Article pubs.acs.org/est
Life Cycle Water Footprints of Nonfood Biomass Fuels in China Tingting Zhang, Xiaomin Xie,* and Zhen Huang Key Laboratory for Power machinery and Engineering of M. O. E., Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, 200240 Shanghai, People’s Republic of China S Supporting Information *
ABSTRACT: This study presented life cycle water footprints (WFs) of biofuels from biomass in China based on the resource distribution, climate conditions, soil conditions and crop growing characteristics. Life cycle WFs including blue, green and gray water were evaluated for the selected fuel pathways. Geographical differences of water requirements were revealed to be different by locations. The results indicated that water irrigation requirements were significantly different from crop to crop, ranging from 2− 293, 78−137, and 17−621 m3/ha, for sweet sorghum, cassava, and Jatropha curcas L., respectively. Four biofuel pathways were selected on this basis to analyze the life cycle WF: cassava based bioethanol in Guangxi, sweet sorghum based bioethanol in Northeast China, Jatropha curcal L. based biodiesel in Yunnan and microalgae based biodiesel in Hainan. The life cycle WFs of bioethanol from cassava and sweet sorghum were 3708, and 17 156 m3 per ton of bioethanol, respectively, whereas for biodiesel produced from Jatropha curcas L. and microalgae, they were 5787, and 31 361 m3 per ton of biodiesel, respectively. The crop growing stage was the main contributor to the whole life cycle of each pathway. Compared to blue and green water, gray water was significant due to the use of fertilizer during the growing of biomass. From the perspective of the WF, cassava based bioethanol in Guangxi and Jatropha based biodiesel in Yunnan were suitable for promotion, whereas the promotion for microalage based biodiesel in Hainan required improvement on technology.
■
INTRODUCTION
more than 61% of water was consumed by agriculture due to irrigation.7 The concept of water footprint (WF) was proposed to analyze how biomass based biofuels relate to issues of water scarcity and pollution and to see how biofuels can become more sustainable from a water perspective.9 It was first introduced by Hoekstra in 200310 and subsequently elaborated by his team.6,9,11−13 They analyzed the WFs for lots of products including crops, agricultural products, biofuel and even transport systems on national scale. The early studies regarding the water consumption for biofuel producing processes focused on the water withdraw and irrigation requirements.14,15 Harto et al.16 adopted a hybrid method to evaluate the life cycle water use of ten low-carbon transportation fuel pathways including corn ethanol, cellulosic ethanol, soy biodiesel and algae biodiesel. However, the water requirements associated the crop growing was still the irrigation data. Not all of the irrigation water were consumed by crops, with some of which may runoff back to the watershed. The method conducted by Hoekstra et al. was considered as the most comprehensive method to assess water requirements of various goods for different countries and regions in a spatially explicit way so far,11 because they subdivided the different kinds of water
Biomass is considered a promising source to produce biofuels for mitigating fossil energy depletion and greenhouse gas (GHG) emissions. By the end of 2011, the world’s total biofuel production reached 110 billion liters, of which 51.2% was contributed by the United States.1 In China, the biofuel production was 2.7 billion liters, including 2.26 billion liters of bioethanol and 0.45 billion liters of biodiesel.1 However, these outputs are far behind the Chinese mandated target of 10 million ton (equivalent to 12.7 billion liters) of noncrop bioethanol and 2 million ton (equivalent to 2.3 billion liters) of biodiesel by 2020.2 Thus, more biomass resources will be required to meet the ambitious biofuel targets due to its merits like biodegradable, nontoxic and more favorable combustion emission profile.3 For biofuels produced from biomass, one should not only be aware of the issues of energy consumption and GHG emission but also should consider the access to available land and water.4 Ensuring inexpensive and clean water is an overriding global challenge, because (1) large quantities of water use are needed to grow fuel crops, and (2) water pollution is exacerbated by agricultural drainage due to the large contents of fertilizers, pesticides and sediment.5 As a big agricultural nation, the water consumption of China for crop production is ranked as the second largest after India.6 In China, the total amounts of water resource and water consumption were 2770 billion m3 7 and 610.7 billion m3 8 in 2011. Of the total water consumption, © 2014 American Chemical Society
Received: Revised: Accepted: Published: 4137
November 4, 2013 January 5, 2014 January 8, 2014 January 8, 2014 dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
demand with blue, green and gray WFs.6,17 However, the WFs of biofuel production processes in factories and the combustion of biofuel in vehicles are not considered in their studies. Wu et al.18,19 extended the methodology of assessing the WF on the basis of Hoekstra et al. with extensive local data to reflect local agricultural practices with increased resolution. Their emphasis was on the water consumption during the crop growing stage based on a high resolution spatial and temporal distribution model. Few studies consider the WF evaluation of biofuel production from biomass from the view of the life cycle, especially for China. This kind of work is significantly meaningful for policy-making. In China, bioethanol production from food crops has been shut down, and nonfood biomass has become the new focus.2 To address the interactions of the increasing of nonfood biofuels production and their water requirements in China, some potential terrestrial biomass were selected in this study. These crops also represent the roadmap of developing biofuels for China in the near future.
indicated as nitrogen, which is one of the several agricultural inputs in the research of Hoekstra et al.9,11,12 However, other inputs like phosphate, which is also used as common fertilizer in China, should also be considered. Thus, gray WF considered in this study contained both nitrogen and phosphorus as representative indicators. As the growing condition for microalgae was different from the other three terrestrial crops, the water footprint calculation was conducted according to mass and energy balance. For the biofuels converting stage, the WFs were calculated based on the mass and energy balance in the factories. The water consumption for biomass and biofuel transportation and distribution was assumed to be 0.18 m3 per ton.20 The water consumption related to the biofuel combustion was minimal and was ignored here. Main Data Sources. The climate data required for green and blue water estimation in the selected location were primarily derived from the China Statistic Yearbook 7 for the period of 2008−2012. The related data are listed in Tables SI2−SI-7, shown in the Supporting Information. Crop data and irrigation information are available from previous research21−23 and field investigations. Fertilizer utilization information shown in Table SI-1 in the Supporting Information was used to evaluate the gray water for each feedstock. Data for biofuel conversion in the factories was based on the well operated biofuel producing factories in China. Detailed data was discussed in section 4. Water Footprint Allocation. Feedstock Allocation. For each crop, the water consumed during the growth is generally referred to the entire plant including grain and straw, and is linearly related to the mass production in each part of a plant. Blue, green and gray water volumes for each crop were allocated into crop grain and its residue was collected for biofuel production based on crop harvest index (HI) and residual removal assumption.18 Mass-based allocation method18 was considered in this study for feedstock water allocation between primary product and residue. The allocation ratios for sweet sorghum and microalgae were assumed to be 0.6526 and 0.75, respectively. As for cassava and Jatropha, because their residues are not deemed as a feedstock, the water footprints associated with their growth were entirely allocated to the cassava and Jatropha seeds. Coproduct Partitioning. Lots of previous research results indicated that the feedstock growing stage was the main water intensive stage over the whole fuel cycle.24 The WF for the biofuel production in the factory only accounts for a small fraction16,25 and would not influence the life cycle results. However, the WF associated with the coproduct in the biofuel production factory was also considered in this study to give a comprehensive assessment. The allocation ratios for sweet sorghum, cassava, Jatropha and microalgae were assumed to be 0.86,18 0.83, 0.91 and 0.9126 by mass, respectively. Selection of Representative Pathways. Resource Distribution of Potential Biomass. Table 1 shows the annual production for the feedstock by the end of 2011 in China. The annual output trend of the three terrestrial crops during the past three decades was shown in Figure SI-1 in the Supporting Information. The production of cassava and Jatropha curcas kept stable growth, while the production of sweet sorghum declined with each passing year. Figure 2 shows the visualized biomass production distribution, which illustrated the biofuel development potential in China. Sweet sorghum27 is an annual grass that has been widely recognized as a promising sugar feedstock crop. It can be grown
■
METHODS Definition of System Boundary. The life cycle producing process of the selected biofuel pathways were exhibited in Figure 1. Four biofuel pathways considered in this study
Figure 1. System boundary of life cycle water footprint for biofuel production from biomass: Blue dotted line refers to the indirect water footprint due to various process fuels and materials; red dotted line refers to the producing process for biofuel production; faint green arrow refers to the green water footprint; faint blue arrow refers to the blue water footprint; faint gray arrow refers to the gray water footprint.
included bioethanol from cassava (CBE) and sweet sorghum (SBE), biodiesel from Jatropha curcas L. (JBD) and microalgae (MBD). Four types of water use were estimated: green water footprint (WFgreen), blue water footprint (WFblue), gray water footprint (WFgray) and life cycle water footprint (WFLC). Green WF refers to the daily rainwater evapotranspiration over the length of the growing period of biomass.17 Blue WF is the consumptive use of irrigation water. It contains two parts: the direct water due to the consumptive use of irrigation, and the indirect water attributed to the use of process fuels and materials.19 Gray WF refers to the amount of water needed to assimilate pollutants discharged into the natural water system during the growth of biomass and the wastewater drainage during the biofuel production. Life cycle water footprint refers to the sum of three WFs for each process. The functional unit was represented as m3 water per ton of biofuel produced. Calculation of WF for Each Process. The detailed calculation of green, blue and gray WFs for the growth of three terrestrial plants followed the approach proposed by Hoekstra et al., which is presented in the Supporting Information.9 It should be noted that the gray WF is only 4138
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
are listed in Table 1, including Guangxi, Guangdong, Hainan and Yunnan. Guangxi is located in subtropical regions and very suitable for growing cassava due to its suitable climate with high temperatures, plentiful rainfall and autumn droughts. The total planting area and yield of cassava in Guangxi was more than 60% of the total national amount of China.31 Thus, Guangxi was chosen as the representative location for cassava based bioethanol. Jatropha curcas L. is a perennial shrub that grows well in semitropical conditions, on poor soils and requires little care. It needs a minimum of 600 mm of rain, even in times of extended drought. Jatropha seeds contain about 40−48% oil depending on different countries.32 Jatropha is considered to be the most promising tree species used to produce biodiesel in China.33 It is estimated that there are 1.99 × 106 ha of suitable land and 5.57 × 106 ha of moderately suitable land in Southwestern China.33 Yunnan, Sichuan and Guizhou were the productionintensive areas, with 95% of the total planting area in China.34 Wu et al.34 concluded that Yunnan was the most important region for the development of Jatropha based biodiesel in the future on the basis of remote sensing data, meteorological observations and soil survey data. As Figure 3 shows, the annual Jatropha seeds production in Yunnan was very considerable. Therefore, the Yuannan province in Southwestern China was chosen to produce biodiesel from Jatropha curcas seeds. Microalgae have been considered as the ultimate alternative to depleting resources of petro-diesel due to their high cellular concentration of lipids, resources and economic sustainability.35 A lot of research has been conducted to try to break through the bottlenecks encountered during the production of microalgal biodiesel.36−38 Large-scale outdoor open ponds were considered to be easy to scale-up, operate and have lower capital costs.39 However, its production was easily affected by
Table 1. Production Status of the Main Biomass of China in 2011 area harvested: ha
annual production: ton
yield: ton/ha
cassava
27575741
451507541
16.4
sweet sorghum
50136041
205431641
4.1
8370743
418535
544
48
13915
290
feedstock
Jatropha curcas L. microalgae 45
main producing area Guangxi, Guangdong, Hainan, Yunnan42 Inner Mongalia, Northeast China, Sichuan, Guizhou29 Yunnan, Sichuan, Guizhou43 Hainan22
in the semiarid area. In general, sweet sorghum produces 2 ton/ ha of grains and 50 t/ha of stems,28 with stem juice rich in sucrose, glucose and fructose. In this study, ethanol was assumed to be produced from the stem. In north China, sweet sorghum produces 1.8−5.0 ton/ha grain yield,23 and 60 ton/ha stalk.21 Inner Mongolia, Jilin, Liaoning, and Heilongjiang have the highest productive potentials of sweet sorghum based ethanol, followed by Sichuan, Guizhou, Hebei, Gansu, Shanxi, and other provinces. The total production in the three northeastern provinces shared 65.2% of the national total production.29 Thus, the Northeast region (Heilongjiang, Jilin, and Liaoning) was chosen as the representative site to produce sweet sorghum based ethanol. Cassava is a kind of starch-containing feedstock with about 75% of the starch content in the dry cassava chips.30 It can be grown in the region with annual rainfall of 600−6000 mm. The technology to convert starch to ethanol is based on the hydrolysis of starch and fermentation of sugar.30 In China, most of the cassava cultivation is undertaken by individual cultivators in widely dispersed areas. The primary cassava producing areas
Figure 2. Distribution of biomass production and the selected representative locations in China. 4139
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Figure 3. Distribution of irrigated water requirements for different biomass in China: (1) Liaoning; (2) Jilin; (3) Heilongjiang; (4) Inner Mongolia; (5) Sichuan; (6) Chongqing; (7) Guizhou; (8) Gansu; (9) Shanxi; (10) Guangxi; (11) Guangzhou; (12) Fujian; (13) Henan; (14) Hubei; (15) Hunan; (16) Yunnan.
outdoor day-to-day weather conditions.38 Our previous research22 investigated regional microalgae production based on different climate conditions in different regions according to an outdoor pond design.40 It showed that the Hainan province is the most appropriate region to grow microalgae with an average growth rate of 12.6 g/(m2d). Water Irrigation Requirements in the Main Producing Areas. Figure 3 indicates the crop irrigation requirements in the main producing areas for the three terrestrial plants. Figure 3a shows the main producing areas for the three selected terrestrial crops in China. Figure 3b,c,d shows the calculated water irrigation requirements for different crops in different regions in China. It indicated that the irrigation requirements of three plants were different both from species and regions. The irrigation requirements for sweet sorghum, cassava and Jatropha curcas ranged from 2 to 293, 78−137, and 17−621 m3/ha, respectively. Jatropha curcas showed the highest average irrigation requirements, followed by cassava and sweet sorghum. This is because Jatropha curcas has the longest crop growth cycle, whereas sweet sorghum has the shortest growth cycle. The longer growth cycle, the more water evaporated through evapotranspiration of the plant. For the same crop growth in different regions, irrigation requirements also showed significant changes. This kind of variations was close to the local climate where the crops were planted. Take sweet sorghum for example (Figure 3b), the irrigation requirements in Sichuan, Chongqing and Guizhou were nonsignificant because there was plenty of rainfall during the crop growth in those areas. On the contrary, in arid inland areas with little rainfall like Gansu and Inner Mongolia, there was not
enough precipitation to meet the water requirement for the crop growth. Therefore, extra irrigation water was required to well supply the growth of sweet sorghum. Many researchers emphasized the importance of taking regional specific into account when assessing the water requirements of biofuel production.11,15,18 Therefore, the suitable location we selected was not only based on the irrigation requirement but also combined with the production and the local supportive policies. Hence, Northeast China (Liaoning, Jilin, and Heilongjiang) was chosen for the production of SBE, Guangxi was selected as the producing location of CBE and Yunnan was the representative region for JBD. The average irrigation requirements for SBE, CBE and JBD were 95.8, 77.9, and 621.2 m3/ha, respectively.
■
PROCESS DESCRIPTIONS FOR EACH PATHWAY Crop Growing Stage. Three Terrestrial Plants. To calculate the green and blue WF of three terrestrial plants, climate data in Northeast China are required, including rainfall, temperature (maximum and minimum), sunshine hours, relative humidity and wind. In this study, the rainfall data from a range of years (2008−2012) was collected.7 And then, these data were further processed into the results for normal (Nor), dry and wet years under the methodology of CROPWAT 8.0 46 as shown in Tables SI-2, SI-4 and SI-6 in the Supporting Information. The data of relative humidity and sunshine hours were also collected7 and processed following the same method as that for rainfall.46 The wind data were extracted from the database of Food and Agricultural Organization (FAO).47 The temperature data regarding the 4140
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
average monthly extreme low and high temperature were collected from the local weather stations on the Internet. In the temperate zone of North China, sweet sorghum is usually sowed in late April and harvested after 111−165 days.23 The plant height often ranges from 75 to 350 mm.48 In this study, 250 mm was chosen as the optimal crop height to calculate the water requirements. The growing stage of cassava includes four periods: (1) a seeding period of 60 days; (2) a root forming period of 50 days with the highest height of 1 m; (3) a root enlargement period of 120 days; and (4) a root maturity period of 30 days. Jatropha usually sprouts buds at the end of March or in early April every year. The seeds begin to mature in May and begin to drop in the middle of November.43 The plant height of Jatropha ranges from 4 to 5.5 m. Soil conditions and correction factors were cited from CROPWAT 8.0.46 On the basis of the above assumptions, the crop evapotranspiration under standard conditions (ETc), effective rainfall (Effrain), and irrigation requirement (Irr) can be obtained by inputting these data into the CROPWAT 8.046 model. Furthermore, the blue and green WF can be also calculated9 with the above data. Results are listed in Tables SI3, SI-5 and SI-7 (Supporting Information). The fertilizer application data (Table SI-1, Supporting Information), the production yield of each crop (Table 1), the leaching-runoff fraction (10%9) and the maximum acceptable concentration (0.002 kg N/m3, and 0.0004 kg P/m3 49) were used to obtain the gray water footprint. The water consumption for producing 1 kg of N and P were assumed to be 0.0362 and 0.1003 m3.50 Results are shown in Tables SI-3, SI-5 and SI-7 (Supporting Information). Microalgae. The production factory of microalgae based biodiesel was assumed to be located in the Hainan province, China. The construction of the factory was modified on the basis of outdoor high rate ponds (HRP),40 and the detailed plant design is shown in the Supporting Information. In brief, there were 12 HRPs designed in this plant with 4 ha of individual area for each pond. The water depth in the pond was about 0.3 m. Mixing was provided by a paddle wheel in each pond to ensure a mean velocity of 0.25 m/s. Freshwater was used for the growth of the algae. The water loss in Hainan was determined by the average annual evaporation in Haikou, Hainan. Thus, the water loss due to the evaporation of the pond was about 0.475 cm/day.51 When the microalgae were ready to be harvested, the broth was directed to the flocculation unit. Forty percent of the water after flocculation was recycled to the HRPs. The main process material and energy inputs are exhibited in Table SI-8 in the Supporting Information. The data listed in the table was used to calculate the indirect water footprint. Biofuel Conversion Stage. Bioethanol Production. Sweet Sorghum. After harvesting, piling and transportation, sweet sorghum was sent to a nearby ethanol production factory. The producing process in this factory was based on a demonstration factory operated in Inner Mongolia, China.52 Advanced solidstate fermentation (ASSF) was employed. The main process included smashing of the sweet sorghum stalk, preheating of the mashed material, preparation of an inoculation medium, fermentation, stripping, and distillation. The main flowchart of this process is shown in Figure 4. From this figure, we can see that 16 ton of sweet sorghum stalk was used to produce 6.62 ton of crude of ethanol (containing 1 ton of 99.5% ethanol) and 16.43 ton of vinasse as coproduct. In this factory, 50% of
Figure 4. Flowchart of material balance and energy inputs for sweet sorghum based ethanol in a demonstration factory in China:52 red arrows refer to the energy input in each stage; green and black arrows refer to the materials balance of the system.
the vinasse was used as cattle feed, and the rest was used as fuel to generate steam for the demonstration system.52 In the ASSF demonstration factory, about 2.37 m3 of water was required to produce 1 ton of 99.5% bioethanol, with 0.08 m3 of condensate water produced.52 Therefore, the direct blue and gray water footprints in this factory were assumed to be 2.37 and 0.08 m3/ ton of 99.5% bioethanol, respectively. In addition, indirect water footprint was also introduced based on the process material and energy inputs such as electricity shown in Figure 4. The water consumption for electricity generation from coal was assumed to be 3.971 L/kWh.16 The electricity input for each process was exhibited in Figure 4, with a total electricity input of 1209.7 MJ/ton of ethanol (99.5%). Thus, the indirect water footprint in this factory was 1.34 m3/ton of bioethanol (99.5%). Cassava. The cassava based ethanol factory was based on a well operated plant located in Beihai, Guangxi. The date related to the ethanol conversion was from our local investigation. In this factory, 1 ton of ethanol can be obtained from 7 ton of fresh cassava or 2.8 ton of dried cassava chips. A batch fermentation process was employed. The conversion process contains smashing, liquefaction, fermentation, rectification and refinery. The concentration of ethanol derived from this factory was about 94−99%. The residue after the fermentation was dried to a solid content of 60%, and then combusted in the utility boiler to generate electricity. The water requirement for producing 1 ton of ethanol was about 2.41−7.60 m3. Biodiesel Production. Oil extracted from Jatropha seeds and microalgae was transported to the nearby biodiesel conversion factory. As there is no commercial biodiesel production factory from microalgae, the biodiesel conversion process was assumed to be same as Jatropha seeds oil. In the factory, homogeneous alkali catalysis was adopted to convert oil into biodiesel.26 The amounts of catalyst and methanol were 0.010 and 0.117 ton/ ton BD. The yield of biodiesel was about 78%. The water consumption in the factory was about 2.035 m3/ton biodiesel produced. The water requirement for producing 1 ton of methanol was 10 m3.20 4141
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Table 2. Direct, Indirect and Life Cycle Water Footprints for Each Biofuel Pathway direct WF (m3/ton biofuel) biofuel pathway
process
CBE
crop growing crop transport BE conversion BE transport BE utilization crop growing crop transport BE conversion BE transport BE utilization crop growing transport BD conversion BD transport BD utilization culture transport BD conversion BD transport BD Utilization
SBE
JBD
MBD
blue 0.00 0.18 6.33 0.18 0.00 0.00 0.18 2.37 0.18 0.00 0.00 0.18 0.26 0.18 0.00 15244 0.00 0.35 0.18 0.00
green 659 0.00 0.00 0.00 0.00 1514 0.00 0.00 0.00 0.00 960 0.00 0.00 0.00 0.00 263 0.00 0.00 0.00 0.00
gray 3021 0.00 0.08 0.00 0.00 15597 0.00 0.08 0.00 0.00 4201 0.00 0.03 0.00 0.00 15803 0.00 0.03 00.00 00.00
indirect WF (m3/ton biofuel) blue 20.00 0.05 1.50 0.03 0.00 40.29 0.05 1.34 0.05 0.00 24.10 0.05 1.75 0.05 0.00 41.00 0.00 9.68 0.05 0.00
Biofuel Transportation and Distribution. The direct water consumption during bioethanol transportation and distribution was assumed to be 0.18 m3 per ton of ethanol.20 Although the indirect electricity and diesel consumption was 2.74 kWh/ton and 9.4 L/ton of ethanol.20 The water consumption of diesel production was about 3.9 L per liter of diesel.16 The resulting water footprint for bioethanol transportation and distribution was 0.23 m3/ton of bioethanol. In this study, the WF of diesel transportation and distribution was assumed to be the same as bioethanol.
green 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
gray 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
life cycle WF (m3/ton biofuel) blue 20.00 0.23 7.83 0.18 0.00 40.29 0.23 3.71 0.18 0.00 24.10 0.23 2.01 0.18 0.00 15285 0.00 10.03 0.18 0.00
green 659 0.00 0.00 0.00 0.00 1514 0.00 0.00 0.00 0.00 960 0.00 0.00 0.00 0.00 263.00 0.00 0.00 0.00 0.00
gray 3021 0.00 0.08 0.00 0.00 15597 0.00 0.08 0.00 0.00 4201 0.00 0.03 0.00 0.00 15803 0.00 0.03 0.00 0.00
total 3700 0.23 7.91 0.23 0.00 17152 0.23 3.79 0.23 0.000 5185 0.23 2.04 0.23 0.00 31351 0.00 10.06 0.23 0.00
direct WF. Gray WF was found to be a positive correlation with fertilizer use during the crop growth. The fertilizer use of sweet sorghum and microalgae were high, which resulted in high gray WF. The WFs of the biofuel conversion stage were small, as shown in Table 2. The WF of bioethanol processing factory for cassava and sweet sorghum were 7.91 and 3.79 m3/ton of bioethanol produced, whereas in the biodiesel processing factory for Jatropha and microalgae, the WF were 2.04 and 10.06 m3/ton of biodiesel produced. The life cycle WF during the biofuel transport and distribution was about 0.23 m3/ton of biofuel listed in Table 2. The influence of indirect water footprint was not significant for the four biofuel pathways. Life Cycle Water Footprint of Four Biofuel Pathways. Figure 5 exhibits the life cycle WFs of four biofuel pathways. Bioethanol produced from cassava and sweet sorghum had the life cycle WF of 3708 and 17 156 m3/ton bioethanol, respectively. Biodiesel produced from Jatropha curcas and microalgae had the life cycle WF of 5787, and 31 361 m3/ton biodiesel, respectively.
■
WATER FOOTPRINT RESULTS AND DISCUSSIONS Comparison of Water Footprints by Processes. In this section, the WFs of four selected biofuel pathways were analyzed based on the aforementioned suitable location. The results of WF contain indirect WF and direct WF in the form of blue, green and gray type. Indirect water refers to the water requirement related to the input of process fuel, energy and materials. In this study, the water footprints embodied in the process inputs are only considered as blue water. The detailed WF of each process of each biofuel pathway is show in Table 2. During the crop growing stage, direct water footprints showed great variability from species to species. The total direct WFs of the four biomasses in the selected locations ranged from 3680 to 31 310 m3/ton of biofuel produced. The direct green WFs of the three terrestrial plants (sweet sorghum, cassava and Jatropha curcas) were 659, 1514 and 960 m3/ton, respectively, whereas it was 263 m3/ton for microalgae. As for direct blue WF, cassava, sweet sorghum, and Jatropha had no contribution to the blue WF, whereas microalgae had significant direct blue WF with 15 244 m3/ton of biodiesel produced. This is because the rainfall in these regions can meet the water requirements for the growth of cassava in Guangxi, sweet sorghum in Northeast China and Jatropha curcas in Yunnan, according to our field investigation and others’ research.30 However, microalgae need a lot of freshwater to sustain growth in an aquatic environment. Among all four biomass, direct gray water accounted for a large part of total
Figure 5. Life cycle water footprints of different biofuels. 4142
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Manufacturing (China) Co. Ltd. The authors thank the “Morningstar Young Scholars Program” and “Graduate Student Innovation Ability Raise Funds” supported by Shanghai Jiao Tong University.
For each biofuel producing process, the gray WF was the biggest contributor to the life cycle water footprint. For CBE, gray WF shared 81.5% of the life cycle WF; for SBE, it shared 90.9% of the life cycle WF; for JBE, gray WF accounted for 81.0% of the life cycle WF. The high gray water ratio of the three terrestrial plants is attributed to the large inputs of fertilizer use and the runoff during the crop growth. Compared to the three terrestrial plants, microalgae had the highest life cycle water footprint. Gray WF and blue WF of microalgae based biodiesel accounted for 50.4% and 48.8%, respectively. This is because more water is required to keep the aquatic environment for microalgae, and more fertilizer is required to provide the nutrients for microalgae. If fertilizer is entirely or partially replaced by wastewater rich in nutrients, the gray water footprint of microalgae would drop drastically. In general, in terms of life cycle water footprints, bioethanol from cassava in Guangxi and biodiesel from Jatropha curcas in Yunnan are more attractive. Bioethanol from sweet sorghum in Northeast China and biodiesel from microalgae in Hainan are water-stressful. Fortunately, the freshwater in these regions is available.53 Therefore, the development of the proposed biofuel production from different biomass is feasible from the perspective of life cycle water footprints. Policy Suggestion. China has mandated to increase the biofuel production, including 4 million ton of bioethanol and 1 million ton of biodiesel by 2015.54 The main biomass promoted was nonfood biomass, such as cassava, sweet sorghum, Jatropha curcas and microalgae. Quantifying water requirements on a regional basis especially distinguishing blue, green and gray water components is important for elucidating how biofuel policies influence national and local water resources. Cassava based bioethanol should be placed on the first developing agenda due to the mature technology in China and the smallest WF. Sweet sorghum is also important to diversify the biomass resource especially in north region where it is the main producing region in China. However, more efficient technology is required to improve the conversion rate. The WF of Jatropha curcas based biodiesel is also small but the land suitable for planting Jatropha is limited. Marginal land was proposed to grow Jatropha to increase the yield of seeds. However, this would lead to more severe environmental issues due to the vulnerability of this kind of land. The current focus of developing Jatropha curcas based biodiesel may be on the improvement of seeds yield. The WF of microalgae is the highest but it grows fast and has high oil content. Microalgae is a very promising resource if the consumed freshwater would be replaced by other water like wastewater or seawater.
■
Notes
The authors declare no competing financial interest.
■
(1) EIA. International energy statistics-total biofuels production, 2013.06.26 ed.; U.S. Energy Information Administration: Washington, DC, 2013. Available from: . (2) NDRC. Mid-Long term Development Plan for Renewable Energy; The National Development and Reform Commission: Beijing, China, 2007; pp 19−22. Available from: . (3) Ribeiro, A.; Carvalho, J.; Castro, J.; Araújo, J.; Vilarinho, C.; Castro, F. Alternative feedstocks for biodiesel production. Mater. Sci. Forum 2012, 730−732, 623−629. (4) Ishola, M. M.; Brandberg, T.; Sanni, S. A.; Taherzadeh, M. J. Biofuels in Nigeria: A critical and strategic evaluation. Renewable Energy 2013, 55, 554−560. (5) Dominguez-Faus, R.; Powers, S. E.; Burken, J. G.; Alvarez, P. J. The water footprint of biofuels: A drink or drive issue? Environ. Sci. Technol. 2009, 43 (9), 3005−3010. (6) Mekonnen, M. M.; Hoekstra, A. Y. The green, blue and grey water footprint of crops and derived crop products. Hydrol. Earth Syst. Sci. 2011, 15 (5), 1577−1600. (7) NBSC. China Statistical Yearbook 2012; National Bureau of Statistics of China: Beijing, China, 2013. (8) NBSC. Environmental Statistics Data 2011; National Bureau of Statistics of China: Beijing, China, 2013. Available from: . (9) Hoekstra, A. Y.; Chapagain, A. K.; Aldaya, M. M.; Mekonnen, M. M. The water footprint assessment manual: setting the global standard; Earthscan: London, UK, 2011. (10) Hoekstra, A. Y. Virtual water trade: proceedings of the international expert meeting on virtual water trade; IHE: Delft, The Netherlands, 2003. (11) Gerbens-Leenes, W.; Hoekstra, A. Y. The water footprint of sweeteners and bio-ethanol. Environ. Int. 2012, 40 (1), 202−211. (12) Gerbens-Leenes, P. W.; van Lienden, A. R.; Hoekstra, A. Y.; van der Meer, T. H. Biofuel scenarios in a water perspective: The global blue and green water footprint of road transport in 2030. Global Environ. Change 2012, 22 (3), 764−775. (13) Gerbens-Leenes, W.; Hoekstra, A. Y. The water footprint of biofuel-based transport. Energy Environ. Sci. 2011, 4 (8), 2658−2668. (14) King, C. W.; Webber, M. E. Water intensity of transportation. Environ. Sci. Technol. 2008, 42 (21), 7866−7872. (15) Chiu, Y. W.; Walseth, B.; Suh, S. Water embodied in bioethanol in the United States. Environ. Sci. Technol. 2009, 43 (8), 2688−2692. (16) Harto, C.; Meyers, R.; Williams, E. Life cycle water use of lowcarbon transport fuels. Energy Policy 2010, 38 (9), 4933−4944. (17) Gerbens-Leenes, W.; Hoekstra, A. Y.; Van Der Meer, T. H. The water footprint of bioenergy. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (25), 10219−10223. (18) Chiu, Y. W.; Wu, M. Assessing county-level water footprints of different cellulosic-biofuel feedstock pathways. Environ. Sci. Technol. 2012, 46 (16), 9155−9162. (19) Wu, M.; Chiu, Y.; Demissie, Y. Quantifying the regional water footprint of biofuel production by incorporating hydrologic modeling. Water Resour. Res. 2012, 48, 10. (20) Xing, A.; Ma, J.; Zhang, Y.; Wang, Y.; Jin, Y. Life cycle assessment of resource and energy consumption for production of biodiesel. Chin. J. Process Eng. 2010, 10 (2), 314−320.
ASSOCIATED CONTENT
S Supporting Information *
Additional information including calculation of WF, assumptions for microalgal biodiesel plant, Table SI-1∼SI-8 and Figure SI-1. This material is available free of charge via the Internet at http://pubs.acs.org.
■
REFERENCES
AUTHOR INFORMATION
Corresponding Author
*X. X. Tel: +86 21 34206860. Fax: +86 21 34205949. E-mail: [email protected]. Funding
This study was funded by National Natural Science Foundation of China (No.50746004) and Toyota Motor Engineering & 4143
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
(42) Wei, B. Cassava cultivation technologies and industry development in China. China Agriculture Press: Beijing, China, 2008. (43) Yuan, L.; Zhang, L.; He, L.; Gao, M.; Guo, P.; Li, J.; Fan, Y. Resources background investigation on Jatropha in Yunnan Province. China Tropical Agriculture 2011, 06, 36−39. (44) Xunmin, O. Life cycle energy use and GHG emissions from the road transport setor in China. Tsinghua University: Beijing, China, 2010. (45) Zhang, T.; Xie, X.; Huang, Z. Life cycle energy consumption and GHGs emissions assessment of microalgal biodiesel based on a plant design in China. Int. J. Life Cycle Assess. 2013, under review. (46) FAO. CROPWAT 8.0 model. Food and Agriculture Organization: Rome, Italy, 2010. Available from: http://www.fao.org/nr/ water/infores_databases_cropwat.html. Accessed July 10, 2013. (47) FAO. CLIMWAT 2.0 database. Food and Agriculture Organization: Rome, Italy, 2010. Available from: http://www.fao. org/nr/water/infores_databases_climwat.html. Accessed July 10, 2013. (48) Yan, H.; Jiao, S.; Wang, L.; Jiang, Y.; Su, D.; Sun, G. Identification and evaluation of sweet sorghum germplasm resources of Heilongjiang province. Heilongjiang Agric. Sci. 2013, 3, 3−6. (49) CMEP. Environmental quality standard for surface water. Ministry of Environmental Protection, PRC: Beijing, China, 2002. (50) Batan, L.; Quinn, J. C.; Bradley, T. H. Analysis of water footprint of a photobioreactor microalgae biofuel production system from blue, green and lifecycle perspectives. Algal. Res. 2013, 2 (3), 196−203. (51) Zhang, L.; Wei, Z.; Qi, Z. Characteristics of rainfall and evaporation of different region in recent 30 years in Hainan province. Chinese Agric. Sci. Bull. 2006, 22 (4), 403−407. (52) Li, S.; Li, G.; Zhang, L.; Zhou, Z.; Han, B.; Hou, W.; Wang, J.; Li, T. A demonstration study of ethanol production from sweet sorghum stems with advanced solid state fermentation technology. Appl. Energy 2013, 102, 260−265. (53) NBSC. Environmental Statistics Data 2010 - Water supply and water consumption of each region in China; 2014.3.14ed. National Bureau of Statistics of China: Beijing, China, 2010. Available from: . (54) NEA. Biomass Energy Development for The Twelfth Five-Year Guideline; National Energy Administration: Beijing, China, 2012; p 7.
(21) Zhang, C.; Xie, G.; Li, S.; Ge, L.; He, T. The productive potentials of sweet sorghum ethanol in China. Appl. Energy 2010, 87 (7), 2360−2368. (22) Zhang, T.; Xie, X.; Huang, Z. The regional potential of microalgal biodiesel production in the open raceway ponds of China, Acta Energiae Solaris Sinica, under review. (23) Zhao, Y. L.; Dolat, A.; Steinberger, Y.; Wang, X.; Osman, A.; Xie, G. H. Biomass yield and changes in chemical composition of sweet sorghum cultivars grown for biofuel. Field Crop Res. 2009, 111 (1−2), 55−64. (24) McMahon, J. E.; Price, S. K. Water and Energy Interactions. Annu. Rev. Env. Resour. 2011, 36 (1), 163−191. (25) Martín, M.; Ahmetović, E.; Grossmann, I. E. Optimization of Water Consumption in Second Generation Bioethanol Plants. Ind. Eng. Chem. Res. 2010, 50 (7), 3705−3721. (26) Wu, M. Biodiesel; Chemical Industry Press: Beijing, China, 2008. (27) Eggleston, G.; Cole, M.; Andrzejewski, B. New Commercially Viable Processing Technologies for the Production of Sugar Feedstocks from Sweet Sorghum (Sorghum bicolor L. Moench) for Manufacture of Biofuels and Bioproducts. Sugar Tech 2013, 15 (3), 232−249. (28) Dutra, E. D.; Neto, A. G. B.; de Souza, R. B.; de Morais Junior, M. A.; Tabosa, J. N.; Menezes, R. S. C. Ethanol Production from the Stem Juice of Different Sweet Sorghum Cultivars in the State of Pernambuco, Northeast of Brazil. Sugar Tech 2013, 15 (3), 316−321. (29) Ministry of Agriculture. China agriculture statistical report 2010; China Agriculture Press: Beijing, China, 2011; p 9. (30) Yu, S.; Tao, J. Energy efficiency assessment by life cycle simulation of cassava-based fuel ethanol for automotive use in Chinese Guangxi context. Energy 2009, 34 (1), 22−31. (31) Feng, X.; Zhan, L. Efficiency analysis on cassava based fuel industry in Guangxi: A case survey on cassava industrial chain in Guiping, Guangxi. China Tropical Agriculture 2009, (2), 19−22 (Chinese). (32) Akminul Islam, A. K. M.; Primandari, S. R. P.; Yaakob, Z.; Anuar, N.; Osman, M. The properties of jatropha curcas seed oil from seven different countries. Energy Sources, Part A 2013, 35 (18), 1698− 1703. (33) Liu, L.; Zhuang, D.; Jiang, D.; Fu, J. Assessment of the biomass energy potentials and environmental benefits of Jatropha curcas L. in Southwest China. Biomass Bioenergy 2013, 56, 342−350. (34) Wu, W.; Huang, J.; Deng, X. Potential land for plantation of Jatropha curcas as feedstocks for biodiesel in China. Sci China Ser DEarth Sci 2009, 39 (12), 1672−1680. (35) Rawat, I.; Ranjith Kumar, R.; Mutanda, T.; Bux, F. Biodiesel from microalgae: A critical evaluation from laboratory to large scale production. Appl. Energy 2013, 103, 444−467. (36) Singh, A.; Pant, D.; Olsen, S. I.; Nigam, P. S. Key issues to consider in microalgae based biodiesel production. Energy Educ. Sci. Technol., Part A 2012, 29 (1), 687−700. (37) DOE. National algal biofuels technology roadmap; Department of Energy: Washington, DC, 2010. (38) Halim, R.; Danquah, M. K.; Webley, P. A. Extraction of oil from microalgae for biodiesel production: A review. Biotechnol. Adv. 2012, 30 (3), 709−732. (39) ANL; NREL; PNNL. Renewable Diesel from Algal Lipids: An Integrated Baseline for Cost, Emissions, and Resource Potential from a Harmonized Model. ANL/ESD/12-4; NREL/TP-5100-55431; PNNL-21437; Argonne National Laboratory: Argonne, IL; National Renewable Energy Laboratory: Golden, CO; Pacific Northwest National Laboratory: Richland, WA, 2012. Available from: . (40) Lundquist, T. J.; Woertz, I. C.; Quinn, N. W. T.; Benemann, J. R. A Realistic Technology and Engineering Assessment of Algae Biofuel Production; Energy Biosciences Institute: Berkeley, CA, 2010. (41) FAO, FAOSTAT-Agriculture. Food and Agriculture Organization: Rome, Italy, 2013. Available from: http://faostat3.fao.org/ home/index.html#HOME. Accessed June 8, 2013. 4144
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Life Cycle Water Footprints of Nonfood Biomass Fuels in China Tingting Zhang, Xiaomin Xie,* and Zhen Huang Key Laboratory for Power machinery and Engineering of M. O. E., Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, 200240 Shanghai, People’s Republic of China S Supporting Information *
ABSTRACT: This study presented life cycle water footprints (WFs) of biofuels from biomass in China based on the resource distribution, climate conditions, soil conditions and crop growing characteristics. Life cycle WFs including blue, green and gray water were evaluated for the selected fuel pathways. Geographical differences of water requirements were revealed to be different by locations. The results indicated that water irrigation requirements were significantly different from crop to crop, ranging from 2− 293, 78−137, and 17−621 m3/ha, for sweet sorghum, cassava, and Jatropha curcas L., respectively. Four biofuel pathways were selected on this basis to analyze the life cycle WF: cassava based bioethanol in Guangxi, sweet sorghum based bioethanol in Northeast China, Jatropha curcal L. based biodiesel in Yunnan and microalgae based biodiesel in Hainan. The life cycle WFs of bioethanol from cassava and sweet sorghum were 3708, and 17 156 m3 per ton of bioethanol, respectively, whereas for biodiesel produced from Jatropha curcas L. and microalgae, they were 5787, and 31 361 m3 per ton of biodiesel, respectively. The crop growing stage was the main contributor to the whole life cycle of each pathway. Compared to blue and green water, gray water was significant due to the use of fertilizer during the growing of biomass. From the perspective of the WF, cassava based bioethanol in Guangxi and Jatropha based biodiesel in Yunnan were suitable for promotion, whereas the promotion for microalage based biodiesel in Hainan required improvement on technology.
■
INTRODUCTION
more than 61% of water was consumed by agriculture due to irrigation.7 The concept of water footprint (WF) was proposed to analyze how biomass based biofuels relate to issues of water scarcity and pollution and to see how biofuels can become more sustainable from a water perspective.9 It was first introduced by Hoekstra in 200310 and subsequently elaborated by his team.6,9,11−13 They analyzed the WFs for lots of products including crops, agricultural products, biofuel and even transport systems on national scale. The early studies regarding the water consumption for biofuel producing processes focused on the water withdraw and irrigation requirements.14,15 Harto et al.16 adopted a hybrid method to evaluate the life cycle water use of ten low-carbon transportation fuel pathways including corn ethanol, cellulosic ethanol, soy biodiesel and algae biodiesel. However, the water requirements associated the crop growing was still the irrigation data. Not all of the irrigation water were consumed by crops, with some of which may runoff back to the watershed. The method conducted by Hoekstra et al. was considered as the most comprehensive method to assess water requirements of various goods for different countries and regions in a spatially explicit way so far,11 because they subdivided the different kinds of water
Biomass is considered a promising source to produce biofuels for mitigating fossil energy depletion and greenhouse gas (GHG) emissions. By the end of 2011, the world’s total biofuel production reached 110 billion liters, of which 51.2% was contributed by the United States.1 In China, the biofuel production was 2.7 billion liters, including 2.26 billion liters of bioethanol and 0.45 billion liters of biodiesel.1 However, these outputs are far behind the Chinese mandated target of 10 million ton (equivalent to 12.7 billion liters) of noncrop bioethanol and 2 million ton (equivalent to 2.3 billion liters) of biodiesel by 2020.2 Thus, more biomass resources will be required to meet the ambitious biofuel targets due to its merits like biodegradable, nontoxic and more favorable combustion emission profile.3 For biofuels produced from biomass, one should not only be aware of the issues of energy consumption and GHG emission but also should consider the access to available land and water.4 Ensuring inexpensive and clean water is an overriding global challenge, because (1) large quantities of water use are needed to grow fuel crops, and (2) water pollution is exacerbated by agricultural drainage due to the large contents of fertilizers, pesticides and sediment.5 As a big agricultural nation, the water consumption of China for crop production is ranked as the second largest after India.6 In China, the total amounts of water resource and water consumption were 2770 billion m3 7 and 610.7 billion m3 8 in 2011. Of the total water consumption, © 2014 American Chemical Society
Received: Revised: Accepted: Published: 4137
November 4, 2013 January 5, 2014 January 8, 2014 January 8, 2014 dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
demand with blue, green and gray WFs.6,17 However, the WFs of biofuel production processes in factories and the combustion of biofuel in vehicles are not considered in their studies. Wu et al.18,19 extended the methodology of assessing the WF on the basis of Hoekstra et al. with extensive local data to reflect local agricultural practices with increased resolution. Their emphasis was on the water consumption during the crop growing stage based on a high resolution spatial and temporal distribution model. Few studies consider the WF evaluation of biofuel production from biomass from the view of the life cycle, especially for China. This kind of work is significantly meaningful for policy-making. In China, bioethanol production from food crops has been shut down, and nonfood biomass has become the new focus.2 To address the interactions of the increasing of nonfood biofuels production and their water requirements in China, some potential terrestrial biomass were selected in this study. These crops also represent the roadmap of developing biofuels for China in the near future.
indicated as nitrogen, which is one of the several agricultural inputs in the research of Hoekstra et al.9,11,12 However, other inputs like phosphate, which is also used as common fertilizer in China, should also be considered. Thus, gray WF considered in this study contained both nitrogen and phosphorus as representative indicators. As the growing condition for microalgae was different from the other three terrestrial crops, the water footprint calculation was conducted according to mass and energy balance. For the biofuels converting stage, the WFs were calculated based on the mass and energy balance in the factories. The water consumption for biomass and biofuel transportation and distribution was assumed to be 0.18 m3 per ton.20 The water consumption related to the biofuel combustion was minimal and was ignored here. Main Data Sources. The climate data required for green and blue water estimation in the selected location were primarily derived from the China Statistic Yearbook 7 for the period of 2008−2012. The related data are listed in Tables SI2−SI-7, shown in the Supporting Information. Crop data and irrigation information are available from previous research21−23 and field investigations. Fertilizer utilization information shown in Table SI-1 in the Supporting Information was used to evaluate the gray water for each feedstock. Data for biofuel conversion in the factories was based on the well operated biofuel producing factories in China. Detailed data was discussed in section 4. Water Footprint Allocation. Feedstock Allocation. For each crop, the water consumed during the growth is generally referred to the entire plant including grain and straw, and is linearly related to the mass production in each part of a plant. Blue, green and gray water volumes for each crop were allocated into crop grain and its residue was collected for biofuel production based on crop harvest index (HI) and residual removal assumption.18 Mass-based allocation method18 was considered in this study for feedstock water allocation between primary product and residue. The allocation ratios for sweet sorghum and microalgae were assumed to be 0.6526 and 0.75, respectively. As for cassava and Jatropha, because their residues are not deemed as a feedstock, the water footprints associated with their growth were entirely allocated to the cassava and Jatropha seeds. Coproduct Partitioning. Lots of previous research results indicated that the feedstock growing stage was the main water intensive stage over the whole fuel cycle.24 The WF for the biofuel production in the factory only accounts for a small fraction16,25 and would not influence the life cycle results. However, the WF associated with the coproduct in the biofuel production factory was also considered in this study to give a comprehensive assessment. The allocation ratios for sweet sorghum, cassava, Jatropha and microalgae were assumed to be 0.86,18 0.83, 0.91 and 0.9126 by mass, respectively. Selection of Representative Pathways. Resource Distribution of Potential Biomass. Table 1 shows the annual production for the feedstock by the end of 2011 in China. The annual output trend of the three terrestrial crops during the past three decades was shown in Figure SI-1 in the Supporting Information. The production of cassava and Jatropha curcas kept stable growth, while the production of sweet sorghum declined with each passing year. Figure 2 shows the visualized biomass production distribution, which illustrated the biofuel development potential in China. Sweet sorghum27 is an annual grass that has been widely recognized as a promising sugar feedstock crop. It can be grown
■
METHODS Definition of System Boundary. The life cycle producing process of the selected biofuel pathways were exhibited in Figure 1. Four biofuel pathways considered in this study
Figure 1. System boundary of life cycle water footprint for biofuel production from biomass: Blue dotted line refers to the indirect water footprint due to various process fuels and materials; red dotted line refers to the producing process for biofuel production; faint green arrow refers to the green water footprint; faint blue arrow refers to the blue water footprint; faint gray arrow refers to the gray water footprint.
included bioethanol from cassava (CBE) and sweet sorghum (SBE), biodiesel from Jatropha curcas L. (JBD) and microalgae (MBD). Four types of water use were estimated: green water footprint (WFgreen), blue water footprint (WFblue), gray water footprint (WFgray) and life cycle water footprint (WFLC). Green WF refers to the daily rainwater evapotranspiration over the length of the growing period of biomass.17 Blue WF is the consumptive use of irrigation water. It contains two parts: the direct water due to the consumptive use of irrigation, and the indirect water attributed to the use of process fuels and materials.19 Gray WF refers to the amount of water needed to assimilate pollutants discharged into the natural water system during the growth of biomass and the wastewater drainage during the biofuel production. Life cycle water footprint refers to the sum of three WFs for each process. The functional unit was represented as m3 water per ton of biofuel produced. Calculation of WF for Each Process. The detailed calculation of green, blue and gray WFs for the growth of three terrestrial plants followed the approach proposed by Hoekstra et al., which is presented in the Supporting Information.9 It should be noted that the gray WF is only 4138
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
are listed in Table 1, including Guangxi, Guangdong, Hainan and Yunnan. Guangxi is located in subtropical regions and very suitable for growing cassava due to its suitable climate with high temperatures, plentiful rainfall and autumn droughts. The total planting area and yield of cassava in Guangxi was more than 60% of the total national amount of China.31 Thus, Guangxi was chosen as the representative location for cassava based bioethanol. Jatropha curcas L. is a perennial shrub that grows well in semitropical conditions, on poor soils and requires little care. It needs a minimum of 600 mm of rain, even in times of extended drought. Jatropha seeds contain about 40−48% oil depending on different countries.32 Jatropha is considered to be the most promising tree species used to produce biodiesel in China.33 It is estimated that there are 1.99 × 106 ha of suitable land and 5.57 × 106 ha of moderately suitable land in Southwestern China.33 Yunnan, Sichuan and Guizhou were the productionintensive areas, with 95% of the total planting area in China.34 Wu et al.34 concluded that Yunnan was the most important region for the development of Jatropha based biodiesel in the future on the basis of remote sensing data, meteorological observations and soil survey data. As Figure 3 shows, the annual Jatropha seeds production in Yunnan was very considerable. Therefore, the Yuannan province in Southwestern China was chosen to produce biodiesel from Jatropha curcas seeds. Microalgae have been considered as the ultimate alternative to depleting resources of petro-diesel due to their high cellular concentration of lipids, resources and economic sustainability.35 A lot of research has been conducted to try to break through the bottlenecks encountered during the production of microalgal biodiesel.36−38 Large-scale outdoor open ponds were considered to be easy to scale-up, operate and have lower capital costs.39 However, its production was easily affected by
Table 1. Production Status of the Main Biomass of China in 2011 area harvested: ha
annual production: ton
yield: ton/ha
cassava
27575741
451507541
16.4
sweet sorghum
50136041
205431641
4.1
8370743
418535
544
48
13915
290
feedstock
Jatropha curcas L. microalgae 45
main producing area Guangxi, Guangdong, Hainan, Yunnan42 Inner Mongalia, Northeast China, Sichuan, Guizhou29 Yunnan, Sichuan, Guizhou43 Hainan22
in the semiarid area. In general, sweet sorghum produces 2 ton/ ha of grains and 50 t/ha of stems,28 with stem juice rich in sucrose, glucose and fructose. In this study, ethanol was assumed to be produced from the stem. In north China, sweet sorghum produces 1.8−5.0 ton/ha grain yield,23 and 60 ton/ha stalk.21 Inner Mongolia, Jilin, Liaoning, and Heilongjiang have the highest productive potentials of sweet sorghum based ethanol, followed by Sichuan, Guizhou, Hebei, Gansu, Shanxi, and other provinces. The total production in the three northeastern provinces shared 65.2% of the national total production.29 Thus, the Northeast region (Heilongjiang, Jilin, and Liaoning) was chosen as the representative site to produce sweet sorghum based ethanol. Cassava is a kind of starch-containing feedstock with about 75% of the starch content in the dry cassava chips.30 It can be grown in the region with annual rainfall of 600−6000 mm. The technology to convert starch to ethanol is based on the hydrolysis of starch and fermentation of sugar.30 In China, most of the cassava cultivation is undertaken by individual cultivators in widely dispersed areas. The primary cassava producing areas
Figure 2. Distribution of biomass production and the selected representative locations in China. 4139
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Figure 3. Distribution of irrigated water requirements for different biomass in China: (1) Liaoning; (2) Jilin; (3) Heilongjiang; (4) Inner Mongolia; (5) Sichuan; (6) Chongqing; (7) Guizhou; (8) Gansu; (9) Shanxi; (10) Guangxi; (11) Guangzhou; (12) Fujian; (13) Henan; (14) Hubei; (15) Hunan; (16) Yunnan.
outdoor day-to-day weather conditions.38 Our previous research22 investigated regional microalgae production based on different climate conditions in different regions according to an outdoor pond design.40 It showed that the Hainan province is the most appropriate region to grow microalgae with an average growth rate of 12.6 g/(m2d). Water Irrigation Requirements in the Main Producing Areas. Figure 3 indicates the crop irrigation requirements in the main producing areas for the three terrestrial plants. Figure 3a shows the main producing areas for the three selected terrestrial crops in China. Figure 3b,c,d shows the calculated water irrigation requirements for different crops in different regions in China. It indicated that the irrigation requirements of three plants were different both from species and regions. The irrigation requirements for sweet sorghum, cassava and Jatropha curcas ranged from 2 to 293, 78−137, and 17−621 m3/ha, respectively. Jatropha curcas showed the highest average irrigation requirements, followed by cassava and sweet sorghum. This is because Jatropha curcas has the longest crop growth cycle, whereas sweet sorghum has the shortest growth cycle. The longer growth cycle, the more water evaporated through evapotranspiration of the plant. For the same crop growth in different regions, irrigation requirements also showed significant changes. This kind of variations was close to the local climate where the crops were planted. Take sweet sorghum for example (Figure 3b), the irrigation requirements in Sichuan, Chongqing and Guizhou were nonsignificant because there was plenty of rainfall during the crop growth in those areas. On the contrary, in arid inland areas with little rainfall like Gansu and Inner Mongolia, there was not
enough precipitation to meet the water requirement for the crop growth. Therefore, extra irrigation water was required to well supply the growth of sweet sorghum. Many researchers emphasized the importance of taking regional specific into account when assessing the water requirements of biofuel production.11,15,18 Therefore, the suitable location we selected was not only based on the irrigation requirement but also combined with the production and the local supportive policies. Hence, Northeast China (Liaoning, Jilin, and Heilongjiang) was chosen for the production of SBE, Guangxi was selected as the producing location of CBE and Yunnan was the representative region for JBD. The average irrigation requirements for SBE, CBE and JBD were 95.8, 77.9, and 621.2 m3/ha, respectively.
■
PROCESS DESCRIPTIONS FOR EACH PATHWAY Crop Growing Stage. Three Terrestrial Plants. To calculate the green and blue WF of three terrestrial plants, climate data in Northeast China are required, including rainfall, temperature (maximum and minimum), sunshine hours, relative humidity and wind. In this study, the rainfall data from a range of years (2008−2012) was collected.7 And then, these data were further processed into the results for normal (Nor), dry and wet years under the methodology of CROPWAT 8.0 46 as shown in Tables SI-2, SI-4 and SI-6 in the Supporting Information. The data of relative humidity and sunshine hours were also collected7 and processed following the same method as that for rainfall.46 The wind data were extracted from the database of Food and Agricultural Organization (FAO).47 The temperature data regarding the 4140
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
average monthly extreme low and high temperature were collected from the local weather stations on the Internet. In the temperate zone of North China, sweet sorghum is usually sowed in late April and harvested after 111−165 days.23 The plant height often ranges from 75 to 350 mm.48 In this study, 250 mm was chosen as the optimal crop height to calculate the water requirements. The growing stage of cassava includes four periods: (1) a seeding period of 60 days; (2) a root forming period of 50 days with the highest height of 1 m; (3) a root enlargement period of 120 days; and (4) a root maturity period of 30 days. Jatropha usually sprouts buds at the end of March or in early April every year. The seeds begin to mature in May and begin to drop in the middle of November.43 The plant height of Jatropha ranges from 4 to 5.5 m. Soil conditions and correction factors were cited from CROPWAT 8.0.46 On the basis of the above assumptions, the crop evapotranspiration under standard conditions (ETc), effective rainfall (Effrain), and irrigation requirement (Irr) can be obtained by inputting these data into the CROPWAT 8.046 model. Furthermore, the blue and green WF can be also calculated9 with the above data. Results are listed in Tables SI3, SI-5 and SI-7 (Supporting Information). The fertilizer application data (Table SI-1, Supporting Information), the production yield of each crop (Table 1), the leaching-runoff fraction (10%9) and the maximum acceptable concentration (0.002 kg N/m3, and 0.0004 kg P/m3 49) were used to obtain the gray water footprint. The water consumption for producing 1 kg of N and P were assumed to be 0.0362 and 0.1003 m3.50 Results are shown in Tables SI-3, SI-5 and SI-7 (Supporting Information). Microalgae. The production factory of microalgae based biodiesel was assumed to be located in the Hainan province, China. The construction of the factory was modified on the basis of outdoor high rate ponds (HRP),40 and the detailed plant design is shown in the Supporting Information. In brief, there were 12 HRPs designed in this plant with 4 ha of individual area for each pond. The water depth in the pond was about 0.3 m. Mixing was provided by a paddle wheel in each pond to ensure a mean velocity of 0.25 m/s. Freshwater was used for the growth of the algae. The water loss in Hainan was determined by the average annual evaporation in Haikou, Hainan. Thus, the water loss due to the evaporation of the pond was about 0.475 cm/day.51 When the microalgae were ready to be harvested, the broth was directed to the flocculation unit. Forty percent of the water after flocculation was recycled to the HRPs. The main process material and energy inputs are exhibited in Table SI-8 in the Supporting Information. The data listed in the table was used to calculate the indirect water footprint. Biofuel Conversion Stage. Bioethanol Production. Sweet Sorghum. After harvesting, piling and transportation, sweet sorghum was sent to a nearby ethanol production factory. The producing process in this factory was based on a demonstration factory operated in Inner Mongolia, China.52 Advanced solidstate fermentation (ASSF) was employed. The main process included smashing of the sweet sorghum stalk, preheating of the mashed material, preparation of an inoculation medium, fermentation, stripping, and distillation. The main flowchart of this process is shown in Figure 4. From this figure, we can see that 16 ton of sweet sorghum stalk was used to produce 6.62 ton of crude of ethanol (containing 1 ton of 99.5% ethanol) and 16.43 ton of vinasse as coproduct. In this factory, 50% of
Figure 4. Flowchart of material balance and energy inputs for sweet sorghum based ethanol in a demonstration factory in China:52 red arrows refer to the energy input in each stage; green and black arrows refer to the materials balance of the system.
the vinasse was used as cattle feed, and the rest was used as fuel to generate steam for the demonstration system.52 In the ASSF demonstration factory, about 2.37 m3 of water was required to produce 1 ton of 99.5% bioethanol, with 0.08 m3 of condensate water produced.52 Therefore, the direct blue and gray water footprints in this factory were assumed to be 2.37 and 0.08 m3/ ton of 99.5% bioethanol, respectively. In addition, indirect water footprint was also introduced based on the process material and energy inputs such as electricity shown in Figure 4. The water consumption for electricity generation from coal was assumed to be 3.971 L/kWh.16 The electricity input for each process was exhibited in Figure 4, with a total electricity input of 1209.7 MJ/ton of ethanol (99.5%). Thus, the indirect water footprint in this factory was 1.34 m3/ton of bioethanol (99.5%). Cassava. The cassava based ethanol factory was based on a well operated plant located in Beihai, Guangxi. The date related to the ethanol conversion was from our local investigation. In this factory, 1 ton of ethanol can be obtained from 7 ton of fresh cassava or 2.8 ton of dried cassava chips. A batch fermentation process was employed. The conversion process contains smashing, liquefaction, fermentation, rectification and refinery. The concentration of ethanol derived from this factory was about 94−99%. The residue after the fermentation was dried to a solid content of 60%, and then combusted in the utility boiler to generate electricity. The water requirement for producing 1 ton of ethanol was about 2.41−7.60 m3. Biodiesel Production. Oil extracted from Jatropha seeds and microalgae was transported to the nearby biodiesel conversion factory. As there is no commercial biodiesel production factory from microalgae, the biodiesel conversion process was assumed to be same as Jatropha seeds oil. In the factory, homogeneous alkali catalysis was adopted to convert oil into biodiesel.26 The amounts of catalyst and methanol were 0.010 and 0.117 ton/ ton BD. The yield of biodiesel was about 78%. The water consumption in the factory was about 2.035 m3/ton biodiesel produced. The water requirement for producing 1 ton of methanol was 10 m3.20 4141
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Table 2. Direct, Indirect and Life Cycle Water Footprints for Each Biofuel Pathway direct WF (m3/ton biofuel) biofuel pathway
process
CBE
crop growing crop transport BE conversion BE transport BE utilization crop growing crop transport BE conversion BE transport BE utilization crop growing transport BD conversion BD transport BD utilization culture transport BD conversion BD transport BD Utilization
SBE
JBD
MBD
blue 0.00 0.18 6.33 0.18 0.00 0.00 0.18 2.37 0.18 0.00 0.00 0.18 0.26 0.18 0.00 15244 0.00 0.35 0.18 0.00
green 659 0.00 0.00 0.00 0.00 1514 0.00 0.00 0.00 0.00 960 0.00 0.00 0.00 0.00 263 0.00 0.00 0.00 0.00
gray 3021 0.00 0.08 0.00 0.00 15597 0.00 0.08 0.00 0.00 4201 0.00 0.03 0.00 0.00 15803 0.00 0.03 00.00 00.00
indirect WF (m3/ton biofuel) blue 20.00 0.05 1.50 0.03 0.00 40.29 0.05 1.34 0.05 0.00 24.10 0.05 1.75 0.05 0.00 41.00 0.00 9.68 0.05 0.00
Biofuel Transportation and Distribution. The direct water consumption during bioethanol transportation and distribution was assumed to be 0.18 m3 per ton of ethanol.20 Although the indirect electricity and diesel consumption was 2.74 kWh/ton and 9.4 L/ton of ethanol.20 The water consumption of diesel production was about 3.9 L per liter of diesel.16 The resulting water footprint for bioethanol transportation and distribution was 0.23 m3/ton of bioethanol. In this study, the WF of diesel transportation and distribution was assumed to be the same as bioethanol.
green 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
gray 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
life cycle WF (m3/ton biofuel) blue 20.00 0.23 7.83 0.18 0.00 40.29 0.23 3.71 0.18 0.00 24.10 0.23 2.01 0.18 0.00 15285 0.00 10.03 0.18 0.00
green 659 0.00 0.00 0.00 0.00 1514 0.00 0.00 0.00 0.00 960 0.00 0.00 0.00 0.00 263.00 0.00 0.00 0.00 0.00
gray 3021 0.00 0.08 0.00 0.00 15597 0.00 0.08 0.00 0.00 4201 0.00 0.03 0.00 0.00 15803 0.00 0.03 0.00 0.00
total 3700 0.23 7.91 0.23 0.00 17152 0.23 3.79 0.23 0.000 5185 0.23 2.04 0.23 0.00 31351 0.00 10.06 0.23 0.00
direct WF. Gray WF was found to be a positive correlation with fertilizer use during the crop growth. The fertilizer use of sweet sorghum and microalgae were high, which resulted in high gray WF. The WFs of the biofuel conversion stage were small, as shown in Table 2. The WF of bioethanol processing factory for cassava and sweet sorghum were 7.91 and 3.79 m3/ton of bioethanol produced, whereas in the biodiesel processing factory for Jatropha and microalgae, the WF were 2.04 and 10.06 m3/ton of biodiesel produced. The life cycle WF during the biofuel transport and distribution was about 0.23 m3/ton of biofuel listed in Table 2. The influence of indirect water footprint was not significant for the four biofuel pathways. Life Cycle Water Footprint of Four Biofuel Pathways. Figure 5 exhibits the life cycle WFs of four biofuel pathways. Bioethanol produced from cassava and sweet sorghum had the life cycle WF of 3708 and 17 156 m3/ton bioethanol, respectively. Biodiesel produced from Jatropha curcas and microalgae had the life cycle WF of 5787, and 31 361 m3/ton biodiesel, respectively.
■
WATER FOOTPRINT RESULTS AND DISCUSSIONS Comparison of Water Footprints by Processes. In this section, the WFs of four selected biofuel pathways were analyzed based on the aforementioned suitable location. The results of WF contain indirect WF and direct WF in the form of blue, green and gray type. Indirect water refers to the water requirement related to the input of process fuel, energy and materials. In this study, the water footprints embodied in the process inputs are only considered as blue water. The detailed WF of each process of each biofuel pathway is show in Table 2. During the crop growing stage, direct water footprints showed great variability from species to species. The total direct WFs of the four biomasses in the selected locations ranged from 3680 to 31 310 m3/ton of biofuel produced. The direct green WFs of the three terrestrial plants (sweet sorghum, cassava and Jatropha curcas) were 659, 1514 and 960 m3/ton, respectively, whereas it was 263 m3/ton for microalgae. As for direct blue WF, cassava, sweet sorghum, and Jatropha had no contribution to the blue WF, whereas microalgae had significant direct blue WF with 15 244 m3/ton of biodiesel produced. This is because the rainfall in these regions can meet the water requirements for the growth of cassava in Guangxi, sweet sorghum in Northeast China and Jatropha curcas in Yunnan, according to our field investigation and others’ research.30 However, microalgae need a lot of freshwater to sustain growth in an aquatic environment. Among all four biomass, direct gray water accounted for a large part of total
Figure 5. Life cycle water footprints of different biofuels. 4142
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
Manufacturing (China) Co. Ltd. The authors thank the “Morningstar Young Scholars Program” and “Graduate Student Innovation Ability Raise Funds” supported by Shanghai Jiao Tong University.
For each biofuel producing process, the gray WF was the biggest contributor to the life cycle water footprint. For CBE, gray WF shared 81.5% of the life cycle WF; for SBE, it shared 90.9% of the life cycle WF; for JBE, gray WF accounted for 81.0% of the life cycle WF. The high gray water ratio of the three terrestrial plants is attributed to the large inputs of fertilizer use and the runoff during the crop growth. Compared to the three terrestrial plants, microalgae had the highest life cycle water footprint. Gray WF and blue WF of microalgae based biodiesel accounted for 50.4% and 48.8%, respectively. This is because more water is required to keep the aquatic environment for microalgae, and more fertilizer is required to provide the nutrients for microalgae. If fertilizer is entirely or partially replaced by wastewater rich in nutrients, the gray water footprint of microalgae would drop drastically. In general, in terms of life cycle water footprints, bioethanol from cassava in Guangxi and biodiesel from Jatropha curcas in Yunnan are more attractive. Bioethanol from sweet sorghum in Northeast China and biodiesel from microalgae in Hainan are water-stressful. Fortunately, the freshwater in these regions is available.53 Therefore, the development of the proposed biofuel production from different biomass is feasible from the perspective of life cycle water footprints. Policy Suggestion. China has mandated to increase the biofuel production, including 4 million ton of bioethanol and 1 million ton of biodiesel by 2015.54 The main biomass promoted was nonfood biomass, such as cassava, sweet sorghum, Jatropha curcas and microalgae. Quantifying water requirements on a regional basis especially distinguishing blue, green and gray water components is important for elucidating how biofuel policies influence national and local water resources. Cassava based bioethanol should be placed on the first developing agenda due to the mature technology in China and the smallest WF. Sweet sorghum is also important to diversify the biomass resource especially in north region where it is the main producing region in China. However, more efficient technology is required to improve the conversion rate. The WF of Jatropha curcas based biodiesel is also small but the land suitable for planting Jatropha is limited. Marginal land was proposed to grow Jatropha to increase the yield of seeds. However, this would lead to more severe environmental issues due to the vulnerability of this kind of land. The current focus of developing Jatropha curcas based biodiesel may be on the improvement of seeds yield. The WF of microalgae is the highest but it grows fast and has high oil content. Microalgae is a very promising resource if the consumed freshwater would be replaced by other water like wastewater or seawater.
■
Notes
The authors declare no competing financial interest.
■
(1) EIA. International energy statistics-total biofuels production, 2013.06.26 ed.; U.S. Energy Information Administration: Washington, DC, 2013. Available from: . (2) NDRC. Mid-Long term Development Plan for Renewable Energy; The National Development and Reform Commission: Beijing, China, 2007; pp 19−22. Available from: . (3) Ribeiro, A.; Carvalho, J.; Castro, J.; Araújo, J.; Vilarinho, C.; Castro, F. Alternative feedstocks for biodiesel production. Mater. Sci. Forum 2012, 730−732, 623−629. (4) Ishola, M. M.; Brandberg, T.; Sanni, S. A.; Taherzadeh, M. J. Biofuels in Nigeria: A critical and strategic evaluation. Renewable Energy 2013, 55, 554−560. (5) Dominguez-Faus, R.; Powers, S. E.; Burken, J. G.; Alvarez, P. J. The water footprint of biofuels: A drink or drive issue? Environ. Sci. Technol. 2009, 43 (9), 3005−3010. (6) Mekonnen, M. M.; Hoekstra, A. Y. The green, blue and grey water footprint of crops and derived crop products. Hydrol. Earth Syst. Sci. 2011, 15 (5), 1577−1600. (7) NBSC. China Statistical Yearbook 2012; National Bureau of Statistics of China: Beijing, China, 2013. (8) NBSC. Environmental Statistics Data 2011; National Bureau of Statistics of China: Beijing, China, 2013. Available from: . (9) Hoekstra, A. Y.; Chapagain, A. K.; Aldaya, M. M.; Mekonnen, M. M. The water footprint assessment manual: setting the global standard; Earthscan: London, UK, 2011. (10) Hoekstra, A. Y. Virtual water trade: proceedings of the international expert meeting on virtual water trade; IHE: Delft, The Netherlands, 2003. (11) Gerbens-Leenes, W.; Hoekstra, A. Y. The water footprint of sweeteners and bio-ethanol. Environ. Int. 2012, 40 (1), 202−211. (12) Gerbens-Leenes, P. W.; van Lienden, A. R.; Hoekstra, A. Y.; van der Meer, T. H. Biofuel scenarios in a water perspective: The global blue and green water footprint of road transport in 2030. Global Environ. Change 2012, 22 (3), 764−775. (13) Gerbens-Leenes, W.; Hoekstra, A. Y. The water footprint of biofuel-based transport. Energy Environ. Sci. 2011, 4 (8), 2658−2668. (14) King, C. W.; Webber, M. E. Water intensity of transportation. Environ. Sci. Technol. 2008, 42 (21), 7866−7872. (15) Chiu, Y. W.; Walseth, B.; Suh, S. Water embodied in bioethanol in the United States. Environ. Sci. Technol. 2009, 43 (8), 2688−2692. (16) Harto, C.; Meyers, R.; Williams, E. Life cycle water use of lowcarbon transport fuels. Energy Policy 2010, 38 (9), 4933−4944. (17) Gerbens-Leenes, W.; Hoekstra, A. Y.; Van Der Meer, T. H. The water footprint of bioenergy. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (25), 10219−10223. (18) Chiu, Y. W.; Wu, M. Assessing county-level water footprints of different cellulosic-biofuel feedstock pathways. Environ. Sci. Technol. 2012, 46 (16), 9155−9162. (19) Wu, M.; Chiu, Y.; Demissie, Y. Quantifying the regional water footprint of biofuel production by incorporating hydrologic modeling. Water Resour. Res. 2012, 48, 10. (20) Xing, A.; Ma, J.; Zhang, Y.; Wang, Y.; Jin, Y. Life cycle assessment of resource and energy consumption for production of biodiesel. Chin. J. Process Eng. 2010, 10 (2), 314−320.
ASSOCIATED CONTENT
S Supporting Information *
Additional information including calculation of WF, assumptions for microalgal biodiesel plant, Table SI-1∼SI-8 and Figure SI-1. This material is available free of charge via the Internet at http://pubs.acs.org.
■
REFERENCES
AUTHOR INFORMATION
Corresponding Author
*X. X. Tel: +86 21 34206860. Fax: +86 21 34205949. E-mail: [email protected]. Funding
This study was funded by National Natural Science Foundation of China (No.50746004) and Toyota Motor Engineering & 4143
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
Environmental Science & Technology
Article
(42) Wei, B. Cassava cultivation technologies and industry development in China. China Agriculture Press: Beijing, China, 2008. (43) Yuan, L.; Zhang, L.; He, L.; Gao, M.; Guo, P.; Li, J.; Fan, Y. Resources background investigation on Jatropha in Yunnan Province. China Tropical Agriculture 2011, 06, 36−39. (44) Xunmin, O. Life cycle energy use and GHG emissions from the road transport setor in China. Tsinghua University: Beijing, China, 2010. (45) Zhang, T.; Xie, X.; Huang, Z. Life cycle energy consumption and GHGs emissions assessment of microalgal biodiesel based on a plant design in China. Int. J. Life Cycle Assess. 2013, under review. (46) FAO. CROPWAT 8.0 model. Food and Agriculture Organization: Rome, Italy, 2010. Available from: http://www.fao.org/nr/ water/infores_databases_cropwat.html. Accessed July 10, 2013. (47) FAO. CLIMWAT 2.0 database. Food and Agriculture Organization: Rome, Italy, 2010. Available from: http://www.fao. org/nr/water/infores_databases_climwat.html. Accessed July 10, 2013. (48) Yan, H.; Jiao, S.; Wang, L.; Jiang, Y.; Su, D.; Sun, G. Identification and evaluation of sweet sorghum germplasm resources of Heilongjiang province. Heilongjiang Agric. Sci. 2013, 3, 3−6. (49) CMEP. Environmental quality standard for surface water. Ministry of Environmental Protection, PRC: Beijing, China, 2002. (50) Batan, L.; Quinn, J. C.; Bradley, T. H. Analysis of water footprint of a photobioreactor microalgae biofuel production system from blue, green and lifecycle perspectives. Algal. Res. 2013, 2 (3), 196−203. (51) Zhang, L.; Wei, Z.; Qi, Z. Characteristics of rainfall and evaporation of different region in recent 30 years in Hainan province. Chinese Agric. Sci. Bull. 2006, 22 (4), 403−407. (52) Li, S.; Li, G.; Zhang, L.; Zhou, Z.; Han, B.; Hou, W.; Wang, J.; Li, T. A demonstration study of ethanol production from sweet sorghum stems with advanced solid state fermentation technology. Appl. Energy 2013, 102, 260−265. (53) NBSC. Environmental Statistics Data 2010 - Water supply and water consumption of each region in China; 2014.3.14ed. National Bureau of Statistics of China: Beijing, China, 2010. Available from: . (54) NEA. Biomass Energy Development for The Twelfth Five-Year Guideline; National Energy Administration: Beijing, China, 2012; p 7.
(21) Zhang, C.; Xie, G.; Li, S.; Ge, L.; He, T. The productive potentials of sweet sorghum ethanol in China. Appl. Energy 2010, 87 (7), 2360−2368. (22) Zhang, T.; Xie, X.; Huang, Z. The regional potential of microalgal biodiesel production in the open raceway ponds of China, Acta Energiae Solaris Sinica, under review. (23) Zhao, Y. L.; Dolat, A.; Steinberger, Y.; Wang, X.; Osman, A.; Xie, G. H. Biomass yield and changes in chemical composition of sweet sorghum cultivars grown for biofuel. Field Crop Res. 2009, 111 (1−2), 55−64. (24) McMahon, J. E.; Price, S. K. Water and Energy Interactions. Annu. Rev. Env. Resour. 2011, 36 (1), 163−191. (25) Martín, M.; Ahmetović, E.; Grossmann, I. E. Optimization of Water Consumption in Second Generation Bioethanol Plants. Ind. Eng. Chem. Res. 2010, 50 (7), 3705−3721. (26) Wu, M. Biodiesel; Chemical Industry Press: Beijing, China, 2008. (27) Eggleston, G.; Cole, M.; Andrzejewski, B. New Commercially Viable Processing Technologies for the Production of Sugar Feedstocks from Sweet Sorghum (Sorghum bicolor L. Moench) for Manufacture of Biofuels and Bioproducts. Sugar Tech 2013, 15 (3), 232−249. (28) Dutra, E. D.; Neto, A. G. B.; de Souza, R. B.; de Morais Junior, M. A.; Tabosa, J. N.; Menezes, R. S. C. Ethanol Production from the Stem Juice of Different Sweet Sorghum Cultivars in the State of Pernambuco, Northeast of Brazil. Sugar Tech 2013, 15 (3), 316−321. (29) Ministry of Agriculture. China agriculture statistical report 2010; China Agriculture Press: Beijing, China, 2011; p 9. (30) Yu, S.; Tao, J. Energy efficiency assessment by life cycle simulation of cassava-based fuel ethanol for automotive use in Chinese Guangxi context. Energy 2009, 34 (1), 22−31. (31) Feng, X.; Zhan, L. Efficiency analysis on cassava based fuel industry in Guangxi: A case survey on cassava industrial chain in Guiping, Guangxi. China Tropical Agriculture 2009, (2), 19−22 (Chinese). (32) Akminul Islam, A. K. M.; Primandari, S. R. P.; Yaakob, Z.; Anuar, N.; Osman, M. The properties of jatropha curcas seed oil from seven different countries. Energy Sources, Part A 2013, 35 (18), 1698− 1703. (33) Liu, L.; Zhuang, D.; Jiang, D.; Fu, J. Assessment of the biomass energy potentials and environmental benefits of Jatropha curcas L. in Southwest China. Biomass Bioenergy 2013, 56, 342−350. (34) Wu, W.; Huang, J.; Deng, X. Potential land for plantation of Jatropha curcas as feedstocks for biodiesel in China. Sci China Ser DEarth Sci 2009, 39 (12), 1672−1680. (35) Rawat, I.; Ranjith Kumar, R.; Mutanda, T.; Bux, F. Biodiesel from microalgae: A critical evaluation from laboratory to large scale production. Appl. Energy 2013, 103, 444−467. (36) Singh, A.; Pant, D.; Olsen, S. I.; Nigam, P. S. Key issues to consider in microalgae based biodiesel production. Energy Educ. Sci. Technol., Part A 2012, 29 (1), 687−700. (37) DOE. National algal biofuels technology roadmap; Department of Energy: Washington, DC, 2010. (38) Halim, R.; Danquah, M. K.; Webley, P. A. Extraction of oil from microalgae for biodiesel production: A review. Biotechnol. Adv. 2012, 30 (3), 709−732. (39) ANL; NREL; PNNL. Renewable Diesel from Algal Lipids: An Integrated Baseline for Cost, Emissions, and Resource Potential from a Harmonized Model. ANL/ESD/12-4; NREL/TP-5100-55431; PNNL-21437; Argonne National Laboratory: Argonne, IL; National Renewable Energy Laboratory: Golden, CO; Pacific Northwest National Laboratory: Richland, WA, 2012. Available from: . (40) Lundquist, T. J.; Woertz, I. C.; Quinn, N. W. T.; Benemann, J. R. A Realistic Technology and Engineering Assessment of Algae Biofuel Production; Energy Biosciences Institute: Berkeley, CA, 2010. (41) FAO, FAOSTAT-Agriculture. Food and Agriculture Organization: Rome, Italy, 2013. Available from: http://faostat3.fao.org/ home/index.html#HOME. Accessed June 8, 2013. 4144
dx.doi.org/10.1021/es404458j | Environ. Sci. Technol. 2014, 48, 4137−4144
