.com/apps/MapSeries/index.html?appid=4e627670073b 4b318be3f901365a2052 Biederman, L.A., and Harpole, W.S. (2013). Biochar and its effects on plant productivity and nutrient cycling: a meta-analysis. GCB Bioenergy 5, 202–214. Bruun, S., Clauson-Kaas, S., Bobuľská, L., and Thomsen, I.K. (2014). Carbon dioxide emissions from biochar in soil: role of clay, microorganisms and carbonates. European Journal of Soil Science 65, 52–59. Carpenter, D., L. Westover, T., Czernik, S., and Jablonski, W. (2014). Biomass feedstocks for renewable fuel production: a review of the impacts of feedstock and pretreatment on the yield and product distribution of fast pyrolysis bio-oils and vapors. Green Chemistry 16, 384–406. Cayuela, M.L., Jeffery, S., and van Zwieten, L. (2015). The molar H:Corg ratio of biochar is a key factor in mitigating N2O emissions from soil. Agriculture, Ecosystems & Environment 202, 135–138. CFI (2013). Carbon Farming Initiative, Department of Climate Change and Energy Efficiency, Australian Government. Last accessed Feb 10, 2013 at http://www.climatechange.gov.au/government/initiatives/carbon-farming- 155 initiative/activities-eligible-excluded/additional-activities-positive-list/application-ofbiochar.aspx. Cheng, C.-H., Lehmann, J., Thies, J.E., and Burton, S.D. (2008). Stability of black carbon in soils across a climatic gradient. J. Geophys. Res. 113, G02027. Clare, A., Shackley, S., Joseph, S., Hammond, J., Pan, G., and Bloom, A. (2014). Competing uses for China’s straw: the economic and carbon abatement potential of biochar. GCB Bioenergy n/a-n/a. Dufour, A. (2013). Geological Sequestration of Biomass Char to Mitigate Climate Change. Environmental Science and Technology Viewpoint. Ecoinvent. (2014). The ecoinvent database: Overview and methodology, Data quality guideline for the ecoinvent database version 3, developed by Weidema, B.P., Bauer, Ch., Hischier, R., Mutel, Ch., Nemecek, T., Reinhard, J., Vadenbo, C.O., Wernet, G. www.ecoinvent.org. Released July 08, 2014. Enders, A., Hanley, K., Whitman, T., Joseph, S., and Lehmann, J. (2012). Characterization of biochars to evaluate recalcitrance and agronomic performance. Bioresource Technology 114, 644–653. Fang, Y., Singh, B., Singh, B.P., and Krull, E. (2014a). Biochar carbon stability in four contrasting soils. Eur J Soil Sci 65, 60–71. Fang, Y., Singh, B.P., and Singh, B. (2014b). Temperature sensitivity of biochar and native carbon mineralisation in biochar-amended soils. Agriculture, Ecosystems & Environment 191, 158–167. Fang, Y., Singh, B., and Singh, B.P. (2015). Effect of temperature on biochar priming effects and its stability in soils. Soil Biology and Biochemistry 80, 136–145. Gao, S., Hoffman-Krull, K., Bidwell, A.L., and DeLuca, T.H. (2016). Locally produced wood biochar increases nutrient retention and availability in agricultural soils of the San Juan Islands, USA. Agriculture, Ecosystems & Environment 233, 43–54. Gaunt, J.L., and Lehmann, J. (2008). Energy Balance and Emissions Associated with Biochar Sequestration and Pyrolysis Bioenergy Production. Environmental Science & Technology, Vol. 42, pp. 4152–4158. Gronwald, M., Vos, C., Helfrich, M., and Don, A. (2016). Stability of pyrochar and hydrochar in agricultural soil - a new field incubation method. Geoderma 284, 85–92. 156 Government of Canada. (2017). Canadian Climate Normals 1981-2010 Station Data, Normals Data. Last accessed Dec 10, 2017 at http://climate.weather.gc.ca/climate_normals/results_1981_2010_e.html?stnID=1275&l ang=e&dCode=1&dispBack=1. Güereña, D., Lehmann, J., Hanley, K., Enders, A., Hyland, C., and Riha, S. (2013). Nitrogen dynamics following field application of biochar in a temperate North American maizebased production system. Plant Soil 365, 239–254. Gurwick, N.P., Moore, L.A., Kelly, C., and Elias, P. (2013). A Systematic Review of Biochar Research, with a Focus on Its Stability in situ and Its Promise as a Climate Mitigation Strategy. PLOS ONE 8, e75932. Hagemann N., Harter J., Kaldamukova R., Guzman-Bustamante I., Ruser R., Graeff S., Kappler A., and Behrens S. (2017). Does soil aging affect the N2O mitigation potential of biochar? A combined microcosm and field study. GCB Bioenergy 9, 953–964. Hammond, J., Shackley, S., Sohi, S., and Brownsort, P. (2011). Prospective lifecycle carbon abatement for pyrolysis biochar systems in the UK. Energy Policy, Vol. 39, pp. 2646– 2655. Hardie, M.A., Oliver, G., Clothier, B.E., Bound, S.A., Green, S.A., and Close, D.C. (2015). Effect of Biochar on Nutrient Leaching in a Young Apple Orchard. J. Environ. Qual. 44, 1273–1282. Harvey, O.R., Kuo, L.-J., Zimmerman, A.R., Louchouarn, P., Amonette, J.E., and Herbert, B.E. (2012). An Index-Based Approach to Assessing Recalcitrance and Soil Carbon Sequestration Potential of Engineered Black Carbons (Biochars). Environ. Sci. Technol. 46, 1415–1421. Harsono, S.S., Grundman, P., Lau, L.H., Hansen, A., Salleh, M.A.M., Meyer-Aurich, A., Idris, A., and Ghazi, T.I.M. (2013). Energy balances, greenhouse gas emissions and economics of biochar production from palm oil empty fruit bunches. Resources, Conservation and Recycling 77, 108–115. He, Y., Zhou, X., Jiang, L., Li, M., Du, Z., Zhou, G., Shao, J., Wang, X., Xu, Z., Hosseini Bai, S., et al. (2017). Effects of biochar application on soil greenhouse gas fluxes: a meta-analysis. GCB Bioenergy 9, 743–755. 157 Hilscher, A., Heister, K., Siewert, C., and Knicker, H. (2009). Mineralisation and structural changes during the initial phase of microbial degradation of pyrogenic plant residues in soil. Organic Geochemistry 40, 332–342. Ibarrola, R., Shackley, S., and Hammond, J. (2012). Pyrolysis biochar systems for recovering biodegradable materials: A lifecycle carbon assessment. Waste Management, Vol. 32, pp. 859–868. ISOa. (2006) ISO 14040:2006 Environmental management - Lifecycle assessment - Principles and framework. International organization for standardization, Geneva, Switzerland. IPCC. (2013). Climate Change 2007: Working Group I: The Physical Science Basis. 2.10.2 Direct Global Warming Potentials. Intergovernmental Panel on Climate Change. Online resource, last accessed Sept 19, 2017 at https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-10-2.html Jeffery, S., Verheijen, F.G.A., Bastos, A.C., and Van Der Velde, M. (2014). A comment on ‘Biochar and its effects on plant productivity and nutrient cycling: a meta-analysis’’: on the importance of accurate reporting in supporting a fast-moving research field with policy implications.’ GCB Bioenergy 6, 176–179. Jeffery, S., Verheijen, F.G.A., van der Velde, M., and Bastos, A.C. (2011). A quantitative review of the effects of biochar application to soils on crop productivity using metaanalysis. Agriculture, Ecosystems & Environment Vol. 144, pp. 175–187. Keith, A., Singh, B., Dijkstra, F.A., and van Ogtrop, F. (2016). Biochar Field Study: Greenhouse Gas Emissions, Productivity, and Nutrients in Two Soils. Agronomy Journal 108, 1805–1815. Köhl, M., and Frühwald, A. (2009). Permanent Wood Sequestration: No Solution to the Global Carbon Dioxide Problem. ChemSusChem 2, 609–613. Kreysa, G. (2009). Sustainable Management of the Global Carbon Cycle Through Geostorage of Wood. ChemSusChem 2, 633–644. Kung, C.-C., Kong, F., and Choi, Y. (2015). Pyrolysis and biochar potential using crop residues and agricultural wastes in China. Ecological Indicators 51, 139–145. Kuzyakov, Y., Bogomolova, I., and Glaser, B. (2014). Biochar stability in soil: Decomposition during eight years and transformation as assessed by compound-specific 14C analysis. Soil Biology and Biochemistry 70, 229–236. 158 Lee, C., Erickson, P., Lazarus, M., and Smith, G. (2010). Greenhouse gas and air pollutant emissions of alternatives for woody biomass residues-FINAL DRAFT Version 2.0 (Stockholm Environment Institute). Lee, U., Han, J., and Wang, M. (2017). Evaluation of landfill gas emissions from municipal solid waste landfills for the life-cycle analysis of waste-to-energy pathways. Journal of Cleaner Production 166, 335–342. Lee, Y., Park, J., Ryu, C., Gang, K.S., Yang, W., Park, Y.-K., Jung, J., and Hyun, S. (2013). Comparison of biochar properties from biomass residues produced by slow pyrolysis at 500°C. Bioresource Technology 148, 196–201. Lehmann, L. and S. Joseph (Eds.) (2009). Biochar for Environmental Management: Science and Technology, Earthscan Ltd, London, UK. Lehmann, L. and S. Joseph (Eds.) (2015). Biochar for Environmental Management: science, technology and implementation, Routledge, New York, NY. Leng, L., Huang, H., Li, H., Li, J., and Zhou, W. (2019). Biochar stability assessment methods: A review. Science of The Total Environment 647, 210–222. Leung, D.Y.C., Caramanna, G., and Maroto-Valer, M.M. (2014). An overview of current status of carbon dioxide capture and storage technologies. Renewable and Sustainable Energy Reviews 39, 426–443. Lindroos, O., Nilsson, B., and Sowlati, T. (2011). Costs, CO2 emissions, and energy balances of applying Nordic slash recovery methods in British Columbia. Western Journal of Applied Forestry 26, 30–36. Lu, Q., Li, W.-Z., and Zhu, X.-F. (2009). Overview of fuel properties of biomass fast pyrolysis oils. Energy Conversion and Management 50, 1376–1383. Lorenz, K., and Lal, R. (2014). Biochar application to soil for climate change mitigation by soil organic carbon sequestration. J. Plant Nutr. Soil Sci. 177, 651–670. McBeath, A.V., Wurster, C.M., and Bird, M.I. (2015). Influence of feedstock properties and pyrolysis conditions on biochar carbon stability as determined by hydrogen pyrolysis. Biomass and Bioenergy 73, 155–173. Malghani, S., Gleixner, G., and Trumbore, S.E. (2013). Chars produced by slow pyrolysis and hydrothermal carbonization vary in carbon sequestration potential and greenhouse gases emissions. Soil Biology and Biochemistry 62, 137–146. 159 Malghani, S., Jüschke, E., Baumert, J., Thuille, A., Antonietti, M., Trumbore, S., and Gleixner, G. (2015). Carbon sequestration potential of hydrothermal carbonization char (hydrochar) in two contrasting soils; results of a 1-year field study. Biology and Fertility of Soils 51, 123–134. Micales, J.A., and Skog, K.E. (1997). The decomposition of forest products in landfills. International Biodeterioration & Biodegradation 39, 145–158. Miller-Robbie, L., Ulrich, B.A., Ramey, D.F., Spencer, K.S., Herzog, S.P., Cath, T.Y., Stokes, J.R., and Higgins, C.P. (2015). Life cycle energy and greenhouse gas assessment of the co-production of biosolids and biochar for land application. Journal of Cleaner Production 91, 118–127. Mohanty, P., Nanda, S., Pant, K.K., Naik, S., Kozinski, J.A., and Dalai, A.K. (2013). Evaluation of the physiochemical development of biochars obtained from pyrolysis of wheat straw, timothy grass and pinewood: Effects of heating rate. Journal of Analytical and Applied Pyrolysis 104, 485–493. Mukherjee, A., Zimmerman, A.R., and Harris, W. (2011). Surface chemistry variations among a series of laboratory-produced biochars. Geoderma 163, 247–255. Nanda, S., Dalai, A.K., Berruti, F., and Kozinski, J.A. (2016). Biochar as an Exceptional Bioresource for Energy, Agronomy, Carbon Sequestration, Activated Carbon and Specialty Materials. Waste Biomass Valor 7, 201–235. Nguyen, B.T., and Lehmann, J. (2009). Black carbon decomposition under varying water regimes. Organic Geochemistry 40, 846–853. Nguyen, B.T., Lehmann, J., Hockaday, W.C., Joseph, S., and Masiello, C.A. (2010). Temperature Sensitivity of Black Carbon Decomposition and Oxidation. Environ. Sci. Technol. 44, 3324–3331. Nyboer, J. (2008). A review of energy consumption and related data in the Canadian Wood Products Industry: 1990, 1995 to 2006. Online resource, last accessed Dec 30, 2015 at Oasmaa, A., and Czernik, S. (1999). Fuel Oil Quality of Biomass Pyrolysis OilsState of the Art for the End Users. Energy Fuels 13, 914–921. OpenLCA. (2014) GreenDelta GmbH. Last accessed March 18, 2014 at http://www.openlca.org/. 160 PCT. (2012). Bio-coal’s Potential for BC’s Economy and Environment, Pacific Carbon Trust. Last accessed Dec 18, 2012 at http://www.pacificcarbontrust.com/newsroom/newsreleases/bio-coal-s-potential-for-bc-s-economy-and-environment/. Peters, J.F., Iribarren, D., and Dufour, J. (2015). Biomass Pyrolysis for Biochar or Energy Applications? A Life Cycle Assessment. Environ. Sci. Technol. 49, 5195–5202. Perkins, G., Bhaskar, T., and Konarova, M. (2018). Process development status of fast pyrolysis technologies for the manufacture of renewable transport fuels from biomass. Renewable and Sustainable Energy Reviews 90, 292–315. Pourhashem, G., Spatari, S., Boateng, A.A., McAloon, A.J., and Mullen, C.A. (2013). Lifecycle Environmental and Economic Tradeoffs of Using Fast Pyrolysis Products for Power Generation. Energy & Fuels, Vol. 27, pp. 2578–2587. Qayyum, M.F., Steffens, D., Reisenauer, H.P., and Schubert, S. (2012). Kinetics of Carbon Mineralization of Biochars Compared with Wheat Straw in Three Soils. Journal of Environmental Quality 41, 1210–1220. Reitsma, L. (2015) Personal phone communication. President & Chief Operating Officer, Pinnacle Renewable Energy Inc. 14 October 2015. Roberts, K.G., Gloy, B.A., Joseph, S., Scott, N.R., and Lehmann, J. (2010). Life Cycle Assessment of Biochar Systems: Estimating the Energetic, Economic, and Climate Change Potential. Environ. Sci. Technol. 44, 827–833. Sambo, S.M. (2002). Fuel consumption for ground-based harvesting systems in western Canada. Forest Engineering Research Institute of Canada, Vancouver, BC. Forest Engineering Research Institute of Canada Advantage Report 3(29), 1–12. Santín, C., Doerr, S.H., Merino, A., Bucheli, T.D., Bryant, R., Ascough, P., Gao, X., and Masiello, C.A. (2017). Carbon sequestration potential and physicochemical properties differ between wildfire charcoals and slow-pyrolysis biochars. Scientific Reports 7, 11233. Shackley, S., Sohi, S., Brownsort, P., Carter, S., Cook, J., Cunningham, C., Gaunt, J., Hammond, J., Ibarrola, R., and Mašek, O. (2010). An assessment of the benefits and issues associated with the application of biochar to soil. Department for Environment, Food and Rural Affairs, UK Government, London. Last accessed May 16, 2014 at http://www.geos.ed.ac.uk/homes/sshackle/SP0576_final_report.pdf. 161 Singh, B.P., Cowie, A.L., and Smernik, R.J. (2012). Biochar Carbon Stability in a Clayey Soil as a Function of Feedstock and Pyrolysis Temperature. Environ. Sci. Technol. 46, 11770–11778. Singh, B.P., Fang, Y., Boersma, M., Collins, D., Zwieten, L.V., and Macdonald, L.M. (2015). In Situ Persistence and Migration of Biochar Carbon and Its Impact on Native Carbon Emission in Contrasting Soils under Managed Temperate Pastures. PLOS ONE 10, e0141560. Sohi, S.P., Krull, E., Lopez-Capel, E., and Bol, R. (2010). Chapter 2 - A Review of Biochar and Its Use and Function in Soil. In Advances in Agronomy, (Academic Press), pp. 47– 82. Sparrevik, M., Field, J.L., Martinsen, V., Breedveld, G.D., and Cornelissen, G. (2013). Lifecycle Assessment to Evaluate the Environmental Impact of Biochar Implementation in Conservation Agriculture in Zambia. Environmental Science & Technology, Vol. 47(3), pp. 1206–1215. Spokas, K.A. (2010). Review of the stability of biochar in soils: predictability of O:C molar ratios. Carbon Management 1, 289–303. Spokas, K.A. (2012). Impact of biochar field aging on laboratory greenhouse gas production potentials. GCB Bioenergy 5, 165–176. Spokas, K.A., Bogner, J., Chanton, J.P., Morcet, M., Aran, C., Graff, C., Golvan, Y.M.-L., and Hebe, I. (2006). Methane mass balance at three landfill sites: What is the efficiency of capture by gas collection systems? Waste Management 26, 516–525. Spokas, K.A., Cantrell, K.B., Novak, J.M., Archer, D.W., Ippolito, J.A., Collins, H.P., Boateng, A.A., Lima, I.M., Lamb, M.C., McAloon, A.J., et al. (2012). Biochar: A Synthesis of Its Agronomic Impact beyond Carbon Sequestration. Journal of Environment Quality 41, 973. Santín, C., Doerr, S.H., Merino, A., Bucheli, T.D., Bryant, R., Ascough, P., Gao, X., and Masiello, C.A. (2017). Carbon sequestration potential and physicochemical properties differ between wildfire charcoals and slow-pyrolysis biochars. Scientific Reports 7, 11233. Thompson, S., Sawyer, J., Bonam, R., and Valdivia, J.E. (2009). Building a better methane generation model: Validating models with methane recovery rates from 35 Canadian landfills. Waste Management 29, 2085–2091. 162 Ventura, M., Sorrenti, G., Panzacchi, P., George, E., and Tonon, G. (2013). Biochar Reduces Short-Term Nitrate Leaching from A Horizon in an Apple Orchard. Journal of Environmental Quality 42, 76–82. Wang, X., Padgett, J.M., De la Cruz, F.B., and Barlaz, M.A. (2011). Wood Biodegradation in Laboratory-Scale Landfills. Environ. Sci. Technol. 45, 6864–6871. Wang, J., Xiong, Z., and Kuzyakov, Y. (2016). Biochar stability in soil: meta-analysis of decomposition and priming effects. GCB Bioenergy 8, 512–523. Wang, Z., Dunn, J.B., Han, J., and Wang, M.Q. (2013). Effects of co-produced biochar on life cycle greenhouse gas emissions of pyrolysis-derived renewable fuels. Biofuels, Bioprod. Bioref. 8, 189–204. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications Vol. 1, pp. 1–9. Zeng, N., King, A.W., Zaitchik, B., Wullschleger, S.D., Gregg, J., Wang, S., and KirkDavidoff, D. (2013). Carbon sequestration via wood harvest and storage: An assessment of its harvest potential. Climatic Change 118, 245–257. Zimmerman, A.R. (2010). Abiotic and Microbial Oxidation of Laboratory-Produced Black Carbon (Biochar). Environmental Science & Technology 44, 1295–1301. 163 6 CHAPTER 6 – Project 4: BC-wide assessment of biocoal industrial emission reduction potentials from wood-based sawmill and roadside slash residues. 6.1 Abstract The province of British Columbia has the potential to optimize the reduction of GHG emissions through the use of existing sawmill and roadside slash residues. Existing bioenergy applications such as bio-electricity have very low emission offset potential due to the province’s abundant hydroelectricity, while petroleum coke displacement has a very large emission reduction potential (Project 2), and either can be substituted from the same wood residues. With the Biocoal examined in the previous project, including as a carbon sequestration method if buried, there is a need to investigate the total available opportunity for BC to reduce greenhouse gas emissions through the use of biocoal in industrial applications. Findings from Projects 1, 2 and 3 of this dissertation were taken, and applied to the estimated total sawmill and roadside slash residues in BC. Residues were derived from the BC forest harvest Annual Allowable Cut and from Timber Supply Area ‘Residual Fibre Recovery - Estimates of Residual Fibre’ reports released through FPInnovations’ forest supply chain simulator called FPInterface. Results for potential GHG emission reduction or carbon sequestration potential was assessed for both current availability, and in 10 years’ time. With an estimated GHG emission reduction or carbon sequestration of 28,000,000 Mg CO2e/year from current available residues, and 20,006,000 Mg CO2e/year in 10 years’ time, BC has the potential to reduce its current emissions of 61,600,000 Mg CO2e/year by around 46%, and 33% in 10 years. Government and industry would benefit from these findings as to how best approach the province’s bioenergy industry direction, and path towards mitigating our contribution to anthropogenic climate change. 164 6.2 Introduction The province of British Columbia (BC) is pursuing carbon reductions across many industries and sectors in order to mitigate climate change. The reported provincial greenhouse gases (GHGs) are 61.6 million Mg CO2e/year and are primarily from industry, such as fossil fuel production and mining, and transportation (BCMOE 2017). The main initiative to reduce emissions has been to institute a province wide carbon tax to price the climate change impact of fossil fuels. Coal and petroleum coke are the two most carbon intensive fuel sources used in the province and offer the largest potential for reducing emissions per mass of fuel. Alternatively, offsetting GHGs released to the atmosphere through carbon sequestration mechanisms offer another potential opportunity to reduce greenhouse gas emissions. Previous chapters of this project were dedicated to the greenhouse gas quantification of biocoal production (Project 1), biocoal combustion carbon displacement factors (Project 2), and biocoal and biochar non-combustion carbon sequestration factors (Project 3). For the purpose of this investigation, biocoal is defined as a solid, high-carbon content, black briquette made from various biomass sources, but mainly assumed to be derived from woodbased residues. Biocoal characteristics were previously described in Project 1. There is a need to investigate the available opportunity for BC to reduce greenhouse gas emissions through the use of biocoal in industrial applications, however optimal use of feedstocks, locational availability feedstocks across the province, and availability into the future will determine the best opportunity. The goal of this project was to assess the potential for greenhouse gas reduction and carbon sequestration across BC using available sawmill and roadside slash residues through the use of biocoal. 165 6.3 Methods 6.3.1 Goal and scope Similar to prior chapters, this investigation adapts ISO 14040 and ISO 14044 protocols in this GHG assessment (ISOa 2006; and ISOb 2006). The major scope for this project encompasses the project scopes in Figures 2.1, 3.1, and 4.1, however regional application of results found in Projects 2 and 3 are applied across BC. This research reflects common methods from existing and related bioenergy GHG assessments (Wang et al. 2013; Pourhashem et al. 2013; Huang et al. 2013; Ibarrola et al. 2012; Hammond et al. 2011; Woolf et al. 2010; and Gaunt and Lehmann 2008) and includes stages from feedstock production end use in combustion and non-combustion applications. From this, the project aims to research and quantify the GHG emission reduction or sequestration potential of biocoal and biochar across BC. 6.3.2 Inventory data collection (Databases, sources, and analysis tools) All factors that affect the assessed production GHGs for biochar and biocoal were performed in the inventory analyses of Projects 1, 2, and 3. Relevant fossil fuel GHGs applicable to this project including biocoal and biochar use values were integrated in this project’s inventory analysis and used for comparison over a 100-year time frame (further discussed in the Application scenarios- Biocoal and biochar applications and Lifecycle impact and GHG assessment section). 6.3.3 BC Biocarbon pyrolysis system and products Project 1 describes BC Biocarbon’s pyrolysis system design and emissions, and is originally sourced from engineering design and operation specifications for their pyrolysis kiln (BC Biocarbon 2015). BC Biocarbon’s system was assumed to perform as outlined in 166 Project 1 for the assessment of the biocoal and biochar GHGs. Physical characteristics of the biocoal and biochar produced by BC Biocarbon are presented in Table 4.1 of Project 3. Mass allocation of emissions in this project is consistent with the three previous chapters and supported by Jungmrirt et al. (2002) for bioenergy products. Biocoal emissions from Project 1 were used as the GHG production emissions basis; however, as similar to Project 2 and 3 only sawmill residue feedstocks and roadside slash feedstocks were used in this analysis. This is due to sawmill and roadside slash residues representing the most likely feedstock. Biocoal production emissions were sourced from the averaged value of sawmill residue scenarios, and roadside slash feedstock ‘at gate’ emissions. For roadside slash the 200 km recovery scenario was used. As calculated in Project 1, scenarios included all upstream emissions for forestry operations to sawmill, and/or recovery operations of roadside slash emissions. 6.3.4 Wood residue supply availability BC wood residue availability for sawmill and roadside slash was derived from the BC Ministry of Forests, Lands, Natural Resource Operations and Rural Development ‘2018/2019 Annual Allowable Cut’ (AAC) for each timber supply region (TSA) (BCMOFLNRORDa 2018). Sawmill residues were calculated by applying a 53% residue factor to the AAC cubic volume of timber (BC Hydro 2015), and then converting to dry mass residues by applying an average BC specific wood density of 0.415 Mg/m3 used in project 3. For example, the 100 Mile House TSA AAC is set at 1,948,002 m3 and at 53% residues and 0.415 Mg/m3 equals 428,463 Mg dry mass from sawmill residues. Roadside slash residues were calculated using ‘Residual Fibre Recovery - Estimates of Residual Fibre’ reports released from FPInnovations for the BC Ministry of Forests, Lands, 167 Natural Resource Operations and Rural Development (BCMOFLNRORDb 2018) using an FPInnovations forest supply chain simulator called FPInterface (FPInnovations 2018). Ten TSA reports have been released and outlined roadside slash residues for 100 Mile House, Arrowsmith, Bulkley, Fraser, Kamloops, Lake, McKenzie, Prince George, Quesnel, Strathcona, and Williams Lake. These reports provide the estimated oven dried Mg (ODMg) of residues per merchantable m3, which was then used to derived roadside residues from the AAC. Missing/not yet published reports include the TSAs of Arrow, Boundary, Cascadia, Cranbrook, Golden, Invermere, Kootenay Lake, Revelstoke, Dawson Creek, Fort Nelson, Fort St. John, MacKenzie, Robson Valley, Bulkley, Cassiar, Kalum, Kispiox, Lakes, Morice, Nass, Fraser, Soo, Sunshine Coast, Kamloops, Lillooet, Merritt, Okanagan, Great Bear Rainforest (GBR) North, GBR South, Haida Gwaii, North Island (formerly Strathcona), Arrowsmith, and Pacific. To estimate the roadside slash residues for missing TSAs, the published regional reports from FPInnovations were used to provide the ODMg of residues per merchantable m3. For TSAs that existed within the same Natural Resource Regions (NRRs) the ODMg of residues per merchantable m3 was applied as the reported ‘Rationale for AAC Determination’ for each TSA (BCMOFLNRORDa 2018). For example, the Fraser TSA ODMg of residues per merchantable m3 was applied to the TSAs of Soo and Sunshine Coast as they all existed within the same South Coast NRR. When a reported ODMg of residues per merchantable m3 was not shared in an NRR, the AAC to Total Harvestable Land Base ratio (AAC/THLB in m3/10,000 m2) was used to equate to the most similar regions and again was obtained from the ‘Rationale for AAC Determination’ for each TSA (BCMOFLNRORDa 2018). The AAC/THLB ratio was assumed to represent the land use similarities for harvest intensities and thus recoverable residues. If two or more TSA FPInnovation reports existed within an NRR, 168 any missing TSA were again allocated to the closest AAC/THLB ratio from within the FPInnovation reports. Due to recent changes in boundaries and TSA titles, THLB data was not available for GBR North, GBR South, and North Island and were allocated based on the North Island TSA which was the closest physical TSA with data. A full breakdown of applied ODMg of residues per merchantable m3 is available in Appendix 4 Supplementary Information. Future sawmill and roadside slash residues were estimated through an applied 10-year residue availability ratio developed from the FPInnovations’ ‘Residual Fibre Recovery Estimates of Residual Fibre’ reports. The 10-year residue ratio availability was determined through two ways: using the reported current and future residues in 10 years (Arrowsmith TSA, Bulkley TSA, Fraser TSA, Prince George TSA, Quesnel TSA, Strathcona TSA, and Williams Lake TSA), and the ODMg/10,000 m2/year (100 Mile House TSA, Lakes TSA, and Mackenzie TSA). These two ways were necessary due to different reporting of similar data between the reports. The 10-year residue availability ratio was then applied to the sawmill and roadside slash residues derived above. The ratio was deemed appropriate to apply to both sawmill and roadside slash residues due to the fact they are both linked to the same level of merchantable timber harvest. As above, the 10 reports already released by FPInnovations were used to provide a proxy calculation for the missing regions through the similar association of AAC/THLB ratios used for the Mg of residues per merchantable m3. A sample calculation of results including values of the AAC, Mg of residues per merchantable m3, and AAC/THLB ratio is presented in Appendix 4 Supplementary Information. Standing timber, pulp logs, and dead timber from the mountain pine beetle were not considered available residues because the GHG accounting for whole log use in bioenergy is 169 generally not considered to be carbon neutral, whereas waste residue combustion emissions are considered carbon neutral and have been modelled through the previous projects as such (IPCC 2006). 6.3.5 Application scenarios 6.3.5.1 BC application regions Timber supply areas were organized into associated BC NRRs for current residue levels and projected availability in 10-years’ time. BC NRRs included: Cariboo, KootenayBoundary, Northeast, Omineca, Skeena, South Coast, Thompson-Okanagan, West Coast (North), and West Coast (South). The West Coast NRR was split in to two regions for this project into South and North because of the large distance separating the regions such as Haida Gwaii and Vancouver Island (BCGa 2018) and shown in Figure 6.1, and were used for modelling the regional GHG offset/carbon sequestration amounts. 170 North West Coast South West Coast Figure 6.1 Natural resource regions used for quantifying wood residues and associated GHG reductions through the use of biocoal across BC. Of note is this project split the West Coast regions into North and South West Coast. Image from BCGa (2018). 6.3.5.2 Biocoal applications From Projects 2 and 3 biocoal applications were imported and applied sequentially based on their highest GHG emission reductions and carbon sequestration factors available to each BC region if applicable (Table 6.1). Wood residues were allocated based on the greatest offset or carbon sequestration potential and applied. If there were insufficient residues in a region only one application was considered to its maximum residue amount. For reference, Table 6.2 shows the total residue requirements at Lehigh Cement, Lafarge Canada Inc. and Teck Resources based on their energy requirements and fuel type. If more residues were 171 available, then the second highest potential GHG emission reduction or carbon sequestration opportunity was applied until regional residues were fully allocated. Table 6.1 Base case GHG reductions and sequestration factors were imported from Research Project 2 and 3 and converted to a wood residue basis (Mg CO2e/Mg wood residue). Biocoal and biochar applications were applied sequentially based on their highest GHG emission reduction. Method of Application Cement Production Offset factor in Mg CO2e/Mg sawmill residue feedstock [kg CO2e/GJ biocoal or biochar*] 1.52 [109.0] Offset factor in Mg CO2e/Mg roadside slash feedstock [kg CO2e/GJ biocoal or biochar*] 1.65 [118.5] Non-combustion Carbon Sequestration 1.29 [92.5] 1.42 [102.1] 3) Coal substitution Combustion Cement Production 1.26 [90.2] 1.39 [100.0] 4) High scenario biochar sequestration and GHG offset. Non-combustion Agricultural soil integration 1.24 [185.9*] 1.30 [194.8*] 1) Petroleum coke substitution 2) Biocoal sequestration Combustion or Non-Combustion Application Process Combustion 5) Coal substitution Combustion Lead Smelting 1.12 [80.3] 1.25 [89.9] 6) Low scenario Non-combustion Agricultural soil 0.70 [104.7*] 0.79 [119.0*] biochar sequestration integration and GHG offset. Offset factors in kg CO2e/GJ Biocoal are provided in parentheses for comparison to previous projects and are calculated through the output of biocoal to input of feedstock ratio of 0.47 and biocoal energy density of 29.6 GJ/Mg, originally presented in CHAPTER 3 – Project 1(biochar to input of feedstock ratio of 0.24 and biochar energy density of 27.8 GJ/Mg). For example: 1.52/0.47/29.6*1000 = 109.0 kg CO2e/GJ biocoal shown in CHAPTER 4 – Project 2 Figure 4.2. Results from roadside slash derived biocoal were not presented in CHAPTER 4 – Project 2 but are used here. Table 6.2 Total residue requirements at Lehigh Cement, Lafarge Canada Inc. and Teck Resources based on their energy requirements and fuel type. Emissions intensity shown 172 include fossil fuel production and combustion emissions, while transportation scenarios are included in the full assessment. Sample calculation for Wood-residue requirements are found in Appendix 4 Supplementary Information. TSA Location Coal/ Petroleum coke user Fuel type Emission intensity of fossil fuel (kg CO2e/Mg) Product produced annually (Mg) Wood-residue requirements (ODMg) South Coast South Coast South Coast Kootenay/Boundary Lafarge Canada Inc. Lafarge Canada Inc. Lehigh Cement Teck Resources Petroleum coke Coal Coal Coal 3,2551,3 2,7142,3 2,7142,3 2,7142,3 1,300,0004 1,300,0004 1,100,0005 109,5006 423,000 360,000 335,000 223,800 1CRS (2013) 2EPA (2014) 3Ecoinvent (2014) ‘Petroleum coke to generic market for coke, alloc, U - GLO’, ‘Hard coal mine operation, alloc. default, U’ per Mg coal. 4Industryabouta (2018) 5Industryaboutb (2018) 6 Teck (2016) An audit of biocoal applications in all regions was performed and built upon the application scenarios presented in Projects 2 and 3 and included a review of the 2015 BC GHG emission report (BCGb 2018) in order to identify large emitters or users of petroleum coke and coal. Some heavy emitters assessed for GHG offset included Lafarge Canada Inc, Richmond BC, Lehigh Cement, Delta BC, and Teck Resources, Trail BC. Coal substitution for cement production was added to the model beyond petroleum coke in Project 2 to better represent the fuel usage at the Lehigh Cement and Lafarge Canada Inc. Emissions for biocoal in each region were fixed for transportation emissions for the region’s combustion or sequestration applications. This assumption was to simplify the assessment and is similar to Research Project 3’s regional application transportation emissions and was set at 100 km round trip. Biocoal was assessed to be transported to various end use locations by freight lorry. Emissions for freight lorry transportation were sourced from the Ecoinvent database and similar to the previous 3 projects. In order to test biocoal transportation to differing regions for greater GHG reductions, the difference in net GHG offset or sequestration was compared between each other and related to the equivalent, or maximum, transportation that could be performed. This was 173 called the ‘Transportation Distance Emission Allowance’. For example, the difference of emissions between cement production from petroleum coke and biocoal sequestration was equal to 394 kg CO2e/Mg biocoal. That difference was translated into transportation distances through shipping by rail, truck, and tanker barge. A sample equation for the rail transportation distance emission allowance of biocoal cement use versus biocoal sequestration is shown in Equation 6.1. 𝑅𝑎𝑖𝑙 𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝐴𝑙𝑙𝑜𝑤𝑎𝑛𝑐𝑒 𝑓𝑜𝑟 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝐶𝑒𝑚𝑒𝑛𝑡 𝑣𝑠 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑆𝑒𝑞𝑢𝑒𝑠𝑡𝑟𝑎𝑡𝑖𝑜𝑛 (𝑘𝑚) = 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑓𝑜𝑟 𝑐𝑒𝑚𝑒𝑛𝑡 𝐶𝐷𝐹 (𝑘𝑔 𝐶𝑂2𝑒) 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑓𝑜𝑟 𝐶𝑆𝐹 (𝑘𝑔 𝐶𝑂2𝑒) ( − ) 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑅𝑎𝑖𝑙 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 (𝑘𝑔 𝐶𝑂2𝑒) 1 𝑀𝑔 ∗ 𝑀𝑔 ∗ 𝑘𝑚 Equation 6.1 Sample equation for rail transportation distance emission allowance of biocoal cement use versus biocoal sequestration use. Biocoal for cement carbon displacement factor (CDF) was obtained from Project 2 (3,189 kg CO2e / Mg biocoal) and biocoal for carbon sequestration factor (CSF) was obtained from Project 3 (2,794 kg CO2e). All transportation emissions were obtained from Ecoinvent (2014) and rail and truck transportation were similar to as initially described in Research Projects 1 and 2, however tanker barge shipping was tested for costal transportation of biocoal. The only modification to the tanker barge (transport, freight, inland waterways, barge tanker, alloc. default (Ecoinvent 2014) was the removal of the listed canal infrastructure. This was done to better represent the island sheltered waterways of the BC coast as opposed to constructed canal waterways. Emission factors for various methods of biocoal transportation are shown in Table 6.3. For simplicity of demonstration, only Cement production from petroleum coke was compared to biochar sequestration across the 3 transportation methods. Table 6.3 Emission factors for various methods of biocoal transportation. Rail transportation emission factor Freight lorry transportation emission factor Tanker barge transportation emission factor 174 6.3.6 (Ecoinvent 2014) kg CO2e/Mg*km (Ecoinvent 2014) kg CO2e/Mg*km (Ecoinvent 2014) kg CO2e/Mg*km 0.0492 0.0759 0.0312 Lifecycle impact and GHG assessment Information collected and assumptions made in the inventory analyses were based on the lifecycle GHG assessments of Projects 1, 2 and 3. This includes using the tools of OpenLCA and the Ecoinvent database (OpenLCA 2015; and Ecoinvent 2014). Results and applicable values were exported to Microsoft Excel for further GHG assessment scenarios along with the additional regional scope data. Non-CO2 GHGs were reported for 100-year global warming potentials (IPCC 2013). Net GHG emissions describe the sum CO2 equivalent (CO2e) emissions for each application in each region, and are referred to as either the Net Carbon Displacement Factor shown in Equation 4.1 in Project 2 or Net Carbon Sequestration/Offset Factor in Equation 5.2 in Project 3. The CO2 released from any oxidative degradation or combustion of biomass including biocoal and biochar were considered carbon neutral, as referenced from the British Columbia Greenhouse Gas Inventory (BCMOE 2017). Results are reported in Mg CO2e/Mg original residue feedstock, and sample calculations and key data are presented in Appendix 4 Supplementary Information. 6.4 Results Total calculated residues in each NRR calculated for current and in 10 year’s-time are shown in Table 6.4 below. Based on the data assessed sawmill residues will provide the majority of residues currently and in 10 years’ time for any biocoal applications. 175 Table 6.4 Total calculated residues in each Natural Resource Region calculated for current and in 10 year’s-time. Natural Resource Region Biocoal Application Cariboo Kootenay-Boundary Northeast Omineca Skeena South Coast Thompson-Okanagan West Coast (North) West Coast (South) Carbon Sequestration Carbon Sequestration Carbon Sequestration Carbon Sequestration Carbon Sequestration Carbon Sequestration Carbon Sequestration Carbon Sequestration Cement Production Lafarge (Petcoke) Total residues by type Current Sawmill Residues from AAC (ODMg/year) 1,970,000 1,100,000 1,460,000 3,450,000 1,820,000 760,000 1,940,000 890,000 320,000 In 10 years Sawmill Residues from AAC (ODMg/year) 1,580,000 450,000 980,000 3,080,000 1,100,000 850,000 320,000 920,000 320,000 Current Roadside slash residues In 10 years Roadside slash residues (ODMg/year) 1,510,000 490,000 1,320,000 1,950,000 740,000 190,000 700,000 210,000 80,000 (ODMg/year) 1,280,000 200,000 1,080,000 1,740,000 380,000 210,000 120,000 220,000 80,000 13,720,000 9,600,000 7,190,000 5,300,000 BC wide GHG reduction results are presented in Figure 6.2. The highest absolute potential for GHG emission reductions is seen in the Omineca NRR, with a total provincial wide reduction of 28,000,000 Mg CO2e/year from current total available residues, and 20,006,000 Mg CO2e/year GHG in 10 years’ time. Potential GHG emission reductions from only roadside slash residues were found to be 10,300,000 Mg CO2e/year and 7,600,000 Mg CO2e/year GHG in 10 years’ time. In 7 out of the 9 regions, GHG reduction potentials will decrease into the future while only small increases will be seen in the South Coast and West Coast (North) NRRs. 176 8,000,000 6 GHG Reduction from Current Total Available Residues Mg CO2e total reduction from application 0 ,00 0 ,45 7,000,000 Total Regional CO2e reduction (Mg ) 0 ,00 20 7,2 GHG Reduction from Total Available Residues in 10 Years 6,000,000 5,000,000 4,000,000 ,0 00 4,7 00 0 ,00 70 3,8 0 ,00 70 3,7 ,0 20 2,1 2,8 00 0 ,00 10 3,000,000 0 ,00 00 3,4 2,000,000 0 00 ,00 0,0 ,400 1 00 Cariboo Kootenay-Boundary 00 Northeast Omineca Skeena South Coast 00 0,0 0,0 58 0 - 0 00 ,00 00,0 1,5 50 1,4 6 1,2 0,0 87 1,000,000 0 ,00 60 1,9 0 ,00 10 3,5 62 Thompson-Okanagan West Coast (North) 00 0,0 62 West Coast (South) British Columbia Natural Resource Region Figure 6.2 Total BC GHG emission reduction potential in the 9 natural resource regions (NRRs) through the use of biocoal for cement production and carbon sequestration applications. Values are presented in Mg CO2e/year. Transportation distance emission allowance between cement produced with petroleum coke and biocoal carbon sequestration is shown in Table 6.5. The most common method of rail transportation would allow 9,930 km of biocoal shipping for cement petroleum coke displacement to be similar in emission reductions to biocoal carbon sequestration. Table 6.5 Transportation distance emission allowance for various modes of biocoal transportation. Comparison is made between Cement produced with petroleum coke and biocoal carbon sequestration. Distances are presented in km. Cement - Rail Biocoal Sequestration - Rail Biocoal Sequestration - Freight Lorry Biocoal Sequestration - Tanker Barge 6.5 Cement - Freight Lorry Cement - Tanker Barge 9,930 6,428 15,658 Discussion If BC were to prioritize the use of biocoal to offset petroleum coke and burial for carbon sequestration, the province could reduce GHG emissions by 28,000,000 Mg CO2e/year from current available residues, and 20,006,000 Mg CO2e/year in 10 years’ time. 177 This means that, at maximum and given the estimated residues available, BC could reduce its current emissions of 61,600,000 Mg CO2e/year by 46%, and 33% in 10 years if the province’s emissions maintain at current levels (BCMOE 2017). With only the use of roadside slash residues, BC could reduce GHG emissions by 10,300,000 Mg CO2e/year and 7,600,000 Mg CO2e/year in 10 years’ time, equal to 17% and 12% respectively. 6.5.1 Biomass residue availability If offset or reduction emissions were prioritized from the use of sawmill and roadside slash residues, the values presented above could be seen. In other words, residues assessed here represent a maximum value of available residues that may or may not be already allocated. For context, in the Prince George region, little to no sawmill or roadside slash residues are available at low cost due to existing uses and thus the vast majority of residues are already allocated, and similarly assumed in 10 years’ time; whereas in the West Kootenay region there are substantial sawmill and roadside residues available (BC Hydro 2015). Another large factor to consider is the percent of sawmill residues produced from a whole log. In this assessment residue generation on a mass basis was set at 61% and based on Athena (2018), which assessed a lifecycle assessment of Canadian surfaced dry softwood. BC Hydro (2015) however set a value of 53% sawmill residues from whole logs, and being 8% lower than Athena (2018). Depending on the more accurate data source, or even specific sawmill operation efficiency, this will change the predicted value of potentially available sawmill residues. Pulp chips were included as a source of residues in this assessment from sawmill residues, however as mentioned above for general residue use, residues in some regions are already allocated, and would likely be the same with pulp chips. From Athena (2018), pulp chips make up 60% of sawmill residues, if those were to be removed from the total 178 assessment it would decrease the total offset reduction or carbon sequestration potential by 38% at current harvest and sawmill residues, and 37% in 10 years’ time. This is a substantial difference, however this project chose to represent the maximum value of residues and subsequently discuss factors that may affect total emissions rather than make defined method assumptions. Research from Dymond et al. (2010) assessed ‘harvesting residues’, similar to roadside slash in this project, and found a total of 15,552,000 oven dried Mg per year for British Columbia. This contrasts with 5,304,000 oven dried Mg per year of roadside slash residue assessed in this project in 10 years’ time; however Dymond et al. applied a 50% discount factor to their assessments resulting in 7,776,000, which is reasonably similar to the provincial value found here. In this assessment, recovered roadside slash residues were dependent on financial cost of recovery laid-out in the Residual Fibre Recovery - Estimates of Residual Fibre reports released by FPInnovations (BCMOFLNRORDb 2018). In the reports released to date, the cost of recovery vs available residues was typically assumed at $60/ODMg threshold for economic cost recovery, however for this project the maximum range of $200/ODMg was used. For example, as reported in the Residual Fibre Recovery - Estimates of Residual Fibre, in the Arrowsmith TSA, which was used within the South West Coast region, total roadside slash residues were calculated to be on average 22,560 ODMg/year, starting at a recovery cost of $200/ODMg; whereas at $60/ODMg recovery cost, the available residues drop to around 3,269 ODMg/year. The Arrowsmith TSA, however, was on the wider range of cost to residue recovery difference, whereas at $200 ODMg the 100 Mile House TSA could recover around 110,192 ODMg/year, while at $60/ODMg would recover around 80,756 ODMg/year. Ultimately, and as stated above, this assessment represents a maximum level of offset 179 potential and thus economic considerations associated with cost of recovery will need to be included for government and industry interested in the results from this project. Future biomass supplies will be challenged in the next 10 years, and potentially beyond, due to a decrease in residues of around 30% as shown in this project. This could be supplemented through increased collection of wood wastes in the regions, at greater cost, or other biomass supplies, such as biosolids or landfill diverted wood waste. There is also possibility of using contaminated biomass residues for biocoal carbon sequestration when not able to be used for petroleum coke substitution or other existing bioenergy use, such as bioelectricity. Additionally, there may develop a need for dedicated bioenergy crops to be grown if the bioenergy industry’s demand continues to grow, and was examined with hybrid poplar in Research Project 1 for assessed lifecycle GHG emissions. 6.5.2 Application scenarios The application scenarios included in this report’s results applied petroleum coke displacement in the South Coast NRR and biocoal carbon sequestration in all other NRRs. This was because the two applications represented the highest offset potential for wood residue applications in the province at this time. The residues available in the South West Coast NRR supplied approximately 92% of the total estimated residue needs for the Lafarge cement plant in Richmond, BC (397,000 Mg vs 421,000 Mg needed on an annual basis). No residues were assumed to be transported in from the other NRRs, however this could be performed and most likely imported from the South West Coast NRR to achieve greater emission reductions. At the time of writing, a quicklime plant is planned to be constructed 50 km northeast of Prince George, BC, and is considering the use of petroleum coke to fuel their lime kilns (BCEAO 2018; Graymont 2018). This application would present a greater potential for GHG 180 offsets versus biocoal carbon sequestration in the Omineca NRR, and consume similar quantities of residues at full capacity as the Lafarge cement plant. Other neighbouring jurisdictions may optimize the use of BC wood residues for the production of biocoal to offset 100% of petroleum coke fuel requirements. These could be other quicklime or cement kilns, or solid fossil fuel fired power plants in Alberta or Washington State. Like the above quicklime plant near Prince George, these plants would increase the GHG offset potential versus biocoal carbon sequestration. Biocoal carbon sequestration may fit as a practical catch-all for reducing emissions where economically stranded biomass residues exist. The advantage of sequestering carbon from readily degradable residues is that it can be done locally in any region, as long as a biocoal pyrolysis kiln is available and based off the BC Biocarbon system as outlined in Research Project 1. Biocoal is also advantaged in that it is in a solid carbon form and can be easily transported and buried, unlike current carbon capture and storage methods where gaseous or liquid CO2 must be managed (Bui et al. 2018). Although listed in the application methods in Table 6.1, biochar application to soils, and biocoal use at Teck Resources and Lehigh Cement were not calculated in the results. This was because, as noted above, other higher GHG reduction potentials were determined. With that said, and although not assumed in this project’s methods, economics may favour these combustion applications. This is due to two factors: fuel cost competitiveness in a carbon taxed market, and the current state of development of the carbon sequestration market and its cost competitiveness to other offset opportunities. Coal and petroleum coke displacement in a carbon taxed market allows for cost competitive lower carbon fuels as long as the displacement cost is lower than the fossil fuel price plus carbon price. This may occur in some markets where low-cost low-carbon fuels exist and can be a cheaper option. 181 The carbon sequestration market is currently in its infancy, and especially when referring to millennium timescale sequestration. Biochar carbon sequestration projects may be sold to potential offsetters through a validated private market project, however existing offset options, such as landfill methane to electricity, is likely of lower cost to the offsetter and thus preferable from an economic standpoint. 6.5.3 Other GHG factors Carbon offset revenue, i.e. the funds raised for the sale of GHG emission reductions or carbon sequestration could be, and is advised to be, added to roadside slash residues by this dissertation’s author. This is because of the reduction in methane and nitrous oxide emissions has a value to GHG offsetting individuals or organizations. That revenue/value can be used to help recover more roadside slash residues with higher recovery costs. Transportation emission allowances are related to the local availability of residues and their application to either local carbon sequestration or distant petroleum coke applications. The transportation emissions were unsurprising, although necessary for context, given that transportation emissions typically contribute a minor amount to overall GHGs of a product (shown in Research Project 1). This did depend on the type of transportation and the GHG offset/sequestration difference seen between the applications. For example, biocoal could be transported up to 9,930 km by rail before the emissions offset premium is lost between offsetting petroleum coke to local use for carbon sequestration. This distance essentially allows biocoal to be transported anywhere in the province to offset petroleum coke, as long as economics allow. The transportation emission allowance while not the primary focus of this research project provides important context to the biocoal applications. One of the main benefits of applying wood and other biomass residues to biocoal carbon sequestration is that production can match possible fluctuations in residue supplies and 182 adjust with little disruption as there is no “end user”. In other bioenergy applications, such as pellet production, large contracts are normally set for supply quantities overseas and must be met to keep customers supplied with energy. The bioenergy industry will likely be doubly challenged in the coming years if growth in the sector continues and when sawmill and roadside slash residue supplies diminish, as broadly shown through this project based on the Residual Fibre Recovery - Estimates of Residual Fibre reports released by FPInnovations and BC Hydro (2015). Biocoal sequestration on the other hand could adapt by possibly incorporating contaminated biomass or simply reducing the amounts buried. 6.5.4 Limitations, considerations, and conclusions Limitations of this project include the need to use proxy-filled data for quantifying roadside slash residues and future residues based on the Residual Fibre Recovery - Estimates of Residual Fibre reports. In the future, when other TSA reports are released, their information should be checked, confirmed or corrected, and updated for residue availability. The results found in this project only prioritize GHG reductions or carbon sequestration potential, and thus the applications of biocoal presented are subject to local economic and other societal use considerations. Government and industry will need to weigh their priorities in order to determine the best use of residues or direction of use of residues. The results of this project, and the foundational results shown in the previous 3 projects, raise important questions and points regarding the future path of BC’s bioenergy economy especially with an estimated 30% reduction in sawmill and roadside slash residues. Of course, any policy or local action would need to firm up available wood resources, however, some questions arise: Should the BC government take a leadership role in establishing a biomass and residue use directive in order to prevent future market supply limits and price volatility? Should the BC government start to incent GHG reduction uses for 183 residues over other applications? Should industry and bioenergy system operators start to develop bioenergy crops or heavily research and develop cheaper options of residue recovery to limit supply or price issues? Should BC export to our neighbouring jurisdictions to help with their GHG emission reductions through the substitution of petroleum coke, or should we sequester carbon locally but at a slightly lower level of GHG reduction? With the high potential for carbon sequestration, will biocoal burial become a major method to mitigate climate change or offset fossil fuels? These questions will be answered in the coming years as a result of market needs and government directives, and represent an exciting array of future possibilities. Wood residues used in the applications outline would very likely yield greater emission reductions than almost all other bioenergy applications currently in the province, and particularly bioelectricity, where there is effectively no reduction in emissions compared to the hydro-electricity it is adding to (BC Hydro 2018). With climate change becoming an ever more pressing issue, the opportunity to use biocoal from sawmill and roadside slash residues would equal around a 46% reduction in BC’s current emissions. This would represent around 3/4 of the province’s current 2030 reduction goals (BC Laws 2018). The primary goal of this project was to assess the total potential GHG emission reductions and carbon sequestration potential from the application of biocoal in BC. This was done by taking the findings from Projects 1, 2 and 3 of this dissertation, and applying them to the estimated total sawmill and roadside slash residues in BC. With an estimated GHG emission reduction or carbon sequestration of 28,000,00 Mg CO2e/year from current available residues, and 20,006,000 Mg CO2e/year in 10 years’ time, BC has the potential to reduce its current emissions by around 46%, and 33% in 10 years. Government and industry would 184 benefit from these findings as to best approach the province’s bioenergy industry direction and path towards mitigating our contribution to anthropogenic climate change. 6.6 References Athena. (2018). A Cradle-to-Gate Life Cycle Assessment of Canadian Surfaced Dry Softwood Lumber. Athena Sustainable Materials Institute. Last accessed Feb 05, 2019 at http://www.athenasmi.org/resources/publications/. BC Hydro. (2015). Wood Based Biomass in British Columbia and its Potential for New Electricity Generation. Last accessed Jan 05, 2018 at https://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/regulatory-planning-documents/integrated-resourceplans/current-plan/rou-characterization-wood-based-biomass-report-201507-industrialforestry-service.pdf. BC Hydro. (2018). Greenhouse Gas Intensities. BC Hydro. Last accessed August 18, 2018 at https://www.bchydro.com/content/dam/BCHydro/customerportal/documents/corporate/environment-sustainability/environmental-reports/ghgintensities-2007-2015.pdf. BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. BCEAO. 2018. Giscome Quarry and Lime Plant. Environmental assessment Office - Project Information & Collaboration. Last accessed August 09, 2018 at https://projects.eao.gov.bc.ca/p/giscome-quarry-and-lime-plant/detail. BCMOFLNRORDa. (2018). Allowable Annual Cut - Timber Supply Areas. Ministry of Forests, Lands, Natural Resource Operations and Rural Development. Last accessed July 5, 2018 at https://www2.gov.bc.ca/gov/content/industry/forestry/managing-ourforest-resources/timber-supply-review-and-allowable-annual-cut/allowable-annual-cuttimber-supply-areas. BCMOFLNRORDb (2018). Residual Fibre Recovery - Estimates of Residual Fibre. Last accessed July 5, 2018 at https://www2.gov.bc.ca/gov/content/industry/forestry/forest-tenures/forest-tenureadministration/residual-fibre-recovery. 185 BCGb. (2018). Regional Assessments Map. Last accessed July 22, 2018 at https://www2.gov.bc.ca/gov/content/environment/natural-resourcestewardship/cumulative-effects-framework/regional-assessments. BCGa. (2018). 2015 Industrial Facility Greenhouse Gas Emissions. BC Government. Last accessed May 05, 2018 at https://www2.gov.bc.ca/gov/content/environment/climatechange/data/industrial-facility-ghg. BC Laws. (2018). Greenhouse Gas Reduction Targets Act - Chapter 42. BC Laws. Last accessed Aug 25, 2018 at http://www.bclaws.ca/civix/document/id/lc/statreg/07042_01. BCMOE. (2017). 2015 British Columbia Greenhouse Gas Inventory. British Columbia Ministry of Environment. Last accessed Aug 16, 2018 at https://www2.gov.bc.ca/gov/content/environment/climate-change/data/provincialinventory. Bui, M., S. Adjiman, C., Bardow, A., J. Anthony, E., Boston, A., Brown, S., S. Fennell, P., Fuss, S., Galindo, A., A. Hackett, L., et al. (2018). Carbon capture and storage (CCS): the way forward. Energy & Environmental Science 11, 1062–1176. CRS (2013). Petroleum Coke: Industry and Environmental. Petroleum Coke: Industry and Environmental Issues. Congressional Research Service. Authored by Andrews, A. and Lattanzio, R.K. October 29, 2013. Last accessed June 1, 2016 at http://www.nam.org/CRSreport/. Dymond, C.C., Titus, B.D., Stinson, G., and Kurz, W.A. (2010). Future quantities and spatial distribution of harvesting residue and dead wood from natural disturbances in Canada. Forest Ecology and Management 260, 181–192. Ecoinvent. (2014). The ecoinvent database: Overview and methodology, Data quality guideline for the ecoinvent database version 3, developed by Weidema, B.P., Bauer, Ch., Hischier, R., Mutel, Ch., Nemecek, T., Reinhard, J., Vadenbo, C.O., Wernet, G. www.ecoinvent.org. Released July 08, 2014. EPA. (2014). Emission Factors for Greenhouse Gas Inventories. Last accessed March 15, 2016 at https://www.epa.gov/sites/production/files/2015-07/documents/emissionfactors_2014.pdf. FAO. 2018. The Food and Agriculture Organization Wood fuels handbook. Last accessed Jan 05, 2018 at http://www.fao.org/forestry/energy/90829/en/. 186 FPInnovations. (2018). FPInterfaceTM, forest supply chain simulator. Last accessed July 15, 2018 at http://fpsuite.ca/l_en/fpinterface.html. Gaunt, J.L., and Lehmann, J. (2008). Energy Balance and Emissions Associated with Biochar Sequestration and Pyrolysis Bioenergy Production. Environmental Science & Technology, Vol. 42, pp. 4152–4158. Graymont. (2018). Giscome Lime Project. Graymont Western Canada Inc. Last accessed August 09, 2018 at http://giscomeproject.ca/about-giscome-project/. GWCI. (2018). Graymont Western Canada Inc., Lime Pavilion Plant. Last accessed May 01, 2018 at http://www.graymont.com/en/locations/lime-plants/western-canada/limeplant/pavilion. Hammond, J., Shackley, S., Sohi, S., and Brownsort, P. (2011). Prospective lifecycle carbon abatement for pyrolysis biochar systems in the UK. Energy Policy, Vol. 39, pp. 2646– 2655. Huang, Y.-F., Syu, F.-S., Chiueh, P.-T., and Lo, S.-L. (2013). Life cycle assessment of biochar cofiring with coal. Bioresource Technology 131, 166–171. Ibarrola, R., Shackley, S., and Hammond, J. (2012). Pyrolysis biochar systems for recovering biodegradable materials: A lifecycle carbon assessment. Waste Management, Vol. 32, pp. 859–868. ISOa. (2006) ISO 14040:2006 Environmental management - Lifecycle assessment - Principles and framework. International organization for standardization, Geneva, Switzerland. ISOb. (2006) ISO 14044:2006 Environmental management - Lifecycle assessment Requirements and guidelines International organization for standardization, Geneva, Switzerland. IPCC. (2006). IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4, Agriculture, Forestry and Other Land Use. Last accessed May 5, 2014 at http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.html. IPCC. (2013). Climate Change 2007: Working Group I: The Physical Science Basis. 2.10.2 Direct Global Warming Potentials. Intergovernmental Panel on Climate Change. Last accessed Sept 19, 2017 at https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-10-2.html. 187 Industryabouta. (2018). Lafarge - Richmond Cement Plant. Industryabout.com. Last accessed August 15, 2018 at https://www.industryabout.com/country-territories-3/318canada/cement-industry/1076-lafarge-richmond-cement-plant. Industryaboutb. (2018). Lehigh - Delta Cement Plant. Industryabout.com. Last accessed August 15, 2018 at https://www.industryabout.com/country-territories-3/318canada/cement-industry/1078-lehigh-delta-cement-plant. OpenLCA. (2014) GreenDelta GmbH. Last accessed March 18, 2014 at http://www.openlca.org/. Pourhashem, G., Spatari, S., Boateng, A.A., McAloon, A.J., and Mullen, C.A. (2013). Lifecycle Environmental and Economic Tradeoffs of Using Fast Pyrolysis Products for Power Generation. Energy & Fuels, Vol. 27, pp. 2578–2587. Reitsma, L. (2015) Personal phone communication. President & Chief Operating Officer, Pinnacle Renewable Energy Inc. 14 October 2015. Teck (2016). Personal email communication. Dave Reynolds, Trail Chief Metallurgist Teck Metals Ltd. March 28, 2016. Wang, Z., Dunn, J.B., Han, J., and Wang, M.Q. (2013). Effects of co-produced biochar on life cycle greenhouse gas emissions of pyrolysis-derived renewable fuels. Biofuels, Bioprod. Bioref. 8, 189–204. Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J., and Joseph, S. (2010). Sustainable biochar to mitigate global climate change. Nature Communications Vol. 1, pp. 1–9. 188 Appendix 1 Supplementary Information Greenhouse gas assessment of a novel pyrolysis retort kiln producing wood-based synthetic coal from sawmill residues, roadside slash, and hybrid poplar feedstocks. Supplementary Information Introduction: Below are a series of images which capture and present a sample calculation for biocoal production from roadside slash. The images are sequential screen captures from the open LCA program used and final excel spreadsheet calculations. Symbols such as and are used to highlight key inputs and outputs that link each successive process. 648+1426 Figure SI1-1. BC Biocarbon infrastructure lifecycle set up. Tabs and main input and output sections are box highlighted for initial orientation. 189 Figure SI1-2. Roadside slash harvest emission output for 200 km recovery return scenario. 190 Figure SI1-3. BC Biocarbon infrastructure plus roadside slash feedstock and other activities input for biocoal output per Mg. 191 Figure SI1-4. Roadside slash feedstock input to biocoal emissions output per GJ. 192 Figure SI1-5. Roadside slash biocoal LCA results from OpenLCA and emissions contribution tree for biocoal with harvest emissions for 200 km recovery distance and delivered to Rotterdam, NL. Figure SI1-6. Screenshot of roadside slash biocoal LCA results from OpenLCA with emissions offset subtracted for final results in manuscript. Appendix 2 Supplementary Information Greenhouse gas assessment and carbon displacement factors of wood-based biocoal in cement, smelting, and electrical power production. 193 Supplementary Information Introduction: This appendix outlines the sample calculation of cement GHG reduction using biocoal performed in Research Project 2. Primary data for lead smelting and coal-fired power plant emission reduction using biocoal is also provided. Bolded values are used for subsequent calculations. Table SI2-1. Source information for cement GHG reduction at Lafarge Canada LTD in Richmond, BC from Lafarge (2016). Assumed 28.6 GJ/Mg petroleum coke to derive Mg Petcoke/Mg cement from quoted GJ/Mg cement. Mg Petcoke / day (if running petcoke) 82.5 Mg coal/day (if running coal) 105 Mg Petcoke / Mg cement GJ / Mg cement GJ / Mg cement (minus 10% biomass GJ) 0.134 Mg coal / Mg cement 0.2 4.27 3.843 Table SI2-2. Source information for petroleum coke transportation to Lafarge Canada LTD in Richmond, BC. Map source for rail line direction confirmation found at https://www.proximityissues.ca/wp-content/uploads/2017/10/BC_rail_map.pdf and measured with Google Maps (2016). Transportation emissions factors from Ecoinvent (2014). Transportation distance (km) Loydminster, SK to Kamloops, BC 1116 km Petroleum coke Fuel Transportation emissions factor/Mg-km (CO2e/GJ) petroleum coke (1116 km) 0.0017 Fuel Transportation emissions/Mg-km (CO2e/Mg) petroleum coke (1116 km) 0.0492 Biocoal Fuel Transportation emissions/Mg-km (CO2e/GJ) (436 km) 0.0017 Fuel Transportation emissions/Mg-km (CO2e/Mg) biocoal (436 km) 0.0492 Transportation distance (km) Kamloops, BC to Lafarge, Richmond 436 km Transportation emissions total 2.631 kg CO2e/GJ 76.28 kg CO2e/Mg 0.7240 kg CO2e/GJ 21.43 kg CO2e/Mg 194 Sample Calculation SI2-1. Sample calculation of ‘Plus petcoke production and transportation’ GHG reduction/displacement factor of biocoal use in cement production. 𝑀𝑔 𝐶𝑒𝑚𝑒𝑛𝑡 (𝑚𝑖𝑛𝑢𝑠 10% 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 𝐺𝐽) 𝐺𝐽 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝐶𝑒𝑚𝑒𝑛𝑡 ∗ = 𝐺𝐽 𝐸𝑛𝑒𝑟𝑔𝑦 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 1 ∗ 29.6 = 𝟕. 𝟕𝟎 3.843 𝑘𝑔 𝐶𝑂2𝑒 (CRS 2013) 𝑘𝑔 𝐶𝑂2𝑒 (𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠) + 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 + 𝑈𝑝𝑡𝑟𝑒𝑎𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 (𝐸𝑐𝑜𝑖𝑛𝑣𝑒𝑛𝑡 2014) = 3254.8 ê113.8 𝑘𝑔 𝑘𝑔 𝐶𝑂2𝑒 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 𝐶𝑂2𝑒 , CRS 2013í + 76.28 + 72.76 (𝐸𝑐𝑜𝑖𝑛𝑣𝑒𝑛𝑡 2014) = 𝟑𝟑𝟑𝟏. 𝟎𝟗 𝐺𝐽 𝑘𝑔 𝐶𝑂2𝑒 (𝐹𝑟𝑜𝑚 𝑃𝑟𝑜𝑗𝑒𝑐𝑡 1) 𝑘𝑔 𝐶𝑂2𝑒 (𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠) 𝑘𝑔 𝐶𝑂2𝑒 + = 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 217.26 + 21.43 = 𝟐𝟑𝟖. 𝟔𝟗 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 𝑀𝑔 𝐶𝑒𝑚𝑒𝑛𝑡 𝑘𝑔𝐶𝑂2𝑒 ∗ ∗ 𝑀𝑔 𝐶𝑒𝑚𝑒𝑛𝑡 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 𝑘𝑔 𝐶𝑂2𝑒 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 (𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑎𝑛𝑑 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠) 𝐺𝐻𝐺 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑘𝑔 𝐶𝑂2𝑒 = 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 − 0.134 ∗ 7.70 ∗ 3331.09 − 238.69 = 𝟑𝟐𝟎𝟖. 𝟗 𝐺𝐻𝐺 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑘𝑔 𝐶𝑂2𝑒 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝐺𝐻𝐺 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑘𝑔 𝐶𝑂2𝑒 ∗ = 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝐺𝐽 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝐺𝐽 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 3208.9 1 ∗ = 𝟏𝟎𝟖. 𝟒 1 29.6 195 Table SI2-3. Calculation table and results for Cement GHG Reduction (displacement factor) using petroleum coke at Lafarge Canada LTD in Richmond, BC. Conversion to GJ Biocoal is through dividing the Mg Biocoal by 29.6 GJ/Mg. Sawmill residues - Petcoke ‘100 km biocoal freight lorry to application’ Full scenario to actual conditions' Petcoke (transportation to Richmond) ‘100 km biocoal freight lorry to application’ Full scenario to actual conditions' Petcoke (transportation to Richmond) Sawmill residues - Coal ‘100 km biocoal freight lorry to application’ Full scenario to actual conditions' Petcoke (transportation to Richmond) ‘100 km biocoal freight lorry to application’ Full scenario to actual conditions' Petcoke (transportation to Richmond) GJ Petcoke / Mg Cement Mg Cement / GJ Biocoal kg CO2 / GJ Petcoke kg CO2 / GJ Biocoal GHG Reduction kg CO2e / GJ Biocoal 108.88 108.41 Mg Petcoke / Mg Cement 0.134 Mg Cement / Mg Biocoal 7.70 kg CO2e / Mg Petcoke 3331.09 kg CO2e / Mg Biocoal 224.86 GHG Reduction kg CO2e / Mg Biocoal 3222.70 0.134 7.70 3331.09 238.96 3208.87 GJ Petcoke / Mg Cement Mg Cement / GJ Biocoal kg CO2e / GJ Petcoke kg CO2e / GJ Biocoal GHG Reduction kg CO2e / GJ Biocoal 89.96 89.49 Mg Petcoke / Mg Cement 0.134 Mg Cement / Mg Biocoal 7.70 kg CO2e / Mg Petcoke 2659.20 kg CO2e / Mg Biocoal 228.41 GHG Reduction kg CO2e / Mg Biocoal 2662.75 0.134 7.70 2645.36 242.25 2648.91 Table SI2-4. Source information for coal-fired power at HR Milner Generating Station near Grande Cache, Alberta, Canada (HR Milner 2016), EPA (2014), and Ecoinvent (2014) based data. HR Milner 2016 Hourly Mg use of coal Plant efficiency Coal Heating value (GJ/Mg) 81.667 0.257 24 Coal Heating value (Mg/GJ) 0.0417 kg CO2 / mmbtu 93.28 kg CO2 / GJ total with mining kg CH4 / mmBtu 0.011 kg CO2e / GJ total with mining 28.99 93.82 0.376 Transportation emissions from Ecoinvent (2014) Fossil fuel transportation distance (km) Coal Valley AB to HR Milner AB 284 Fuel Transportation emissions/Mg-km (CO2e/GJ) 0.00166 Fuel Transportation emissions/Mg-km (CO2e/Mg) 0.0492 EPA 2014 Bitumenous Coal (MMBTU/Short ton) 24.93 Bitumenous Coal (GJ/Mg) GJ / MWh (at 140 Mw) 14 MWh / GJ 0.0714 kg N2O per mmBtu 0.0016 kg CO2e / GJ total with mining 0.480 Mg CO2 / MWh 1.4 Mg CO2 / hour 196 Total kg CO2e / GJ 94.68 196 Table SI2-5. Calculation table and results for GHG reductions in ‘Full scenario to actual conditions’ using biocoal at HR Milner Generating Station near Grande Cache, Alberta, Canada. Displacement Factor / GJ Biocoal GJ Coal / MWh MWh / GJ Biocoal kg CO2 / GJ Coal 107.7 kg CO2 / GJ Biocoal (from Project 1 plus rail emissions to Grande Cache, AB) 9.46 98.3 14 0.0714 HR Milner numbers 106.0 14 0.0714 95.8 9.48 EPA numbers Table SI2-6. Source information for smelting GHG reduction using biocoal at Teck Resources LTD in Trail, BC. Teck 2016 Fixed carbon % Coal use for Lead (Mg/day) 300 Lead production annually 90,000 Mg coal/tonne lead 1.277 Mg Lead production in 2015 83,400 Mg Lead produced per day 234.93 GJ/tonne lead 38.12 kg CO2/tonne coal burned Short ton in kg 907.19 CO2e factor CH4 34 kg CO2/tonne coal burned CO2e factor N2O 298 kg CO2/tonne coal burned Total kg CO2e/tonne coal 2339 10.27 13.14 2562.87 475 Total Biocoal for Lead Emissions by Lorry Truck kg CO2/GJ Biocoal Transportation from Kamloops to Teck, Trail by Freight Lorry 468 Total Biocoal for Lead Emissions by Rail kg CO2/GJ Biocoal Transportation from Kamloops to Teck, Trail by Rail 891 Total Biocoal for Lead Emissions by Lorry Truck kg CO2/tonne Lead Total Biocoal for Lead Emissions by Rail kg CO2/tonne Lead 6.53 6.81 193.288 201.576 73-76 Lead Concentrate production annually 117,600 EPA 2014 Transportation numbers Fossil fuel transportation distance (km) Coal Mountain to Teck, Trail Days operation 355 Tonne lead/GJ 0.02623 Table SI2-5. Calculation table and results for GHG reductions using biocoal at Teck Resources LTD in Trail, BC. Displacement Factor / GJ Biocoal 80.0 GJ coal / Mg lead Mg Lead / GJ Biocoal kg CO2 / GJ coal 78.8 kg CO2 / GJ Biocoal 7.716 8.939 Displacement Factor / Mg Biocoal Mg coal / Mg lead Mg lead / Mg Biocoal kg CO2 / Mg coal 2369.47 1.277 0.777 2616.234 kg CO2 / Mg Biocoal 224.856 2333.27 1.277 0.777 2616.234 261.057 ‘100 km biocoal freight lorry to application’ ‘Full scenario to actual conditions' ‘100 km biocoal freight lorry to application’ ‘Full scenario to actual conditions' 197 Appendix 3 Supplementary Information Greenhouse gas assessment and carbon displacement factors of soil and carbon sequestration applications of biochar, biocoal and wood wastes in BC Supplementary Information Introduction: This appendix outlines the carbon reduction potentials of Research Project 3. Three scenarios are outlined and highlight key findings: Biocoal sequestration, wood waste sequestration, and biochar soil sequestration and associated carbon reduction potential. Table SI3-1. Table of key values and constants used. C molar mass (kg/kmol) CO2 molar mass (kg/kmol) O molar mass (kg/kmol) H molar mass (kg/kmol) CH4 molar mass (kg/kmol) Calcium Carbonate (ash) molar mass (kg/kmol) Nitrogen molar mass (kg/kmol) Sulfur molar mass (kg/kmol) Air molar mass Biocoal energy density (GJ/Mg biocoal) (from BC Biocarbon 2015) Biochar energy density (GJ/Mg biochar) (from BC Biocarbon 2015) Mg biochar / Mg wood waste (from BC Biocarbon 2015) Mg biocoal / Mg wood waste (from BC Biocarbon 2015) Biocoal Bulk Density (from BC Biocarbon 2015) (kg/m^3) Biochar Bulk Density (assumed from literature) (kg/m^3) Wood Bulk Density (assumed from literature) (kg/m^3) Biocoal Specific Density (from BC Biocarbon 2015) (kg/m^3) Biochar Specific Density (Santín et al. 2017) (kg/m^3) Wood Specific Density (assumed from literature) (kg/m^3) Biochar Carbon Content (%) (from BC Biocarbon 2015) Biocoal Carbon Content (%) (from BC Biocarbon 2015) Wood Carbon Content (%) (assumed from literature) Biochar Oxygen Content (%) (from BC Biocarbon 2015) Biocoal Oxygen Content (%) (from BC Biocarbon 2015) Wood Oxygen Content (%) (assumed from literature review) O in air (% by mass) density of air (kg/m3) Proportion of biochar in biocoal CH4 GWP (IPCC 2013) 12.01 44.01 15.999 1.01 16.04 100.09 14.01 32.07 29 29.6 27.84 0.24 0.47 800 224 267.5 1110 1850 415 92.53 80.88 50.7 3.38 12.94 41.23 23.2 1.2466 0.5 32 198 199 Table SI3-2. Biocoal carbon sequestration data and results table. Sample calculation of biocoal ‘No degradation’ carbon sequestration scenario found in Sample Calculation SI3-1. Sample Calculation SI3-1. Sample calculation of biocoal ‘No degradation’ carbon sequestration scenario found in Table SI3-2 above. Bolded values are used in subsequent calculations and ° marked values are from Table SI3-1. 𝑔 °𝑀𝑔 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 °𝐶𝑂2 𝑚𝑜𝑙𝑎𝑟 𝑚𝑎𝑠𝑠 û𝑚𝑜𝑙ü 𝑀𝑔 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 ∗ = 𝑔 °𝐶 𝑚𝑜𝑙𝑎𝑟 𝑚𝑎𝑠𝑠 û𝑚𝑜𝑙ü °0.8088 ∗ 𝑨𝒔𝒔𝒖𝒎𝒆𝒅 𝟏𝟎𝟎𝒚 𝑴𝒈 𝑪𝑶𝟐𝒆 𝑺𝒆𝒒𝒖𝒆𝒔𝒕𝒆𝒓𝒆𝒅 𝑴𝒈 𝑩𝒊𝒐𝒄𝒐𝒂𝒍 °44.01 = 𝟐. 𝟗𝟔𝟒 °12.01 𝑨𝒔𝒔𝒖𝒎𝒆𝒅 𝟏𝟎𝟎𝒚 𝑴𝒈 𝑪𝑶𝟐𝒆 𝑺𝒆𝒒𝒖𝒆𝒔𝒕𝒆𝒓𝒆𝒅 𝑴𝒈 𝑩𝒊𝒐𝒄𝒐𝒂𝒍 𝐴𝑡 𝑔𝑎𝑡𝑒 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑀𝑔 𝐶𝑂2𝑒 + (− 𝑀𝑔 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 100 𝑘𝑚 𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑀𝑔 𝐶𝑂2𝑒 − 𝑀𝑔𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝐿𝑎𝑛𝑑𝑓𝑖𝑙𝑙 𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠𝑀𝑔 𝐶𝑂2𝑒 − ) 𝑀𝑔 𝐵𝑖𝑜𝑐𝑜𝑎𝑙 𝑵𝒆𝒕 𝟏𝟎𝟎𝒚 𝑴𝒈 𝑪𝑶𝟐𝒆 𝒔𝒆𝒒𝒖𝒆𝒔𝒕𝒆𝒓𝒆𝒅 = 𝑴𝒈 𝑩𝒊𝒐𝒄𝒐𝒂𝒍 𝟐. 𝟗𝟔𝟒 + (−0.2208 − 0.0759 − 0.0412) = 𝟐. 𝟕𝟑𝟓 𝑵𝒆𝒕 𝑴𝒈 𝑪𝑶𝟐𝒆 𝒔𝒆𝒒𝒖𝒆𝒔𝒕𝒆𝒓𝒆𝒅 °𝑀𝑔 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 𝑁𝑒𝑡 100𝑦 𝑀𝑔 𝐶𝑂2𝑒 𝑠𝑒𝑞𝑢𝑒𝑠𝑡𝑒𝑟𝑒𝑑 ∗ = 𝑴𝒈 𝑩𝒊𝒐𝒄𝒐𝒂𝒍 𝑀𝑔 𝑤𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝑀𝑔 𝑤𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝟐. 𝟕𝟑𝟓 ∗ °0.47 = 1.29 (biocoal ‘No degradation’ carbon sequestration scenario) 200 201 Table SI3-2. Wood waste carbon sequestration data and results table. Sample calculation of wood waste ‘Full CO2 based on embedded CO2 and macropore O2’ carbon sequestration scenario is shown in Sample Calculation SI3-2. Sample Calculation SI3-2. Sample calculation of wood waste ‘Full CO2 based on embeded CO2 and macropore O2’ carbon sequestration scenario found in table Table SI3-3. Bolded values are used in subsequent calculations and ° marked values are from Table SI3-1. 𝑀𝑔 °𝑊𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝐵𝑢𝑙𝑘 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 û 𝑚3 ü ∫1 − ª 𝑀𝑔 Ωæ °𝑊𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 û 𝑚3 ü 𝒎𝟑 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 = 𝑀𝑔 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 °𝑊𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝐵𝑢𝑙𝑘 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 û 𝑚3 ü °0.268 ¬1 − û °0.415ü√ °0.268 = 𝟏. 𝟑𝟐𝟗 °k𝑔 𝐴𝑖𝑟 𝒎𝟑 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 𝒌𝒈 𝑨𝒊𝒓 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 ∗ = °𝑚3 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 °1.2466 ∗ 𝟏. 𝟑𝟐𝟗 = 𝟏. 𝟔𝟓𝟔 𝒌𝒈 𝑨𝒊𝒓 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 °𝑘𝑔 𝑖𝑛 𝑊𝑜𝑜𝑑 ∗ °𝑅𝑎𝑡𝑖𝑜 𝑜𝑓 𝑂𝑥𝑦𝑔𝑒𝑛 𝑖𝑛 𝐴𝑖𝑟 + 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝒌𝒈 𝑶𝒙𝒚𝒈𝒆𝒏 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 𝒂𝒏𝒅 𝑾𝒐𝒐𝒅 = 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝟏. 𝟔𝟓𝟔 ∗ °0.232 + °412.28 = 𝟒𝟏𝟐. 𝟔𝟔 𝒌𝒈 𝑶𝒙𝒚𝒈𝒆𝒏 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 𝒂𝒏𝒅 𝑾𝒐𝒐𝒅 𝒌𝒎𝒐𝒍 𝑶𝒙𝒚𝒈𝒆𝒏 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 = °k𝑔 𝑂𝑥𝑦𝑔𝑒𝑛 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝑘𝑚𝑜𝑙 𝟒𝟏𝟐. 𝟔𝟔 = 𝟐𝟓. 𝟕𝟗 °15.999 𝒌𝒎𝒐𝒍 𝑶𝒙𝒚𝒈𝒆𝒏 𝒊𝒏 𝑽𝒐𝒊𝒅 𝑺𝒑𝒂𝒄𝒆 𝒌𝒎𝒐𝒍 𝑪 𝒐𝒙𝒊𝒅𝒊𝒛𝒆𝒅 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 = 𝑂𝑥𝑦𝑔𝑒𝑛 𝑡𝑜 𝐶𝑎𝑟𝑏𝑜𝑛 𝑟𝑎𝑡𝑖𝑜 𝑖𝑛 𝐶𝑂2 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝟐𝟓. 𝟕𝟗 = 𝟏𝟐. 𝟗𝟎 2 𝑘𝑔 𝐶𝑂2 𝒌𝒎𝒐𝒍 𝑪 𝒐𝒙𝒊𝒅𝒊𝒛𝒆𝒅 𝒌𝒈 𝑪𝑶𝟐 𝒐𝒙𝒊𝒅𝒊𝒛𝒆𝒅 ∗ = 𝑘𝑚𝑜𝑙 𝐶𝑂2 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 °44.01 ∗ 𝟏𝟐. 𝟗𝟎 = 𝟓𝟔𝟕 202 𝑘𝑔 °𝑀𝑔 𝐶 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 °𝐶𝑂2 𝑚𝑜𝑙𝑎𝑟 𝑚𝑎𝑠𝑠 ê𝑘𝑚𝑜𝑙í 𝑴𝒈 𝑪𝑶𝟐 𝒐𝒙𝒊𝒅𝒊𝒛𝒆𝒅 ∗ − 𝑘𝑔 °𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝑴𝒈 𝑾𝒐𝒐𝒅 𝑾𝒂𝒔𝒕𝒆 °𝐶 𝑚𝑜𝑙𝑎𝑟 𝑚𝑎𝑠𝑠 ê í 𝑘𝑚𝑜𝑙 𝐴𝑠𝑠𝑢𝑚𝑒𝑑 100𝑦 𝑘𝑔 𝐶𝑂2𝑒 𝑆𝑒𝑞𝑢𝑒𝑠𝑡𝑒𝑟𝑒𝑑 = 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 °0.507 ∗ °44.01 − 𝟎. 𝟓𝟔𝟖 = 𝟏. 𝟐𝟗𝟎 °12.01 𝐴𝑠𝑠𝑢𝑚𝑒𝑑 100𝑦 𝑀𝑔 𝐶𝑂2𝑒 𝑆𝑒𝑞𝑢𝑒𝑠𝑡𝑒𝑟𝑒𝑑 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑟𝑒𝑠𝑖𝑑𝑢𝑒 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑘𝑔 𝐶𝑂2𝑒 + ê− 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 100 𝑘𝑚 𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡 𝑒𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑘𝑔 𝐶𝑂2𝑒 − 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝐿𝑎𝑛𝑑𝑓𝑖𝑙𝑙 𝐶𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑘𝑔 𝐶𝑂2𝑒 − í 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝑁𝑒𝑡 100𝑦 𝑘𝑔 𝐶𝑂2𝑒 𝑠𝑒𝑞𝑢𝑒𝑠𝑡𝑒𝑟𝑒𝑑 = 𝑀𝑔 𝑊𝑜𝑜𝑑 𝑊𝑎𝑠𝑡𝑒 𝟏. 𝟐𝟗𝟎 + (−0.0978 − 0.01608 − 0.01231) = 𝟏. 𝟏𝟔𝟒 (biocoal ‘ Full CO2 based on embeded CO2 and macropore O2’ carbon … … sequestration scenario) Table SI3-3. Biochar soil integration summary table for baseline and sourced nitrous oxide emission reductions in soil. Key values used for calculations in subsequent tables and final results are bolded. 203 204 Table SI3-4. Biochar soil integration summary table for nitrogen fertilizer requirements in one high need crop (Timothy grass) and one low need crop (Bush Beans). Emission reductions from biochar integration are used in the final table (Table SI3-5). Key values used for calculations in subsequent tables and final results are bolded. Table SI3-5. Biochar soil integration summary table showing referenced degradation scenario values and final calculated results. 205 Appendix 4 Supplementary Information BC-wide assessment of biocoal industrial emission reduction potentials from wood-based sawmill and roadside slash residues. Supplementary Information Introduction: This appendix outlines the residues assessment of Research Project 4. Below are a series of tables which present the basis of data assessment, total residues assessed, and a sample calculation. Table SI4-1. GHG emission reduction potential used for biocoal made from wood-based residues and applied with equal local transportation to application (30 km). Columns are organized from highest GHG emission reduction potential to lowest and units are in Mg CO2e/Mg original wood residue. Method of Application Combustion or Non-Combustion Application Process 1) Petroleum Coke Substitution 2) Biocoal Sequestration 3) Coal Substitution Combustion Non-combustion Combustion Cement Production Carbon Sequestration Cement Production 4) High scenario biochar sequestration and GHG offset. 5) Coal Substitution 6) Low scenario biochar sequestration and GHG offset. Non-combustion Agricultural soil integration Lead Smelting Agricultural soil integration Combustion Non-combustion Offset factor/Mg original sawmill residue feedstock. (Mg CO2e / Mg feedstock) 1.52 1.29 1.26 Offset factor/Mg original roadside slash feedstock. (Mg CO2e / Mg feedstock) 1.65 1.42 1.39 1.24 1.34 1.12 0.70 1.25 0.79 Sample Calculation SI4-1. Sample calculation for total Cariboo Natural Resource Region GHG emission reduction from sawmill residues. The Cariboo Natural Resource Region consists of 100 Mile House, Quesnel, and Williams Lake TSAs. Sawmill residues ratio from original whole log was set at 61% (Athena 2018). 100 𝑀𝑖𝑙𝑒 𝐻𝑜𝑢𝑠𝑒 𝐴𝑛𝑛𝑢𝑎𝑙 𝐴𝑙𝑙𝑜𝑤𝑎𝑏𝑙𝑒 𝐶𝑢𝑡 (𝑚À ) ∗ 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑊𝑎𝑠𝑡𝑒 𝑅𝑒𝑠𝑖𝑑𝑢𝑒 % ∗ 𝐴𝑠𝑠𝑢𝑚𝑒𝑑 𝑂𝑣𝑒𝑛 𝐷𝑟𝑖𝑒𝑑 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 𝑜𝑓 𝑤𝑜𝑜𝑑 𝑀𝑔/𝑚À = 100 𝑀𝑖𝑙𝑒 𝐻𝑜𝑢𝑠𝑒 𝑇𝑆𝐴 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 1,948,002 ∗ 0.61 ∗ 0.428 = 508,584 100 Mile House TSA Sawmill Residues + Quesnel TSA AAC 2,607,000 --> 680,683 Mg Quesnel TSA Sawmill Residues Williams Lake AAC 3,000,000 --> 783,240 Mg Williams Lake TSA Sawmill Residues 1,972,460 Mg Total Cariboo Natural Resource Region Sawmill Residues 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔) ∗ 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟 (𝑀𝑔 𝐶𝑂2𝑒 𝑝𝑒𝑟 𝑀𝑔 𝑤𝑜𝑜𝑑 𝑟𝑒𝑠𝑖𝑑𝑢𝑒) = 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔 𝐶𝑂2𝑒) 1,972,460 ∗ 1.29 = 2,544,473 CO2e (prerounded) 206 Sample Calculation SI4-2. Sample calculations for total Cariboo Natural Resource Region GHG emission reduction from roadside slash residues. 100 Mile House Biomass Oven Dried Biomass per Merchantable m^3 is found in Table SI4-2 and taken from BCMOFLNRORDb (2018). 100 𝑀𝑖𝑙𝑒 𝐻𝑜𝑢𝑠𝑒 𝐴𝑛𝑛𝑢𝑎𝑙 𝐴𝑙𝑙𝑜𝑤𝑎𝑏𝑙𝑒 𝐶𝑢𝑡 (𝑚À ) ∗ 100 𝑀𝑖𝑙𝑒 𝐻𝑜𝑢𝑠𝑒 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 𝑂𝑣𝑒𝑛 𝐷𝑟𝑖𝑒𝑑 𝐵𝑖𝑜𝑚𝑎𝑠𝑠 𝑝𝑒𝑟 𝑀𝑒𝑟𝑐ℎ𝑎𝑛𝑡𝑎𝑏𝑙𝑒 𝑚À = 100 𝑀𝑖𝑙𝑒 𝐻𝑜𝑢𝑠𝑒 𝑇𝑆𝐴 𝑅𝑜𝑎𝑑𝑠𝑖𝑑𝑒 𝑆𝑙𝑎𝑠ℎ 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 1,948,002 ∗ 0.159 = 310,901 100 Mile House TSA Roadside Slash Residues + Quesnel TSA AAC 2,607,000 --> 285,734 Mg Quesnel TSA Roadside Slash Residues Williams Lake AAC 3,000,000 --> 918,000 Mg Williams Lake TSA Roadside Slash Residues 1,514,635 Mg Total Cariboo Natural Resource Region Roadside Slash Residues 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝑅𝑜𝑎𝑑𝑠𝑖𝑑𝑒 𝑆𝑙𝑎𝑠ℎ 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔) ∗ 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟 (𝑀𝑔 𝐶𝑂2𝑒 𝑝𝑒𝑟 𝑀𝑔 𝑤𝑜𝑜𝑑 𝑟𝑒𝑠𝑖𝑑𝑢𝑒) = 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑅𝑜𝑎𝑑𝑠𝑖𝑑𝑒 … … 𝑆𝑙𝑎𝑠ℎ 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔 𝐶𝑂2𝑒) 1,514,635 ∗ 1.42 = 2,153,441 CO2e (prerounded) Sample Calculation SI4-3. Sample calculation for total Cariboo Natural Resource Region GHG emission reduction from both sawmill and roadside slash residues. 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑆𝑎𝑤𝑚𝑖𝑙𝑙 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔 𝐶𝑂2𝑒) + 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 … … 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑅𝑜𝑎𝑑𝑠𝑖𝑑𝑒 𝑆𝑙𝑎𝑠ℎ 𝑅𝑒𝑠𝑖𝑑𝑢𝑒𝑠 (𝑀𝑔 𝐶𝑂2𝑒) = 𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑖𝑏𝑜𝑜 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑅𝑒𝑔𝑖𝑜𝑛 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑅𝑒𝑑𝑢𝑐𝑡𝑖𝑜𝑛 (𝑀𝑔 𝐶𝑂2𝑒) 2,544,473 + 2,153,441 = 4,697,884 = 4,700,000 CO2e (roundned) 207 8,000,000 GHG Reduction from Current Total Available Residues Mg CO2e total reduction from application 00 0,0 7,000,000 Total Regional CO2e reduction (Mg ) 0 ,00 20 7,2 5 6,4 GHG Reduction from Total Available Residues in 10 Years 6,000,000 5,000,000 4,000,000 ,0 00 4,7 00 0 ,00 70 3,8 0 ,00 70 3,7 1 3,000,000 2 2,8 0 ,00 0 ,12 0 ,00 00 3,4 0 0 0,0 0 ,00 60 1,2 0 ,00 0 87 1,000,000 0 ,00 60 1,9 2,000,000 Cariboo Kootenay-Boundary 0 ,00 00 1,4 0 00 ,00 00,0 1,5 50 1,4 00 0,0 58 0 - 0 ,00 10 3,5 Northeast Omineca Skeena South Coast Thompson-Okanagan West Coast (North) 00 0,0 62 00 0,0 62 West Coast (South) British Columbia Natural Resource Region Figure SI4-1. Total BC GHG emission reduction potential in the 9 natural resource regions (NRRs) with highlighted Cariboo NRR results matching Sample Calculation SI4-3 above. 208 Table SI4-2. Full breakdown of applied Oven Dried Mg (ODMg) of residues per merchantable m3. Columns are organized from referenced low to high AAC/THLB (Timber Harvest Land Base) ratio (m^3/Ha) (columns 3 and 4). All TSA’s in the far-right column were applied with the corresponding ‘biomass factor’ from column 2. TSA’s aligned on the right are from outside the Natural Resource Region from which the biomass factor (roadside slash residues) was applied. Timber Supply Area from known referenced data North Island (General region of former Strathcona TSA) Referenced and applied residue values from ‘biomass factor’ ‘Biomass factor’ (roadside slash residues) ODMg / Merchantable m³ 0.067 Corresponding AAC/THLB (m^3/Ha) ratio for roadside slash residues. (THLB not available due to change in TSA name and boundary) Williams Lake TSA 0.306 1.64 Kamloops TSA 0.0946 2.47 Quesnel TSA 0.110 2.55 Prince George TSA 0.148 2.72 100 Mile House TSA 0.159 2.91 Mackenzie TSA 0.147 3.00 Bulkley TSA 0.0726 3.01 Lake TSA 0.146 3.15 Fraser TSA 0.0642 4.96 Arrowsmith TSA (General 0.0628 5.83 region of former Southern Van Isl) Relating AAC/THLB (m^3/Ha) ratio TSAs to apply residue amounts from ‘biomass factor’ Not available Not available 9.55 2.10 GBR North TSA GBR South TSA Pacific TSA Haida Gwaii TSA 1.13 2.07 2.28 2.53 3.93 2.74 2.46 2.30 2.54 2.45 2.68 Fort Nelson TSA Fort St. John TSA Lillooet TSA Merritt TSA Okanagan TSA Boundary TSA Cranbrook TSA Invermere TSA Dawson Creek TSA Robson Valley TSA 2.88 Revelstoke TSA 0.94 2.93 1.35 Cassiar TSA Morice TSA Nass TSA 5.25 3.32 Kalum TSA Kispiox TSA 5.15 5.41 3.43 3.21 4.60 Arrow TSA Golden TSA Kootenay Lake TSA Soo TSA Sunshine Coast TSA Cascadia TSA Table SI4-3. Complete assessment of roadside slash residues for current amounts and in 10 years, with ratio for residues in 10 years shown. Ratio for residues in 10 years is also used for 209 the calculation of future sawmill residues (shown in Table SI4-3 below). Values presented in Oven Dried Mg and are presented before rounding and significant figures. Natural Resource Region Timber Supply Area (TSA) Annual Allowable Cut (m3) Current Total regional roadside slash residues available (ODMg/year) Ratio for residues in 10 years Total regional roadside slash residues available in 10 years (ODMg/year) Cariboo 100 Mile House TSA Quesnel TSA Williams Lake TSA 1,948,002 2,607,000 3,000,000 310,901 285,734 918,000 0.78 0.68 0.92 241,273 195,563 845,758 Kootenay-Boundary Arrow TSA Boundary TSA Cascadia TSA Cranbrook TSA Golden TSA Invermere TSA Kootenay Lake TSA Revelstoke TSA 500,000 670,142 402,818 808,000 485,000 496,720 640,000 225,000 73,750 63,395 25,861 76,437 70,907 46,990 93,568 35,910 0.87 0.16 1.11 0.16 0.29 0.16 0.29 0.78 64,373 10,427 28,763 12,572 20,820 7,729 27,474 27,868 Northeast Dawson Creek TSA Fort Nelson TSA Fort St. John TSA 1,860,000 1,625,000 2,115,000 175,956 497,250 647,190 0.16 0.92 0.92 28,941 458,119 596,260 Omineca MacKenzie TSA Prince George TSA Robson Valley TSA 4,500,000 8,350,000 363,559 661,500 1,231,625 53,625 0.93 0.87 0.87 616,468 1,075,029 46,807 Skeena Bulkley TSA Cassiar TSA Kalum TSA Kispiox TSA Lakes TSA Morice TSA Nass TSA 852,000 196,000 424,000 1,087,000 1,648,660 1,900,000 865,000 61,855 14,230 61,989 158,919 241,034 137,940 62,799 0.87 0.87 0.29 0.29 0.29 0.87 0.87 53,530 12,314 18,202 46,664 70,775 119,375 54,347 South Coast Fraser TSA Soo TSA Sunshine Coast TSA 1,241,602 480,000 1,204,808 79,711 30,816 77,349 1.11 1.11 1.11 88,656 34,274 86,029 Thompson-Okanagan Kamloops TSA Lillooet TSA Merritt TSA Okanagan TSA 2,300,000 570,000 1,500,000 3,078,405 217,580 53,922 141,900 291,217 0.16 0.16 0.16 0.16 35,787 8,869 23,339 47,898 West Coast (North) GBR North TSA GBR South TSA Haida Gwaii TSA North Island TSA (Former Strathcona) 803,000 830,500 512,000 1,248,100 53,801 55,644 17,955 83,623 1.04 1.04 1.04 1.04 55,923 57,838 18,663 Arrowsmith TSA (Southern Van Isl) Pacific TSA 348,000 21,854 0.90 19,568 865,700 58,002 7,190,738 Total Forestry Roadside Slash Residues Now (Mg) 1.04 60,290 5,303,504 Total Forestry Roadside Slash Residues In 10 years (Mg) West Coast (South) 86,921 210 Sample Calculation SI4-4. Sample calculation for Wood-residue requirements to displace petroleum coke (petcoke) at Lafarge Canada Inc in Richmond, BC. Values and sources for calculation: Annual Mg Cement Produced: 1,310,000 Source: Industryabout.com. (2014). Lafarge – Richmond Cement Plant. Industryabout.com. Last accessed Dec 26, 2018 at https://www.industryabout.com/country-territories-3/318canada/cement-industry/1076-lafarge-richmond-cement-plant Supported by Geocycle. (2018). Lafarge Richmond Kiln: Integral to BC and the Lower Mainland Waste Diversion. Coast Waste Management Association. Last accessed Dec 26, 2018 at http://cwma.ca/wp-content/uploads/2018/02/RPunja.pdf Snook, A. (2018). Doubling down: Lafarge increases low carbon fuel usage at Richmond, B.C. plant. Rocktoroad.com Last accessed Dec 26, 2018 at https://www.rocktoroad.com/aggregates/technology/doubling-down-5979 kg CO2e/Mg petcoke: 3,255 Source: From Project 2 CRS (2013). Petroleum Coke: Industry and Environmental. Petroleum Coke: Industry and Environmental Issues. Congressional Research Service. Authored by Andrews, A. and Lattanzio, R.K. October 29, 2013. Last accessed June 1, 2016 at http://www.nam.org/CRSreport/. kg CO2e/Mg Cement: 442.5 Source: From Project 2 Lafarge (2016). Personal email communication. Eric Isenor, Plant Manager, Kamloops Cement Plant, Lafarge Canada Inc. Feb 15, 216. Petcoke GJ/Mg: 33.05 Source: From Project 2 Indian Oil. (2016). Raw Petroleum Coke (RPC). Last accessed September 15, 2018 at https://www.iocl.com/Products/RawPetroleumCokeSpecifications.pdf Mg biocoal out / Mg wood waste in: 0.47 211 Source: From Project 1 BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. Biochar GJ/Mg: 29.6 Source: From Project 1, 2, 3 and 4 BC Biocarbon. (2015). Personal in person, email and phone communication. Marsh, P., chief technology officer and Kim, J.K., mechanical design engineer BC Biocarbon LTD. May 22 - Dec 31, 2015. kg CO2e 𝐺𝐽 𝑝𝑒𝑡𝑐𝑜𝑘𝑒 1 Mg Cement 𝑀𝑔 𝑀𝑔 𝐴𝑛𝑛𝑢𝑎𝑙 𝐶𝑒𝑚𝑒𝑛𝑡 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 ∗ ∗ ∗ kg CO2e 𝐺𝐽 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 𝑀𝑔 𝑏𝑖𝑜𝑐𝑜𝑎𝑙 𝑜𝑢𝑡 𝑀𝑔 𝑀𝑔 𝑃𝑒𝑡𝑐𝑜𝑘𝑒 𝑀𝑔 𝑤𝑜𝑜𝑑 𝑤𝑎𝑠𝑡𝑒 𝑖𝑛 = 𝐴𝑛𝑛𝑢𝑎𝑙 Mg original feedstock needs for Lafarge Richmond, BC 1,310,000 ∗ 442.5 33.05 1 ∗ ∗ = 423,064 (𝑝𝑟𝑒𝑟𝑜𝑢𝑛𝑑𝑖𝑛𝑔) 3,255 29.6 0.47 212