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The analysis on energy and environmental impacts of microalgae-based fuel methanol in China
ARTICLE IN PRESS Energy Policy 37 (2009) 1479–1488
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The analysis on energy and environmental impacts of microalgae-based fuel methanol in China Jing Liu , Xiaoqian Ma Electric Power College, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou 510640, China
a r t i c l e in fo
abstract
Article history: Received 22 May 2008 Accepted 5 December 2008 Available online 10 January 2009
The whole life of methanol fuel, produced by microalgae biomass which is a kind of renewable energy, is evaluated by using a method of life cycle assessment (LCA). LCA has been used to identify and quantify the environment emissions and energy efficiency of the system throughout the whole life cycle, including microalgae cultivation, methanol conversion, transport, and end-use. Energy efficiency, defined as the ratio of the energy of methanol produced to the total required energy, is 1.24, the results indicate that it is plausible as an energy producing process. The environmental impact loading of microalgae-based fuel methanol is 0.187mPET2000 in contrast to 0.828mPET2000 for gasoline. The effect of photochemical ozone formation is the highest of all the calculated categorization impacts of the two fuels. Utilization of microalgae an raw material of producing methanol fuel is beneficial to both production of renewable fuels and improvement of the ecological environment. This Fuel methanol is friendly to the environment, which should take an important role in automobile industry development and gasoline fuel substitute. & 2008 Elsevier Ltd. All rights reserved.
Keywords: Life cycle assessment Microalgae Methanol fuel
1. Introduction China has been a net importer of oil since 1993. In 2005, more than 140 million tons are imported. China is the second biggest country of oil importing, just behind the US. Imported oil currently accounts for about 25% (Zhongyu, 2000) of China’s total domestic needs, and the amount will probably increase to more than 50% by the year 2015 due to the rapidly rising demand for oil by the flourishing economy (Dadong et al., 2001; Yongguang, 2001). Around 35% of the total oil was consumed as fuel by automobiles, where gasoline consumption is some 70 million tons (Liu et al., 2007a, b). To deal with the higher and higher oil price and to keep the fast development of automobile industry, alternative fuels are regarded highly. Biomass resources include wood and wood wastes, energy crops, aquatic plants, agricultural crops and their waste byproducts, municipal wastes and animal wastes. Among these, microalgae have been suggested as very good candidates for fuel production because of their advantages of higher photosynthetic efficiency, higher biomass production and faster growth compared to those lignocellulosic materials (Xiaoling et al., 2004). Though the microalgae biomass can be used as a solid fuel because of its high heating value of more than 4000 kcal/kg (Sakai and Kaneko, 1996), we direct our attention to the conversion of it into methanol since methanol is one of liquid fuels which are easy to transport and is useful for other various purposes.
For these reasons, the Chinese government has to develop biomass methanol as one of its transportation fuels for the sake of energy security and environmental improvement reasons. Methanol fuel was affirmed to be a kind of possible alternative energy source and could be used in methanol vehicles, according to statements made at a conference held by the State Council in November, 2006. Many countries including Japan and United States (Bechtold et al., 1996) are taking great interest in methanol vehicle for practical use. Therefore, there will be an increasing demand for methanol in the future. Like other biomass fuel, methanol fuel, derived from microalgae in China, is also confronted with two controversial issues: one is whether methanol fuel is environmental friendly; the other is whether it produces positive net energy? For these issues, some reports relating to the utilization of microalgae have been conducted (Hirano et al., 1998; Michele et al., 2005; Sawayama et al., 1999; Minowa and Sawayama, 1999), but the method of LCA was not used in the previous research. The purpose of this paper is to study the energy analysis and environmental impacts of the microalgae-based methanol in its whole life. The method of LCA, including air emissions and energy requirement, was carried out for the microalgae-based methanol fuel.
2. Methodology Corresponding author. Tel.: +86 20 87110232; fax: +86 20 87110613.
E-mail address: [email protected] (J. Liu). 0301-4215/$ - see front matter & 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2008.12.010
LCA is a systematic analytical method to identify, evaluate and help minimize environmental impacts of a specific process or
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competing processes. Material and energy balances are used to quantify emissions, resource depletion and energy consumption of all processes between transformation of raw materials into useful products and the final disposal of all products and byproducts. The results are then used to evaluate the environmental impacts of the process so that efforts can be focused on mitigating possible effects. The LCA methodology consists of four interrelated components (Fig. 1):
Goal definition and scoping: The explanation of the study’s
purpose and objective; the identification of the product, process, or activity of interest; the identification of the intended end-use study results; and the key assumptions and methods employed. Inventory analysis: The identification and quantification of raw materials and energy inputs, air emissions, water effluents, solid waste and other life cycle inputs and outputs. Impact assessment: the qualitative or quantitative classification, characterization, valuation of impacts of the inventory items to ecosystems, human health, and natural resources, based on the results of an inventory analysis and application of various methods and models to determine significance of the inventory items. Interpretation: The identification and evaluation of opportunities to achieve improvements in products and/or processes that result in reduced environmental impacts, based on the results of an inventory analysis or impact assessment.
2.1. Functional unit
to support decision-making of methanol fuel policy for the Chinese government. The scope of the study includes the whole life cycle of microalgae-based methanol fuel, which includes microalgae cultivation and treatment, transport, methanol conversion, transport of Fuel methanol, burning of Fuel methanol. The investigated system is depicted in Fig. 2. A traditional inventory quantifies three categories of environmental releases or emissions: atmospheric emissions, waterborne waste, and solid waste. But we only examined atmospheric emissions and solid waste in this study because of the lack of some date. The system under investigation was assumed to be located in some region with the long coastline in China, so the microalgae can be cultured and collected conveniently. In this paper, the microalgae from Futian mangrove reserves of Shenzhen were studied. (Wang et al., 2007). Based on investigation and published surveys, some general assumptions were set for the product system to produce 1000 kg microalgae biomass: (1) The electricity used in this system is recalculated to primary energy, which is based on 100% coal fuels because of the fact that China’s electricity mainly generated from coal. The data about electricity in the form of energy will be recalculated to coal consumption and the releases from coal combustion to generate electricity will be added to the related environmental releases; (2) The unsure-type category of energy in this paper is considered as oil;
Fertilizer
In LCA, the function provided by the analyzed system is uniquely defined in terms of the functional unit. The primary purpose of a functional unit is to provide a reference to which the inputs and outputs are related. Once the functional unit is defined, all the energy and mass flows in the inventory are normalized (ISO 14041, 1998). In this paper, the functional unit is to produce 1000 kg of dry microalgae biomass.
Cultivation
Electricity
Concentration
Solar
Drying
Oil
Transport of dry microalgae
Facility construction
2.2. Definition of goal and scope The first phase of the life cycle assessment is the goal and scope definition. The goal of the study is to identify the environmental impacts and energy efficiency of the microalgaebased methanol fuel, to search opportunities to improve the environmental aspects at various points in its whole life cycle, and
Dry microalgae
Milling
Mixing
Auxiliary materals
Gasification
elctricity
Hydrocarbon reforming
Oil
Gas condintioning
Goal definition and scoping
Methanol synthesis Inventory analysis
Air emissions
Solid waste
Water emissions
Interpretation
Fuel methanol Oil Impact assessment
Fig. 1. The LCA framework.
Transport of methanol
Air emissions
Methanol combustion Fig. 2. Detailed system flow diagram for microalgae-based methanol fuel.
ARTICLE IN PRESS J. Liu, X. Ma / Energy Policy 37 (2009) 1479–1488
(3) SOX is treated as SO2; (4) All solid waste emitted during each process is added up as ‘‘Bulk waste’’, which will be collected and buried; and (5) Only dust and fumes emitted to atmosphere are considered as soot and ashes, during each process.
2.3. Unit processes Product systems are subdivided into a set of unit processes. Unit processes are linked to one another by flows of intermediate products and waste for treatment, to other product system by product flows, and to the environment by elementary flows. (ISO 14041, 1998). Fig. 2 shows the detailed system flow diagram for microalgae-based methanol fuel. According to the method of life cycle inventory, the product system is divided into five unit processes, which are described as the following. 2.3.1. Microalgae cultivation and treatment In the process of microalgae biomass production, the productivity of microalgae biomass cultured outdoors depends on the kind of microalgae, the method and location of the cultivation. The dry microalgae biomass yield is estimated to be about 0.0314 kg/m2, according to the published experimental results (Kadam, 2002).The productivity dominates the scale of the cultivation for a production of 1000 kg microalgae biomass. We set some general assumptions for the production system to produce 1000 kg microalgae biomass. (1) Planting area: 31,800 m2; (2) Fresh microalgae yield: 0.0628 kg/m2; and (3) Dry microalgae conversion rate of fresh microalgae: 2:1. Before the gasification, the microalgae biomass is concentrated by using sedimentation ponds and centrifuges. Based on the agricultural experience with solar drying, it is assumed that solar drying of microalgae is feasible. Fig. 3 shows the system flow diagram for 1000 dry microalgae product. 2.3.2. Transportation of dry microalgae There are many ways to transport the dry microalgae from the culture pond to the methanol plant. Main assumptions are as follow: (1) During the transportation of dry microalgae, the trucks consume oil only; (2) The average transport distance is 100 km; (3) The unit gasoline consumption is 0.07 L/(t km); and (4) The density of gasoline is 0.73 kg/L.
Fertilizer
Cultivation
Electricity
Concentration
Solar
Drying
Facility construction
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2.3.3. Methanol conversion The microalgae were supposed to be gasified under the oxygen atmosphere, and O2 required for the gasification was supplied by a physical adsorption method. During the unit process of methanol conversion, many other materials were consumed, such as coal, electricity, catalyst and so on. Gas composition obtained by the gasification of microalgae biomass at the temperature of 900 1C (Hirano et al., 1998). This gas contained H2, CO, CO2, and CH4 as the main constituents. Fig. 4 shows the unit process in detail. This unit process was simplified by the following assumptions: (1) Energy used in the unit process was converted into the heavy oil mass; (2) The gas obtained by the gasification was not emitted to the air directly but collected. Since the CO and CH4 are gas fuels, they are supposed to be collected in the unit process of methanol conversion. The collected gases can be used to supply heat to some processes in this product system; (3) Only gas emissions were accounted in the conversion; (4) Methanol conversion rate of dry microalgae: 2.17:1; (5) Methanol density: 0.792 kg/L; and (6) Life of facilities were 20 years, 3% of the energy for facility construction was required for maintenance.
2.3.4. Transport of methanol There are many ways to transport the methanol fuel from the methanol plants to methanol vehicles. Main assumptions are set as follow to simplify the unit process. (1) During the transportation of dry microalgae, the trucks consume oil only; (2) The average transportation distance is 100 km; (3) The unit gasoline consumption is 0.07 L/(t km); and (4) The density of gasoline is 0.73 kg/L.
2.3.5. Methanol combustion The end-use of this methanol fuel is to be burned in the methanol vehicle. The amount of methanol fuel required is
Dry microalgae
Milling
Mixing
Auxiliary materals
Gasification
elctricity
Hydrocarbon reforming
Oil
Gas condintioning
Air emissions
Solid waste
Methanol synthesis Water emissions
Microalgae Fig. 3. Unit of microalgae cultivation and treatment.
Methanol Fig. 4. Unit of microalgae-based methanol conversion.
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dependent on the fuel economy of the bus engine, and the emissions are dependent on many factors, including the type of engine. According to the characteristics of vehicles in China, we make some assumptions as follow: (1) The combustion engine efficiency of the methanol vehicle is 16.2% (Wei et al., 2007) and (2) The consumption of the methanol vehicle is 16.5 L/100 km (Wei et al., 2007). 2.4. Data collection and validation of data Based on investigation and literature surveys, a large amount of data, such as data related to fertilizers, microalgae cultivate, etc, during microalgae cultivation, transportation distance, and so forth, are obtained. Some data come from journals and books published in China. The net energy and gas emissions of the methanol used as vehicle fuel were taken from the published journals. The data are reviewed and verified, based on the best knowledge available in China. Table 1 shows the data references.
3. Life cycle inventory
the culture pond and their associated emissions, as well as the manufacturing, harvesting, and processing of the inputs used to grow microalgae. For example, the energy required coaling, process, construction of facilities including those for their maintenance and operation is estimated. In the unit process, energy for the cultivation of microalgae and energy for their treatment were calculated individually. These upstream environmental flows are combined with the flows associated with the actual microalgae growing and harvesting to calculate the total emissions. In this process, to get 1000 kg dry microalgae, there are a large amount of emissions, material inputs and energy consumption, which are shown in Table 2. It can be seen that the air emissions are mainly resulted from the microalgae cultivation, but CO2 is taken out of the atmosphere during the growth of the microalgae. 3.2. Transport of dry microalgae In this unit process, emissions are due to the dry microalgae distributed to the methanol plant by trucks. According to the former assumptions, emissions and energy consumption from the transport of 1000 kg dry microalgae are shown in Table 3. It can be seen that, in this process, the main emissions are CO2 and CO.
3.1. Microalgae cultivation and treatment 3.3. Methanol conversion The unit process of this LCI study involves identification of the complete environmental flows associated with microalgae production. This includes the amounts of chemicals and fuels used in
In this unit process, the air emissions are related to the temperature of the gasification. We assumed that gas composition
Table 1 Data resource. Item
Data source
Feedstock production
Fertilizer, feedstock plant, management, and harvest
Kadam (2002); Wang et al. (2007)
Methanol fuel production
Methanol production technics, energy and emissions
Hirano et al. (1998); Michele et al. (2005); Sawayama et al. (1999); Minowa and Sawayama (1999) Zhou and Xiao-qian (2004); Wei et al. (2007)
Assistant material production energy (electricity, coal, diesel oil) Coproducts
Transport Combustion
Energy consumption and emissions Data
Hirano et al. (1998); Kadam (2002)
Zhou and Xiao-qian (2004) Wei et al. (2007); Liu et al. (2007a, b)
Table 2 Inventory results of microalgae cultivation and treatment. Fertilizer production
Microalgae cultivation
Concen-tration
Mainten-ance
Drying
227.12 /
/ 25.6
/ 20.7
/ /
/ / 0.459 0.734 / / 91.75 4.59
/ / 0.371 0.593 / / 74.18 3.71
/ / / / / / / /
Electricitya Oil
kw h kg
/
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
0.049 0.421 1.033 1.071 1.607 0.007 821.387 0.089
1.1356 9.312 120.8 288 0.908 1.136 894327b 12.4
Solid waste
Solid
g
/
4661
Resource consumption
a b
0.29
The electricity used is recalculated to primary energy, which is based on 100% coal fuels. CO2 is taken out of the atmosphere during growth of the microalgae.
/
/
/
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was obtained by the gasification of microalgae biomass at the temperature of 900 1C. In this process, emissions from getting 460 kg Fuel methanol are shown in Table 4. It can be seen that CO2, CH4 and SOX are the main gas compositions.
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Table 5 Emissions and energy consumption for the transport of methanol. Transport of 460 kg methanol Resource consumption
Oil
MJ
119.7
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
6.348 169.1 8.418 2.116 / / 9761.2 1.012
Solid waste
Solid
g
/
3.4. Transport of methanol In this unit process, emissions are due to the Fuel methanol distributed to the methanol plant by trucks. According to the former assumptions, emissions and energy consumption from the transport of methanol fuel are shown in Table 5.
3.5. Methanol combustion In this unit process, emissions are due to the methanol burned in the methanol vehicle. According to the former assumptions, emissions and energy consumption of this process are shown in Table 6.
Table 6 Emissions and energy consumption for the microalgae combustion.
3.6. Sensitivity analysis
Methanol combustion
The purpose of the sensitivity analysis is to estimate the effects on the outcome of a study of the data. In the study, the influence of increasing and decreasing some production factors by 10% (Rubo et al., 2007), one at a time, was studied. The sensitivity analysis results are shown in Table 7.
Resource consumption
Oil
MJ
147.9
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
588.1 8123.8 781.7 24.65 / / 717658 31.69
Solid waste
Solid
g
/
Table 3 Emissions and energy consumption for the transport of microalgae. Transport of 1000 kg dry microalgae Resource consumption
Oil
MJ
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
Solid waste
Solid
g
260.2
13.8 367.6 18.3 4.6 / / 21220 2.2
/
Table 4 Emissions and energy consumption for the microalgae conversion. Methanol conversion Resource consumption
Resource consumption Air emissions
Methanol yield Solid waste
Oil Dry microalgae
kg kg
57.7 1000
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
1.023 8 108.9 259.5 401 1.023 885426 10.84
Methanol Solid
kg g
460 4200
From Table 7, we can see that the change of use of fertilizer has little effect on the output of this microalgae-based Fuel methanol production system. As the microalgae average yield increased 10%, the amount of CO2 emission decreased 12.5788% whereas that of the other emissions increased. And the amount of CO2 emission changed the most obviously, that is mainly because CO2 is the main raw material for photosynthesis in the growth of microalgae.
4. Impact assessment 4.1. Energy efficiency analysis Adding up energy consumption during all stages, it will get total energy consumption for the entire life cycle of microalgaebased Fuel methanol. Energy requirements for the whole life cycle were converted to oil based on the aforementioned assumptions. Total energy consumption and energy consumption for each process step are presented in Table 8. It can be seen that microalgae cultivation and treatment and methanol conversion are the two most energy consumed processes. The two unit processes consume 61.1% and 32% of the total energy, respectively.
Z¼
qmethanol LCAenergy
(1)
qmethanol is the heating value of produced methanol; LCAenergy is the energy used in the whole life cycle. The energy conversion efficiency is a key indicator to evaluate the eco-performance of a renewable energy source. It can be likely
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Table 7 Sensitivity analysis results of the life cycle inventory.
VOC CO NOx SOx CH4 N2O CO2 Solid PM10
Use of fertilizer (10%)
Use of fertilizer (+10%)
Microalgae average yield (10%)
Microalgae average yield (+10%)
0.0013 0.0000 0.0076 0.0186 0.0002 0.0319 0.0114 0.0000 0.0162
0.0008 0.0000 0.0167 0.0186 0.0002 0.0319 0.0114
0.0192 0.0005 1.1851 5.0321 0.0001 5.1825 12.5788
0.0192 0.0004 1.2002 5.0321 0.0001 5.1825 12.5788
0.0000 0.0162
5.2646 2.1971
5.2646 2.1971
In the EDIP method (Hauschild and Wenzel, 1998) the interpretation of the inventory is done by three steps:
Table 8 Life cycle energy consumption of microalgae-based fuel methanol. Stage
Energy consumption (kg)
Miacroalgae cultivation and treatment Transport of dry microalgae Methanol conversion Transport of methanol Methanol combustion
110.18 6.2 57.7 2.85 3.52
Total
180.45
Distribution (%) 61.1 3.4 32 1.6 1.9
100
defined as the heating value of 460 kg methanol equivalent to the energy used to produce it during all the life cycle phases. Total processes required 180.45 kg of oil, which equals to 7398.45 MJ. The produced energy, on the other hand, was corresponded to 9235.25 MJ obtainable from 460 kg Fuel methanol. According to the formula (1), the ratio of produced energy to required energy was 1.24 which indicated the energy balance was positive. It can be seen that the major part of the required energy, about 61.1%, was occupied in the process of microalgae biomass production. In this process, microalgae cultivation was a major contributor of about 61.1% in the energy requirement, which led us to an idea that the energy balance would be improved by using microalgae which was produced in natural environment without an artificial cultivation. If microalgae can be used as a raw material, the energy requirement for the biomass production would be reduced almost only to harvest, concentration, and transportation. This meant that an excellent energy producing process by selecting an appropriate method for biomass production which would consume smaller amount of energy. The life cycle energy consumption of producing 1 MJ oil is 0.162 MJ (Yang et al., 2002), so the energy conversion efficiency of oil is 6.17. It can be seen that the energy conversion efficiency of Fuel methanol is compared unfavorably with oil. Although the energy conversion efficiency of Fuel methanol is much lower than oil, there is an emerging interest in the development of Fuel methanol because of the increasing in environmental pollutions and uncertainty concerning oil reserve.
4.2. Environment impact assessment For life cycle assessment to be able to support decisions with respect to product solutions, the data obtained in the inventory must be interpreted to show which of the environmental exchanges are significant, and how great their contributions are compared to each other, so as to help to examine and evaluate the environmental impacts.
(1) Characterization: How much do the emissions contribute to the various types of environmental impacts? In the characterization step, it is determined how much the emissions associated with the product contribute to the various types of environmental impacts (e.g. global warming, acidification etc.). For example, all emissions that contribute to global warming are expressed in CO2-equivalents. The characterization is based on properties of the emitted species, and characterization factors available in the literature are globally valid. (2) Normalization: How great are the potentials for impacts on the environment relative to the impacts from the society’s activities as a whole? In the normalization step, contributions from the product to each type of environmental impact is divided by the expected lifetime of the product and the yearly contribution to each impact from an average person in one year. (3) Weighting: Which of the environmental impacts are the most important? Some environmental impacts may be considered more important than others, and the purpose of the weighting step is to weight the results obtained in the normalization step in accordance with the users concern with the studied environmental impacts. The rating of concern with environmental impacts is of course subjective, a several individual sets of weighting factors can be established, based on different means. Politically determined environmental targets have been selected as basis for weighting by the EDIP method, and year 2000 has been chosen as the common target year. The result of the weighting is a ‘‘weighted environmental impact potential’’, with the unit milliperson equivalents, targeted, mPET2000. The weighting factors indicate how important various environmental impacts area considered in China. A weighting factor of one indicates that status in 1990 will be maintained in year 2000 according to the national plants. Weighting factors smaller than 1 indicate how much the environmental impact will grow between 1990 and 2000 whereas weighing factors larger than 1 indicate how much the environmental impact will be reduced between 1990 and 2000. The normalization references and weighting factor are specific for different countries. Due to lack of such factors for China, the classification of the inventory data to impact categories was made using the method reported by Yang and Nielsen (2001). The emissions of the system have been grouped into impacts (characterization step) based on the method of Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences
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0.0005mPET2000 0.0062mPET2000
0.0048mPET2000 0.73
0.61 0.62 0.016 2.519
1 1 PM10 Solid Soot and ashes Bulk waste
0.016 2.519
62,000 g NO3-eq/ (person?a) 18,000 g/(person?a) 2,51,000 g/(person?a) 1.35 0.290 NOx Nutrient enrichment
0.391 g NO 3 eq/g
0.1393mPET2000 0.53 650 g C2H4-eq/ (person?a) 0.6 0.03 0.007 0.168 2.312 0.115 VOC CO CH4 Photochemical ozone formation
1 0.7 0.163 0.290 SOx NOx
1 25 320 2
Acidification
0.1708 C2H 4 eq/g
0.0074mPET2000 0.73 36,000 g SO2-eq/ (person?a)
0.0288mPET2000 0.83
0.366 g SO2 eq/g
Equivalent mass Equivalent factor
201.9 0.115 0.290 2.312
Global Regional Regional Regional Local Local
CO2 CH4 NOx CO
Global warming (GW) Acidification (AC) Nutrient enrichment (NE) Photochemical ozone formation (PO) Solid waste (BW) Slag and ashes (SA)
Global warming
Environmental impacts
Emission value
Table 9 Categorization of the impacts.
Emission
4.2.1.4. Photochemical ozone formation. Non-methane volatile organic compounds (NMVOC), CO and CH4 are considered as the main contributors to photochemical ozone formation in China
Impact category
4.2.1.3. Nutrient enrichment. The main sources of nutrient enrichment are N and P emitted to water and NOX and NH3 emitted into the atmosphere (Yang and Nielsen, 2001).The contribution in this impact category is measured in terms of nitrogen equivalents released per gram of emission. Table 10 shows the results of nutrient enrichment characterizations of the different processes in the life cycle. The values are expressed in grams of equivalent NO 3 per g. The emission related to the nutrient enrichment in the LCI analyzed is NOX which has the corresponding characterization factors of 1.35. (Yang et al., 2002)
Table 10 The weighted environmental potentials of microalgae-based methanol for different environmental impact categories.
4.2.1.2. Acidification. Substances such as SOX, NOX, NH3, H3PO4, HF, H2S, HCl and organic acids all contribute to acidification of the environment. In the Chinese inventory the main contributions of SOX, NOX are addressed (Yang and Nielsen, 2001). Acidification includes the processes that increase the acidity of water and soil systems by releasing SO2 or equivalents. Table 10 shows the results of acidification characterizations of processes in the life cycle. The values are expressed in grams of equivalent SO2 per g. The emissions related to the acidification in the LCI analyzed are SO2, and NOX, which have the corresponding characterization factors of 1.0 and 0.7, respectively (Yang et al., 2002). The total influence of SO2 on the acidification effect, accounted for 44.55%, is a litter smaller than the contribution of NOX.
Normalization reference
4.2.1. Characterization 4.2.1.1. Global warming. This impact category refers to the change in earth’s climate due to the build-up of chemicals that trap heat from the sunlight. The contribution in global warming impact category indicates the potential contribution to global warming using. Table 10 shows the results of the global warming characterization of the whole life cycle. The values are expressed in grams of equivalent CO2 per gram. The total influence of NOX and CO on the global warming effect is very small in comparison to the contribution of CO2, accounted for 66.83%. This is because, in despite of having a lower characterization factor, the amount of CO2 emitted is comparatively higher than the other gases.
87,00,000 g CO2-eq/ (person?a)
Weighting factor
(Yang et al., 2002). This method leads to a single score. Six impact categories were considered: global warming, acidification, nutrient enrichment, photochemical ozone formation, bulk waste and soot and ashes. The impact categories were considered in this paper are shown in Table 9. The following section introduced the environment impact assessment of microalgae-based Fuel methanol and gasoline. This paper studied the environmental impact of the two fuels consumed by vehicles of 1 km journey, respectively. The data needed in the following section were based on the previous work.
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302.1 g CO2 eq/g
Weighted environment potential
J. Liu, X. Ma / Energy Policy 37 (2009) 1479–1488
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0.0131mPET2000 0.0031mPET2000 0.0017mPET2000 62,000 g NO3-eq/(person?a) 18,000 g/(person?a) 2,51,000 g/(person?a) 1.35 1 1 0.808 0.093 0.684 NOx PM10 Solid Nutrient enrichment Soot and ashes Bulk waste
1.094 g NO 3 eq/g 0.0923 0.684
0.73 0.61 0.62
0.681mPET2000 0.53 0.581 16.06 0.648 VOC CO CH4 Photochemical ozone formation
650 g C2H4-eq/(person?a) 0.6 0.03 0.007
0.152 0.808 SOx NOx Acidification
0.8354 C2H 4 eq/g
0.0145mPET2000 0.73 36,000 g SO2-eq/(person?a)
0.1148mPET2000 0.83 Global warming
Almost every year, microalgae blooms cover extensive areas of many Chinese lakes, such as Chaohu Lake, Taihu Lake and Dianchi Lake due to serious eutrophication. This results in deterioration of water, death of fish and disaster to residents around the lakes. Elimination of the microalgae blooms becomes an urgent project. Enormous microalgae biomass consisting of Chllorella,
896.9 0.648 0.808 16.06
5. Discussion
Table 11 The weighted environmental potentials of gasoline for different environmental impact categories.
4.2.4. Comparison of environment impact loadings The system scope for LCA of gasoline is from its exploitation to end-use. In this research, the data needed for the analysis were collected from various sources including institutional statistics (China statistical yearbook, 2000), and published studies (Liu et al., 2007a, b; Yang et al., 2002). The EIL of gasoline consumed by vehicles of 1 km journey was calculated using the same method as methanols. The EIL of gasoline is 0.828mPET2000 in contrast to 0.187mPET2000 of Fuel methanol. A more detailed data of this LCA is summarized in Table 11. Fig. 5 illustrates the environmental impact of Fuel methanol is much less than gasoline, especially the photochemical ozone formation value of Fuel methanol is about 20% of gasoline. From this comparison, it can be seen that Fuel methanol has advantages over gasoline (conventional fossil fuel) including reduced emissions, renewability and cleaning properties. Fuel methanol can be regarded as a new measure for solving energy and environmental problems effectively.
Equivalent mass
The EIL of the microalgae-based methanol consumed by vehicles of 1 km journey is 0.187mPET2000, in which that the value of 1 point is representative for one thousandth of the yearly environmental load of one average Chinese inhabitant. Table 11 shows that the effect of photochemical ozone formation is the highest of all the calculated categorization of the impacts. This phenomenon is mainly due to the high emissions of some gases, such as VOC, CO and CH4.
0.7174 g SO2 eq/g
(2)
CO2 CH4 NOx CO
j
X EPðjÞ 90 WFðjÞ T ERðjÞ90 j
Equivalent factor
WPðjÞ ¼
Emission value
X
Emission
EIL ¼
1 0.7
4.2.3. The environmental impact loading At the final step, the weighted environmental potentials are added up to give an environmental impact loading (EIL), which can be defined as follows:
8,700,000 g CO2-eq/(person?a)
Normalization reference
Weighting factor
4.2.2. Normalization and weighting Table 10 summarizes the results from the categorization of the impacts, for the chosen functional unit. Weighting factors are applied in order to scale the seriousness of the results, measured in indicator points. The normalization references and weighting factors used for the purpose of this study are shown in Table 10. Photochemical ozone formation is the biggest contributing factor, which accounts for 74.5% of the total environmental impact.
1 25 320 2
(Yang and Nielsen, 2001). Table 10 shows the results of photochemical ozone formation characterizations of the different processes in microalgae-based methanol life cycle. The values are expressed in grams of equivalent C2H4 per g. The emissions related to the photochemical ozone formation in the LCI analyzed are CO and CH4, which have the corresponding characterization factors of 0.03 and 0.007, respectively (Yang et al., 2002). The total influence of VOC on the photochemical ozone formation effect, accounted for 59.02%, has the most contribution to the photochemical ozone formation.
1204 g CO2 eq/g
Weighted environment potential
J. Liu, X. Ma / Energy Policy 37 (2009) 1479–1488
Impact category
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treatment, transport of dry microalgae, methanol conversion, transport of methanol, methanol combustion are checked. Several conclusions were drawn from this study.
mPET2000 The weighted environment potential
0.0007
Methanol
0.0006
1487
Gasoline
0.0005 0.0004 0.0003 0.0002 0.0001 w as te So lid
as he s nd
So ot a
or m at on
Ph ot oc
he m ic a
lo zo ne f
nr ic
hm en t
tio n ut rie
nt e
ci di fic a A N
G
lo ba l
w ar
m in g
0
Fig. 5. The weighted environmental potentials of microalgae-based methanol and gasoline.
Microcystis and other genera could be harvested from these eutrophic lakes for fuel production. Meanwhile, utilization of planktonic microalgae for Fuel methanol may decrease the eutrophication of lakes. Therefore, utilization of microalgae is beneficial to both production of renewable fuels and improvement of the ecological environment. There were 5 cities taking part in the first stage demonstration of E10 (10% ethanol in volume and 90% gasoline in volume) fuel blends since 2002, and more cities and provinces joined in the program in 2004 accordingly. It is said that methanol is widely used in commercial gasoline. More and more governments and companies are paying attentions to the industry for the importance and higher benefit. Methanol shows a prosperous market for its huge recourse, easy obtainment and low emissions. So, many researchers and officials in China think that it should take an important role in automobile industry development and gasoline fuel substitute. The promotion of methanol as a fuel substitute is a huge social project, which needs the help of related departments. The production criterion and development planning of Fuel methanol must be established as soon as possible. The government should set down some favorable policies which can attract more investments to the Fuel methanol industry. And the most urgent thing is to encourage automobile manufactories to manufacture automobiles which can use diverse kinds of fuels. The energy consumption inventories and environmental impact type inventories in this paper are not enough complete, however, they are still valuable for providing us with a round estimate of the energy efficiency and environmental impacts of microalgae-based Fuel methanol in China. The normalization references and weighting factors used in this paper should be considered as rough estimates and a little bit old, especially, the weighting factors presented in this paper are based on target emissions in 2000 which is actually not ‘‘the future’’ when this paper comes out. However, they are still useful to conduct us to research the life cycle of microalgae-based Fuel methanol in China because these normalization references and weighting factors have not changed greatly for a number of years anyway, and an updated version can be determined more easily based on the results presented here.
6. Conclusions The present study shows the results of an LCA performed upon microalgae-based Fuel methanol. Microalgae cultivation and
(1) From sensitivity analysis on life cycle inventory, we can see that the use of fertilizer has little effect on the output of this microalgae-based Fuel methanol production system. In the same condition of variable presupposition, CO2 emission has the biggest variation. But CO2 emission decreased 12.5788% while the microalgae yield increased 10% that is mainly because CO2 is the main raw material for photosynthesis in the growth of microalgae. (2) The energy conversion efficiency of Fuel methanol is 1.24. In this study, microalgae cultivation was a major contributor of about 61.1% in the energy requirement, which led us to an idea that the energy balance would be improved by using microalgae which was produced in natural environment without an artificial cultivation. (3) The environmental impact loading of microalgae-based fuel methanol is 0.187mPET2000 in contrast to 0.828mPET2000 for gasoline. The effect of photochemical ozone formation is the highest of all the calculated categorization impacts of the two fuels. (4) Utilization of microalgae an raw material of producing methanol fuel is beneficial to both production of renewable fuels and improvement of the ecological environment. This fuel is friendly to the environment, which should take an important role in automobile industry development and gasoline fuel substitute.
Acknowledgements This work was supported by Natural Science Foundation of Guangdong Province (China) Research Team (No. 003045). References Bechtold, R., Vatsky, A., Moog, C., Yelne, A., Laughlin, M., 1996. Special Publications Society of Automotive Engineers 9, 263–273. Dadong, L., Fusheng, H., Chengen, X., Xieqing, W., 2001. Direction towards environmental-friendly automotive fuel in China. In: Proceedings of state-of-art and perspective of environmental-friendly automotive fuel in China; October 2001. Hauschild, M., Wenzel, H., 1998. Environmental assessment of products. Vol. 2: Scientific background, United Kingdom. Hirano, A., Hon-Nami, K., Kunito, S., Hada, M., Ogushi, Y., 1998. Temperature effect on continuous gasification of microalgal biomass: theoretical yield of methanol production and its energy balance. Catalysis Today 45, 399–404. ISO 14041, 1998. ISO 14041 environment management—life cycle assessment— goal and scope definition and inventory analysis. International organization for Standardization. Kadam, K.L., 2002. Environmental implications of power generation via coalmicroalgae cofiring. Energy 27, 905–922. Liu, Hong, Yu, He-wu, Hou, Zhi-chao, 2007a. The life cycle assessment of coal based fuels of methanol and electric automotive. Marine energy saving 05, 27–32 (in Chinese). Liu, Shenghua, Eddy, R., Hu, Tiegang, Wei, Yanjv, 2007b. Study of spark ignition engine fueled with methanol/gasoline fuel blends. Applied Thermal Engineering 27, 1904–1910. Aresta, Michele, Dibenedetto, Angela, Barberio, Grazia, 2005. Utilization of macroalgae for enhanced CO2 fixation and biofuels production: development of a computing software for an LCA study. Fuel Processing Technology 86, 1679–1693. Minowa, T., Sawayama, S., 1999. A novel microalgal system for energy production with nitrogen cycling. Fuel 78, 1213–1215. Leng, Rubo, Wang, Chengtao, Zhang, Cheng, Dai, Du, Pu, Gengqiang, 2007. Life cycle inventory and energy analysis of cassava-based Fuel methanol in China. Cleaner production xx, 1–11. Sakai, M., Kaneko, M., 1996. Biomass Fuel for the 21st Century, MAFF International Work Shop on Versatile Use of Agricultural Products. Sawayama, S., Minowa, T., Yokoyama, S-Y., 1999. Possibility of renewable energy production and CO2 mitigation by thermochemical liquefaction of microalgae. Biomass and Bioenergy 17, 33–39. Wang, Yu, Lu, Changyi, Tam, Nora Fung-Yee, Xu, Hulin, Tang, Senming, 2007. Seasonal and spatial variation of phytoplankton and relationship with
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water-quality factors in Futian Mangroves of Shenzhen. Ecological Science 26 (6), 505–512 (in Chinese). Wei, Ying-chun, Deng, Shu-ping, Jiang, Yun-feng, 2007. Analysis of life cycle greenhouse gases emission of coal-based methanol and coal-based ft diesel. Coal conversion 30 (4), 80–85 (in Chinese). Xiaoling, Miao, Qingyu, Wu, Changyan, Yang, 2004. Fast pyrolysis of microalgae to produce renewable fuels. Journal of analytical and applied pyrolysis 71, 855–863. Yang, Jian-xin, Nielsen, Per H., 2001. Chinese life cycle impact assessment factors. Journal of Environmental Sciences 13 (2), 205–209.
Yang, Jian-xin, Xu, Cheng, Wang, Ru-song, 2002. Methodology and application of life cycle assessment. China Meteorological Press, Beijing (in Chinese). Yongguang, Z., 2001. Direction towards automotive alternative fuel in 21st century. In: Proceedings of state-of-art and perspective of environmental friendly automotive fuel in China; October 2001. Zhongyu, X., 2000. Economic globalization and petroleum security strategy in China. Theory Front 13, 6–9. Zhou, Zhi-ping, Xiao-qian, M.A., 2004. Life cycle assessment on the solar thermal power generation. Renewable Energy 2, 12–15 (in Chinese).
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Energy Policy journal homepage: www.elsevier.com/locate/enpol
The analysis on energy and environmental impacts of microalgae-based fuel methanol in China Jing Liu , Xiaoqian Ma Electric Power College, South China University of Technology, 381 Wushan Road, Tianhe District, Guangzhou 510640, China
a r t i c l e in fo
abstract
Article history: Received 22 May 2008 Accepted 5 December 2008 Available online 10 January 2009
The whole life of methanol fuel, produced by microalgae biomass which is a kind of renewable energy, is evaluated by using a method of life cycle assessment (LCA). LCA has been used to identify and quantify the environment emissions and energy efficiency of the system throughout the whole life cycle, including microalgae cultivation, methanol conversion, transport, and end-use. Energy efficiency, defined as the ratio of the energy of methanol produced to the total required energy, is 1.24, the results indicate that it is plausible as an energy producing process. The environmental impact loading of microalgae-based fuel methanol is 0.187mPET2000 in contrast to 0.828mPET2000 for gasoline. The effect of photochemical ozone formation is the highest of all the calculated categorization impacts of the two fuels. Utilization of microalgae an raw material of producing methanol fuel is beneficial to both production of renewable fuels and improvement of the ecological environment. This Fuel methanol is friendly to the environment, which should take an important role in automobile industry development and gasoline fuel substitute. & 2008 Elsevier Ltd. All rights reserved.
Keywords: Life cycle assessment Microalgae Methanol fuel
1. Introduction China has been a net importer of oil since 1993. In 2005, more than 140 million tons are imported. China is the second biggest country of oil importing, just behind the US. Imported oil currently accounts for about 25% (Zhongyu, 2000) of China’s total domestic needs, and the amount will probably increase to more than 50% by the year 2015 due to the rapidly rising demand for oil by the flourishing economy (Dadong et al., 2001; Yongguang, 2001). Around 35% of the total oil was consumed as fuel by automobiles, where gasoline consumption is some 70 million tons (Liu et al., 2007a, b). To deal with the higher and higher oil price and to keep the fast development of automobile industry, alternative fuels are regarded highly. Biomass resources include wood and wood wastes, energy crops, aquatic plants, agricultural crops and their waste byproducts, municipal wastes and animal wastes. Among these, microalgae have been suggested as very good candidates for fuel production because of their advantages of higher photosynthetic efficiency, higher biomass production and faster growth compared to those lignocellulosic materials (Xiaoling et al., 2004). Though the microalgae biomass can be used as a solid fuel because of its high heating value of more than 4000 kcal/kg (Sakai and Kaneko, 1996), we direct our attention to the conversion of it into methanol since methanol is one of liquid fuels which are easy to transport and is useful for other various purposes.
For these reasons, the Chinese government has to develop biomass methanol as one of its transportation fuels for the sake of energy security and environmental improvement reasons. Methanol fuel was affirmed to be a kind of possible alternative energy source and could be used in methanol vehicles, according to statements made at a conference held by the State Council in November, 2006. Many countries including Japan and United States (Bechtold et al., 1996) are taking great interest in methanol vehicle for practical use. Therefore, there will be an increasing demand for methanol in the future. Like other biomass fuel, methanol fuel, derived from microalgae in China, is also confronted with two controversial issues: one is whether methanol fuel is environmental friendly; the other is whether it produces positive net energy? For these issues, some reports relating to the utilization of microalgae have been conducted (Hirano et al., 1998; Michele et al., 2005; Sawayama et al., 1999; Minowa and Sawayama, 1999), but the method of LCA was not used in the previous research. The purpose of this paper is to study the energy analysis and environmental impacts of the microalgae-based methanol in its whole life. The method of LCA, including air emissions and energy requirement, was carried out for the microalgae-based methanol fuel.
2. Methodology Corresponding author. Tel.: +86 20 87110232; fax: +86 20 87110613.
E-mail address: [email protected] (J. Liu). 0301-4215/$ - see front matter & 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2008.12.010
LCA is a systematic analytical method to identify, evaluate and help minimize environmental impacts of a specific process or
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competing processes. Material and energy balances are used to quantify emissions, resource depletion and energy consumption of all processes between transformation of raw materials into useful products and the final disposal of all products and byproducts. The results are then used to evaluate the environmental impacts of the process so that efforts can be focused on mitigating possible effects. The LCA methodology consists of four interrelated components (Fig. 1):
Goal definition and scoping: The explanation of the study’s
purpose and objective; the identification of the product, process, or activity of interest; the identification of the intended end-use study results; and the key assumptions and methods employed. Inventory analysis: The identification and quantification of raw materials and energy inputs, air emissions, water effluents, solid waste and other life cycle inputs and outputs. Impact assessment: the qualitative or quantitative classification, characterization, valuation of impacts of the inventory items to ecosystems, human health, and natural resources, based on the results of an inventory analysis and application of various methods and models to determine significance of the inventory items. Interpretation: The identification and evaluation of opportunities to achieve improvements in products and/or processes that result in reduced environmental impacts, based on the results of an inventory analysis or impact assessment.
2.1. Functional unit
to support decision-making of methanol fuel policy for the Chinese government. The scope of the study includes the whole life cycle of microalgae-based methanol fuel, which includes microalgae cultivation and treatment, transport, methanol conversion, transport of Fuel methanol, burning of Fuel methanol. The investigated system is depicted in Fig. 2. A traditional inventory quantifies three categories of environmental releases or emissions: atmospheric emissions, waterborne waste, and solid waste. But we only examined atmospheric emissions and solid waste in this study because of the lack of some date. The system under investigation was assumed to be located in some region with the long coastline in China, so the microalgae can be cultured and collected conveniently. In this paper, the microalgae from Futian mangrove reserves of Shenzhen were studied. (Wang et al., 2007). Based on investigation and published surveys, some general assumptions were set for the product system to produce 1000 kg microalgae biomass: (1) The electricity used in this system is recalculated to primary energy, which is based on 100% coal fuels because of the fact that China’s electricity mainly generated from coal. The data about electricity in the form of energy will be recalculated to coal consumption and the releases from coal combustion to generate electricity will be added to the related environmental releases; (2) The unsure-type category of energy in this paper is considered as oil;
Fertilizer
In LCA, the function provided by the analyzed system is uniquely defined in terms of the functional unit. The primary purpose of a functional unit is to provide a reference to which the inputs and outputs are related. Once the functional unit is defined, all the energy and mass flows in the inventory are normalized (ISO 14041, 1998). In this paper, the functional unit is to produce 1000 kg of dry microalgae biomass.
Cultivation
Electricity
Concentration
Solar
Drying
Oil
Transport of dry microalgae
Facility construction
2.2. Definition of goal and scope The first phase of the life cycle assessment is the goal and scope definition. The goal of the study is to identify the environmental impacts and energy efficiency of the microalgaebased methanol fuel, to search opportunities to improve the environmental aspects at various points in its whole life cycle, and
Dry microalgae
Milling
Mixing
Auxiliary materals
Gasification
elctricity
Hydrocarbon reforming
Oil
Gas condintioning
Goal definition and scoping
Methanol synthesis Inventory analysis
Air emissions
Solid waste
Water emissions
Interpretation
Fuel methanol Oil Impact assessment
Fig. 1. The LCA framework.
Transport of methanol
Air emissions
Methanol combustion Fig. 2. Detailed system flow diagram for microalgae-based methanol fuel.
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(3) SOX is treated as SO2; (4) All solid waste emitted during each process is added up as ‘‘Bulk waste’’, which will be collected and buried; and (5) Only dust and fumes emitted to atmosphere are considered as soot and ashes, during each process.
2.3. Unit processes Product systems are subdivided into a set of unit processes. Unit processes are linked to one another by flows of intermediate products and waste for treatment, to other product system by product flows, and to the environment by elementary flows. (ISO 14041, 1998). Fig. 2 shows the detailed system flow diagram for microalgae-based methanol fuel. According to the method of life cycle inventory, the product system is divided into five unit processes, which are described as the following. 2.3.1. Microalgae cultivation and treatment In the process of microalgae biomass production, the productivity of microalgae biomass cultured outdoors depends on the kind of microalgae, the method and location of the cultivation. The dry microalgae biomass yield is estimated to be about 0.0314 kg/m2, according to the published experimental results (Kadam, 2002).The productivity dominates the scale of the cultivation for a production of 1000 kg microalgae biomass. We set some general assumptions for the production system to produce 1000 kg microalgae biomass. (1) Planting area: 31,800 m2; (2) Fresh microalgae yield: 0.0628 kg/m2; and (3) Dry microalgae conversion rate of fresh microalgae: 2:1. Before the gasification, the microalgae biomass is concentrated by using sedimentation ponds and centrifuges. Based on the agricultural experience with solar drying, it is assumed that solar drying of microalgae is feasible. Fig. 3 shows the system flow diagram for 1000 dry microalgae product. 2.3.2. Transportation of dry microalgae There are many ways to transport the dry microalgae from the culture pond to the methanol plant. Main assumptions are as follow: (1) During the transportation of dry microalgae, the trucks consume oil only; (2) The average transport distance is 100 km; (3) The unit gasoline consumption is 0.07 L/(t km); and (4) The density of gasoline is 0.73 kg/L.
Fertilizer
Cultivation
Electricity
Concentration
Solar
Drying
Facility construction
1481
2.3.3. Methanol conversion The microalgae were supposed to be gasified under the oxygen atmosphere, and O2 required for the gasification was supplied by a physical adsorption method. During the unit process of methanol conversion, many other materials were consumed, such as coal, electricity, catalyst and so on. Gas composition obtained by the gasification of microalgae biomass at the temperature of 900 1C (Hirano et al., 1998). This gas contained H2, CO, CO2, and CH4 as the main constituents. Fig. 4 shows the unit process in detail. This unit process was simplified by the following assumptions: (1) Energy used in the unit process was converted into the heavy oil mass; (2) The gas obtained by the gasification was not emitted to the air directly but collected. Since the CO and CH4 are gas fuels, they are supposed to be collected in the unit process of methanol conversion. The collected gases can be used to supply heat to some processes in this product system; (3) Only gas emissions were accounted in the conversion; (4) Methanol conversion rate of dry microalgae: 2.17:1; (5) Methanol density: 0.792 kg/L; and (6) Life of facilities were 20 years, 3% of the energy for facility construction was required for maintenance.
2.3.4. Transport of methanol There are many ways to transport the methanol fuel from the methanol plants to methanol vehicles. Main assumptions are set as follow to simplify the unit process. (1) During the transportation of dry microalgae, the trucks consume oil only; (2) The average transportation distance is 100 km; (3) The unit gasoline consumption is 0.07 L/(t km); and (4) The density of gasoline is 0.73 kg/L.
2.3.5. Methanol combustion The end-use of this methanol fuel is to be burned in the methanol vehicle. The amount of methanol fuel required is
Dry microalgae
Milling
Mixing
Auxiliary materals
Gasification
elctricity
Hydrocarbon reforming
Oil
Gas condintioning
Air emissions
Solid waste
Methanol synthesis Water emissions
Microalgae Fig. 3. Unit of microalgae cultivation and treatment.
Methanol Fig. 4. Unit of microalgae-based methanol conversion.
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dependent on the fuel economy of the bus engine, and the emissions are dependent on many factors, including the type of engine. According to the characteristics of vehicles in China, we make some assumptions as follow: (1) The combustion engine efficiency of the methanol vehicle is 16.2% (Wei et al., 2007) and (2) The consumption of the methanol vehicle is 16.5 L/100 km (Wei et al., 2007). 2.4. Data collection and validation of data Based on investigation and literature surveys, a large amount of data, such as data related to fertilizers, microalgae cultivate, etc, during microalgae cultivation, transportation distance, and so forth, are obtained. Some data come from journals and books published in China. The net energy and gas emissions of the methanol used as vehicle fuel were taken from the published journals. The data are reviewed and verified, based on the best knowledge available in China. Table 1 shows the data references.
3. Life cycle inventory
the culture pond and their associated emissions, as well as the manufacturing, harvesting, and processing of the inputs used to grow microalgae. For example, the energy required coaling, process, construction of facilities including those for their maintenance and operation is estimated. In the unit process, energy for the cultivation of microalgae and energy for their treatment were calculated individually. These upstream environmental flows are combined with the flows associated with the actual microalgae growing and harvesting to calculate the total emissions. In this process, to get 1000 kg dry microalgae, there are a large amount of emissions, material inputs and energy consumption, which are shown in Table 2. It can be seen that the air emissions are mainly resulted from the microalgae cultivation, but CO2 is taken out of the atmosphere during the growth of the microalgae. 3.2. Transport of dry microalgae In this unit process, emissions are due to the dry microalgae distributed to the methanol plant by trucks. According to the former assumptions, emissions and energy consumption from the transport of 1000 kg dry microalgae are shown in Table 3. It can be seen that, in this process, the main emissions are CO2 and CO.
3.1. Microalgae cultivation and treatment 3.3. Methanol conversion The unit process of this LCI study involves identification of the complete environmental flows associated with microalgae production. This includes the amounts of chemicals and fuels used in
In this unit process, the air emissions are related to the temperature of the gasification. We assumed that gas composition
Table 1 Data resource. Item
Data source
Feedstock production
Fertilizer, feedstock plant, management, and harvest
Kadam (2002); Wang et al. (2007)
Methanol fuel production
Methanol production technics, energy and emissions
Hirano et al. (1998); Michele et al. (2005); Sawayama et al. (1999); Minowa and Sawayama (1999) Zhou and Xiao-qian (2004); Wei et al. (2007)
Assistant material production energy (electricity, coal, diesel oil) Coproducts
Transport Combustion
Energy consumption and emissions Data
Hirano et al. (1998); Kadam (2002)
Zhou and Xiao-qian (2004) Wei et al. (2007); Liu et al. (2007a, b)
Table 2 Inventory results of microalgae cultivation and treatment. Fertilizer production
Microalgae cultivation
Concen-tration
Mainten-ance
Drying
227.12 /
/ 25.6
/ 20.7
/ /
/ / 0.459 0.734 / / 91.75 4.59
/ / 0.371 0.593 / / 74.18 3.71
/ / / / / / / /
Electricitya Oil
kw h kg
/
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
0.049 0.421 1.033 1.071 1.607 0.007 821.387 0.089
1.1356 9.312 120.8 288 0.908 1.136 894327b 12.4
Solid waste
Solid
g
/
4661
Resource consumption
a b
0.29
The electricity used is recalculated to primary energy, which is based on 100% coal fuels. CO2 is taken out of the atmosphere during growth of the microalgae.
/
/
/
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was obtained by the gasification of microalgae biomass at the temperature of 900 1C. In this process, emissions from getting 460 kg Fuel methanol are shown in Table 4. It can be seen that CO2, CH4 and SOX are the main gas compositions.
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Table 5 Emissions and energy consumption for the transport of methanol. Transport of 460 kg methanol Resource consumption
Oil
MJ
119.7
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
6.348 169.1 8.418 2.116 / / 9761.2 1.012
Solid waste
Solid
g
/
3.4. Transport of methanol In this unit process, emissions are due to the Fuel methanol distributed to the methanol plant by trucks. According to the former assumptions, emissions and energy consumption from the transport of methanol fuel are shown in Table 5.
3.5. Methanol combustion In this unit process, emissions are due to the methanol burned in the methanol vehicle. According to the former assumptions, emissions and energy consumption of this process are shown in Table 6.
Table 6 Emissions and energy consumption for the microalgae combustion.
3.6. Sensitivity analysis
Methanol combustion
The purpose of the sensitivity analysis is to estimate the effects on the outcome of a study of the data. In the study, the influence of increasing and decreasing some production factors by 10% (Rubo et al., 2007), one at a time, was studied. The sensitivity analysis results are shown in Table 7.
Resource consumption
Oil
MJ
147.9
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
588.1 8123.8 781.7 24.65 / / 717658 31.69
Solid waste
Solid
g
/
Table 3 Emissions and energy consumption for the transport of microalgae. Transport of 1000 kg dry microalgae Resource consumption
Oil
MJ
Air emissions
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
Solid waste
Solid
g
260.2
13.8 367.6 18.3 4.6 / / 21220 2.2
/
Table 4 Emissions and energy consumption for the microalgae conversion. Methanol conversion Resource consumption
Resource consumption Air emissions
Methanol yield Solid waste
Oil Dry microalgae
kg kg
57.7 1000
VOC CO NOX SOX CH4 N2O CO2 PM10
g g g g g g g g
1.023 8 108.9 259.5 401 1.023 885426 10.84
Methanol Solid
kg g
460 4200
From Table 7, we can see that the change of use of fertilizer has little effect on the output of this microalgae-based Fuel methanol production system. As the microalgae average yield increased 10%, the amount of CO2 emission decreased 12.5788% whereas that of the other emissions increased. And the amount of CO2 emission changed the most obviously, that is mainly because CO2 is the main raw material for photosynthesis in the growth of microalgae.
4. Impact assessment 4.1. Energy efficiency analysis Adding up energy consumption during all stages, it will get total energy consumption for the entire life cycle of microalgaebased Fuel methanol. Energy requirements for the whole life cycle were converted to oil based on the aforementioned assumptions. Total energy consumption and energy consumption for each process step are presented in Table 8. It can be seen that microalgae cultivation and treatment and methanol conversion are the two most energy consumed processes. The two unit processes consume 61.1% and 32% of the total energy, respectively.
Z¼
qmethanol LCAenergy
(1)
qmethanol is the heating value of produced methanol; LCAenergy is the energy used in the whole life cycle. The energy conversion efficiency is a key indicator to evaluate the eco-performance of a renewable energy source. It can be likely
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Table 7 Sensitivity analysis results of the life cycle inventory.
VOC CO NOx SOx CH4 N2O CO2 Solid PM10
Use of fertilizer (10%)
Use of fertilizer (+10%)
Microalgae average yield (10%)
Microalgae average yield (+10%)
0.0013 0.0000 0.0076 0.0186 0.0002 0.0319 0.0114 0.0000 0.0162
0.0008 0.0000 0.0167 0.0186 0.0002 0.0319 0.0114
0.0192 0.0005 1.1851 5.0321 0.0001 5.1825 12.5788
0.0192 0.0004 1.2002 5.0321 0.0001 5.1825 12.5788
0.0000 0.0162
5.2646 2.1971
5.2646 2.1971
In the EDIP method (Hauschild and Wenzel, 1998) the interpretation of the inventory is done by three steps:
Table 8 Life cycle energy consumption of microalgae-based fuel methanol. Stage
Energy consumption (kg)
Miacroalgae cultivation and treatment Transport of dry microalgae Methanol conversion Transport of methanol Methanol combustion
110.18 6.2 57.7 2.85 3.52
Total
180.45
Distribution (%) 61.1 3.4 32 1.6 1.9
100
defined as the heating value of 460 kg methanol equivalent to the energy used to produce it during all the life cycle phases. Total processes required 180.45 kg of oil, which equals to 7398.45 MJ. The produced energy, on the other hand, was corresponded to 9235.25 MJ obtainable from 460 kg Fuel methanol. According to the formula (1), the ratio of produced energy to required energy was 1.24 which indicated the energy balance was positive. It can be seen that the major part of the required energy, about 61.1%, was occupied in the process of microalgae biomass production. In this process, microalgae cultivation was a major contributor of about 61.1% in the energy requirement, which led us to an idea that the energy balance would be improved by using microalgae which was produced in natural environment without an artificial cultivation. If microalgae can be used as a raw material, the energy requirement for the biomass production would be reduced almost only to harvest, concentration, and transportation. This meant that an excellent energy producing process by selecting an appropriate method for biomass production which would consume smaller amount of energy. The life cycle energy consumption of producing 1 MJ oil is 0.162 MJ (Yang et al., 2002), so the energy conversion efficiency of oil is 6.17. It can be seen that the energy conversion efficiency of Fuel methanol is compared unfavorably with oil. Although the energy conversion efficiency of Fuel methanol is much lower than oil, there is an emerging interest in the development of Fuel methanol because of the increasing in environmental pollutions and uncertainty concerning oil reserve.
4.2. Environment impact assessment For life cycle assessment to be able to support decisions with respect to product solutions, the data obtained in the inventory must be interpreted to show which of the environmental exchanges are significant, and how great their contributions are compared to each other, so as to help to examine and evaluate the environmental impacts.
(1) Characterization: How much do the emissions contribute to the various types of environmental impacts? In the characterization step, it is determined how much the emissions associated with the product contribute to the various types of environmental impacts (e.g. global warming, acidification etc.). For example, all emissions that contribute to global warming are expressed in CO2-equivalents. The characterization is based on properties of the emitted species, and characterization factors available in the literature are globally valid. (2) Normalization: How great are the potentials for impacts on the environment relative to the impacts from the society’s activities as a whole? In the normalization step, contributions from the product to each type of environmental impact is divided by the expected lifetime of the product and the yearly contribution to each impact from an average person in one year. (3) Weighting: Which of the environmental impacts are the most important? Some environmental impacts may be considered more important than others, and the purpose of the weighting step is to weight the results obtained in the normalization step in accordance with the users concern with the studied environmental impacts. The rating of concern with environmental impacts is of course subjective, a several individual sets of weighting factors can be established, based on different means. Politically determined environmental targets have been selected as basis for weighting by the EDIP method, and year 2000 has been chosen as the common target year. The result of the weighting is a ‘‘weighted environmental impact potential’’, with the unit milliperson equivalents, targeted, mPET2000. The weighting factors indicate how important various environmental impacts area considered in China. A weighting factor of one indicates that status in 1990 will be maintained in year 2000 according to the national plants. Weighting factors smaller than 1 indicate how much the environmental impact will grow between 1990 and 2000 whereas weighing factors larger than 1 indicate how much the environmental impact will be reduced between 1990 and 2000. The normalization references and weighting factor are specific for different countries. Due to lack of such factors for China, the classification of the inventory data to impact categories was made using the method reported by Yang and Nielsen (2001). The emissions of the system have been grouped into impacts (characterization step) based on the method of Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences
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0.0005mPET2000 0.0062mPET2000
0.0048mPET2000 0.73
0.61 0.62 0.016 2.519
1 1 PM10 Solid Soot and ashes Bulk waste
0.016 2.519
62,000 g NO3-eq/ (person?a) 18,000 g/(person?a) 2,51,000 g/(person?a) 1.35 0.290 NOx Nutrient enrichment
0.391 g NO 3 eq/g
0.1393mPET2000 0.53 650 g C2H4-eq/ (person?a) 0.6 0.03 0.007 0.168 2.312 0.115 VOC CO CH4 Photochemical ozone formation
1 0.7 0.163 0.290 SOx NOx
1 25 320 2
Acidification
0.1708 C2H 4 eq/g
0.0074mPET2000 0.73 36,000 g SO2-eq/ (person?a)
0.0288mPET2000 0.83
0.366 g SO2 eq/g
Equivalent mass Equivalent factor
201.9 0.115 0.290 2.312
Global Regional Regional Regional Local Local
CO2 CH4 NOx CO
Global warming (GW) Acidification (AC) Nutrient enrichment (NE) Photochemical ozone formation (PO) Solid waste (BW) Slag and ashes (SA)
Global warming
Environmental impacts
Emission value
Table 9 Categorization of the impacts.
Emission
4.2.1.4. Photochemical ozone formation. Non-methane volatile organic compounds (NMVOC), CO and CH4 are considered as the main contributors to photochemical ozone formation in China
Impact category
4.2.1.3. Nutrient enrichment. The main sources of nutrient enrichment are N and P emitted to water and NOX and NH3 emitted into the atmosphere (Yang and Nielsen, 2001).The contribution in this impact category is measured in terms of nitrogen equivalents released per gram of emission. Table 10 shows the results of nutrient enrichment characterizations of the different processes in the life cycle. The values are expressed in grams of equivalent NO 3 per g. The emission related to the nutrient enrichment in the LCI analyzed is NOX which has the corresponding characterization factors of 1.35. (Yang et al., 2002)
Table 10 The weighted environmental potentials of microalgae-based methanol for different environmental impact categories.
4.2.1.2. Acidification. Substances such as SOX, NOX, NH3, H3PO4, HF, H2S, HCl and organic acids all contribute to acidification of the environment. In the Chinese inventory the main contributions of SOX, NOX are addressed (Yang and Nielsen, 2001). Acidification includes the processes that increase the acidity of water and soil systems by releasing SO2 or equivalents. Table 10 shows the results of acidification characterizations of processes in the life cycle. The values are expressed in grams of equivalent SO2 per g. The emissions related to the acidification in the LCI analyzed are SO2, and NOX, which have the corresponding characterization factors of 1.0 and 0.7, respectively (Yang et al., 2002). The total influence of SO2 on the acidification effect, accounted for 44.55%, is a litter smaller than the contribution of NOX.
Normalization reference
4.2.1. Characterization 4.2.1.1. Global warming. This impact category refers to the change in earth’s climate due to the build-up of chemicals that trap heat from the sunlight. The contribution in global warming impact category indicates the potential contribution to global warming using. Table 10 shows the results of the global warming characterization of the whole life cycle. The values are expressed in grams of equivalent CO2 per gram. The total influence of NOX and CO on the global warming effect is very small in comparison to the contribution of CO2, accounted for 66.83%. This is because, in despite of having a lower characterization factor, the amount of CO2 emitted is comparatively higher than the other gases.
87,00,000 g CO2-eq/ (person?a)
Weighting factor
(Yang et al., 2002). This method leads to a single score. Six impact categories were considered: global warming, acidification, nutrient enrichment, photochemical ozone formation, bulk waste and soot and ashes. The impact categories were considered in this paper are shown in Table 9. The following section introduced the environment impact assessment of microalgae-based Fuel methanol and gasoline. This paper studied the environmental impact of the two fuels consumed by vehicles of 1 km journey, respectively. The data needed in the following section were based on the previous work.
1485
302.1 g CO2 eq/g
Weighted environment potential
J. Liu, X. Ma / Energy Policy 37 (2009) 1479–1488
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0.0131mPET2000 0.0031mPET2000 0.0017mPET2000 62,000 g NO3-eq/(person?a) 18,000 g/(person?a) 2,51,000 g/(person?a) 1.35 1 1 0.808 0.093 0.684 NOx PM10 Solid Nutrient enrichment Soot and ashes Bulk waste
1.094 g NO 3 eq/g 0.0923 0.684
0.73 0.61 0.62
0.681mPET2000 0.53 0.581 16.06 0.648 VOC CO CH4 Photochemical ozone formation
650 g C2H4-eq/(person?a) 0.6 0.03 0.007
0.152 0.808 SOx NOx Acidification
0.8354 C2H 4 eq/g
0.0145mPET2000 0.73 36,000 g SO2-eq/(person?a)
0.1148mPET2000 0.83 Global warming
Almost every year, microalgae blooms cover extensive areas of many Chinese lakes, such as Chaohu Lake, Taihu Lake and Dianchi Lake due to serious eutrophication. This results in deterioration of water, death of fish and disaster to residents around the lakes. Elimination of the microalgae blooms becomes an urgent project. Enormous microalgae biomass consisting of Chllorella,
896.9 0.648 0.808 16.06
5. Discussion
Table 11 The weighted environmental potentials of gasoline for different environmental impact categories.
4.2.4. Comparison of environment impact loadings The system scope for LCA of gasoline is from its exploitation to end-use. In this research, the data needed for the analysis were collected from various sources including institutional statistics (China statistical yearbook, 2000), and published studies (Liu et al., 2007a, b; Yang et al., 2002). The EIL of gasoline consumed by vehicles of 1 km journey was calculated using the same method as methanols. The EIL of gasoline is 0.828mPET2000 in contrast to 0.187mPET2000 of Fuel methanol. A more detailed data of this LCA is summarized in Table 11. Fig. 5 illustrates the environmental impact of Fuel methanol is much less than gasoline, especially the photochemical ozone formation value of Fuel methanol is about 20% of gasoline. From this comparison, it can be seen that Fuel methanol has advantages over gasoline (conventional fossil fuel) including reduced emissions, renewability and cleaning properties. Fuel methanol can be regarded as a new measure for solving energy and environmental problems effectively.
Equivalent mass
The EIL of the microalgae-based methanol consumed by vehicles of 1 km journey is 0.187mPET2000, in which that the value of 1 point is representative for one thousandth of the yearly environmental load of one average Chinese inhabitant. Table 11 shows that the effect of photochemical ozone formation is the highest of all the calculated categorization of the impacts. This phenomenon is mainly due to the high emissions of some gases, such as VOC, CO and CH4.
0.7174 g SO2 eq/g
(2)
CO2 CH4 NOx CO
j
X EPðjÞ 90 WFðjÞ T ERðjÞ90 j
Equivalent factor
WPðjÞ ¼
Emission value
X
Emission
EIL ¼
1 0.7
4.2.3. The environmental impact loading At the final step, the weighted environmental potentials are added up to give an environmental impact loading (EIL), which can be defined as follows:
8,700,000 g CO2-eq/(person?a)
Normalization reference
Weighting factor
4.2.2. Normalization and weighting Table 10 summarizes the results from the categorization of the impacts, for the chosen functional unit. Weighting factors are applied in order to scale the seriousness of the results, measured in indicator points. The normalization references and weighting factors used for the purpose of this study are shown in Table 10. Photochemical ozone formation is the biggest contributing factor, which accounts for 74.5% of the total environmental impact.
1 25 320 2
(Yang and Nielsen, 2001). Table 10 shows the results of photochemical ozone formation characterizations of the different processes in microalgae-based methanol life cycle. The values are expressed in grams of equivalent C2H4 per g. The emissions related to the photochemical ozone formation in the LCI analyzed are CO and CH4, which have the corresponding characterization factors of 0.03 and 0.007, respectively (Yang et al., 2002). The total influence of VOC on the photochemical ozone formation effect, accounted for 59.02%, has the most contribution to the photochemical ozone formation.
1204 g CO2 eq/g
Weighted environment potential
J. Liu, X. Ma / Energy Policy 37 (2009) 1479–1488
Impact category
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treatment, transport of dry microalgae, methanol conversion, transport of methanol, methanol combustion are checked. Several conclusions were drawn from this study.
mPET2000 The weighted environment potential
0.0007
Methanol
0.0006
1487
Gasoline
0.0005 0.0004 0.0003 0.0002 0.0001 w as te So lid
as he s nd
So ot a
or m at on
Ph ot oc
he m ic a
lo zo ne f
nr ic
hm en t
tio n ut rie
nt e
ci di fic a A N
G
lo ba l
w ar
m in g
0
Fig. 5. The weighted environmental potentials of microalgae-based methanol and gasoline.
Microcystis and other genera could be harvested from these eutrophic lakes for fuel production. Meanwhile, utilization of planktonic microalgae for Fuel methanol may decrease the eutrophication of lakes. Therefore, utilization of microalgae is beneficial to both production of renewable fuels and improvement of the ecological environment. There were 5 cities taking part in the first stage demonstration of E10 (10% ethanol in volume and 90% gasoline in volume) fuel blends since 2002, and more cities and provinces joined in the program in 2004 accordingly. It is said that methanol is widely used in commercial gasoline. More and more governments and companies are paying attentions to the industry for the importance and higher benefit. Methanol shows a prosperous market for its huge recourse, easy obtainment and low emissions. So, many researchers and officials in China think that it should take an important role in automobile industry development and gasoline fuel substitute. The promotion of methanol as a fuel substitute is a huge social project, which needs the help of related departments. The production criterion and development planning of Fuel methanol must be established as soon as possible. The government should set down some favorable policies which can attract more investments to the Fuel methanol industry. And the most urgent thing is to encourage automobile manufactories to manufacture automobiles which can use diverse kinds of fuels. The energy consumption inventories and environmental impact type inventories in this paper are not enough complete, however, they are still valuable for providing us with a round estimate of the energy efficiency and environmental impacts of microalgae-based Fuel methanol in China. The normalization references and weighting factors used in this paper should be considered as rough estimates and a little bit old, especially, the weighting factors presented in this paper are based on target emissions in 2000 which is actually not ‘‘the future’’ when this paper comes out. However, they are still useful to conduct us to research the life cycle of microalgae-based Fuel methanol in China because these normalization references and weighting factors have not changed greatly for a number of years anyway, and an updated version can be determined more easily based on the results presented here.
6. Conclusions The present study shows the results of an LCA performed upon microalgae-based Fuel methanol. Microalgae cultivation and
(1) From sensitivity analysis on life cycle inventory, we can see that the use of fertilizer has little effect on the output of this microalgae-based Fuel methanol production system. In the same condition of variable presupposition, CO2 emission has the biggest variation. But CO2 emission decreased 12.5788% while the microalgae yield increased 10% that is mainly because CO2 is the main raw material for photosynthesis in the growth of microalgae. (2) The energy conversion efficiency of Fuel methanol is 1.24. In this study, microalgae cultivation was a major contributor of about 61.1% in the energy requirement, which led us to an idea that the energy balance would be improved by using microalgae which was produced in natural environment without an artificial cultivation. (3) The environmental impact loading of microalgae-based fuel methanol is 0.187mPET2000 in contrast to 0.828mPET2000 for gasoline. The effect of photochemical ozone formation is the highest of all the calculated categorization impacts of the two fuels. (4) Utilization of microalgae an raw material of producing methanol fuel is beneficial to both production of renewable fuels and improvement of the ecological environment. This fuel is friendly to the environment, which should take an important role in automobile industry development and gasoline fuel substitute.
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