Greenhouse gas emission reduction potential and cost of bioenergy in British Columbia, Canada

Energy Policy 138 (2020) 111285

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Greenhouse gas emission reduction potential and cost of bioenergy in British Columbia, Canada Haoqi Wang a, Siduo Zhang a, Xiaotao Bi a, b, *, Roland Clift a, c a

Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall, Vancouver, BC, V6T 1Z3, Canada Clean Energy Research Centre, University of British Columbia, 2360 East Mall, Vancouver, BC, V6T 1Z3, Canada c Centre for Environment and Sustainability, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom b

A R T I C L E I N F O

A B S T R A C T

Keywords: Bioenergy Greenhouse gas reduction Life cycle assessment Economic assessment GHG abatement costs

The Canadian province of British Columbia (BC) provides an informative case study of bioenergy development, because it relies heavily on fossil fuels but has enormous bioenergy potential. We have examined the potential contribution of bioenergy to reducing BC’s GHG emissions. The approach of combining life cycle assessment and economic evaluation to prioritize options should be applicable generally. Biomass availability, including forestry resources, agricultural waste and municipal solid waste, is estimated. Through simplified Life Cycle Assessment, GHG reduction potential of biogas, bioethanol, biofuels from hydrothermal liquefaction, and district heating are quantified, along with the associated GHG reduction costs. The analysis shows that existing biomass resources could yield 110–176 PJ per year, reducing GHG emissions by 13.0–15.7%. Bioenergy from waste streams is already cost-effective and should be prioritized in the short term. However, bioenergy from forestry resources, especially conversion to liquid biofuels, is prohibitively expensive, with GHG reduction cost exceeding CAD $300/t CO2-eq. The total extra cost required to achieve full utilization of BC’s biomass resources is estimated as 0.8–2.4 billion dollars. To close the cost gaps between bioenergy and fossil fuels, both technological improve­ ment and external cost adjustment through measures like carbon taxation will be needed.

1. Introduction Canada is one of the most energy and carbon-intensive economies in the world (OECD, 2017). British Columbia (BC), the westernmost Ca­ nadian province, provides an informative case study to explore the po­ tential for bioenergy to contribute to mitigation of greenhouse gas (GHG) emissions. BC resembles other regions, notably the Nordic countries, in its low overall population density, with the population concentrated in a few large to medium-sized conurbations, large forested area with large stocks and arisings of lignocellulosic biomass, and aspiration to be a leader in combatting climate change. In 2016, BC had a total population of 4.65 million, 49% of it concentrated in the Greater Vancouver area and 13% in three smaller population centers in southern BC (Statistics Canada, 2019a). BC’s energy demand in 2016 was 1165 PJ, 38% as refined petroleum products (RPPs), 30% from natural gas, and the rest mostly from hydropower and biomass (National Energy Board, 2019). Of the RPPs, 94% are used in transportation, while 46% of natural gas is used for heating in residential and commercial buildings (Statistics Canada, 2019b). BC’s GHG emissions were 62.1

million tonnes (Mt) CO2-eq in 2017, of which almost 80% (47.6 Mt CO2) came directly from fossil fuel consumption (Environment and Climate Change Canada, 2019). In 2016, Canada ratified the Paris Agreement and committed to reduce national GHG emissions by 30%, from 738 Mt CO2-eq in 2005 to 516 Mt in 2030 (Environment and Climate Change Canada, 2017). BC’s updated Climate Action Plan (British Columbia, 2016a) sets a long-term GHG reduction target of 80% below 2007 levels, from 64.8 Mt in 2007 to 13.0 Mt in 2050 (Environmental Reporting BC, 2019). BC’s largest city, Vancouver, announced a target of eliminating fossil fuel consumption by 2050, by reducing total energy use from 59 PJ in 2014 to 38 PJ and transforming its energy profile (46% natural gas, 23% RPPs, and 31% renewable) to a fully renewable one in 2050 (60% electricity, mainly hydro, 15% district heating and cooling, 14% biofuels for transport, 10% biomethane, and 1% hydrogen) (City of Vancouver, 2015). The BC government has promoted a series of policies to displace fossil fuels used for heating and mobility, including a relatively high carbon tax: $35/t CO2-eq in 2018, increasing by $5/t CO2-eq annually to $50/t CO2-eq in 2021 (British Columbia, 2019a). The BC Low Carbon Fuel Standard currently requires 5% renewable content in gasoline and

* Corresponding author. Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall, Vancouver, BC, V6T 1Z3, Canada. E-mail addresses: [email protected] (H. Wang), [email protected] (S. Zhang), [email protected] (X. Bi), [email protected] (R. Clift). https://doi.org/10.1016/j.enpol.2020.111285 Received 25 July 2019; Received in revised form 11 January 2020; Accepted 14 January 2020 Available online 25 January 2020 0301-4215/© 2020 Elsevier Ltd. All rights reserved.

Energy Policy 138 (2020) 111285

H. Wang et al.

GHG GWP HTL IPCC LCA MPB MSP Mt ODT RPP WL WR WW

Abbreviations AAC AD AM BC CAD CR DH DM EtOH FM FW

Annual Allowable Cut Anaerobic Digestion Animal Manure British Columbia Canadian Dollar Crop Residues District Heating Dry Matter (Bio)Ethanol Fresh Matter Food Waste

4% in diesel (British Columbia, 2017), with plans to increase the stan­ dard for liquid fuels to 20% and introduce a requirement for 15% renewable natural gas by 2030 (British Columbia, 2018a). These policies generate incentives to use BC’s abundant but under-utilized biomass resources for bioenergy, including wood residues from logging and processing of lumber, crop residues, animal manure, and the organic fraction of municipal solid waste. Lignocellulosic materials can be combusted to provide district heating and displace natural gas con­ sumption, or converted to liquid biofuels to replace RPPs for transport. Agricultural and food wastes can be converted to biogas via anaerobic digestion to substitute for natural gas. The Intergovernmental Panel on Climate Change (IPCC, 2019) warned that cuts in GHG emissions must go beyond current interna­ tional commitments to limit global warming below 2 � C to avoid cata­ strophic losses for vulnerable people and societies. The economic cost will also escalate dramatically if actions are continually delayed (Nordhaus, 2016; Stern, 2007). Therefore, all technically feasible op­ tions must be evaluated based on GHG reduction potential and cost-effectiveness. This paper develops such an analysis to optimize exploitation of BC’s biomass; to the best of our knowledge, no such study has previously been reported. Firstly, the availability of all forms of biomass in BC is examined. A simplified life cycle assessment (LCA) is then conducted to investigate the GHG reduction potential of technol­ ogies to use biomass to displace natural gas and RPPs. A discounted cash flow model is used to calculate minimum selling prices for bioenergy products, enabling different options to be compared on the basis of GHG reduction cost, leading to recommendations on policies to prioritize and support the bioenergy sector in BC based on GHG reduction potential and cost-effectiveness. The approach of combining life cycle assessment and economic evaluation to prioritize options should be applicable generally.

Greenhouse Gas Greenhouse Warming Potential Hydrothermal Liquefaction (UN) Intergovernmental Panel on Climate Change Life Cycle Assessment Mountain Pine Beetle Minimum Selling Price Million tonne Oven-dry tonne Refined Petroleum Product Wood Logs Wood Residues Wood Waste

forest biomass is assumed to be 20 GJ/ODT (Natural Resources Canada, 2017), and the moisture content (MC) at source is assumed to be 50%. There are two categories of available forest biomass. The first is whole wood logs, including standing timbers within AAC but unhar­ vested due to economic and other reasons (Canadian Council of Forest Ministers, 2019), and dead trees infested with the mountain pine beetle (MPB). For MPB-infested trees, 750 Mm3 of timber in total will be affected (British Columbia, 2016b), of which 50% is considered unsal­ vageable for lumber (Eng et al., 2004). It is further assumed here that 50% of the unsalvageable MPB timber can be recovered for bioenergy production over the next 20 years; based on a density of 0.41 ODT/m3 (Industrial Forestry Service Ltd, 2015), this results in an estimated annual feedstock availability of 3.8 million ODT. The second category is wood residues, including harvest residues and sawmill residues. Harvest residues refer to branches and tops left on timber harvesting sites. Based on 64 Mm3 of timbers harvested in 2017 (Canadian Council of Forest Ministers, 2019), the estimated harvest residue/timber ratio of 11% (MacDonald et al., 2012), and the density of 0.41 ODT/m3, 2.9 million ODT of harvest residues were collectable annually. Excluding 0.5 million ODT of harvest residues (1.3 Mm3) used in pulp, chip, and pellet mills (British Columbia, 2019b), it is estimated that annually 2.4 million ODT of harvest residues are uncollected. Meanwhile, sawmill residues include sawdust, shavings and tree bark generated by timber processing at sawmills. Based on 47 Mm3 of timbers processed in BC sawmills in 2017 (British Columbia, 2019b), the esti­ mated sawmill residue/timber ratio of 36% (British Columbia, 2019b; McCloy and Associates Inc., 2006), and the density of 0.41 ODT/m3, it is estimated that 5.8 million ODT of sawmill residues were generated annually. Of sawmill residues, 4.2 million ODT (10.2 Mm3) were used in pulp and pellet mills (British Columbia, 2019b), with 1.8 million ODT of the wood pellets produced exported (British Columbia, 2018b). There­ fore, the unused sawmill residues are estimated to be 1.6 million ODT.

2. Methodology and data

2.1.2. Animal manure Livestock farming in BC generates 10.2 Mt of animal manure (AM) each year (Hofmann and Beaulieu, 2001; British Columbia, 2016c) ac­ counting for 82% of total organic waste (Electrigaz Technologies Inc.,

2.1. Biomass resources in BC 2.1.1. Forestry resource BC is rich in forestry resources. In 2017, 64 million cubic meters (Mm3) of timber were produced; the average harvest since 2010 is 67 Mm3 per year (Canadian Council of Forest Ministers, 2019). Meanwhile, the sustainability of forest management in BC is improving: by the end of 2016, 52 million hectares of forest in BC were under certified sustainable management, the largest area of any province in Canada and second only to Russia in the world (Certification Canada, 2018). Harvesting is limited to the Annual Allowable Cut (AAC), set by the BC government to regulate timber harvesting and allow for reforestation. As shown in Table 1, forest biomass in BC potentially available annually for bio­ energy production is estimated as 10.5 million oven-dry tonnes (ODT, assuming 0% moisture content). The higher heating value (HHV) of all

Table 1 Annual woody biomass potentially available for energy in BC. Amount (million ODT) Wood logs (WL) standing timbers within AAC MPB-infested trees Wood residues (WR) Harvest residues Sawmill residues Total

2

6.5 2.7 3.8 4.0 2.4 1.6 10.5

Source Canadian Council of Forest Ministers (2019) Estimated, see Section 2.1.1 Estimated, see Section 2.1.1 Estimated, see Section 2.1.1

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Energy Policy 138 (2020) 111285

2007), as shown in Table 2. Solid content of manure ranges from 8% to €rjesson, 2006; Shin et al., 2008; Wang et al., 30% (Berglund and Bo 2012a); in this study it is taken as 13%, the value for cattle manure (Nennich et al., 2005), leading to an estimate for the solid content of 1.3 million ODT.

Table 3 Annual crop residues (CR) availability in BC.

Barley Canola Corn Oat Spring wheat Total

2.1.3. Crop residues Crop residues (CR) refers to the parts of vegetative crops left after harvesting, which is a potential lignocellulosic biomass feedstock. Common field crops typically have residue/grain ratios no less than 1 (Kim and Dale, 2004). Field crops produced in BC are estimated to leave 449,000 ODT per year of crop residues (Table 3), at a moisture content of 7% with average HHV of 18 GJ/ODT (Zhang et al., 2015).

a b c

191.9 39.5 12.0 190.0 66.8 75.1 38.0 17.5

13,444 662 15,364 4321 8904 22,706 1358 1287

2580 26 184 819 595 1705 52 23

613

19

42 117

3835 363 10201 1300 (, 000 ODT)

31.5 c

91,320.0 3102.0c

Amount (, 000 ODT)

19.3 41.2 11.8 24.3 32

1.2 N/A 1 1.3 1.3

2.82 N/A 6.7 2.64 3.16

3.4 3c 6.7 3.4 4.1

61 115 74 78 122

3.5

449

128.6

Food Waste (FW) Wood Waste (WW)

Residential (, 000 wet tonne)

Nonresidential (, 000 wet tonne)

Total (, 000 wet tonne)

Total (, 000 ODT)

374 24

357 266

731 290

220 200

the system model. GHG emissions are expressed as CO2-equivalents, weighted by the 100-year GWP given in the Fourth Assessment Report of the IPCC (2007); CO2 from biogenic carbon is not included as a GHG (IPCC, 2011). The usual argument for ignoring biogenic CO2 is that the carbon is removed from the atmosphere by incorporation into the next gener­ ation of plants. In the specific case of waste forest biomass in BC, there is an additional argument leading to the same conclusion: if not recovered and used, the material is in any case burned so that it does not provide a fuel for wildfires (Clift et al., 2020). The assessment allows for the higher GWP of any biogenic carbon emitted as non-CO2 GHGs. 2.2.1. Feedstock supply The relevant life cycle of waste streams, specifically food waste, wood waste, animal manure, and crop residues, starts at the point where the waste is generated (Clift et al., 2000). Consequently, the supply chain includes waste collection and transportation, and additionally chipping for wood waste, as shown in Table 5. For wood residues, separate supply chains are assumed for roadside residues and sawmill residues. Roadside residues are assumed to be loaded from the harvest site in northern BC, chipped on site, and transported 750 km by rail and 45 km by heavy duty vehicle (HDV). Sawmill residues are taken to be recovered from sawmills, pelletized, and transported 180 km using HDV. The average GHG emissions from the supply chain of wood resi­ dues are then estimated based on the ratio between the two feedstocks in Table 2. For wood logs, the energy consumption of timber harvesting is accounted, and the rest of the supply chain is assumed to be the same as roadside residues.

Table 2 Annual animal manure (AM) generation in BC.

Beef cows Sheep & lambs Bulls Calves Heifers Dairy cows Boars & sows Grower & finishing pigs Nursing & weaner pigs Laying hens Turkeys Total Total dry weight

Residue yield (ODT/ha)

Table 4 Annual generation of organic fraction of municipal solid waste in BC.

In this work, we consider anaerobic digestion, gasification for district heating, thermochemical conversion to bioethanol, and hydrothermal liquefaction to biofuels, to replace natural gas, natural gas heating, gasoline, and liquid transport fuels, respectively. Note that coal is no longer used in BC. To evaluate the GHG reduction potential of these options, LCA is conducted. The functional unit as 1 GJ final bioenergy produced, either directly in the case of heat or from using derived bio­ fuels. For each bioenergy option, the system boundary includes two constituent sub-systems: the supply chain of the specific feedstock, and fuel or energy production using a specific conversion technology. Ma­ terials and energy sources displaced, in this case primarily fossil fuels replaced by bioenergy, are considered avoided burdens; i.e. credits (Clift et al., 2000),. Particularly for the biomass heating option, for which the final product is heat delivered with natural gas displaced, thermal effi­ ciency and emissions from biomass combustion are also included within

Total (, 000 wet tonne)

Grain yielda (t/ha)

British Columbia (2016c). b Kim and Dale (2004). c Yousefi (2009).

2.2. LCA models for bioenergy production in BC

Manure generation (kg/head/)b

Residue to Grain Ratiob

a

2.1.4. Organic fraction of municipal solid waste To facilitate recycling and divert waste from landfill, the BC gov­ ernment has been actively promoting organic waste sorting: by 2015, 64.3% of the provincial population was sorting its waste (British Columbia, 2018c). As of 2014, 2.72 Mt of municipal solid waste were generated in BC, of which 0.94 Mt came from residential sources and 1.78 Mt from non-residential sources (Statistics Canada, 2016). For residential waste, 40% was organic food waste (FW) and 2.6% was wood waste (WW). Non-residential waste, including construction waste, included 20% FW and 15% WW (BC Stats, 2010). Based on these data, it is estimated that 0.73 Mt of food waste and 0.29 Mt of wood waste are produced in BC annually; see Table 4.

Head (103)a

Hectaresa (, 000)

2.2.2. Anaerobic digestion (AD) Anaerobic digestion (AD) can be used to convert food waste, animal manure, and crop residues into biogas. The biogas typically contains 60% v/v methane (CH4) and 40% carbon dioxide (CO2) with other trace gases. The energy yield of the biogas is typically 12.4, 6.2 and 7.1 GJ/ ODT for food waste, animal manure and crop residues, respectively (Berglund and B€ orjesson, 2006). Methane itself is a strong GHG so that fugitive emissions are significant in assessing climate impacts; in this study, fugitive emissions are assumed to be 2% of the total CH4 produced (Evangelisti et al., 2015). Feedstock pretreatment is required to kill pathogens and increase digestibility. Sterilization is carried out in a heated and pressurized

British Columbia (2016c). Hofmann and Beaulieu (2001). Calculated by total mass of animals and average animal mass. 3

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Energy Policy 138 (2020) 111285

Table 5 Parameters for supply chains of waste streams and forest resources. MC Animal manure Crop residues Food waste Wood waste Roadside residue Sawmill residue Whole logs (chipped) a b c d e f g

87% a

7%

70%b 30% 50% 50% 50%

Collection

processing c

Transportation

HDV, 2 km

HDV, 50 km

4.7 L diesel/ ODTd MSW collection, 15 km HDV, 15 km

HDV, 50 km

0.82 L diesel/ODTe 0.82 L diesel/ODTe 3.5 L diesel/ ODTe

Table 6 Biogas yield and nutrient content of different AD feedstock.

Food waste Animal manure Crop residue

HDV, 50 km

a b

Chipping 1.3 L diesel/ODTe Chipping 1.3 L diesel/ODTe Pelletizing 490 MJe þ 24 MJ diesel þ6.2 MJ propane/ODTf Chipping 1.3 L diesel/ODTe

c

HDV, 50 km

d

Rail, 750 km þ HDV, 45 kmg HDV, 180 km

Biogas yield (GJ/ODT)

N (kg/ODT)

P (kg/ODT)

K (kg/ODT)

12.4a 6.2a 7.1a

31.6b 50.62c 8d

5.2b 7.63c 0.79d

9.0b 22.99c 6.9d

Berglund and B€ orjesson (2006). Zhang et al. (2007). Nennich et al. (2005). Hoskinson et al. (2008).

Table 7 Efficiencies and emission factors of heating from natural gas and biomass gasification.

Rail, 750 km þ HDV, 45 kmg

Zhang et al. (2015). Zhang et al. (2007). Berglund and B€ orjesson (2006). GHGenius ((S&T)2 Consultants Inc., 2013). Johnson et al. (2012). Pa et al. (2012). Sokhansanj (2015).

Parameters

Natural gasa

Biomassa,b

Efficiency, %

93%

CO2 (fossil), g/GJ fuel HHV CO2 (biogenic), g/GJ fuel HHV CH4, g/GJ fuel HHV N2O, g/GJ fuel HHV

59050 79.9 72.3 1.67

74% (crop residues) 79% (woody biomass) 0 91700 9.0 5.6

a b

€schl et al., 2010); other pretreatment processes include environment (Po grinding and mixing (Møller et al., 2009). The digestor also consumes energy, to maintain the digestion temperature. Generally, electricity and heat consumption in AD depends on the type of feedstock and digester; in this study, it is assumed that electricity and heat consumption are 11% and 13% respectively of the energy content of the biogas (Berglund €rjesson, 2006; Evangelisti et al., 2015). and Bo The digestate residue is rich in nutrients, and thus can be used as €ller and Müller, 2012), creating organic fertilizer and soil improver (Mo further environmental benefits by displacing synthetic fertilizers. The associated credits depend on the nutrient value (specifically the N, P and K content) of the digestate (Table 6). In this work, the avoided burdens from digestate application as fertilizer are calculated from the GHG in­ tensity of commercial fertilizers in the Ecoinvent database (Wernet et al., 2016).

Pa et al. (2011). Wernet et al. (2016).

bioethanol from corn and sugarcane, bioethanol from lignocellulosic feedstock can have significantly lower life cycle GHG emissions (Wang et al., 2012b). Generally, two pathways are available to convert ligno­ cellulosic feedstocks into bioethanol: thermochemical and biochemical. Thermochemical conversion can be applied to a wider range of feedstock than biochemical (Foust et al., 2009; Gonzalez et al., 2012; Mu et al., 2010). Therefore, thermochemical conversion is considered in this study. Process parameters for thermochemical bioethanol conversion are shown in Table 8. Biomass is air-dried and gasified to produce syngas, as in use for district heating (Section 2.2.3). The syngas is then cleaned up and catalytically synthesized into bioethanol and other higher alcohols. The entire conversion process is essentially autothermal, with heat and electricity provided within the process (Dutta et al., 2011); energy consumption and associated GHG emissions for ancillary operations such as in-plant transportation and engine start-up are negligible (Mu et al., 2010). Reported studies show a range of ethanol yield, from 310 to 460 l/ODT, with conversion efficiency, defined as the ratio between HHV of bioethanol product and feedstock, ranging from 45% to 49% (Bright and Strømman, 2009; Dutta et al., 2011; Mu et al., 2010). In this study, it is assumed that wet wood feedstocks are air-dried to 30% MC and then converted to bioethanol with efficiency 45% (Dutta et al., 2011). For crop residues, with lower feedstock MC, the overall conver­ sion efficiency is adjusted to 48%. The process generates no reported emissions of CH4, N2O or other non-CO2 greenhouse gases (Foust et al., 2009).

2.2.3. District heating (DH) Pellets and chips made from lignocellulosic feedstocks can be used as fuel. Since nearly 50% of energy consumption in heating in BC comes from natural gas (Statistics Canada, 2011), district heating using biomass can potentially bring significant GHG reductions by displacing natural gas consumption. Biomass can be converted to syngas, a gaseous mixture consisting primarily of H2, CO and CO2, by gasification. Gasification of wood or straw typically yields syngas with up to 85% of the HHV of the biomass1 (Ptasinski, 2008) and manageable emissions of air pollutants (Petrov et al., 2015). Syngas is then combusted to provide heating, displacing natural gas. Woody biomass typically has higher MC and is assumed to be air-dried to 30% MC to increase thermal efficiency. Overall thermal efficiencies, defined as the ratio between heat delivered and HHV of fuel, are assumed to be 79% and 74% for dried crop residues and woody biomass, respectively (Forest Products Lab, 2004). Emission factors are shown in Table 7.

2.2.5. Hydrothermal liquefaction Hydrothermal liquefaction (HTL) converts biomass into bio-oil, which can be further upgraded to liquid fuels, primarily for use in transport. HTL uses wet feedstock and therefore avoids the energy consumption for drying (Zhu et al., 2014). Typically, wet biomass feedstock is ground to fine particles and then fed to an HTL reactor, which operates at a temperature of 250–380 � C and pressure of 5–30 MPa (Zhu et al., 2014). The bio-oil produced is catalytically hydroge­ nated into a mixture of hydrocarbons, which is distilled to produce gasoline, diesel, jet fuel and heavy oil fractions. The energy required for the HTL process comes mostly from the biomass feedstock, but some electricity and heat must be imported to maintain operation. The hydrogen for hydrogenating the bio-oil is

2.2.4. Thermochemical bioethanol Ethanol (EtOH) from lignocellulosic biomass is considered a “second generation” biofuel. Compared to gasoline and first-generation

1 Ptasinski (2008) defines conversion efficiency in terms of LHV but, within the precision of the estimate, this figure also applies in terms of HHV.

4

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Energy Policy 138 (2020) 111285

2.3. Economic analysis

Table 8 Process parameters for thermochemical bioethanol production. Parameters

Value

Unit

1 1.7E-1 3.8E-2 9.8E-3 1.1E-3 2.2E-1 4.2E-2 3.9E-1

ODT kg kg kg kg kg kg kg

9.0 8.6

GJ/ODT GJ/ODT

4.2E-2a 15

m3 kg

The minimum selling prices (MSPs, in 2018 Canadian dollars) of bioenergy products required for the sector to be viable are calculated, to compare their economic performance. This study is specific to the cur­ rent BC context, with the principal assumptions and simplifications shown in Table 11. Baseline prices of liquid fossil fuels and natural gas are based on average commodity prices over 2017, and the price of natural gas heating is estimated based on a representative residential furnace.

a

Inputs Biomass Nickle, as catalyst MgO, as bed material Dimethyl ether Amine Sodium hydroxide Other chemicals Diesel Outputs Ethanol (HHV, for wood) Ethanol (HHV, for crop residue) Waste Wastewater Solid waste a

2.3.1. Capital cost Capital costs of different energy conversion technologies, including equipment and installation, are taken from literature and summarized in Table 12. All data are converted to 2018 Canadian dollars based on annual inflation rate of 2% and the average exchange rate over the relevant year (OzForex Ltd, 2018). Of the capital costs, 60% are assumed to be financed by loan, com­ pounded annually at an interest rate of 6.5% and paid in 10 years. Annual payment is calculated as follows:

Dutta et al. (2011).

derived from natural gas. Wastewater from the HTL process contains 30–40% of the total carbon input; it is processed by anaerobic digestion to recover energy (Tews et al., 2014; Zhu et al., 2014). Additionally, solid waste from the HTL process contains 0.5–2.8% of total carbon as biochar (Tews et al., 2014; Zhu et al., 2014) and 0.45% of total nitrogen (Wright et al., 2010); it can therefore potentially be used as a soil ad­ ditive to reduce use of synthetic fertilisers, sequestering carbon to improve soil productivity and also claim carbon credits. The main process parameters for HTL are shown in Table 9, based on projected plants of industrial scale with feed rate 2000 ODT/day and conversion efficiency 52%. The estimated volumetric yield is about 260 L/ODT (Zhu et al., 2014). Air emissions from the process itself are neglected, as no CH4 or N2O emissions are reported (Nie and Bi, 2018a; Tews et al., 2014). The emission factors for natural gas are taken from the GHGenius database ((S&T)2 Consultants Inc., 2013). The GHG in­ tensities of BC electricity, materials consumed, and nitrogen fertilizers displaced, are based on the Ecoinvent database (Wernet et al., 2016). The GWP impacts from the process itself and the avoided burdens are allocated between the different hydrocarbon products in proportion to their HHV.

L¼ ​

Inputs Biomass Natural gas Electricity Zeolite, as catalyst Dimethyl sulfide, as catalyst Na2CO3 buffer Outputs Biofuels (HHV, for wood) Biofuels (HHV, for crop residues) Biochar carbon credit Nitrogen credit Waste Wastewater Solid waste a b

Bioenergy conversion route

Feedstock

Fossil fuel replaced (Baseline)

Baseline GHG emission (kg/ GJ)

Baseline price ($/GJ)

AD

CR, FW, AM CR, WW, WR, WL CR, WW, WR, WL CR, WW, WR, WL

Natural gas

59

2.3c

Natural gas heating Gasoline

66b

12.8d

90

21.4e

Fossil hydrocarbon mixa

93

17.5e

EtOH

1 2.0a 160a 0.26b 0.28b 100a

ODT kg kWh kg kg kg

10.4 9.4 8.3 0.14

GJ GJ kg, carbon kg

1.4b 56

m3 kg

​

Table 10 Bioenergy feedstocks and conversion routes, and baselines for replaced fossil fuels.

DH

Unit

N

2.3.2. Production cost In this study, production cost includes feedstock cost and other operating and maintenance (O&M) costs. Supply chain parameters used to estimate feedstock cost are given in Table 13. Chips from wood logs

Table 9 Process input and output parameters for the HTL process. Value

P�r ​ ð1 ​ þ ​ rÞ

where: L ¼ annual loan payment, P ¼ initial loan principal, r ¼ the annual interest rate, and N ¼ years of loan term. Depreciation is determined by Canadian tax code Capital Cost Allowance (CCA) Class 43.2, which allows renewable energy projects to depreciate faster (Natural Resources Canada, 2013). In this tax code, annual capital depreciation is calculated using the declining balance method, at 25% rate in the first year and then 50% for the rest. Capital depreciation is deducted from the net revenue in the calculation of annual taxable income.

2.2.6. Greenhouse gas balances and mitigation Bioenergy conversion routes, feedstock useable, and fossil fuel replaced by each conversion route are summarized in Table 10. Burdens avoided by replacing liquid fossil fuels are calculated based on the GHGenius database ((S&T)2 Consultants Inc., 2013). Baseline GHG emissions from burning natural gas are taken from Pa et al. (2011).

Parameters

1

HTL

AM ¼ Animal Manure, CR ¼ Crop Residues, FW ¼ Food Waste, WL ¼ Wood Logs, WR ¼ Wood Residues, WW ¼ Wood Waste. AD ¼ Anaerobic Digestion, DH ¼ District Heating, EtOH ¼ Ethanol, HTL ¼ Hydrothermal Liquefaction. Figures for AD, EtOH & HTL refer to the biofuels; figures for DH refer to the heating service. a Average of gasoline, diesel, jet fuel and heavy oil. b Based on energy efficiency of 93%. c Average natural gas bulk price over 2017 in Canada (Canadian Gas Associ­ ation, 2018). d Average cost for an average household in BC using about 80 GJ per year (Statistics Canada, 2011): based on the furnace cost of $3600 (20 year lifespan) and the residential rate (carbon tax excluded) in BC of $8.4/GJ (FortisBC Energy Inc., 2018a). e Average fuel rack price over 2017 in Vancouver, tax excluded (Natural Re­ sources Canada, 2018).

Zhu et al. (2014). Tews et al. (2014). 5

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Energy Policy 138 (2020) 111285

Table 11 Major assumptions of economic model.

Table 13 Parameters used for estimating feedstock cost.

Parameter

Assumption

Financing by equity/debt Interest rate for debt financing Term of debt financing Real rate of return Annual inflation rate Depreciation Plant salvage value Construction period Plant life Corporate tax

40%/60% 6.5% annually 10 years 10% 2% CCA Class 43.2 (50% annual rate) 0% 3 years (8% Y1, 60% Y2, 32% Y3) 20 years 26%

Loading Crop residue harvesting Chipping HDV, forest resources HDV, waste streams Rail transportation

n X ðMSP t¼0

CP CI ð1 þ rÞt

CTÞt

Johnson et al. (2012) Stephen (2008) Johnson et al. (2012) Austin (2015) Austin (2015) Austin (2015)

3.1. GHG intensities of bioenergy Fig. 1 shows the GHG emissions per GJ associated with the different bioenergy options, including process emissions, avoided emissions, and net change in emissions resulting from the use of the biofuel. Process emissions include direct and indirect GHG emissions from bioenergy production. In general, biogas produced from AD of waste streams has higher process GHG emissions, with a significant contribution from fugitive emissions of methane during production. Amongst the tech­ nologies to convert lignocellulosic feedstocks, HTL in general generates higher process GHG emissions than district heating and bioethanol op­ tions. Additionally, it is evident that utilization of waste streams, i.e. wood waste and crop residues, leads to lower GHG intensity of derived bioenergy products than forestry resources. This is because forestry re­ sources are located in remote areas in BC, requiring long-distance transportation and thus generating higher GHG emissions along sup­ ply chains. To assess GHG reduction potential, the avoided emissions from byproduct utilization, such as digestate from AD and biochar from HTL, must be included as well as fossil fuels replaced. As shown in Fig. 1, for biogas options, GHG credit for the digestate is significant, especially for feedstocks with higher nitrogen content, such as animal manure and food waste, which displace substantial quantities of synthetic nitrogen fertilizers. In contrast, the contribution from utilization of biochar from HTL is relatively small. Comparing alternative technologies, the bio­ ethanol and HTL options lead to greater avoided emissions per GJ en­ ergy than biomass district heating, because the liquid fossil hydrocarbons are associated with higher GHG emissions than natural gas. With process and avoided emissions included, the performance of the possible biofuels is dominated by the avoided emissions for the fossil fuel replaced. AD of animal manure gives the greatest net GHG savings per GJ energy. However, AD of other materials and biomass district

2.3.3. Minimum selling price Based on the capital and production cost, Minimum Selling Prices (MSPs, in 2018 Canadian dollars) of bioenergy have been estimated using a discounted cash flow model. Essentially, this model calculates the minimum revenue and hence selling price of bioenergy required to set the Net Present Value (NPV) of the plant to zero after 20 years of operation. It is assumed that production cost and revenue of bioenergy increase at a constant inflation rate of 2%, and that the discount rate includes both real rate of return (10%) and inflation rate (2%). The model is defined as follows: Iþ

Reference

$5.3/ODT $31.7/ODT $7.1/ODT $0.13/tkm $0.13/tkm $0.032/tkm

3. GHG reduction potential from bioenergy

and pellets from sawmill residues are already commercial products. In this analysis, their costs are taken as the market price at the beginning of 2018: $210/t for chips (British Columbia, 2018d) and $160/t for pellets (Wood Pellet Association of Canada, 2018). For chips from roadside residues and other unused waste streams, it is assumed that the raw materials are available free of charge, so that feedstock costs cover only collection and transportation. Except for feedstock cost, other operating and maintenance (O&M) costs include variable components such as energy, chemicals, catalysts and waste handling, and fixed costs such as labor, maintenance, tax and insurance. Data from different literature sources have been converted to 2018 Canadian dollars and summarized in Table 12.

NPV ¼

Cost

¼0

where I ¼ initial investment, MSP ¼ minimum selling price, CD ¼ capital depreciation, CP ¼ production cost, CI ¼ interest, CT ¼ tax, n ¼ 20 years, and r ¼ discount rate (12% pa).

Table 12 Capital and operating costs of different bioenergy technologies. Year of data

Capacity (mGJ/year)

Capital cost (m$)

O&M Cost ($/GJ)

Source

AD

2011 2009 2005 2013 2009

7.43E-03 1.57E-01 7.00E-02 3.27E-03 3.95E-01

6.5E-1 13 4.9 3.5E-1 17

6.2 7.1 8.2 6.1 7.9

Nolan et al. (2012) Gebrezgabher et al. (2010) Krich et al. (2005)a Klavon et al. (2013)a Karellas et al. (2010)

DH

2008 2008 2008 2011

2.16 9.00E-1 3.60E-1 1.55E-1

43 20 8.7 11

1.1 1.1 1.1 1.5

B€ orjesson and Ahlgren (2010) B€ orjesson and Ahlgren (2010) B€ orjesson and Ahlgren (2010) Tallaksen and Kildegaard (2011)

EtOH

2007 2007 2010

6.00 6.00 6.00

690 480 160

6.8 7.2 3.1

Foust et al. (2009) Dutta et al. (2011) He and Zhang (2011)

HTL

2007 2014 2011 2018

6.93 6.93 6.93 3.29

680 440 430 300

12.0 7.4 5.7 16.2

Zhu et al. (2014) Tews et al. (2014) Knorr et al. (2013) Nie and Bi (2018b)

a

Average value.

6

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Energy Policy 138 (2020) 111285

Fig. 1. Process GHG emissions, avoided emissions, and net GHG saving of bioenergy options. AM ¼ Animal Manure, CR ¼ Crop Residues, FW ¼ Food Waste, WL ¼ Wood Logs, WR ¼ Wood Residues, WW ¼ Wood Waste. AD ¼ Anaerobic Digestion, DH ¼ District Heating, EtOH ¼ Ethanol, HTL ¼ Hydrothermal Liquefaction. Avoided emissions include GHG Credit from displacing fossil fuels for all bio­ energy options. For AD, displacing natural gas avoids emissions of 59 kg CO2eq/GJ; for HTL, displacing liquid hydrocarbons avoids emissions of 93 kg CO2eq/GJ. The remaining avoided emissions for these two options come from digestate and biochar, respectively.

Fig. 3. GHG reduction potential of bioenergy from waste streams and forestry resources in BC.

3.3. Total GHG reduction potential Fig. 3 shows the estimates for the potential GHG reduction for the various combinations of feedstocks and technologies, by multiplying the estimates for GHG mitigation potential per GJ bioenergy (Fig. 1) with bioenergy production potential (Fig. 2). Depending on the choice of bioenergy options, 8.3–10.0 Mt/year of GHG emissions can be mitigated if the biomass resources are fully utilized, corresponding to 13.0%– 15.7% of BC’s GHG emissions of 63.9 Mt in 2005 (Environment and Climate Change Canada, 2017). Potential GHG reductions are largely dependent on feedstock size. As potentially the largest feedstock flow, unharvested wood logs can displace 7.1%–8.0% of 2005 GHG emissions. Wood residues follow closely behind, potentially providing 4.5%–5.3% reduction. Compared to forestry resources, the potential reduction from each individual waste stream is much smaller, but in total these reductions amount to 2.0% below 2005 emissions. Comparing options using the same feedstock, DH has lower GHG savings per GJ than HTL or EtOH (see Fig. 1) but nonetheless leads to higher potential GHG reductions due to its higher overall energetic ef­ ficiency. Therefore, given the limited availability of biomass resources, DH should be the preferred bioenergy option to maximize GHG re­ ductions, where conditions such as dense population and properly insulated heat pipe networks can be met. As 2.9 million of BC’s popu­ lation inhabit four metropolitan areas (Statistics Canada, 2019a), ample opportunities for biomass-fired DH systems should exist.

heating (DH) give lower GHG savings than bioethanol production and hydrothermal liquefaction (HTL), primarily due to higher avoided emissions from replaced fossil hydrocarbons. 3.2. Bioenergy production potential Fig. 2 shows the potential for bioenergy production for the different options, based on the estimates for feedstock availability in section 2.1. Most of the bioenergy potential in BC is represented by unharvested wood logs, followed by wood residues. For each feedstock, bioenergy production potential is affected by the overall efficiency of the tech­ nology selected: DH has higher overall energy efficiency than HTL or EtOH and can produce more useable energy. For crop residues, DH also shows significantly higher efficiency than AD. Based on the range of yields of the technologies applicable to each feedstock, it is estimated that in total 110–176 PJ of bioenergy could be produced annually from all available biomass resources in BC. Based on BC energy consumption in 2016, full utilization of biomass feedstock identified in this study can potentially meet up to 15% of total energy demand, displacing nearly 22% of fossil fuel consumption. As bioenergy potential identified in this study is far from enough to meet the total energy demand, it is crucial to utilize limited biomass resources as effectively as possible.

Fig. 2. Bioenergy production potential from waste streams and forestry re­ sources in BC.

Fig. 4. Comparison of bioenergy process GHG emissions with litera­ ture estimates. 7

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Energy Policy 138 (2020) 111285

3.4. Comparison with previous studies

their fossil fuel counterparts and therefore should already be economi­ cally profitable. However, MSPs for most other options are notably higher than current fossil fuel prices, indicating that additional financial support would be necessary. It is particularly significant that biogas, which is specifically advocated by the government of BC in its Climate Leadership Plan (British Columbia, 2016a), has the greatest price disadvantage, resulting from the low price of natural gas. Full utilization of crop residues and wood waste can lead to annual economic savings up to 46 million dollars a year. However, full utili­ zation of wood logs (WL) will lead to annual extra cost of at least 690 million dollars, whereas processing food waste and animal manure (AM) via AD will generate additional annual extra costs of 240 million dollars. The aggregated annual cost for full utilization of the bioenergy potential is estimated as 0.8–2.4 billion dollars.

To validate the estimated GHG intensities of different bioenergy options in BC, our results have been compared with those from other peer-reviewed studies (Fig. 4), specifically estimates of process GHG emissions associated with bioenergy production from forestry resources and waste streams, excluding dedicated energy crops. Mean values are represented by blocks in Fig. 4, with minimum and maximum values represented by error bars. For lignocellulosic feedstocks, HTL has the highest process GHG emissions per GJ, followed by EtOH and finally DH; this ranking is consistent with literature studies. For anaerobic digestion of waste streams, the results from this study also accord with previous studies. However, our minimum estimates are generally lower than literature values for the DH, EtOH and HTL options. This may be explained by differences in feedstock procurement. The minimum values in our re­ sults represent bioenergy from crop residues and wood waste, while most literature studies have investigated wood chips and whole logs; waste streams tend to have shorter supply chains than forest resources, so that conversion to bioenergy is associated with lower process emis­ sions. On the other hand, the maximum values in our results, which represent bioenergy produced from whole wood logs, are consistent with literature values.

4.2. GHG reduction cost To compare the cost effectiveness of potential ways to exploit biomass resources, the GHG reduction cost is defined as the additional cost (in 2018 Canadian dollars) divided by the associated reduction in total GHG emissions, expressed as $/tCO2-eq. Bioenergy options with lower GHG reduction costs are more cost-effective and should be prioritized. GHG reduction costs can also be interpreted as the level of carbon price required to offset the additional cost of bioenergy and thereby promote its use. Fig. 6 shows the estimates for GHG reduction potential (in tonne CO2-eq) and total extra cost (in 2018 Canadian dollars) for the various fuels and technologies. The GHG reduction costs are given by the gradients of the lines from the origin to the datapoints. In general, DH has the lowest GHG reduction cost for any feedstock, followed by EtOH and HTL. AD options have the highest GHG reduction costs, even though they are highly effective in reducing GHG emissions per GJ energy. Using the foreseeable pan-Canadian carbon tax of $50/tCO2-eq as reference (Government of Canada, 2017), we argue that bioenergy op­ tions should be categorized by their GHG reduction costs: negative, low ($0–50/tCO2-eq), moderate ($50–100/tCO2-eq) and high (>$100/tCO2-eq). Bioenergy production from crop residues and wood waste mostly show negative to low GHG reduction costs, and thus should already be pursued on both economic and environmental grounds. The next group of options are bioenergy produced from wood residues (WR), for which the GHG reduction costs range from negative to high. DH should be prioritized to utilize wood residues due to its cost-effectiveness in GHG mitigation. However, with currently foresee­ able technology, liquid biofuel production is associated with much higher costs and therefore would require much stronger policy inter­ vention to be viable. AD of waste streams and bioenergy production from wood logs fall into the category of high GHG reduction costs. However, it can be argued that AD should still be pursued, for two main reasons: (1) AD brings other environmental benefits via waste reduction and improved €rjesson and Berglund, 2007; Evangelisti et al., nutrient management (Bo 2014); (2) the total amount of feedstock is small, so total extra cost is limited. For wood logs, liquid biofuel options are currently not economically feasible, in view of the size of the feedstock and high GHG reduction cost. DH is the most cost-effective use for wood logs, but is still expensive and should only be considered once waste streams and wood residues are fully utilized.

4. Economics of bioenergy 4.1. Minimum selling price Fig. 5 summarizes the estimated Minimum Selling Prices (MSPs) for the different bioenergy options, in 2018 Canadian dollars. District heating (DH) options are in general the least expensive, whereas liquid biofuels, specifically bioethanol (EtOH) and Hydrothermal Liquefaction (HTL) fuels, are much more expensive. For biogas produced by AD, the MSP lies between DH and liquid fuels. Economic viability of bioenergy is also critically dependent on the feedstock. AD of food waste (FW) results in the lowest biogas MSP. For other options including DH, EtOH and HTL, bioenergy produced from waste streams shows obvious price ad­ vantages over forestry resources, due to lower feedstock costs. To evaluate the competitiveness of bioenergy, extra costs are calcu­ lated as the MSP of the bioenergy minus the base price of the fossil fuel displaced (Fig. 5). Positive extra costs represent the cost gap to be filled by investors, government and consumers to support the deployment of bioenergy, whereas negative extra costs indicate margins available by selling bioenergy at current market prices. It is evident that DH and EtOH from wood waste (WW) and crop residues (CR) are cheaper than

4.3. Sensitivity analysis Literature data and assumptions used in this study are subject to uncertainty. Average values of technical and economic data reported in the past decade were used, and simplified models, especially for the supply chains of biomass, were adopted. To test the robustness of our conclusions on GHG reduction costs, a sensitivity analysis has been carried out on the factors with highest potential uncertainty or impact

Fig. 5. Minimum Selling Prices of bioenergy options and comparison with baseline energy prices. AM ¼ Animal Manure, CR ¼ Crop Residues, FW ¼ Food Waste, WL ¼ Wood Logs, WR ¼ Wood Residues, WW ¼ Wood Waste. AD ¼ Anaerobic Digestion, DH ¼ District Heating, EtOH ¼ Ethanol, HTL ¼ Hydrothermal Liquefaction. 8

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Energy Policy 138 (2020) 111285

Fig. 6. Total GHG reduction, annual extra cost and GHG reduction cost of bioenergy options.

bioenergy feedstocks could rise as future demand for bioenergy in­ creases, while increased tipping fees for wastes could lower the effective cost of that feedstock. Our results show that price fluctuation of �$2/GJ ($12/barrel crude oil, $0.07/L refined petroleum products, or $0.08/m3 natural gas) in fossil fuels or �$20/ODT in bioenergy feedstock has higher impact on GHG reduction cost of bioenergy than variation of 20% in capital or operating costs. However, uncertainty in feedstock trans­ portation distances of �50/km has nugatory impact, except for feed­ stock with high moisture content such as animal manure and food waste. Overall, variation in any single factor does not change the conclu­ sions on the cost-effectiveness of bioenergy and the ranking of different options. Barring unforeseeably large and unfavorable variations in several factors, bioenergy options with negative GHG reduction costs will remain viable. On the other hand, promoting bioenergy options with high GHG reduction costs, such as HTL of forestry resources and AD of waste streams, will continue to require major (and probably unpop­ ular) policy measures, such as a carbon tax in excess of $100/tCO2-eq.

Table 14 Parameters used for sensitivity analysis of GHG reduction costs of bioenergy. Category

Parameter

Variation

Bioenergy costs

Capital cost (CAP) Operating cost (OP) Feedstock price (Feed) Baseline energy price (Baseline) Feedstock transportation distance (Trans) Bioenergy GHG intensity (GHG) Bioenergy conversion efficiency (Efficiency)

�20% �20% �$20 �$2 �50 km �20% �10%

Commodity prices Bioenergy production

(Table 14). In general, GHG reduction costs of AD are much more sus­ ceptible to data uncertainty than those of other bioenergy options (Fig. 7). Bioenergy conversion efficiency shows the most significant impact on almost every bioenergy option, because energy yield affects both the possible displacement of fossil fuels and the revenues from bioenergy products. This implies that improvement of conversion efficiency is the key to improving the economics of bioenergy. Variations in capital and operating costs have rather less impact, while variation in process GHG emissions has negligible impact on cost-effectiveness of bioenergy, except for HTL of forestry resources and AD of waste streams because HTL and AD have higher process GHG emissions, due to long-distance transportation and fugitive methane emissions, respectively. Another important uncertainty lies in the prices of bioenergy feed­ stocks and fossil fuels. As the crude oil price has fluctuated widely over the past 5 years, its future price will make the economic prospect of liquid biofuels highly uncertain. To add to this uncertainty, the prices of

5. Discussion 5.1. Prospects for technological improvement Due to limitations on the availability of biomaterials, BC’s abundant yet expensive forestry resources will eventually become indispensable to its low-carbon energy aspirations. This leads to the question of whether it is possible to reduce the cost gap between biofuels and low-priced fossil fuels. As an emerging energy technology, biofuel production from lignocellulosic feedstock mostly remains at experimental or pilot stage but with good prospects for both technical and economic 9

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Energy Policy 138 (2020) 111285

Fig. 7. Sensitivity analysis on GHG reduction cost of bioenergy options.

improvements. As shown in Section 4.3, conversion efficiency is the most crucial factor to improve cost-effectiveness of bioenergy. Many possibilities to improve efficiency have been identified. For example, biogas yield from anaerobic digestion (AD) can be enhanced through pretreatment (Ma et al., 2011; Zhang et al., 2014) and co-digestion (Cavinato et al., 2010; Ward et al., 2008), and bioethanol (EtOH) yield can be improved by as much as 50% by advanced pretreatment and energy recovery (Spatari et al., 2010). For biofuels from Hydrothermal Liquefaction (HTL), Zhu et al. (2014) predicted that the overall energy conversion efficiency can be increased from 42% to 66% as upgrading technology improves. However, given that the inputs and energy out­ puts have relatively low value, improved processes must remain simple and cost-effective. The overall system efficiency can also be improved by more effective use of byproducts. As shown in Fig. 8, byproduct credits, specifically digestate, wastewater, and biochar, contribute considerably to the GHG reduction potential of selected bioenergy technologies. For AD, nutrientrich digestate can displace synthetic fertilizers, whose production is

resource-intensive. If BC’s food waste and animal manure resources can be fully utilized by AD, the total nitrogen, phosphorus, and potassium contents in digestate are estimated to be 74000, 11000, and 32000 tonnes, respectively. For HTL, while carbon credit from biochar is relatively small, methane recovery from the wastewater significantly reduces reliance on external energy. Similarly, byproduct utilization can also generate extra revenue. Thus, identification of possibilities for process integration and value-added byproducts, such as CO2 integra­ tion with greenhouse operation and algae production (Uggetti et al., 2014; Zhang et al., 2013), can play a key role in further improving the cost-effectiveness of bioenergy. From a policy perspective, it is crucial to maintain the momentum of technology development and deployment for bioenergy systems via financial support, in hope of achieving further cost reduction. Historical data for many renewable energy systems show that as technology ma­ tures over time, energy affordability improves steadily. For example, the unit cost of solar PV has seen a 5–7% annual price decrease since 1998 (Feldman et al., 2012); from 2010 to 2014, its unit cost decreased by 44–52% while the cumulative installed capacity increased by 360% (IRENA, 2015). Similarly, the unit cost of onshore wind power decreased by 7–12% from 2010 to 2014 while cumulative capacity increased by 81% (IRENA, 2015). 5.2. Possible impacts of policy measures To evaluate the actual cost gap between fossil fuel and bioenergy, we have excluded policy factors from the cost model set out above. How­ ever, as the BC provincial and Canadian federal governments continue to promote deeper GHG reduction targets, new policies in favor of bio­ energy are being enforced to lower the cost barrier. In terms of liquid biofuel support, BC’s Low Carbon Fuel Requirement has a credit transfer system, currently at a trading price of $170/tCO2 (British Columbia, 2018e). For renewable natural gas, distributors in BC offer a premium RNG purchasing price up to $30/GJ (FortisBC Energy Inc., 2018b). In 2018, BC’s carbon tax was $35/tCO2 on consumption of fossil fuels. In addition, transport fuels in BC are subject to provincial motor fuel tax and federal excise tax, which amount to $1.6/GJ, $7.9/GJ and $10.2/GJ for jet fuel, diesel and gasoline, respectively (British

Fig. 8. GHG credit from byproduct utilization. AM ¼ Animal Manure, CR ¼ Crop Residues, FW ¼ Food Waste, WL ¼ Wood Logs, WR ¼ Wood Residues, WW ¼ Wood Waste. AD ¼ Anaerobic Digestion, HTL ¼ Hydrothermal Liquefaction. 10

H. Wang et al.

Energy Policy 138 (2020) 111285

Columbia, 2018f; Government of Canada, 2018). Because biodiesel and bioethanol are not exempted from any tax, tax exemption could provide a legislatively simple option to promote biofuels. On the other hand, fuel tax for natural gas is as low as $0.6/GJ, because the BC government sees natural gas as preferable to other more GHG-intensive fossil fuels and plans to expand the natural gas sector in the province (British Columbia, 2016a). Fig. 9 compares these possible fiscal adjustments with the extra costs of selected bioenergy options with the highest GHG-reduction costs, in 2018 Canadian dollars. For natural gas used for heating, the current feed-in-tariff (FiT) for renewable natural gas should be sufficient to cover the extra cost of biogas. However, there are no policy measures to promote biomass-fired district heating, despite its low GHG reduction costs. For road transportation, the low carbon fuel credit alone fails to close the cost gap between liquid biofuels produced from premium forestry resources and fossil fuels, which means that other policy mea­ sures, such as tax exemption, would be required. In summary, the BC government needs to go beyond its current policy measures to support the production and use of bioenergy for mobility and heating. Even though biomass-fired district heating is the most cost-effective approach for GHG abatement, current fiscal in­ centives may attract investors towards other bioenergy options that have higher extra costs but appear to be seen as higher policy priority and receive more fiscal support. Therefore, to achieve cost-effective GHG abatement, financial support should also extend to biomass-fired district heating systems, for example in the form of capital grants and/ or accelerated depreciation. This is particularly important to promote the use of premium wood logs for heating.

costs. There are also limitations on the supply of other waste streams. Collection of food waste and wood waste depends on whether regula­ tions on diverting organic wastes from landfills are enforced. By 2015, such regulations had been imposed on urban areas with 64.3% of BC’s population (British Columbia, 2018c). However, as the remainder of BC’s population is scattered across the province, collection and trans­ portation of its organic wastes are more costly and energy intensive. For the livestock industry, 43% of cattle manure in Canada is left on pasture lands (FAO, 2018). Based on this ratio and the generation of cattle manure in BC (Table 3), about 2.5 million wet tonnes of cattle manure, i. e. 25% of the maximum available animal manure, is scattered on pasture lands and thus difficult and costly to collect. The remaining 75%, which represents cattle manure generated in barns and all the poultry manure, is easier to manage. Crop residues from 12% of cropped areas in BC are currently bailed (Statistics Canada, 2019c) for on-farm uses such as bedding and animal feed. Meanwhile, from a sustainability perspective, at least 0.75 ODT/ha of crop residues must be retained on the fields to prevent soil erosion (Stephen, 2008; Stumborg et al., 1996). These data imply that roughly 70% of the maximum recovery potential for crop residues can be collected as bioenergy feedstock, without conflicting with current uses or compromising soil quality. In summary, 50–75% of the forms of biomass investigated in this study can be considered as easily accessible and described by the anal­ ysis of environmental and economic performances for bioenergy use set out here. Collection and use of the remaining potential biomass resource depend not only on economic feasibility but also on the relationships between actors in the forestry sector and governance of their activities. How these materials can be sustainably and economically collected and utilized remains to be explored in future studies.

5.3. Limitations on the cost and supply model

5.4. Global context

The estimates of biomass availability in this study represent the maximum resource recovery potential. However, the actual biomass supply for energy production and the resulting GHG reduction are affected by economic, accessibility, and conservation factors. For example, the recovery of MPB-killed trees and harvest residues is con­ strained by economic feasibility, as these materials can be far away from roads and thus difficult to access. Data for the whole of BC are not available, but results for specific areas show that 50–70% of residual biomass from logging is recovered to the roadside; collection costs range from $50 to $170/ODT, with $80–90/ODT as the median range (FPIn­ novations, 2019, 2018a; 2018b). In comparison, the feedstock cost of wood residues used in this study is $90/ODT. Therefore, while easily-accessible wood residues should be cheaper than the estimate in this study, using less accessible feedstocks would impose much higher

The potential for exploitation of bioenergy depends on regional or national energy profiles. As in BC, most developed economies in the North Temperate Zone have intensive fossil fuel consumption for heat­ ing and mobility, including US, most European countries, and other Canadian provinces. Our finding that biomass district heating (DH) is more effective in GHG mitigation and cost than liquid biofuels is generally applicable, because it arises from biomass DH’s inherent ad­ vantages of lower capital investment and higher conversion efficiency. Especially for economies still reliant on coal for heating, biomass DH can achieve even higher GHG mitigation. This conclusion is supported by the example of the Nordic countries, specifically Denmark, Finland and Sweden. These countries share many characteristics with BC: compa­ rable population, high proportion of renewable electricity supply, and traditionally high proportion of fossil fuels for heating (European Union, 2018; IEA, 2019). In these countries, the market share of biomass DH has already grown, to surpass the use of fossil fuels (European Union, 2018; Werner, 2017), confirming the validity of this bioenergy development model for BC. On the other hand, in lower latitude and tropical countries where heating demand is low, it is more reasonable to pursue other bioenergy options. For example, the Central American country Costa Rica is similar to BC in terms of rich forestry resources and hydropower capacity. While almost half of the country’s energy supply comes from renewable sources, the other half is predominantly RPPs (IEA, 2019). In this case, conversion to liquid biofuel could be a suitable option for domestic utilization of biomass. Electricity generation from biomass within BC has not been consid­ ered in this paper, because the province has abundant hydropower ca­ pacity. However, elsewhere, such as in the US, China, and BC’s adjacent province of Alberta, where electricity generation from coal is still prevalent, electricity generation from biomass can be a viable and competitive option, meriting investigation. Substantial quantities of wood pellets are already exported from BC, for use in electricity

Fig. 9. Comparison of policy adjustment to offset costs of replacing fossil fuels by bioenergy. AM ¼ Animal Manure, FW ¼ Food Waste, WL ¼ Wood Logs. AD ¼ Anaerobic Digestion, DH ¼ District Heating, EtOH ¼ Ethanol, HTL ¼ Hydrothermal Liquefaction. 11

H. Wang et al.

Energy Policy 138 (2020) 111285

generation. Notwithstanding the processing and large transport dis­ tances, this practice is economically and environmentally attractive (Yun et al., 2019). Another global uncertainty arises from regional fossil fuel prices and taxes, which affects the relative economic prospects for bioenergy. Pri­ ces of natural gas and RPPs depend in part on fiscal policies which vary across jurisdictions, giving rise to differences in the GHG reduction costs of biomass-fired DH and liquid biofuels. In Europe, fossil fuel prices are much higher than in BC and elsewhere in Canada, largely due to gov­ ernment taxes (British Columbia, 2018f; European Commission, 2018; Government of Canada, 2018). Such high energy taxes help to close the cost gap between bioenergy and fossil fuels, to create a favorable envi­ ronment for bioenergy development (and to encourage international trade in commodity biofuels such as wood pellets). However, as shown in Section 4.3, it is highly unlikely that local differences in fossil fuel prices will be large enough anywhere to make liquid biofuels more cost-effective than biomass-fired DH.

Author contribution Haoqi Wang: Data curation, Methodology, Formal analysis, Visu­ alization, Writing - Original Draft. Siduo Zhang: Resources, Writing - Original Draft. Xiaotao Bi: Conceptualization, Funding acquisition, Supervision, Writing – Review & Editing. Roland Clift: Supervision, Writing – Review & Editing. Declaration of competing interest None. Acknowledgement The authors are grateful to Pacific Institute for Climate Solutions (PICS), Natural Sciences and Engineering Research Council (NSERC), and UBC Graduate and Postdoctoral Studies for financial support.

6. Conclusions and policy implications

References

This study seeks to analyze the potential production and use of bioenergy in the Canadian province of British Columbia (BC). BC is an instructive case because it aspires to achieve major reductions in GHG emissions and has an enormous bioenergy potential, but also has sig­ nificant barriers to full exploitation of bioenergy. Full exploitation of the available resource could reduce GHG emissions in the province by 8.3–10.0 Mt annually, corresponding to 13.0%–15.7% of GHG emissions in 2005. Many bioenergy options from waste streams are already economically feasible. However, potential development of the bio­ energy sector in BC faces two main challenges: (1) bioenergy supply is limited compared to the potential for fossil fuel replacement, and (2) production of bioenergy from forestry resources, the largest bioenergy feedstock in BC, is currently prohibitively expensive. Under current conditions, biomass-fired district heating is the most effective option in both GHG mitigation and cost, and thus should be prioritized over conversion to liquid biofuels. For the same reason, waste streams should be prioritized over forest resources. In the longer term, technological improvement in bioenergy production can potentially lower the GHG reduction cost. Government support for research, development and deployment of bioenergy technologies is needed, with subsidies used as stimulants to incubate the technology and enable the bioenergy market and industry to develop together. There is also a role for government in facilitating the use of byproducts from bioenergy production, such as digestate, biochar, and wastewater, to further improve the environmental benefits. Due to data uncertainty and the use of simplified models, the estimates for biomass availability, potential GHG reduction, and total extra cost obtained in this study may differ from their true values under current conditions but the ranking and prioritization of different bioenergy options will remain valid. Based on the environmental and economic performance of bioenergy options, a three-step deployment strategy is recommended. The first step is to prioritize bioenergy production from waste streams, which can reduce GHG emissions by 2.0% below 2005 level at the lowest cost. The second step is to exploit the energy potential in wood residues, and to support district heating projects using more expensive forestry re­ sources; full implementation can contribute at least another 4.5% GHG reduction. With additional financial help from government, these bio­ energy options from forestry resources can become more affordable, while at the same time help the bioenergy industry and market to mature. The third step is longer term: to fully utilize the abundant yet expensive forestry resources in BC. This will be essential to meeting long-term GHG reduction target in BC and Canada, but will require further technology development as well as stronger and more targeted support from policies such as more stringent renewable fuel mandate and higher carbon pricing.

Austin, D., 2015. Pricing Freight Transport to Account for External Costs. Retrieved from. https://www.cbo.gov/publication/50049. Berglund, M., B€ orjesson, P., 2006. Assessment of energy performance in the life-cycle of biogas production. Biomass Bioenergy 30, 254–266. https://doi.org/10.1016/j. biombioe.2005.11.011. B€ orjesson, M., Ahlgren, E.O., 2010. Biomass gasification in cost-optimized district heating systems-A regional modelling analysis. Energy Policy 38, 168–180. https:// doi.org/10.1016/j.enpol.2009.09.001. B€ orjesson, P., Berglund, M., 2007. Environmental systems analysis of biogas systems—Part II: the environmental impact of replacing various reference systems. Biomass Bioenergy 31, 326–344. https://doi.org/10.1016/j.biombioe.2007.01.004. Bright, R.M., Strømman, A.H., 2009. Life cycle assessment of second generation bioethanols produced from scandinavian Boreal forest resources a regional analysis for middle Norway. J. Ind. Ecol. 13, 514–531. https://doi.org/10.1111/j.15309290.2009.00149.x. British Columbia, 2016a. Climate Leadership Plan. British Columbia, 2016b. Mountain Pine Beetle Infestation Model V13. British Columbia, 2016c. Fast Stats 2015 - British Columbia’s Agrifood and Seafood Sector. British Columbia, 2017. Renewable and Low Carbon Fuel Requirement Regulation. British Columbia, 2018a. CleanBC. Retrieved from. https://www2.gov.bc.ca/assets/ gov/environment/climate-change/action/cleanbc/cleanbc_2018-bc-climate-strate gy.pdf. British Columbia, 2018b. 2017 economic stare of the BC forest sector. Retrieved from. htt ps://www2.gov.bc.ca/assets/gov/farming-natural-resources-and-industry/forestry /forest-industry-economics/economic-state/2017_economic_state_of_bc_forest_sector -with_appendix.pdf. British Columbia, 2018c. Waste management [WWW Document]. Obtained from. . htt ps://www2.gov.bc.ca/gov/content/environment/waste-management/recycling/org anics. British Columbia, 2018d. British Columbia Forest Industry - Prices for Selected Products. Retrieved from. https://www2.gov.bc.ca/assets/gov/farming-natural-resourcesand-industry/forestry/forest-industry-economics/weekly-prices/weekly-price-report _2018-1-5.pdf. British Columbia, 2018e. In: Renewable and Low Carbon Fuel Requirements Regulation Low Carbon Fuel Credit Market Report Information Bulletin RLCF-017. Retrieved from. https://www2.gov.bc.ca/assets/gov/farming-natural-resources-and-industr y/electricity-alternative-energy/transportation/renewable-low-carbon-fuels/rlcf017.pdf. British Columbia, 2018f. Tax Rates on Fuels. Tax Bulletin MFT-CT 005. British Columbia, 2019a. British Columbia’s carbon tax [WWW Document]. Retrieved from. . https://www2.gov.bc.ca/gov/content/environment/climate-change/plannin g-and-action/carbon-tax. British Columbia, 2019b. Major Primary Timber Processing Facilities in British Columbia - 2017. Canadian Council of Forest Ministers, 2019. National forestry database [WWW Document]. URL. http://nfdp.ccfm.org/en/. Cavinato, C., Fatone, F., Bolzonella, D., Pavan, P., 2010. Thermophilic anaerobic codigestion of cattle manure with agro-wastes and energy crops: comparison of pilot and full scale experiences. Bioresour. Technol. 101, 545–550. https://doi.org/ 10.1016/j.biortech.2009.08.043. Certification Canada, 2018. Forest management certification in Canada - 2017 Year-end statistics [WWW Document]. URL. http://certificationcanada.org/en/statistics/pro vincial-statistics/. City of Vancouver, 2015. Renewable City Strategy 2015-2050. Clift, R., Doig, A., Finnveden, G., 2000. The application of life cycle assessment to integrated solid waste management: Part 1 - methodology. Trans IChemE 78, 279–287. https://doi.org/10.1205/095758200530790.

12

H. Wang et al.

Energy Policy 138 (2020) 111285

Clift, R., Bi, X., Wang, H., Yun, H., 2020. Chapter 4 of Section 4: prioritising uses for waste biomass: a case study from British Columbia. In: Sikdar, S.K., Princiotta, F. (Eds.), Advances in Carbon Management Technologies. CRC Press, Boca Raton, Florida. Dutta, A., Talmadge, M., Hensley, J., Worley, M., Dudgeon, D., Barton, D., Groenendijk, P., Ferrari, D., Stears, B., Searcy, E., Wright, C., Hess, J., 2011. Process Design and Economics for Conversion of Lignocellulosic Biomass to Ethanol Thermochemical Pathway by Indirect Gasification and Mixed Alcohol Synthesis. NREL technical report NREL/TP-5100-51400. Electrigaz Technologies Inc, 2007. Feasibility Study – Anaerobic Digester and Gas Processing Facility in the Fraser Valley , British Columbia. Eng, M., Fall, A., Hughes, J., Shore, T., Riel, B., Hall, P., 2004. Provincial Level Projection of the Current Mountain Pine Beetle Outbreak: an Overview of the Model (BCMPB) and Draft Results of Year 1 of the Project. Environment and Climate Change Canada, 2017. Canadian Environmental Sustainability Indicators - Greenhouse Gas Emissions. doi:10.1016/B978-0-12-409548-9.05178-2. Environment, Climate Change Canada, 2019. National Inventory Report 1990–2017: Greenhouse Gas Sources and Sinks in Canada Part 3. Environmental Reporting, B.C., 2019. Trends in Greenhouse Gas Emissions in BC (19902017). European Commission, 2018. Excise Duty Tables - Part II Energy Products and Electricity. Evangelisti, S., Lettieri, P., Borello, D., Clift, R., 2014. Life cycle assessment of energy from waste via anaerobic digestion: a UK case study. Waste Manag. 34, 226–237. https://doi.org/10.1016/j.wasman.2013.09.013. Evangelisti, S., Tagliaferri, C., Clift, R., Lettieri, P., Taylor, R., Chapman, C., 2015. Life cycle assessment of conventional and two-stage advanced energy-from-waste technologies for municipal solid waste treatment. J. Clean. Prod. 100, 212–223. https://doi.org/10.1016/j.jclepro.2015.03.062. Fao, 2018. Nitrogen Inputs to Agricultural Soils from Livestock Manure: New Statistics. Integrated Crop Management. Feldman, D., Barbose, G., Wiser, R., Darghouth, N., Goodrich, A., 2012. Photovoltaic (PV) Pricing Trends: Historical, Recent, and Near-Term Projections. Forest Products Lab, 2004. Fuel Value Calculator. FortisBC Energy Inc, 2018a. Natural Gas Rates. FortisBC Energy Inc, 2018b. Renewable Natural Gas Supplier Guide. Foust, T.D., Aden, A., Dutta, A., Phillips, S., 2009. An economic and environmental comparison of a biochemical and a thermochemical lignocellulosic ethanol conversion processes. Cellulose 16, 547–565. https://doi.org/10.1007/s10570-0099317-x. FPInnovations, 2018a. Using FPInterface to Estimate Availability of Forest-Origin Biomass in British Columbia. Lakes TSA. FPInnovations, 2018b. Using FPInterface to Estimate Availability of Forest-Origin Biomass in British Columbia. Prince George TSA. FPInnovations, 2019. Using FPInterface to Estimate Available Forest-Origin Biomass in British Columbia: Arrow, Boundary, and Kootenay Lake TSA. Canadian Gas Association, 2018. In: Natural Gas Prices. Retrieved from. http://www.cga .ca/wp-content/uploads/2018/04/Chart-3-Natural-Gas-Price-new.pdf. Gebrezgabher, S.A., Meuwissen, M.P.M., Prins, B.A.M., Lansink, A.G.J.M.O., 2010. Economic analysis of anaerobic digestion-A case of Green power biogas plant in The Netherlands. NJAS - Wageningen J. Life Sci. 57, 109–115. https://doi.org/10.1016/ j.njas.2009.07.006. Gonzalez, R., Daystar, J., Jett, M., Treasure, T., Jameel, H., Venditti, R., Phillips, R., 2012. Economics of cellulosic ethanol production in a thermochemical pathway for softwood, hardwood, corn stover and switchgrass. Fuel Process. Technol. 94, 113–122. https://doi.org/10.1016/j.fuproc.2011.10.003. Government of Canada, 2017. Pan-Canadian Framework on Clean Growth and Climate Change. Government of Canada, 2018. Excise Tax Act (R.S.C., 1985, C. E-15). He, J., Zhang, W., 2011. Techno-economic evaluation of thermo-chemical biomass-toethanol. Appl. Energy 88, 1224–1232. https://doi.org/10.1016/j. apenergy.2010.10.022. Hoskinson, R.L., Karlen, D.L., Birrell, S.J., Radtke, C.W., Wilhelm, W.W., 2008. Engineering , nutrient removal, and feedstock conversion evaluations of four corn stover harvest scenarios. Biomass Bioenergy 31, 126–136. https://doi.org/10.1016/ j.biombioe.2006.07.006. Iea, 2019. World energy statistics 2018 [WWW Document]. Retrieved from. . https ://www.iea.org/statistics/?country¼COSTARICA&year¼2016&category¼Energy% 20supply&indicator¼TPESbySource&mode¼chart&dataTable¼BALANCES. Industrial Forestry Service Ltd, 2015. Wood Based Biomass in British Columbia and its Potential for New Electricity Generation. IPCC, 2007. Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change [Core Writing Team IPCC. https://doi.org/10.1256/004316502320517344. IPCC, 2011. Special report: renewable energy sources and climate change; annex II: methodology. UN Environ Program. IPCC, 2019. In: Global Warming of 1.5� C. https://doi.org/10.1002/9780470996621. ch50. IRENA, 2015. Renewable Power Generation Costs in 2014. Johnson, L., Lippke, B., Oneil, E., 2012. Modeling biomass collection and woods processing life-cycle analysis. For. Prod. J. 62, 258. Karellas, S., Boukis, I., Kontopoulos, G., 2010. Development of an investment decision tool for biogas production from agricultural waste. Renew. Sustain. Energy Rev. 14, 1273–1282. https://doi.org/10.1016/j.rser.2009.12.002.

Kim, S., Dale, B.E., 2004. Global potential bioethanol production from wasted crops and crop residues. Biomass Bioenergy 26, 361–375. https://doi.org/10.1016/j. biombioe.2003.08.002. Klavon, K.H., Lansing, S.A., Mulbry, W., Moss, A.R., Felton, G., 2013. Economic analysis of small-scale agricultural digesters in the United States. Biomass Bioenergy 54, 36–45. https://doi.org/10.1016/j.biombioe.2013.03.009. Knorr, D., Lukas, J., Schoen, P., 2013. Production of Advanced Biofuels via Liquefaction Hydrothermal Liquefaction Reactor Design, NREL report. doi:REPORT 30352.00/01. Krich, K., Augenstein, D., Batmale, J., Benemann, J., Rutledge, B., Salour, D., 2005. Biomethane from Dairy Waste: A Sourcebook for the Production and Use of Renewable Natural Gas in California. Ma, J., Duong, T.H., Smits, M., Verstraete, W., Carballa, M., 2011. Enhanced biomethanation of kitchen waste by different pre-treatments. Bioresour. Technol. 102, 592–599. https://doi.org/10.1016/j.biortech.2010.07.122. MacDonald, A.J., Bernardo, J., Spencer, S., 2012. Assessment of Forest Feedstock (Biomass) for Campbell River, Prepared for British Columbia. BW McCloy & Associates Inc., 2006. Estimated Production, Consumption and Surplus Mill Wood Residue in Canada - 2004: A National Report, ISBN 0-662-42572-3. https://doi.org/10.1016/S0959-6526(97)00040-1. M€ oller, K., Müller, T., 2012. Effects of anaerobic digestion on digestate nutrient availability and crop growth: a review. Eng. Life Sci. 12, 242–257. https://doi.org/ 10.1002/elsc.201100085. Møller, J., Boldrin, A., Christensen, T.H., 2009. Anaerobic digestion and digestate use: accounting of greenhouse gases and global warming contribution. Waste Manag. Res. 27, 813–824. https://doi.org/10.1177/0734242X09344876. Mu, D., Seager, T., Rao, P.S., Zhao, F., 2010. Comparative life cycle assessment of lignocellulosic ethanol production: biochemical versus thermochemical conversion. Environ. Manag. 46, 565–578. https://doi.org/10.1007/s00267-010-9494-2. National Energy Board, 2019. Provincial and territorial energy profiles – British Columbia [WWW Document]. Retrieved from. . https://www.neb-one.gc.ca/nrg/n tgrtd/mrkt/nrgsstmprfls/bc-eng.html. Natural Resources Canada, 2013. Technical Guide to Class 43.1 and 43.2 - 2013 Edition. Natural Resources Canada, 2017. Primer for solid biofuels – definitions, classes/grades and fuel properties. Solid Biofuels Bull. No.2. Natural Resources Canada, 2018. Transportation fuel prices [WWW Document]. retrieved from. . http://www.nrcan.gc.ca/energy/fuel-prices/4593. Nennich, T.D., Harrison, J.H., VanWieringen, L.M., Meyer, D., Heinrichs, A.J., Weiss, W. P., St-Pierre, N.R., Kincaid, R.L., Davidson, D.L., Block, E., 2005. Prediction of manure and nutrient excretion from dairy cattle. J. Dairy Sci. 88, 3721–3733. https://doi.org/10.3168/jds.S0022-0302(05)73058-7. Nie, Y., Bi, X., 2018a. Life-cycle assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia. Biotechnol. Biofuels 11, 1–14. https://doi.org/10.1186/s13068-018-1019-x. Nie, Y., Bi, X.T., 2018b. Techno-economic assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia. Energy 153, 464–475. https://doi.org/10.1016/j.energy.2018.04.057. Nolan, T., Troy, S.M., Gilkinson, S., Frost, P., Xie, S., Zhan, X., Harrington, C., Healy, M. G., Lawlor, P.G., 2012. Economic analyses of pig manure treatment options in Ireland. Bioresour. Technol. 105, 15–23. https://doi.org/10.1016/j. biortech.2011.11.043. Nordhaus, W.D., 2016. Projections and Uncertainties about Climate Change in an Ear of Minal Climate Policies. Cowles Foundation. Discussion Paper No. 2057. OECD, 2017. OECD Environmental Performance Reviews : Canada 2017. OzForex Ltd, 2018. Yearly Average Exchange Rates for Currencies [WWW Document]. https://www.ofx.com/en-ca/forex-news/historical-exchange-rates/yearly-average -rates/. Pa, A., Bi, X.T., Sokhansanj, S., 2011. A life cycle evaluation of wood pellet gasification for district heating in British Columbia. Bioresour. Technol. 102, 6167–6177. https://doi.org/10.1016/j.biortech.2011.02.009. Pa, A., Craven, J.S., Bi, X.T., Melin, S., Sokhansanj, S., 2012. Environmental footprints of British Columbia wood pellets from a simplified life cycle analysis. Int. J. Life Cycle Assess. 17, 220–231. https://doi.org/10.1007/s11367-011-0358-7. Petrov, O., Bi, X., Lau, A., 2015. Impact assessment of biomass-based district heating systems in densely populated communities. Part I: dynamic intake fraction methodology. Atmos. Environ. 115, 70–78. https://doi.org/10.1016/j. atmosenv.2015.05.036. P€ oschl, M., Ward, S., Owende, P., 2010. Evaluation of energy efficiency of various biogas production and utilization pathways. Appl. Energy 87, 3305–3321. https://doi.org/ 10.1016/j.apenergy.2010.05.011. Ptasinski, K.J., 2008. Thermodynamic efficiency of biomass gasification and biofuels conversion. Biofuels, Bioprod. Biorefining 2, 239–253. https://doi.org/10.1002/ bbb. S&T2 Consultants Inc, 2013. GHGenius Model 4.03 Volume 2: Data and Data Sources. Natural Resources Canada, Delta, BC. Shin, J., Han, S., Eom, K., Sung, S., Park, S., Kim, H., 2008. Predicting methane production of anaerobic Co-digestion of swine manure and food waste. Environ. Eng. Res. 13, 93–97. https://doi.org/10.5338/KJEA.2008.27.2.145. Sokhansanj, S., 2015. Cost of Producing Wood Pellets. Biofuelnet Canada. Spatari, S., Bagley, D.M., MacLean, H.L., 2010. Life cycle evaluation of emerging lignocellulosic ethanol conversion technologies. Bioresour. Technol. 101, 654–667. https://doi.org/10.1016/j.biortech.2009.08.067. Statistics Canada, 2011. Households and the Environment: Energy Use, Catalogue, 11526-S 1920-7522. Statistics Canada, 2016. CANSIM table 153-0041 [WWW Document]. http://www.statc an.gc.ca/tables-tableaux/sum-som/l01/cst01/envir25c-eng.htm.

13

H. Wang et al.

Energy Policy 138 (2020) 111285 Ward, A.J., Hobbs, P.J., Holliman, P.J., Jones, D.L., 2008. Optimisation of the anaerobic digestion of agricultural resources. Bioresour. Technol. 99, 7928–7940. https://doi. org/10.1016/j.biortech.2008.02.044. Werner, S., 2017. International review of district heating and cooling. Energy 137, 617–631. https://doi.org/10.1016/j.energy.2017.04.045. Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-ruiz, E., Weidema, B., 2016. The ecoinvent database version 3 (part I): overview and methodology. Int. J. Life Cycle Assess. 3, 1218–1230. https://doi.org/10.1007/s11367-016-1087-8. Wood Pellet Association of Canada, 2018. Wood Pellets 90 Day Index [WWW Document]. https://www.pellet.org/about/markets. Wright, M.M., Daugaard, D.E., Satrio, J.A., Brown, R.C., 2010. Techno-economic analysis of biomass fast pyrolysis to transportation fuels. Fuel 89, S2–S10. https://doi.org/ 10.1016/j.fuel.2010.07.029. Yousefi, H., 2009. Canola straw as a bio-waste resource for medium density fiberboard (MDF) manufacture. Waste Manag. 29, 2644–2648. https://doi.org/10.1016/j. wasman.2009.06.018. Yun, H., Bi, X., Clift, R., 2019. Torrefied Wood Pellets from British Columbia: Energetic, Environmental, and Economic Performances of Supply Chains to Different Markets. To be Publ. Zhang, R., El-Mashad, H., Hartman, K., Wang, F., Liu, G., Choate, C., Gamble, P., 2007. Characterization of food waste as feedstock for anaerobic digestion. Bioresour. Technol. 98, 929–935. https://doi.org/10.1016/j.biortech.2006.02.039. Zhang, S., Bi, X.T., Clift, R., 2013. A Life Cycle Assessment of integrated dairy farmgreenhouse systems in British Columbia. Bioresour. Technol. 150, 496–505. https:// doi.org/10.1016/j.biortech.2013.09.076. Zhang, C., Su, H., Baeyens, J., Tan, T., 2014. Reviewing the anaerobic digestion of food waste for biogas production. Renew. Sustain. Energy Rev. 38, 383–392. https://doi. org/10.1016/j.rser.2014.05.038. Zhang, Y., Ghaly, A.E., Li, B., 2015. Availability and physical properties of residues from major agricultural crops for energy conversion through thermochemical processes. Am. J. Agric. Biol. Sci. 7, 312–321. https://doi.org/10.3844/ajabssp.2012.312.321. Zhu, Y., Biddy, M.J., Jones, S.B., Elliott, D.C., Schmidt, A.J., 2014. Techno-economic analysis of liquid fuel production from woody biomass via hydrothermal liquefaction (HTL) and upgrading. Appl. Energy 129, 384–394. https://doi.org/10.1016/j. apenergy.2014.03.053.

Statistics Canada, 2019a. Population and dwelling count highlight tables , 2016 census [WWW Document]. Retrieved from. . https://www12.statcan.gc. ca/census-recensement/2016/dp-pd/hlt-fst/pd-pl/Table.cfm? Lang¼Eng&T¼801&SR¼1&S¼3&O¼D&RPP¼50&PR¼59&CMA¼0#tPopDwell. Statistics Canada, 2019b. Table 25-10-0030-01: supply and demand of primary and secondary energy in natural units [WWW Document]. Retrieved from. . https:// www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid¼2510003001. Statistics Canada, 2019c. Table 32-10-0415-01: Crop residue baled in the year prior to the census [WWW Document]. BC Stats, 2010. British Columbia’ s Solid Waste Flow, 2006 Summary Report. Stephen, J.D., 2008. Biorefinery Feedstock Availability and Price Variability: Case Study of the Peace River Region. Univ. Br. Columbia, Alberta. Stern, N., 2007. Stern Review: the Economics of Climate Change. Cambridge University Press. https://doi.org/10.1017/CBO9780511817434. Stumborg, M., Townley-Smith, L., Coxworth, E., 1996. Sustainability and economic issues for cereal crop residue export. Can. J. Plant Sci. 669–673. Tallaksen, J., Kildegaard, A., 2011. Biomass Gasification : A Comprehensive Biomass Energy System Biomass Gasification Project. Final Report to the USDA Rural Development. Tews, I.J., Zhu, Y., Drennan, C.V., Elliott, D., Snowden-Swan, L.J., Onarheim, K., Solantausta, Y., Beckman, D., 2014. Biomass Direct Liquefaction Options: Technoeconomic and Life Cycle Assessment. Pacific Northwest National Laboratory. Uggetti, E., Sialve, B., Trably, E., Steyer, J.-P., 2014. Integrating microalgae production with anaerobic digestion: a biorefi nery approach. Biofuels, Bioprod. Biorefining 8, 516–529. https://doi.org/10.1002/bbb. Union, European, 2018. Energy statistical pocketbook. https://doi.org/10.2833/77817, 2018. Wang, M., Han, J., Dunn, J.B., Cai, H., Elgowainy, A., 2012b. Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environ. Res. Lett. 7, 045905 https://doi.org/10.1088/17489326/7/4/045905. Wang, X., Yang, G., Feng, Y., Ren, G., Han, X., 2012a. Optimizing feeding composition and carbon-nitrogen ratios for improved methane yield during anaerobic codigestion of dairy, chicken manure and wheat straw. Bioresour. Technol. 120, 78–83. https://doi.org/10.1016/j.biortech.2012.06.058.

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