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1 Applied Energy 86 (2009) S197 S208 Contents lists available at ScienceDirect Applied Energy journal homepage: Energy consumption and GHG emissions of six biofuel pathways by LCA in (the) People s Republic of China Ou Xunmin a,b,c, Zhang Xiliang b,c, *, Chang Shiyan b,c, Guo Qingfang b,c a School of Public Policy and Management (SPPM), Tsinghua University, Beijing , (the) People s Republic of China b China Automotive Energy Research Center (CAERC), Tsinghua University, Beijing , (the) People s Republic of China c Institute of Energy, Environment and Economy (3E), Tsinghua University, Beijing , (the) People s Republic of China article info abstract Article history: Received 13 January 2009 Received in revised form 22 April 2009 Accepted 23 April 2009 Available online 7 June 2009 This article is sponsored by the Asian Development Bank as part of the Supplement Biofuels in Asia. Keywords: (the) People s Republic of China Greenhouse gas Energy consumption Biofuel Bio-ethanol Bio-diesel This paper presents life-cycle-analysis (LCA) energy consumption (EC) and greenhouse gas (GHG) emissions of China s current six biofuel pathways, which are: corn-derived ethanol (CE); cassava-derived ethanol (KE); sweet sorghum-derived ethanol (SE); soybean-derived bio-diesel (SB); jatropha fruit-derived bio-diesel (JB); and used cooking oil (UCO)-derived bio-diesel (UB). The tool utilized here is the WTW (Well-to-Wheels) module of Tsinghua-CA3EM model covering the entire lifecycle including: raw materials cultivation (or feedstock collection); fuel production; transportation and distribution; and application in automobile engines, compared with Conventional Petroleum-based gasoline and diesel Pathways (CPP). The results indicate: (1) the fossil energy inputs are about times the energy contained in the fuel for the CE, SE and SB pathways, but times for the KE, UB and JB pathways; (2) compared with CPP, the JB, KE and UB pathways can reduce both fossil fuel consumption and GHG emissions; the CE and SB pathways can only reduce fossil fuel consumption, but increase GHG emission; the SE pathway increases not only fossil fuel consumption but also GHG emission; and (3) the main factors inducing high EC and GHG emission levels include: high EC levels during the fuel production stage and high fertilizer application rates during the planting of raw feedstocks. Conclusions are that of the aforementioned biofuel pathways in (the) People s Republic of China: (1) only the JB, KE and UB pathways have energy-saving merits as indicated by the LCA energy inputs and outputs; (2) compared with CPP, all but the SE pathway reduces fossil fuel consumption. However, the SB and CE pathway increase GHG emission; (3) all six displace petroleum by utilizing more coal; and (4) feedstock productivity levels must be increased, and there must be a reduction in fertilizer utilization and EC consumption during the cultivation and transportation stages in order to achieve the goals of energy balance and GHG emission reduction. Ó 2009 Elsevier Ltd. All rights reserved. 1. Introduction Over the past few decades, driven by the goals of promoting agricultural development, guaranteeing energy security, coping with the climate change issue and protecting ecological environment, many countries have promoted large-scale development of the bio-liquid fuel industry as the most near term alternative for conventional petroleum-based gasoline and diesel fuel through designing active strategies and robust policies [1 4]. In 2007, global production of bio-ethanol (EtOH) and bio-diesel (BD) were 39,570,000 and 8,820,000 tons, respectively, and 1,290,000 and 100,000 tons, respectively, for (the) PRC [5]. Currently, about 80% of (the) PRC s EtOH uses corn as its feedstock and many bio-refineries have turned to using newly or genetically produced corn to * Corresponding author. Tel.: ; fax: address: zhang_xl@tsinghua.edu.cn (X. Zhang). displace low quality and old stocks of corn. Other feedstock crops in use for EtOH, but on a much smaller scale, include rapeseed, cassava, sweet potato, sugarcane, sugarbeet, forestry waste, etc. [6 8]. Meanwhile, BD has increasingly been produced from used cooking oil (UCO) or plant oil residuals [8]. However, to what degree the role of reducing GHG emissions and saving energy plays, especially in displacing petroleum fuel, by these biofuel pathways has become a focus for discussion in recent years [9 11]. Since the 1990s, researchers and institutions have began to build lifecycle analysis (LCA) models to model energy consumption (EC) and greenhouse gas (GHG) emissions. The result is a model that comprehends GHG, Regulated Emission and Energy consumption of Transportation fuel (GREET), and a lifecycle emissions model (LEM) [12 17]. These models are able to evaluate alternative liquid fuel LCA [18 22]. Numerous research reports have been published for North-America, Europe and other countries, with localized conclusions based on these models [4,23,24]. The conclusions are very geographically dependent and therefore cannot nec /$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi: /j.apenergy
2 S198 X. Ou et al. / Applied Energy 86 (2009) S197 S208 Nomenclature BD CE CPP EF GHG KE NER NG NGRV PF SB T&S UB WTP bio-diesel corn-derived ethanol conventional petrol-based pathways emission factor greenhouse gas cassava-derived ethanol net energy rate natural gas net GHG reduction value process fuel soybean-derived bio-diesel transportation and storage UCO-derived bio-diesel Well-to-Pump CD CG EC EtOH JB LCA NEV NGRR PE PTW SE TSD UCO WTW conventional diesel conventional gasoline energy consumption bio-ethanol jatropha fruit-derived bio-diesel life-cycle-analysis net energy value net GHG reduction rate primary energy Pump-to-Wheels sorghum-derived ethanol transportation, storage and distribution used cooking oil Well-to-Wheels essarily be applied to other places [10,25]. (the) PRC s biofuel LCA studies are mainly based on unique single pathways. Therefore, it is not possible to compare it to other platforms [26 42]. From an entire life cycle viewpoint, every biofuel pathway is a complex system as shown in Fig. 1. The illustration indicates that the system: cuts across each of the three major sectors from agriculture, industry to services sector; covers all of the stages including raw materials cultivation/collection, fuel production, transportation, to fuel storage and distribution; uses all sorts of energy including coal, electricity, petroleum products, natural gas (NG), hydropower and other renewable energy, as well as chemical fertilizer and pesticides, etc.; and its EC and GHG emissions calculations are comprehended under a national-level energy balance framework. Some of the results from the LCA studies for (the) PRC s biofuels, are indicating problems with accuracy due to: (1) the incomplete data from foreign models or from the process simulation software directly [30,43]; and (2) the lack of full comprehension of the complexity of the energy system requirements, especially for biofuel LCA, which is deeply affected by the nation s general energy mix, the fertilizer production and utilization situation, and electricity generation and consumption status [10,30,31]. So, based on (the) PRC s actual conditions, carrying out a comparison of the EC and GHG emissions of various biofuel pathways is a fundamental and essential requirement to enable (the) PRC to develop strategies and policies promoting large-scale development of the biofuel industry. 2. Methods 2.1. Model utilized (Tsinghua-CA3EM) In this study we use the Well-to-Wheels (WTW) analysis module of the Tsinghua-CA3EM (China Automotive Energy, Environment and Economy Model) model, which is an integrated computerized model module for China s automotive energy supply and demand balance calculation and analysis. The model is based on China s national conditions with the integration of the widely known transportation energy micro-level computing GREET model [22]. Part of the GREET model structure has been adjusted to Chinese specific situations, such as the dominance of coal utilization. Therefore, a majority of the parameters have been modified with local Chinese data [44] System boundary Well-to-Pump (WTP) and Pump-to-Wheels (PTW) are the two stages included in this WTW EC and GHG analysis: WTP studies the upstream production stage, including the exploitation of raw resources/feedstock plantation, feedstock transportation, fuel pro- Fig. 1. Complex energy consumption system of biofuels pathways. Adapted from Ref. [30].
3 X. Ou et al. / Applied Energy 86 (2009) S197 S208 S199 Fig. 2. EtOH EC and GHG emissions LCA diagram (KE pathway case). Table 1 Well-to-Wheels research framework for biofuel pathways. Pathway no. Exploitation of raw resources/ feedstock plantation Feedstock transportation (WTP) Fuel production Fuel TSD Vehicle operation (PTW) CG/baseline1 Oil exploitation Oil transportation Gasoline and oxygenates production, blend Oxygenated gasoline TSD Oxygenated gasoline combustion CE Corn plantation Corn transportation EtOH production EtOH TSD EtOH combustion KE Cassava plantation Cassava transportation EtOH production EtOH TSD EtOH combustion SE Sweet-sorghum plantation Sweet-sorghum transportation EtOH production EtOH TSD EtOH combustion CD/baseline2 Oil exploitation Oil transportation Diesel production Diesel TSD Diesel combustion SB Soybean plantation Soybean transportation BD production BD TSD BD combustion JB Jatropha plantation Jatropha fruit transportation BD production BD TSD BD combustion UB UCO collection UCO transportation BD production BD TSD BD combustion Note: CG: conventional gasoline; CE: corn-derived ethanol; KE: cassava-derived ethanol; SE: sweet sorghum-derived ethanol; CD: conventional diesel; SB: soybean-derived bio-diesel; JB: jatropha fruit-derived bio-diesel; UB: UCO-derived bio-diesel. duction, fuel transportation, storage and distribution (TSD) and PTW studies the downstream fuel combustion process in the vehicle s engine, as described in Fig. 2 and Table 1. E LCA ¼ X4 E LCA;p ¼ X3 p¼1 i¼1 E LCA;i ð5þ 2.3. LCA primary energy consumption calculation When 1 MJ biofuel is supplied to the vehicle, we can calculate the LCA primary energy (PE) consumption based on; (1) the pathway s total process fuel (PF) consumption; and (2) the PFs LCA PE input using the following equations and Table 2. EN p;j ¼ EN p RA p;j EN j ¼ X4 E LCA;p ¼ X9 E LCA;i ¼ X4 EN p;j p¼1 E LCA;p;j E LCA;p;i p¼1 ð1þ ð2þ ð3þ ð4þ Here, EN p,j is the PF j consumption during the unit p; EN p is the total PF consumption during the unit of p; EN j is the total PF consumption during all the units; RA p,j is the PF j consumption share during the unit p; E LCA,p is the LCA PE input of the unit of p; E LCA,i is the LCA PE i input of all the units; E LCA is the LCA PE input of all the units; i indicates the name of PE; j indicates the name of PF; p indicates the name of unit within the studied pathway; and the details behind i, j and p can be seen in Table 2. Just as indicated in the Appendix and [44], the PF s LCA PE input factors can be calculated following these methods and when 1 MJ PF j is achieved, its LCA total PE input (EF LCA,j ) results is the sum of each total PE LCA input (EF LCA,j,i ): EF LCA;j ¼ X3 EF LCA;j;i i¼1 ð6þ
4 S200 X. Ou et al. / Applied Energy 86 (2009) S197 S208 Table 2 The interpretation of i, j and p. i (PE) j (PF) p (Unit of the pathways) 1 Coal Crude coal Feedstock production (including the related fertilizer and herbicide production) 2 NG Crude NG Feedstock transportation 3 Petrol Crude oil Fuel production 4 Coal Fuel transportation 5 NG 6 Diesel 7 Gasoline 8 Residual oil 9 Electricity So combined, Eqs. (1) (5) result in: CO 2;direct ¼ X9 CO 2;direct;j CO 2;direct;j ¼ ERCO 2;j EN j ERCO 2;j ¼ CC j FOR j ð16þ ð17þ ð18þ Here, CO 2,direct,j is the LCA CO 2 direct emission for PF j utilized; ER- CO 2,j is the CO 2 emission rate for PF j; EN j is the EC of PF j; CC j is the Carbon Content Factor of PF j; FOR j is the Oxidation Rate of PF j. CO 2,indirect is calculated based on the carbon balance functions [23,44] and each PF s indirect LCA CO 2 emission rate (TCO 2,j )is shown in the Appendix and [44]: CO 2;indirect ¼ X9 CO 2;indirect;j CO 2;indirect;j ¼ TCO 2;j EN j ð19þ ð20þ E LCA;p ¼ X9 E LCA;i ¼ X4 E LCA ¼ X4 X 3 i¼1 X 9 p¼1 X 9 X 3 p¼1 i¼1 ðen p;j EF LCA;j;i Þ ðen p;j EF LCA;j;i Þ ðen p;j EF LCA;j;i Þ ð7þ ð8þ ð9þ CH 4 emissions calculation CH 4,direct is calculated based on each PF s CH 4 emission rate (ERCH 4,j ): CH 4;direct ¼ X9 CH 4;direct;j CH 4;direct;j ¼ ERCH 4;j EN j ð21þ ð22þ Here each EF LCA,j,i is calculated in the CA3EM model and can be referred from [44], as the Appendix shows NEV and NER We define the net energy value (NEV) and net energy rate (NER) to assess the biofuel pathways energy saving effect: NEV is the result of the energy contained in the fuel minus its LCA PE consumption; NER is the ratio of the energy contained in the fuel to the LCA fossil fuel consumption. Therefore, when 1 MJ biofuel is supplied to the vehicle, NEV and NER are calculated to be: NEV ¼ 1 E LCA NER ¼ 1=E LCA 2.5. LCA GHG emissions calculation ð10þ ð11þ General description For each unit, when 1 MJ biofuel is supplied to the vehicle, we first calculate both direct and indirect emissions of each of three key types of GHG emissions (CO 2,CH 4 and N 2 O) and convert all of them to their CO 2 equivalents (CO 2,e ) according to their global warming potential (GWP) value [45]. CO 2;LCA ¼ CO 2;direct þ CO 2;indirect CH 4;LCA ¼ CH 4;direct þ CH 4;indrect N 2 O LCA ¼ N 2 O direct þ N 2 O indirect GHG LCA ¼ CO 2;LCA þ 23 CH 4;LCA þ 296 N 2 O LCA ð12þ ð13þ ð14þ ð15þ Here, CO 2,LCA is the LCA CO 2 emission; CO 2,direct is the LCA CO 2 direct emission; CO 2,indirect is the LCA CO 2 indirect emission; CH 4,LCA is the LCA CH 4 emission; CH 4,direct is the LCA CH 4 direct emission; CH 4,indrect is the LCA CH 4 indirect emission; N 2 O LCA is the LCA N 2 O emission; N 2 O direct is the LCA N 2 O direct emission; N 2 O indirect is the LCA N 2 O indirect emission CO 2 emissions calculation CO 2,direct is calculated according to each PF s Carbon Content Factor and Oxidation Rate [46,47]. CH 4,indrect is calculated based on each PF s indirect LCA CH 4 emission rate (TCH 4,j ) which is shown in the Appendix and [44]: CH 4;indirect ¼ X9 CH 4;indirect;j CH 4;indirect;j ¼ TCH 4;j EN j ð23þ ð24þ N 2 O emissions calculation N 2 O direct is calculated in two parts: one is the EC induced and the other is N 2 O soil emissions from N-fertilizers applied in biofuel feedstock farming (N 2 O direct,fertilizer ): N 2 O direct ¼ X9 N 2 O direct;j þ N 2 O direct;fertilizer N 2 O direct;j ¼ ERN 2 O j EN j N 2 O direct;fertilizer ¼ ER NF AMOUNT NF ð25þ ð26þ ð27þ Here N 2 O direct,j is the LCA N 2 O emission of PF j; ERN 2 O j is the N 2 O emission rate for PF j; ER NF is the N 2 O emission rate of N-fertilizers applied; AMOUNT NF is the application amount of the N-fertilizers. N 2 O indirect is calculated based on each PF s indirect LCA N 2 O emission rate (TN 2 O j ) as shown in the Appendix: N 2 O indirect ¼ X9 N 2 O indirect;j N 2 O indirect;j ¼ TN 2 O j EN j ð28þ ð29þ Resource for these EFs All the TCO 2,j, TCH 4,j and TN 2 O j are analyzed in the Appendix and can be found in [44] NGRV and NGRR We define the net GHG reduction value (NGRV) and net GHG reduction rate (NGRR) to assess the biofuel pathways GHG emission reduction effect, where NGRV is result of the LCA GHG emission of the responding baseline pathway minus the studied biofuel pathway s LCA GHG emission; NGRR is the ratio of the NGRV of the studied biofuel pathway to the LCA GHG emission of the
5 X. Ou et al. / Applied Energy 86 (2009) S197 S208 S201 responding baseline pathway. Therefore, when 1 MJ of biofuel, CG or CD, is supplied to the vehicle, NGRV and NGRR can be calculated, as shown, in Eqs. (30) and (31). NGRV ¼ GHG LCA;baseline GHG LCA;biofuel NGRR ¼ NGRV=GHG LCA;baseline 3. Basic data 3.1. Basic parameters for biofuel pathways ð30þ ð31þ The basic parameters of (the) PRC s current six biofuel pathways including: CE, KE, SE, SB, JB and UB are shown in Tables 3 and Data within the LCA calculations For each PF, the related LCA PE consumption rates (sorted by coal, NG and petrol), LCA GHG indirect emission rates (sorted by CO 2, CH 4 and N 2 O), direct emission rates (sorted by CH 4 and N 2 O), and Carbon Content Factor and Oxidation Rate are shown in Table 5. We assume that 2% of N in N-fertilizers is released to form N 2 O [22,30,31], so the N 2 O emission rate of N-fertilizers applied (ER NF ) is 31.5 g/kg N-fertilizers (31.5 = 2% 44/ ). 4. Results analysis 4.1. WTP EC All types of PE consumption (including the heat value of the obtained fuel) of these pathways, when 1 MJ fuel is obtained, are shown in Table 6. As Fig. 3 shows, like both CG and CD baselines, the biofuel pathways of CE, SE and SB have negative NEV; but the pathways of KE, JB and UB have positive NEV s. Ranked by their low to high NER efficiencies, the pathways are SE, CG, CD, CE, SB, UB, KE and JB. The fossil EC of these biofuel pathways, excluding the SE pathway, is decreased from that of conventional petroleum-based Table 3 Basic parameters of EtOH biofuel pathways. Pathway CE Data source KE Data Source SE h Production (tons/ha) 6.5 Jilin data in Ref. [48] 13.3 [27] 64.5 Planting energy (MJ/ha) 4047 a [24] 1572 [27] c 2800 i N fertilizer inputs (kg/ha) 162 [31] 100 [27] 600 P fertilizer inputs (kg/ha) 13.3 [31] 100 [27] 150 K fertilizer inputs (kg/ha) 131 [31] 200 [27] 0 Pesticide inputs (kg/ha) 8 [31] 0 [33] 0 Collection radius (km) 125 The average of [30,24] b 250 [27] d 50 Conversion rate (tons of feedstock/tons of fuel) 3.2 [24] 3.0 [27] 18.8 Energy for extraction (GJ/ton) 25 [30] 13.9 [27] e 20 j Distance transmission and distribution (km) 520 [30] 450 [27] f 300 Sharing ratio of the by-product (%) [22] [27] g 20 a The energy mix is gasoline (7.16%), diesel (86.62%) and electricity (6.02%). b The values of [30] and [24] are 100 and 150 km, respectively. c According to [27], diesel fuel and electricity are 44 l ha 1 and 60,923 kw h yr 1 (200,000 ha), so the total planting energy can be determined based on the LHV and the density of diesel are 42.7 MJ kg 1 and kg l 1. d Including 200 km in lorry mode and 50 km in truck mode. e In [27] the energy consumption per liter EtOH is MJ and near 100% of it is coal. f Including 350 km in lorry mode and 100 km in truck mode. g According to its average results. h The data of SE are based on the field visit to Inner Mongolia of China. i The energy mix is gasoline (10%), diesel (80%) and electricity (10%). j The energy mix is coal (90%) and electricity (10%), and the energy efficiency from coal to steam is 80%. Table 4 Basic parameters of BD biofuel pathways. Pathway SB Data source JB d UB g Production (tons/ha) 1.8 Heilongjiang data in [48] 5.0 Planting energy (MJ/ha) 4494 a [24] 800 N fertilizer inputs (kg/ha) 88 [31] 97 P fertilizer inputs (kg/ha) 33 [31] 27 K fertilizer inputs (kg/ha) 27 [31] 18 Pesticide inputs (kg/ha) 4 [31] 0 Collection radius (km) 200 [30] h Conversion rate (tons of feedstock/tons of fuel) 5.9 [24] 3.3 e 20.0 Energy for extraction (GJ/ton) 12.9 b [31] 10 f 7.5 Distance transmission and distribution (km) 200 c Field visit Sharing ratio of the by-product (%) [31] 40 0 a The energy mix is gasoline (7.33%), diesel (88.87%) and electricity (3.80%). b The energy mix is coal (90%) and electricity (10%), and the energy efficiency from coal to steam is 80%. c In current (the) PRC, most of the BD is being used in some agricultural machines and fishing boats because it is forbidden for vehicle fuel. d The data of JB are based on the field visit to Hainan of (the) PRC. e The data are confirmed by [24]. f The data are confirmed by [24]. g The data of UB are based on the field visit to Beijing of China and [24]. h Collection energy for UCO is 30 MJ/ton (to collection points) and 135 MJ/ton (transported to processing plants).
6 S202 X. Ou et al. / Applied Energy 86 (2009) S197 S208 Table 5 LCA PE consumption rates, direct and indirect GHG emission rates for PFs. a PF EF LCA,j,Coal (MJ/MJ) EF LCA,j,NG (MJ/MJ) EF LCA,j,Petrol (MJ/MJ) TCO 2,j (g/mj) TCH 4,j (g/mj) TN 2 O j (10 3 g/mj) ERCH 4,j (g/mj) ERN 2 O j (g/mj) CC j (g-c/mj) Crude coal b Crude NG b Crude oil b Coal NG Diesel /0.028 c Gasoline Resid. oil Electricity a Details to [44]. b These fuel are just mined and transported and not processed for secondary energy. c For these vehicles, the utilization value is but for others the value is FOR j Table 6 WTP EC of biofuel pathways (1 MJ fuel obtained). Pathway no. CG CE KE SE CD SB JB UB NEV NER Fossil EC (MJ) Reduction rate (%) Coal EC (MJ) Increase rate (%) NG EC (MJ) Petrol EC (MJ) Reduction rate (%) (a) NEV (MJ/MJ) (b) NER Fig. 3. NEV and NER of the pathways. (a) Petrol energy input (MJ/MJ) (b) Coal energy input (MJ/MJ) Fig. 4. Petrol energy and coal energy input of the pathways. gasoline and diesel pathways (CPP) fuels. What s more, all of the alternative fuel pathways, according to their fossil energy inputs, increase coal consumption and reduce petroleum consumption, as Fig. 4 shows. This is compared with CPP where the coal increase
7 X. Ou et al. / Applied Energy 86 (2009) S197 S208 S203 rates from % to % and the associated petroleum reduction rates are from 68.00% to 93.55% WTW GHG emissions As shown in Table 7, when 1 MJ of fuel is obtained and utilized, SE and CE pathways lead to significant increases in GHG emissions up to 26.43% and 39.91%, respectively, but KE, JB and UB indicate significant GHG emission reductions of 33.96%, 49.34% and 21.54%, respectively Factors in the decomposition of fossil energy consumption As shown in Table 8, when 1 MJ fuel is obtained, all pathways fossil energy consumption amounts are large in each of the two divided stages the feedstock stage and the fuel stage, especially during the latter one: EC amounts are from 0.33 to 0.75 MJ, and the proportion in total amount are from 41% to 70%, which is an important factor leading to these pathways high EC. For the pathways based on biomass plantations, high fertilizer input is the main reason for high EC during the feedstock stage resulting in an increased total stage. The energy inputs derived from fertilizer input take the proportion of total EC from 16% to 43%. The N fertilizer input is the most important sub-factor. The current (the) PRC inputs are higher than the value of 2.8% estimated in [9], which represents the US CE pathway. Plantation energy, pesticide input and energy for feedstock transportation are also important factors for a high EC feedstock stage. During the fuel stage, the EC for fuel production is the dominant factor and the EC for fuel transportation is a minor factor Factors in the decomposition of GHG emissions As shown in Table 9, when 1 MJ fuel is obtained and utilized, all pathways GHG emission amounts are large in two divided stages the feedstock stage and the fuel stage, especially during the first Table 7 WTW GHG emission of biofuel pathways (1 MJ fuel obtained and utilized). Pathway No. CG CE KE SE CD SB JB UB Emission amount (g CO 2,e ) Increase amount (g CO 2,e ) Increase rate (%) Note: 1. Emission amount is the GHG emissions amount when 1 MJ of fuel is obtained and utilized (that is, use phase emissions of the vehicle are included); 2. The feedstocks of pathways CE, KE, SE, SB, and JB are planted biomass and absorb CO 2 from the air, therefore acting as a carbon sink. Consequently, use phase emissions from the vehicle can therefore be offset by these sinks or credits. Table 8 Fossil energy consumption factor decomposition of biofuel pathways (1 MJ fuel obtained and utilized). Pathway no. (unit) CE (MJ) CE (%) KE (MJ) KE (%) SE (MJ) SE (%) SB (MJ) SB (%) JB (MJ) JB (%) UB (MJ) UB (%) Total Feedstock stage Plantation energy Fertilizer input N input P input K input Pesticide input Feedstock transportation Fuel stage Fuel production Fuel transportation Note: When 1 MJ fuel is obtained and utilized, the EC (corresponding proportions) of the two stages are 0.66/0.69 MJ (49%/51%) for the gasoline pathway, and 0.72/0.58 MJ (55%/45%) for the diesel pathway, respectively. Table 9 GHG emission factor decomposition of biofuel pathways (g CO 2,e /MJ fuel obtained and utilized). Pathway no. (unit) CE (g) CE (%) KE (g) KE (%) SE (g) SE (%) SB (g) SB (%) JB (g) JB (%) UB (g) UB (%) Total Feedstock stage Plantation energy Fertilizer input N input N 2 O effect P input K input Pesticide input Feedstock transportation Fuel stage Fuel production Fuel transportation Note: 1. When 1 MJ fuel is obtained and utilized, the GHG emissions (corresponding proportions) of the two stages are 50.82/53.10 g (49%/51%) for the gasoline pathway, and 56.84/45.76 g (55%/45%) for the diesel pathway, respectively. 2. N 2 O effect means N 2 O emissions from nitrogen nitrification and denitrification.
8 S204 X. Ou et al. / Applied Energy 86 (2009) S197 S208 stage: GHG emission amounts are from g to g, and the proportion in total amounts are from 30% to 67%, which is an important factor leading to the pathways GHG emission increase compared to that of CPPs; for the pathways based on biomass plantations, high fertilizer input is the main reason for high GHG emissions during both the feedstock stage and the total stage. The proportions of GHG emission derived from fertilizer input are from 19% to 37% and N fertilizer input is the most important sub-factor due to the N 2 O effect. High energy intensity during the sub stages of plantation, pesticide input and feedstock transportation are also important factors in the high GHG emission level of the feedstock stage. During the fuel stage, the high energy intensity for fuel production is the dominant factor, while fuel transportation is a minor factor By-product credits of EC and GHG emissions During their process, there are some by-products for the CE, KE, SE, SB and JB pathways [22,24,27,30,31,33]. Consequently, when 1 MJ fuel is obtained and utilized, certain amounts of EC and GHG emissions have been assigned to their by-products and the credit rates are different for each pathway, as shown in Table Discussions 5.1. Sensitivity analysis The purpose of a sensitivity analysis is to estimate the data effects on the outcome of this study. The influence of increasing and Table 10 By-products credit of EC and GHG emissions of biofuel pathways (1 MJ fuel obtained and utilized). Pathways CE KE SE SB JB By-product credit rates (%) Fossil energy shared (MJ) GHG shared (g CO 2,e ) Table 11 Fossil EC change of each pathway due to the energy input value variation of 10% (MJ/ MJ). Pathway no. CE KE SE SB JB Origin value Plantation energy (+10%) Plantation energy ( 10%) Fertilizer input (+10%) Fertilizer input ( 10%) N input (+10%) N input ( 10%) Fuel production energy (+10%) Fuel production energy ( 10%) decreasing input factors by 10%, one at a time, was studied. The sensitivity analysis results are shown in Tables 11 and Comparison of the results to other studies As Table 13 indicates, the EC results of different studies, including (the) PRC and other countries, are compared. For CE and SB pathways, this study has a relatively pessimistic result where the NER values are only 88.57% and 98.04%, but the NER values of other studies for (the) PRC are all greater than 100% [26,28,41,51]; for KE and JB pathways, all studies for (the) PRC (including this study) have similar results [27,28,33,43,51]; (the) PRC s KE pathway is less optimistic than that of Thailand [25]. As Table 14 indicates, the GHG emission results of different studies, including (the) PRC and other countries, are compared. For the SB pathway, this study has a relatively pessimistic results, where the NGRR is 7.71%; for the CE pathway, this study generates an even more pessimistic, negative NGRR, which is opposite to the results from the studies done in the US and Sweden [10,22]; for the KE pathway, all studies for (the) PRC (including this study) have similar positive results to that of Thailand [26,49,50]. The following reasons explain the differences between the (the) PRC studies and other countries studies: (1) China s coal-dominant energy mix [52]; (2) China farmers utilize high fertilizer application rates for their agricultural practices [30,31]; and (3) (the) PRC s relatively higher energy consumption in the industries processes producing EtOH and BD [53]. The following reasons explain the differences between this study and other (the) PRC studies [44]: (1) on-site monitoring of China s nitrogen fertilizer issues including feedstock source, transportation modes, and process energy consumption; (2) full consideration of the N 2 O emissions in N-fertilizer applications. For example, this factor is 15% of the total LCA GHG emission for the SE pathway; and (3) comprehension of the CO 2 and CH 4 emissions associated with China s coal mining, crude oil and NG exploration stages [30,31,37] Changes of a variety of factors can influence each pathway NEV and GHG emissions levels For these pathways, if their feedstock productivity (production amount/ha) have increased, accompanied by stable fertilizer inputs (input amount/ha), then the total WTP fossil energy per MJ fuel obtained will decrease because of the corresponding reductions in fertilizer input, and EC for transport (due to the distance being shorter). Other ways of reducing EC are during cultivation, and during the application of fertilizer. EC for refining processes and transportation can in fact reduce the WTP fossil energy consumption and GHG emissions. As shown in Table 15, these factors have different changing rates in order to achieve the goal of Positive NEV (the calorific value contained in the fuel obtained is more than the WTP fossil energy input). Table 12 GHG emission increasing rate change of each pathway due to the energy input value variation of 10%. Pathway no. CE KE SE SB JB Origin value 26.43% 33.96% 39.91% 7.71% 49.34% Plantation energy (+10%) 27.02% 33.77% 40.07% 9.15% 49.15% Plantation energy ( 10%) 25.78% 34.23% 39.73% 5.85% 49.45% Fertilizer input (+10%) 30.89% 32.71% 45.24% 11.62% 47.54% Fertilizer input ( 10%) 21.91% 35.29% 34.56% 3.38% 51.06% N input (+10%) 30.30% 32.78% 45.13% 11.29% 47.59% N input ( 10%) 22.50% 35.22% 34.67% 3.71% 51.01% Fuel production energy (+10%) 32.97% 29.53% 39.90% 11.02% 46.66% Fuel production energy ( 10%) 19.83% 38.47% 39.90% 3.98% 51.94%
9 X. Ou et al. / Applied Energy 86 (2009) S197 S208 S205 Table 13 Biofuel pathways LCA EC results compared in different studies. Fuel pathways Region Source Press time EC (MJ/MJ) NEV (MJ/MJ) NER (%) CG (the) PRC In this study from [44] CD (the) PRC In this study from [44] CE (the) PRC In this study CE (the) PRC [41] CE (the) PRC [51] CE (the) PRC [28] CE US [9] KE (the) PRC In this study KE (the) PRC [51] KE (the) PRC [33] KE (the) PRC [27] KE (the) PRC [28] KE (the) PRC [43] KE Thailand [25] SB (the) PRC In this study SB (the) PRC [51] SB (the) PRC [26] JB (the) PRC In this study JB (the) PRC [34] Table 14 Biofuel pathways LCA GHG emission results compared in different studies. Fuel pathways Region Source Press time GHG (g CO 2,e /MJ) GHG (g CO 2,e /l) NGRR (%) CG (the) PRC In this study from [44] CD (the) PRC In this study from [44] CE (the) PRC In this study CE US [22] CE Sweden [10]: The forest chips as fuel situation CE Sweden [10]: The NG as fuel situation CE Sweden [10]: The coal as fuel situation KE (the) PRC In this study KE (the) PRC [49] KE Thailand [50] SB (the) PRC In this study SB (the) PRC [26] Table 15 The factor s changing rates for Positive NEV goal of the biofuel pathways (%). Pathway no. CE SE SB To increase productivity To reduce plantation energy N.E. N.E To reduce fertilizer input To reduce process energy To reduce transportation energy N.E. N.E Note: N.E. stands for not effective. As shown in Table 16, these factors have different changing rates in order to achieve the goal of Positive NGRR (the GHG emission level of the biofuel pathway is lower than that of its alternative fuel: gasoline or diesel pathway). 6. Concluding remarks 6.1. China s current biofuel pathways are geographically unique: they behave differently from LCA EC and GHG emission analysis and conclusions for the US, EU, Brazil, etc As Fig. 5 shows, the six pathways located in three different quadrants separated by the EC and GHG emission levels of CD and CG. JB, KE and UB pathways are in quadrant I, which indicates that both are lower in EC and GHG emission levels than CPP. SB and CE pathways are in quadrant II, which indicates that they are lower Table 16 The factor s changing rates for Positive NGRR goal of the biofuel pathways (%). Pathway no. CE SE SB To increase productivity To reduce plantation energy N.E. N.E To reduce fertilizer input Of which: N P N.E. N.E. N.E. K N.E. N.E. N.E. To reduce process energy To reduce transportation energy N.E. N.E Note: N.E. stands for not effective. Fig. 5. Fossil energy input and GHG emissions for biofuel pathways.
10 S206 X. Ou et al. / Applied Energy 86 (2009) S197 S208 in EC but higher in GHG emissions than CPP. Only the SE pathway is in quadrant III, which indicates that it has higher EC and GHG emissions than CPP. The dominant biofuel pathways of SB and CE indicate only energy savings without any GHG reduction effect. However, the non-food feedstock pathways like JB, KE and UB, are very sustainable in the sense that they reduce both EC and GHG emissions. And, the results indicate that careful research should be conducted before the pathway of SE is encouraged All current pathways are feasible in (the) PRC due to their petroleum substitution effect, though they have not obvious energysaving or GHG reduction effect Currently, for all of the biofuel pathways compared to CPPs, petroleum consumption can be reduced through the increase in coal consumption. So, they are all feasible in (the) PRC due to the rich coal and poor petroleum scenario described in [52] Fertilizer inputs and energy for fuel production are the two major factors for the high EC and GHG emission levels For feedstock-planting biomass liquid fuel pathways, the EC is high due to (the) PRC s custom of utilizing high fertilizer application rates in the process of agricultural production, where half of the nitrogen fertilizer is made from coal-feedstock. Therefore, each pathway s GHG level is especially high because of the nitrogen fertilizer s N 2 O emissions effect and the coal s dominant power role during the process stage The current EC and GHG situation can be improved by productivity increases, resource reductions, and by-product output optimization Within the current pathways, the EC and GHG situation can be improved by applying the following measurements: higher productivity through seed selection and gene engineering; reduction of EC for cultivation and fertilizer inputs through selecting appropriate planting sites, resulting in reduced EC for irrigation and fertilizer usage; reduction in EC for transportation of feedstock and fuel, through rationalizing the fuel plant sites arrangement and localizing the fuel deployment; reduction in EC during the extraction process, through promotion of high-performance low-ec refining equipments; and higher energy efficiencies and credits through optimizing by-product output. Acknowledgements The project is co-supported by the China National Natural Science Foundation (Grant No ) and the CAERC program (Tsinghua/GM/SAIC-China). The authors would like to thank the three colleagues for their valuable reviewing comments and Dr. Kristin. B. Zimmerman of GM and Mr. Benny Zhang of GM-China for their generous help. Appendix A. Calculation methods for LCA EC and GHG emission A.1. Basic assumptions There are three types of primary energy (PE) considered in this study, coal, NG, and petrol. We set i to stand for them, respectively, there are nine types of process fuel and we set j to stand for them, respectively. For each type of process fuel (PF), its lifecycle analysis (LCA) includes m stages; all of them are shown in Table A. 1. Each type of PF has K kinds of technologies to be utilized in the stage of m, and each of them has different emission factor (EF). Table A. 1 The interpretation of i, j and m. A.2. Calculation of LCA EC In this section, calculation of the LCA energy consumption (EC) for a specific PF is based on the energy transformation efficiency, the EC mix and energy utilization technology of each of its LCA stages. A.2.1. Relationship of energy input of each stage There are the efficiency equations as followed: EI m 1;j ¼ EI m;j =EFF m 1 ðj ¼ 1; 2;...; 9; m ¼ 2; 3; 4Þ ða:1þ Here, EI m,j is the total PE input during stage m, when 1 MJ of PF j is finally produced; EFF m is the energy transformation efficiency factor of stage m, when 1 MJ of PF j is produced. The resulting equation is: EI 4;j ¼ 1=EFF 4 ðj ¼ 1; 2;...; 9Þ ða:2þ A.2.2. LCA energy input factors calculation Here we define EF LCA,j,i as the LCA PE i input for 1 MJ of PF j obtained. The types of PE and PF have the same content: coal, NG, and crude oil, therefore, the following equations can be solved with iterative methods using a computer that combines Eqs. (A.1) and (A.2):! EF LCA;j;i ¼ X4 EI m;j X9 ðsh m;j;z EF LCA;z;i Þ m¼1 z¼1 ði ¼ 1; 2; 3; j ¼ 1; 2;...; 9Þ ða:3þ Here SH m,j,z is the share of PF z for all EC in stage m for 1 MJ of PF j produced. Knowing SH m,j,z and EFF m, and combining the equations from (A.1), (A.2), (A.3), results in EF LCA,j,i and EI m,j (i =1, 2, 3; j =1, 2,...,9;m =1,2,3,4). In addition, we can get the LCA total PE input for 1 MJ of PF j obtained (EF LCA,j ): EF LCA;j ¼ X3 i¼1 i¼1 i (PE) j (PF) m (stage name) 1 Coal Crude coal Feedstock production 2 NG Crude NG Feedstock transportation 3 Petrol Crude oil Fuel production 4 Coal Fuel transportation 5 NG 6 Diesel 7 Gasoline 8 Residual oil 9 Electricity EF LCA;j;i ðj ¼ 1; 2;...; 9Þ ða:4þ Combined with Eq. (A.3), we get:! EF LCA;j ¼ X3 X 4 ðei m;j X9 ðsh m;j;z EF LCA;z;i ÞÞ m¼1 ðj ¼ 1; 2;...; 9Þ z¼1 ða:5þ The details of the above calculation process and results can be found in [44]. A.3. Direct emissions of CO 2,CH 4,N 2 O of PF utilized A.3.1. Direct emissions of CO 2 of PF utilized To calculate the LCA EC for 1 MJ of PF, the results indicate that the LCA stages utilize a lot of PF x. Therefore, the calculation of the emissions of such PF x utilized must be completed first.
11 X. Ou et al. / Applied Energy 86 (2009) S197 S208 S207 When 1 MJ of PF x is utilized, the direct emission of CO 2 in the stage of m can be calculated by the following carbon balance equations: FCO 2;m;x ¼ XK ðfco 2;m;x;k SH m;x;k Þ k¼1 FCO 2;m;x;k ¼½DEN x =LHV x ROC x 0:85 HC m;x;k 0:43 CO m;x;k 0:75 CH 4;m;x;k Š=0:27 ða:6þ ða:7þ where FCO 2,m,x is the CO 2 EF for PF x during the stage of m; FCO 2,m,x,k is the CO 2 EF for PF x using technology k during the stage of m; SH m,x,k is the share of technology k in the PF x during the stage of m; DEN x is the density of the PF x; LHV x is the low heat value of the PF x; ROC x is the average carbon content for PF x; HC m,x,k is the HC EF for PF x using technology k during the stage of m; 0.85 is the average carbon content for HC emissions; CO m,x,k is the CO EF for PF x using technology k during the stage of m; 0.85 is the average carbon content for CO emissions; CH 4,m,x,k is the CH 4 emissions factor for PF x using technology k during the stage of m; 0.75 is the carbon content for CH 4 emissions; and 0.27 is the carbon content for CO 2 emissions. The result is the LCA CO 2 emissions of the stage of m (TCO 2,m,x ) and all stages (TCO 2,x ) when EI m,x of PF x is utilized: TCO 2;m;x ¼ EI m;x FCO 2;m;x TCO 2;x ¼ X4 m¼1 TCO 2;m;x ða:8þ ða:9þ Finally, the resulting LCA CO 2 emissions of all stages when 1 MJ of PF j is obtained (TCO 2 ) is: TCO 2 ¼ X9 x¼1 TCO 2;x A.3.2. Direct emissions of CH 4 of PF utilized Similarly, CH 4 EF for PF x utilized during the stage of m is: FCH 4;m;x ¼ XK k¼1 FCH 4;m;x;k ða:10þ ða:11þ where FCH 4,m,x,k is the CH 4 EF for PF j using technology k during the stage of m. The resulting LCA CH 4 emissions of the stage of m (TCH 4,m,x ) and all stages (TCH 4,x ) when EI m,x of PF x is utilized, is: TCH 4;m;x ¼ EI m;x FCH 4;m;x TCH 4;x ¼ X4 m¼1 TCH 4;m;x ða:12þ ða:13þ Finally, the resulting LCA CH 4 emissions of all stages when 1 MJ of PF j is obtained (TCH 4 ) is: CH 4 ¼ X9 x¼1 TCH 4;x A.3.3. Direct emissions of N 2 O of PF utilized Similarly, N 2 O EF for PF x during the stage of m is: FN 2 O m;x ¼ XK k¼1 FN 2 O m;x;k ða:14þ ða:15þ where FN 2 O m,x,k is the N 2 O EF for PF x using technology k during the stage of m. The resulting LCA N 2 O emissions of the stage of m (TN 2 O m,x ) and all stages (TN 2 O x ) when EI m,x of PF x is utilized is: TN 2 O m;x ¼ EI m;x FN 2 O m;x TN 2 O x ¼ X4 m¼1 N 2 O m;x ða:16þ ða:17þ Finally, the resulting LCA N 2 O emission of all stages when 1 MJ of PF j is obtained (TN 2 O) is: TN 2 O ¼ X9 x¼1 References TN 2 O x ða:18þ [1] Chang SY, Zhang XL, Chai QM. The impact of Chinese EtOH industry from cellulosic ethanol technology innovation. Forum Sci Technol Chin 2008;5:58 61 [in Chinese]. [2] Zhang XL, Lv W. Chinese forestry energy. Beijing: China Agriculture Press; 2008 [in Chinese]. [3] Hammond GP, Kallu S, McManus MC. Development of biofuels for the UK automotive market. Appl Energy 2008;85: [4] Concawe, EUCAR & EC Joint Research Centre. 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