木薯燃料乙醇的碳效应(英文)
J. Resour. Ecol. 2012 3 (1) 055-063 DOI:10.5814/https://www.wendangku.net/doc/c915246256.html,
March, 2012
Journal of Resources and Ecology V
ol.3 No.1Received: 2011-11-23 Accepted: 2012-01-20
Foundation: the National Natural Science Foundation of China (40971270).* Corresponding author: LV Yao. Email: 136********@https://www.wendangku.net/doc/c915246256.html,.
1 Introduction
The reduction of greenhouse gas emission is a shared global challenge. The Chinese Government promised at the Copenhagen Climate Change Conference in 2009 that China would endeavor to reduce its carbon dioxide emission per unit of GDP by 40%–45% by 2020 compared with 2005 levels (https://www.wendangku.net/doc/c915246256.html,/cj/cj-hbht/news/2009/11-26/1986490.shtml). The CO 2 emission of China from oil consumption has amounted to 12.95 ×108 ton in 2010 (IEA 2011), and more than 30% of total emissions come from transportation. Therefore, exhaust gas from automobiles is an important source of greenhouse gas emissions. Bio-fuel ethanol as a substitution for gasoline can effectively reduce vehicle greenhouse gas emission from burning fossil fuels. Consequently, the study of the carbon balance of bio-fuel
ethanol has great significance in reducing CO 2 emissions from transportation. In recent years, the bio-fuel ethanol industry has developed rapidly and the Chinese Government also gives great support to this developing bio-fuel ethanol industry. Considering food security, the Government promotes bio-fuel ethanol from cassava, sweet potato, sweet sorghum and other non-grain crops.
There are many different views on carbon emission from bio-fuel ethanol production. International Energy Agency (IEA) and Food and Agriculture Organization (FAO)assessed the greenhouse gas emission of bio-fuel ethanol globally (FAO 2008), and found that despite variation in benefits, bio-liquid fuels were able to reduce greenhouse gas emission to some extent (Revin 2001; Hu et al . 2003; Hu et al . 2004). However, recent researches have shown that carbon emissions from bio-fuel ethanols are almost the
Carbon Balance of Cassava-based Ethanol Fuel in China
YANG Hailong 1, 2, LV Yao 1* and FENG Zhiming 1
1 Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2 Graduate University of Chinese Academy Sciences, Beijing 100049, China
Abstract: Considering energy security and greenhouse gas emission, many governments are developing bio-liquid fuel industries. The Chinese Government advocates the development of a fuel ethanol industry with non-food crops such as cassava. However, scientists debate the carbon emission of these bio-liquid fuels. The focuses are the influence of soil carbon pool destruction and by-product utilization. This study built a carbon balance analysis model, and assessed carbon emission of cassava fuel ethanol across its life cycle. The results show that the carbon emission of cassava fuel ethanol per kilogram in its life cycle was 0.457 kg under new technical conditions and 0.647 kg under old technical conditions. Carbon emission mainly came from the use of nitrogen fertilizer (9% of total emissions), the destruction of the soil carbon pool (29%) and fossil energy inputs (50%). Taking gasoline as a reference, the carbon emission of cassava fuel ethanol was 90% of that of gasoline. This percentage would drop to 64% if soil carbon pool destruction was avoided. Therefore, in order to promote the development of cassava fuel ethanol in China, farms should apply fertilizer properly, grow cassava on marginal land, and not alter land use patterns of woodland, grassland and other environments. In addition, we should exploit efficient fuel ethanol conversion technologies and strengthen the use of by-products.
Key words: fuel ethanol; life cycle assessment (LCA); carbon impact; carbon balance analysis; cassava
Journal of Resources and Ecology V ol.3 No.1, 2012 56
same as those of the oil (Farrell et al. 2006; Renton et al. 2007; Zhang et al. 2006). Conversely, if energy crops were grown in tropical rain forest, peatland, savanna or grassland, carbon emissions would be even worse (Joseph et al. 2008; Adler et al. 2007; Elsayed et al. 2003; Searchinger et al. 2008 ).
Carbon emission from bio-fuel ethanol is affected by many complicated factors such as plant management, input levels, land use types, converting technology and by-product processing. The most significant reason for the discrepancies is the ignorance of carbon emissions arising from land use change and by-product distribution. Additionally, the uncertainty of the system boundary and the difficult accessibility of some indirect factors also lead to different results. The destruction of the soil carbon pool and how to use by-products are essential when assessing carbon emission. For instance, cassava dregs can be used as manure or materials for generating power, namely ‘avoiding’ greenhouse gas emissions, and these have enormous impact on evaluation results.
In this study, applying life cycle assessment (LCA) and establishing a fuel ethanol carbon balance model we (i) bring the impact on the soil carbon pool when growing cassava and the substitution effect of by-products into the research system, (ii) analyze the cassava-based fuel ethanol carbon emissions in China, and (iii) provide a basis for decision-making for the development of a cassava-based fuel ethanol industry in China.
2 Methods and data
2.1 Life cycle assessment and carbon balance model The methodological framework applied in this study is based on the life cycle assessment (LCA) methodology. Ideally, the LCA methodology makes it possible to account for all materials and energy flows associated with the production system while keeping track of outputs (products, energy and waste materials) along the production cycle (Fig.
1).
The carbon balance model of bio-fuel ethanol is as follow:
C net = C fossil + C soil + C substitute (1) where, C net is net carbon emissions; C fossil is carbon emissions from fossil energy input in the life cycle of the cassava-based fuel ethanol; C soil is the carbon emission from the destruction to soil carbon pool when planting cassava; C substitute is the reduction of carbon emissions due to the secondary utilization of by-products, the so called “substitution effect”. For instance, generating biogas or cogeneration by cassava residue can reduce fossil energy input and thereby reduce carbon emissions.
2.2 Date collection
Primary data was mainly collected from field surveys and
Fig. 1 Analysis framework
for carbon balance in life
cycle assessment.
YANG Hailong, et al .: Carbon Balance of Cassava-based Ethanol Fuel in China
57published literature. Besides, official databases were also important data sources. In order to obtain primary data, the authors went to Guangxi Zhuang Autonomous Region three times in October 2010, March and August 2011 to do surveys and administer questionnaires. We took detailed records of energy input-output involved in cassava planting. We visited enterprises to collect data on the processing and transformation of bio-fuel ethanol.
3 Results
3.1 Carbon emission from cassava cultivation
Cultivation, management and transportation of cassava consume a lot of chemicals such as fertilizers, pesticides and fuel. The carbon emissions due to the production of these chemicals should be included in the analysis. Besides, the original equilibrium state of the soil environment was destroyed because local farmers reclaimed wasteland in a large-scale to grow cassava, which also caused great carbon emissions. Consequently, carbon emissions caused by soil carbon pool destruction should be included in the analysis system.
3.1.1 Carbon emission from fossil energy input Carbon emissions of fossil energy inputs are as follows: C fossil = C 1+ C 2
(2)
where, C 1 is carbon emissions from fossil energy input for planting cassava; C 2 is carbon emissions from fossil energy input of harvesting and transporting cassava. C 1 was calculated as follows:
(3)
where, X i is the quantity of i material consumed in planting cassava; EF i is the carbon emission coefficient of i material; A is the cassava planting area.
As the warming effect of N 2O is obvious, the consumption of nitrogen fertilizer during cassava cultivation needs a separate discussion. The formula is as follow:
(4)
where, X N is the quantity of nitrogenous fertilizer consumed during the cassava cultivation (calculated as N); α is the proportion of N 2O due to the nitrification of nitrogenous fertilizer, in this study, the value of α is 0.18% (Zhang et al . 2010); GWPN 2O is the global warming potential index of N 2O and its value is set to 296 (IPCC, 1996); M N is the atomic weight of nitrogen and its value is 14; and M C is the atomic weight of carbon and its value is 12.
(5)
where, D 1 is the average transportation distance; TE 1 is the fuel consumption intensity of transporting cassava and TEF 1 is the carbon emission coefficient of transport fuel.
The main fossil energy inputs for sowing, and management (including transportation and storage) of cassava are nitrogen, phosphate, potash, pesticides, herbicides and mechanical fuel. Considering the actual situation we took the average value after doing field research. From the investigation results we obtained the average value of transportation distance as 4 km, the diesel consumption intensity of transporting cassava is 0.06 L(t·km)-1 and the yield of cassava is 41 t ha -1. Thus, diesel consumption for transporting cassava is 9.84 L per hectare. Taking into account the fuel consumption for cultivation (34 L ha -1), we derive that the total fuel consumption for planting cassava per hectare is 43.84 L. Because cassava’s water requirements are met mainly by rainfall, the power consumption of irrigation is zero. Seed investment is negligible because farmers kept the seed themselves annually. According to formula (2)–(5), we can calculate the carbon emissions from fossil energy input per hectare (including cassava transportation) (Table 1).
As shown in Table 1 and Fig. 2, total carbon emissions from fossil energy input during cassava cultivation are 429.44 kg per hectare. Nitrogen is the main source of carbon emissions and accounts for 42% of total emissions. The use of plastic film also plays a great role, which takes up 10% of total emissions, followed by diesel fuel and pesticides
Nitrogen (N) 210 (kg) 0.857 179.97 41.91 Phosphate (P 2O 5) 146 (kg) 0.165 24.09 5.61 Potash (K 2O) 178 (kg) 0.120 21.36 4.97 Pesticide 8 (kg) 4.932 39.46 9.19 Herbicide
7 (kg) 4.702 32.91 7.66 Diesel (cultivation/harvesting/transporting) 44 (L) 0.849 37.36 8.70 Plastic film
30 (kg) 1.469 44.07 10.26 Power for irrigation
0 (kW·h) 0.355 0 0.00 Gasoline for transportation 0 (L) 0.853 0 0.00 N effect — — 50.22 11.69 Total
—
—
429.44
100
Items
Input (unit) Coefficient (kg C unit -1)
Carbon emission (kg C)
Proportion (%)Table 1 Carbon emissions of fossil energy inputs per hectare.
Journal of Resources and Ecology V ol.3 No.1, 2012 58
(both 9% of the total emissions). In order to reduce carbon emissions, we should adopt advanced cultivation technology and scientific fertilization methods that reduce nitrogen loss and ultimately reduce carbon emissions.
3.1.2 Carbon emissions from soil carbon pool destruction We built a model to calculate carbon emissions caused by soil carbon pool destruction. Some parameters should be defined first:
L0: carbon stored in the litter pool in equilibrium at time 0;
L(t): carbon stored in the litter pool at time t;
H0: carbon stored in the humus pool in equilibrium at time 0;
H(t): carbon stored in the humus pool at time t;
S0: carbon stored in the soil pool in equilibrium at time 0; S(t): carbon stored in the soil pool at time t;
LP0: carbon content in annual litter production in equilibrium at time 0;
LP (t): carbon content in annual litter production at time t; NPP: annual net primary production;
CP: annual harvest of cassava;
LNP: the amount of removed plant waste when
reclamation;
LRE: annual amount of cassava straw returning;
k: share of the carbon flux out of the litter pool that enters the humus pool [(1–k) is emitted to the
atmosphere];
Ф: share of the carbon flux out of the humus pool that enters the soil pool [(1–Ф) is emitted to the
atmosphere];
k la: carbon flux fraction from litter to atmosphere;
k ha: carbon flux fraction from humus to atmosphere;
k sa: carbon flux fraction from soil to atmosphere;
k lh: carbon flux fraction from litter to humus;
k hs: carbon flux fraction from humus to soil.
The system is assumed to be in equilibrium at time 0, therefore,
LP0 = NPP–CP (6) F lh, 0 (carbon flux from litter to humus in
equilibrium)=k×LP0 (7) F la, 0 (carbon flux from litter to atmosphere in
equilibrium)=(1–k)×LP0 (8) F hs, 0 (carbon flux from humus to soil in
equilibrium)=k×φ×LP0 (9) F ha, 0(carbon flux from humus to atmosphere in
equilibrium)=k×(1–φ)×LP0 (10) F sa, 0 (carbon flux from soil to atmosphere in
equilibrium)=k×φ×LP0 (11) According to the formulas (6)–(11), the carbon flux from litter to soil to atmosphere ultimately follows a dynamic equilibrium. However, the dynamic equilibrium of th esoil system is destroyed in actual practice which causes large carbon emissions from the soil carbon pool.
LP = NPP-CP-LNP+LRE= LP0 – LNP+LRE (12) F lh (carbon flux from litter to humus in actual practice)
=L×k lh (13) F la (carbon flux from litter to atmosphere in actual
practice )=L×k la (14) F hs (carbon flux from humus to soil in actual practice)
=H×k hs (15) F ha (carbon flux from humus to atmosphere in actual
practice )=H×k ha (16) F sa (carbon flux from soil to atmosphere in actual
practice )=S×k sa (17) The following equations for the carbon mass balance of the three pools have to be solved:
(18)
(19)
(20) With the initial equilibrium the proportionality factors
Fig. 2 Carbon emissions of fossil energy input
YANG Hailong, et al.: Carbon Balance of Cassava-based Ethanol Fuel in China59
kxy can be calculated:
dL/dt = 0; L=L0; k la=[(1–k)×LP0] / L0; k lh=(k×LP0)/L0;
dH/dt = 0; H=H0; k ha=[(1–φ)×k×LP0] /H0;
k hs=(φ×k×LP0) / H0;
dS/dt = 0; S=S0; k sa=(φ×k×LP0) /S0
According to k xy and equations (18), (19) and (20)
(21)
(22)
(23) Solving differential equation (21):
(C1 is arbitrary constant) (24) Solving differential equation (22):
(C1, C2 are arbitrary constants ) (25) Solving differential equation (23):
(C1, C2, C3 are arbitrary constants ) (26) So, the carbon emission equation is:
C loss(t) = L0 + H0 + S0 – L(t) – H(t) – S(t) (27) Most of the local soil is lateritic red soil. The thickness of the humus of the topsoil is 10–20 cm before reclamation; we regard the average value as 15 cm in this paper. The proportion of organic matter is between 4% and 6% (from survey data). The conversion coefficient which describes the organic matter transformation into organic carbon is 0.58 (SSAACC, 1989). The homogeneous layer thickness is 0.5–2 m. Cassava cultivation layer is generally between 15–30 cm, and we took the mean value 0.25 m as the depth of soil disturbance. The soil bulk density is about 1.59 (WBS, 2008). Soil organic matter content is 2.3% (Wei et al. 2007). Soil organic carbon content is 1.35% (Ni et al. 2007). Accordingly to these data, we can estimate H0 = 69.2 t C ha-1, S0 = 53.7 t C ha-1. This value roughly approximates to the FAO-UNESCO soil classification (5.7–16.9 kg m-2) (Batjes et al. 1996).
Some data is accessible from the survey data and literature where NPP = 5.3 t C ha-1y-1 (Atjay et al.1979), CP=1.8 t C ha-1y-1, LP0=NPP–CP=3.5 t C ha-1y-1, LNP=1.2t C ha-1y-1, LRE=0.3t C ha-1y-1, L0=26.8t C ha-1, H0=69.2t C ha-1, S0=53.7 t C ha-1, k=0.25, and Ф = 0.1 (Schlamadinger et al. 1995), After substituting these values into the equations 24 to 27, the parameters are described as below: L(t)=6.9e-0.13t+19.9;
L(t)=19.7e-0.012t–1.9e-0.131t+51.4e0.013t
S(t)=50.8e-0.002t–1.8e-0.131t+0.02e-0.0131t+4.6e0.013t
C LOSS(t)=129.8–5.02e-0.131t–19.7e-0.012t–56.00.013t–
50.8e-0.002t+1.8e-0.013t
According to the above equations, C LOSS (1)=0.7 t C=700 kg C; C LOSS (5)=0.1 t C=100 kg C; C LOSS (6)=–0.01 t C=–10 kg C;
C LOSS (10)=–1.04 t C=–1040 kg C.
Carbon emissions caused by soil carbon pool destruction are 700 kg after one year of cassava planting; this is 1.6 times more than carbon emissions caused by fossil energy input. As most of the plant waste is removed during reclamation, the original balance of the soil carbon pool is broken, and leads to a massive release of soil carbon. Meanwhile, the soil humus layer decreases because of the reduction in raw materials on the surface layer which leads to a reduction in soil carbon accumulation. After years of cassava growing carbon emissions from the soil carbon pool will gradually decrease, and the soil carbon pool will be in a new dynamic equilibrium again in the sixth year. If more cassava straw is returned to the fields, many years later, such as the tenth year, soil carbon storage will be greater than the carbon emitted.
Among all the carbon emissions during cassava planting, soil carbon emissions are 700 kg which accounts for 62% of the total carbon emissions. Therefore, in order to reduce carbon emissions, we should not significantly change land use types, particularly for woodlands and grasslands. We should instead make full use of woodland and grassland for carbon sequestration.
3.2 Carbon emissions from cassava-based fuel ethanol
production
Carbon emissions from bio-fuel ethanol are correlated with technological process. In particular, the secondary utilization of by-products is a key factor which affects carbon emissions.
3.2.1 Carbon emissions from fossil energy input during the
production
Coal consumption accounts for 76.7% of total energy consumption in China. Thermal power accounts for 82.98% of total generating capacity (NBS. 2009). Thus, we believe the power consumed for producing cassava-based fuel ethanol is thermal power. Firstly, different types of energy should be converted into standard coal, and then carbon emissions calculated. The main energy inputs and
the
Journal of Resources and Ecology V ol.3 No.1, 2012 60
carbon emissions are shown in Table 2.
According to Table 2 carbon emissions from the three different technologies are 0.51 kg, 0.35 kg and 0.65 kg per kilogram of bio-fuel ethanol respectively. This shows that improvements in production technology are essential to reduce carbon emissions. Carbon emissions can be reduced by 31.4% after utilizing new technology. Small and medium-sized enterprises have the greatest potential to reduce carbon emissions by introducing new technology. As shown in Fig. 3, the main sources of carbon emissions are cooking/liquefaction, distillation and dehydration. New technology greatly reduces carbon emissions from these sources. Carbon emissions from cooking/liquefaction, distillation and dehydration were reduced by 32.7%, 37.0% and 19.6% respectively when using new technology compared with old technology. Therefore, the enterprises should introduce new technology to radically reduce carbon emissions.
Items Input (unit) Data source
Old technology New technology Technology in
small and medium-sized
enterprises
Water 8–10 t t-1 ethanol a3–4t t-1 ethanol 12–15t t-1 ethanol Survey and reference (fresh water)
Steam 4.5–5.2 t t-1 2.2t t-1 ethanol — Survey and reference
ethanol a
Power 250 kWh t-1180 kWh t-1300 kWh t-1 ethanol Survey and reference
ethanol a ethanol
Natural gas — 0.9m3 t-1 ethanol — Survey
Fuel — — 1.2 L t-1 ethanol Survey
Chemical reagent — 1.98 kg t-1 ethanol 1.56 kg t-1 ethanol Survey
(H2SO4 etc.)
Microbial preparation — 3.75 kg t-1 ethanol 3.34 kg t-1 ethanol Survey
(amylase etc.)
Fungicide (penicillin etc.) — 0.08 kg t-1 ethanol — Survey
Equipment depreciation — — —
Total energy consumption 19.67 MJ kg-113.35 MJ kg-125.24 MJ kg-1 ethanol Survey and reference
ethanol b ethanol
19.82 MJ kg-1
ethanol c
Converted into 0.67 kg kg-10.46 kg kg-10.86 kg kg-1Converting
standard coal ethanol ethanol ethanol
Carbon emission 0.7559 0.7559 0.7559 IPCC
coefficient of standard coal
Carbon emission 0.51 kg kg-10.35 kg kg-10.65 kg kg-1Converting
ethanol ethanol ethanol
Table 2 Main energy inputs and carbon emissions
a: Reference (Hao et al. 2009); b: Reference (Dai et al. 2005); c: Reference (Dong et al. 2008)
Fig. 3 Carbon emission of cassava-based ethanol in different technical conditions.
YANG Hailong, et al .: Carbon Balance of Cassava-based Ethanol Fuel in China
61
adopting new technology. The cassava growth cycle and cassava fuel ethanol processing are the two main carbon emission sources. Carbon emissions from these two links accounts for 47% and 50% of total emissions. Carbon emission caused by the soil carbon pool destruction is the key factor during the cassava planting link.
Fig. 5 shows life cycle carbon emissions of different bio-fuels under different technical conditions. Carbon emission from maize bio-fuel ethanol is greater than that of other fuel ethanol. The highest emission of maize bio-fuel ethanol is two times more than gasoline. Carbon emission from maize bio-fuel ethanol in the most advanced technology is even higher than that of gasoline. This indicates that it is not rational to produce maize fuel ethanol using current technology.
Sugarcane fuel ethanol industry is mature in Brazil. Its carbon emission only takes up 17.4% of that of gasoline. It benefits from a wealth of sugarcane resources and advanced processing technology. The sugarcane fuel ethanol industry in Brazil has long existed. After decades of development, this industry chain is mature and greatly reduces carbon emissions.
Carbon emission from herbaceous cellulose fuel ethanol in America is 3.16g C MJ -1. Taking herbaceous cellulose as raw materials to produce bio-fuel can effectively avoid carbon emissions during planting raw material species. However, this technology is not mature and it cannot be used in large-scale commercial production. Technical problems hamper the development of this industry; however, the cellulosic fuel ethanol industry has potential once technical breakthroughs are achieved.
Considering food security, some countries such as China and Thailand, advocate the production of bio-fuel ethanol from non-food crops like cassava and sweet sorghum. Fig. 5 shows that the highest carbon emission of cassava bio-fuel ethanol is 33.53 g C MJ -1. The lowest emission is 12.44 g C MJ -1, which only accounts for 65.8% of that by gasoline. In this study, the life cycle carbon emission of cassava bio-fuel ethanol under old technical conditions is 24.16 g C MJ -1, which is higher than that produced by gasoline. However,
3.2.2 Substitution effect of by-products secondary
utilization
The main by-products are cassava dregs. Dregs can be used as manure or the materials for biogas and power. Using cassava dregs as manure would reduce carbon emissions to some extent. Cassava dregs are used to generate biogas or power which also replaces a certain amount of electrical energy and thermal energy consumption. All of these effects should be removed so that we can objectively assess carbon emissions throughout the life cycle.
Company research showed that cassava dregs were mainly used for cogeneration, which per kilogram bio-fuel ethanol would generate 0.47 kW·h power. The current thermal power generating efficiency is about 0.334 kg standard coal kW h -1 in China. It is equivalent to substitute 0.16 kg standard coal consumption. In other words, it equals a reduction of 0.12 kg in carbon emissions.
In small and medium-sized enterprises cassava dregs are mainly used for generating biogas or manure. This equals a reduction of 0.09 kg in carbon emissions. In summary, under new and old technical conditions, carbon emissions during cassava processing and transformation are 0.23 kg and 0.42 kg respectively.
3.3 Carbon emissions of cassava-based fuel ethanol
across the life cycle Carbon emissions during the transportation and consumption link are mainly generated by the fuel consumption of transport vehicles. Based on survey data, the distribution range of cassava fuel ethanol is about 300 km, and the fuel consumption intensity of the diesel truck is about 0.06 L t -1 km -1 . The carbon emission coefficient of diesel is 20.2 t C (TJ)-1 (IPCC 1996), namely 0.777 kg C L -1. Thus the carbon emission during the transportation and consumption link is calculated as 14 kg per ton cassava fuel ethanol.
It is shown in Fig.4 that total carbon emissions across the life cycle are 0.647 kg and 0.457 kg respectively in the old and new technical conditions. It is reduced by 29.4% after
Fig. 4 Life cycle carbon emission of cassava-based fuel
ethanol in different technical conditions.
Journal of Resources and Ecology V ol.3 No.1, 2012
62
emissions decrease to 16.93 g C MJ -1 after the application of new technology, lower than that of gasoline.
4 Conclusions
This study assessed carbon emissions from cassava bio-fuel ethanol across its life cycle in China. Comparative analysis with other bio-fuel ethanol was also done. The main conclusions are as follows.
(1) Carbon emissions during the cultivation link were mainly generated from the emission of fossil energy input, especially nitrogen fertilizer and the destruction of the soil carbon pool. Carbon emission from nitrogen fertilizer and soil carbon were 0.043 kg and 0.132 kg per kilogram fuel ethanol respectively, accounting for 9% and 29% of the total life cycle carbon emissions.
(2) Carbon emission during the processing link differs across different technologies. Carbon emission in this link is reduced 31% after the application of new technology, which are from 0.51 kg to 0.35 kg. New technology mainly reduces the energy consumption of raw material cooking, distillation and dehydration, while enhancing secondary utilization of by-products. All these improvements effectively reduce carbon emission.
(3) Carbon emissions during the transportation link are negligible because they only account for 2% to 3% of total emissions. The cassava bio-fuel ethanol industry in China is developing fast, but carbon emissions across the whole life cycle are higher than that of gasoline, with current processing technology. Therefore, improving production technology is the key point to achieve positive environmental benefits.
(4) It should be noted that we have considered carbon emissions caused by land use change.However, these emissions can be avoided if we plant cassava on marginal land. Life cycle carbon emissions will decrease to 12.14 g C MJ -1 if this part is removed: 64% of that of gasoline.
5 Discussion
Several studies have been conducted to assess the carbon emissions of bio-fuel ethanol. Most bio-fuel ethanols
cannot effectively reduce carbon emissions compared to gasoline. The carbon emission of herbaceous cellulose fuel ethanol in America is lower than that of gasoline. But the technology is not mature, and cannot be used in large-scale commercial production. Cassava fuel ethanol in China will achieve positive environmental benefits if the carbon emissions caused by soil carbon pool destruction are avoided. Additionally, it is noteworthy to emphasize that many benefits of cassava fuel ethanol cannot be captured adequately by our analysis. They are (i) reducing oil imports and saving foreign exchange, (ii) enhancing technological development, (iii) stimulating domestic agricultural production and expanding the market for domestic agricultural commodities, and (iv) generating rural employment and improving farmer income. If these benefits are taken into account in a green gas abatement cost analysis, the cost would be more favorable to cassava fuel ethanol.
6 Acknowledgments
This research was supported by the National Natural Science Foundation of China (40971270). The authors would like to thank the officers and farmers for help in cassava farming data collection in Wuming County, Guangxi Zhuang Autonomous Region. Thanks are also extended to Wei Xuebing and other technicians at Jiaolong Alcohol Energy Ltd. Co. for providing cassava bio-fuel ethanol processing-conversion data. We are also grateful to an anonymous reviewer for useful comments and suggestions.
References
Adler P, Del S J and Parton W J. https://www.wendangku.net/doc/c915246256.html, greenhouse gas flux of bioenergy cropping systems using DAYCENT. Ecology Application , 13(8):345-352. Atjay G L, Ketner P and Duvigneaud P. 1979.Terrestrial primary production and phytomass. In: Bolin B, Degens E T, Kempe S, Ketner P(eds). The Global Carbon Cycle. Chichester, UK: John Wiley and Sons. 129-181.Batjes N H. 1996.Total carbon and nitrogen in the soil of the world. Soil Sciences , 47: 151-163.
China Renewable Energy Development Strategy Research Group (CREDSRG). 2008. China renewable energy development strategy study series book-volume of biomass. Beijing: China Electric Power Press.
Dai D, Liu R H and Pu G Q. 2005. Evaluation of energy production efficiency of biomass based fuel ethanol program. Transactions of the CSAE
, 21(11): 121-123. (in Chinese)
Fig. 5 Life cycle carbon emission of different bio-fuels in different technical conditions.
1: reference (Zhang et al . 2009); 2: reference (CREDSRG 2008); 3: reference (Thu et al . 2007); 4: reference (IPCC 1996).
YANG Hailong, et al.: Carbon Balance of Cassava-based Ethanol Fuel in China63
Dong D D, Zhao D Q, Liao C P, et al. 2008. Energy consumption analysis in life cycle of cassava fuel ethanol production and the advantages of the new technology in energy consumption. Transactions of the CSAE, 24(7): 160-164. (in Chinese)
IEA. 2011.World energy outlook 2011. IEA.
Elsayed M, Matthews R and Mortimer N. 2003. Carbon and energy balances for a range of biofuel options. Sheffield Hallam University.
FAO. 2008. Food and agricultural situation—bioenergy: prospect, risk and chance. Rome.
Farrell A E, Plevin R J, Turner B T. et al. 2006. Ethanol can contribute to energy and environmental goals. Science, 311(5760): 506-508.
Hao H Y, Deng L K and Du J B. 2009. Discussion on energy comprehensive utilization pattern in cassava fuel ethanol production process. Cereal and Food Industry, 16(4): 30-33. (in Chinese)
Hu Z Y, Dai D and Zhang C. 2003. Life cycle assessment on mixed fuel of cassava-based ethanol and gasoline. Journal of Internal Combustion Engine, 21(5): 341-345. (in Chinese)
Hu Z Y, Dai D, Pu G Q, et al. 2004. Life cycle energy efficiency assessment of cassava-based fuel ethanol . Journal of Shanghai Jiao Tong University, 38(10): 1715-1718. (in Chinese)
Hu Z Y, Pu G Q and Wang C G. 2004. Life cycle assessment on emission of cassava-based ethanol. Automotive Engineering, 26(1): 16-19. (in Chinese)
Hu Z Y, Zhang C and Pu G Q. 2004. Life cycle assessment on energy-environment and economy of cassava-based ethanol and gasoline mixed fuel. Journal of Internal Combustion Engine, 25(1): 13-16. (in Chinese) IPCC. 1996. Climate Change 1995: The science of climate change (Report of Working Group 1): New York: Cambridge University Press, 1996, 4. Joseph F, Jason H, David T, et al. 2008. Land clearing and the biofuel carbon debt. Science, 319 (5867): 1235-1238.
National Bureau of Statistics of China (NBS). 2009. China Statistical Yearbook. Beijing: China Statistics Press.
Ni J B, Wang W B, Tian K, et al. 2007. A Study on soil organic carbon content change of betula alnoides plantation in hot areas of Yunnan
Province. Journal of West China Forestry Science, 36(1):57-60. (in Chinese)
Renton R and Dominick V S. 2007. Carbon mitigation by biofuels or by saving and restoring forests? Science, 317: 902.
Revin P B. 2001. Carbon balance of sugarcane bioenergy systems. Biomass and Bioenergy, 20(5): 361-370.
Schlamadinger B, Spitzer J and Kohlmaier G H, et al. 1995. Carbon balance of bioenergy from logging residues. Biomass and Bioenergy, 8(4):221-234.
Searchinger T, Heimlich R, Houghton R A. et al. 2008. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land use change. Science, 319(5867):1238-1240.
Soil Sciences Academy of Agricultural Chemistry Committee (SSAACC). 1989. Routine analysis methods of soil agricultural chemical. Beijing: Science Press.
Thu L T N, Shabbir H G, Heewala, et al. 2007. Energy balance and GHG-abatement cost of cassava utilization for fuel ethanol in Thailand. Energy Policy, 35, 4585-4596.
Tropical Research Institute. 2008. Some biofuels are worse environmentally than fossil fuels. Science Daily, 2008-01-03.
Wei Z Y, Qi Z P and Li K M. 2007. Soil nutrition and countermeasures of cassava plants in Wuming. Journal of Anhui Agricultural. Science, 35(32):10385-10387. (in Chinese)
Wuming Bureau of Statistics (WBS). 2008. Wuming Statistical Yearbook. Wuming: Statistics Press.
Zhang X L, Chang S Y, Ou X M, et al. 2009. A study on resources and technical potential of the development of Chinese bio-liquid fuel. Energy, Environment and Economic Research Institute of Tsinghua University. Zhang Z J, Zhu B and Xiang H Y. 2010. N2O emission and denitrification of N fertilizer on winter wheat in southwest purple soil. Journal of Agriculture Environmental Science, 29(10):2033-2040. (in Chinese) Zhang Z S and Yuan X G. 2006. Carbon balance analysis of corn fuel ethanol in life cycle. Environmental Science, 27(4): 616-619.
木薯燃料乙醇的碳效应分析
杨海龙1,2, 吕 耀1, 封志明1
1 中国科学院地理科学与资源研究所，北京 100101
2 中国科学院研究生院，北京 100049
摘 要：出于能源安全的考虑及对温室气体减排的关注，世界各国近些年大力发展生物液体燃料，我国政府提倡以木薯等非粮作物为原料生产燃料乙醇。但一直以来科学家们对生物液体燃料的碳效应争论激烈，争论的焦点在于原料种植对土壤碳库的影响及不同技术条件下副产品利用的评估。本文通过建立碳平衡分析模型，将原料种植对土壤碳库影响及副产品利用的替代效应纳入研究体系，评估了我国木薯燃料乙醇生命周期内的碳排放，研究结果显示：我国每生产单位质量(1kg)木薯燃料乙醇，在新旧两种技术条件下的碳排放分别为0.457kg和0.647kg。碳排放主要来自于氮肥的使用、木薯种植对土壤碳库的破坏及木薯燃料乙醇加工转化过程能源投入，在新技术条件下分别占总排放量的9%、29%和50%。以汽油的碳排放为参照，在旧技术条件下我国木薯燃料乙醇碳排放呈现负效益，在新技术条件下其碳排放为汽油的90%，倘若能避免对土壤碳库的破坏，则这一比例将下降到64%。因此，为了促进我国木薯燃料乙醇的发展，首先应该引导农民合理施肥，利用边际土地种植木薯，不转换林地、草地等土地类型的利用方式；此外，要开发高效节能的燃料乙醇转化技术及加强对副产品的二次利用。
关键词： 燃料乙醇；生命周期分析（LCA）；碳效应；碳平衡分析；木薯