Biofuel sustainability according to emergy assessment

Transcription

1 Biofuel sustainability according to emergy assessment by Marcos Watanabe, PhD Student Enrique Ortega, PhD and professor State University of Campinas, Food Engineering College Laboratory of Ecological Engineering Campinas, Sao Paulo, Brazil +(55) / marcosw@fea.unicamp.br / ortega@fea.unicamp.br Abstract Environmental concerns have emerged as new constraints for energy policymakers on decision-making processes. The development of technologies able to exploit the available energy in the environment (solar, geothermal, wind, hydro, biomass) can be considered so important as the creation of new tools capable to assess costs and benefits of such energy-producing activities regarding both economical and environmental impacts. Emergy analysis (Odum, 1996), is an energetic approach useful to quantify sustainability of any system, mainly those ones dependent both from environmental and economic inputs like agricultural production systems. The increase of biofuel use in European Union transport sector since Triple 20 shows that agriculture will tend to renewable energy production in the next years. Although energy policymakers expects an environmental positive externality derived from biofuel consumption specially avoided carbon emissions compared to gasoline the economical and environmental advantages will depend on many variables as spatial scale adopted, fossil inputs used, land-use change impacts, and others that could transform biofuel production on a source of negative externalities. Moreover, sustainability of biofuel can depend on the method used to assess it, and emergy analysis sounds as a good tool to deal with biofuel production systems, since it doesn t simplify biofuel assessment only to carbon dioxide emissions, assessing economic and environmental contributions to the production system. This publication will review the performance indices of biofuel alternatives in some regions of the world and compare them with other systems based on renewable alternatives such as wind, geothermal, ocean thermal energy conversion (OTEC) and hydro aiming to generate electricity. 1 Emergy Analysis and biofuel production All products or services produced by systems have emergy. Emergy means energy memory or the available required energy used up directly and indirectly to make a service or product (Odum, 1996). Under an energeticbased approach, the Emergy concept converts all types of energy, mass and money flows of a certain production system into a same energy basis. Emergy analysis differs to conventional methodologies in which the main indices generated are CO 2 released and output/input energy ratio. Instead of tons of oil equivalent (toe), this methodology uses solar energy equivalent joules (sej) as standard. Moreover, instead of dealing only with commercial inputs in a small timescale (limited to the production process), emergy analysis opens its scope of analysis and includes the environmental inputs and deals with them regarding their large timescale (associated to the biosphere processes such as generation of minerals, fossil fuels, top soil, water storages, etc.).

2 As figure 1 shows, the emergy approach distinguishes inputs in three main categories: Environmental Renewable inputs (R) such as sunlight, wind and rain; Environmental Non-Renewable Inputs (N) such as soil, groundwater, fossil fuels; and Material and Services from the economy (F) such as human labor, electricity, buildings and others. The output can be a product or service which contains the total Emergy (Y). All inputs are converted to a same basis, the solar energy equivalent joule. Figure 1. Production system according to emergy approach Natural Nonrenewable inputs N F Economic inputs Natural Renewable inputs R Ecosystem processes Economic Processes Y Productive system In case of biofuel production, the accounting procedure includes the environmental work related to the chemical potential of rain, nutrient content of soil organic matter, sunlight contribution, earth material cycle and other inputs required to produce biomass. The economic inputs such as human labor, fertilizer, diesel, buildings, etc, are also accounted in terms of solar equivalent energy value. The next step is to do calculations with the different categories of inputs in order to generate emergy indices necessary to assess the system s environmental and economic performance. Among the main performance indicators, this article will highlight four of them: Transformity (Tr) is equal to the emergy content (Y in solar equivalent joules) divided by total energy content (given in joules or calories). The higher the value, the lower the system s efficiency. Renewability (%R) is equal to the Renewable Input (R) divided by total emergy (Y). This indice quantifies the percentage of renewable energy (sun, wind, rain, etc.) used up in the production process. The higher the value, the greater the sustainability of the production system. Emergy Yield Ratio (EYR) is equal to the total emergy (Y) divided by total economic inputs (F) such as human labor, machinery, fertilizers and other. It reflects the ability of a certain system to deliver energy to the economy by amplifying its investment. The higher the value, the lower the system s reliance on economic investment and the higher the enterprise competitiveness. Emergy Loading Ratio (ELR) is equal to Non-renewable resources from economy and from environment (F+N) divided by Renewable Input (R). It is a measure of

3 environmental impact of a production system. The lower the value, the lower the environmental stress caused by the system on the surrounding areas. Considering that biofuel production systems are managed under different set of practices, techniques, and technologies, each of them will show different performance indices. Aiming to compare different performances of biofuel production systems regarding both environmental and economic constraints, this paper will highlight some case studies of biofuel production in different regions of the world. Moreover, this paper will show other performance indices from other renewable options such as electricity power plants based on fossil fuel, wind, geothermal, ocean thermal energy conversion (OTEC) and hydro power. 2 Biofuel production in the world: case studies There are many studies that have been published regarding biofuel production. Basically, this paper will review studies of corn (or maize) ethanol production in Europe and in the U.S. (Ulgiati, 2001; Bastianoni and Marchetini, 1996), sugarcane ethanol production in Brazil (Pereira, 2008) and soybean biodiesel in Brazil (Cavalett, 2008). Moreover, this section compares biofuel performances with fossil fuel systems such as those producing gasoline and diesel (Odum, 1996; Bastianoni et al. 2009). The following indices don t represent a permanent reality but can change over time as much as the land-management practices and environmental conditions alter the system s input and output data. Table 1 shows the Transformity (Tr) indices for different biofuel options. Sugarcane ethanol produced in Brazil (Pereira, 2008) has presented the same magnitude of Transformity as for fossil fuels in these reviewed cases, which means the same level of efficiency in terms of emergy invested to the amount of emergy delivered. However, other biofuel options have presented higher Tr indices, which means lower efficient processes. Table 1. Transformity performance indice among different fuel options. Usually, fossil fuels have better Tr indices because such natural stocks were produced in a timescale of millions years (natural processes such as deposition of layers of organic matter and other non-organic materials, inducing high pressure and high temperatures). Whether oil ventures have abundant and wellpositioned storages, relatively lower effort is necessary to extract and to refine

4 them if compared with other sources of energy, such some biofuel options. Of course, as human consumption depletes oil reserves, such proportion of emergy invested per emergy delivered as fuel increases (Tr increases) and may reduce the efficiency of the process. When assessing biofuel production, crop production cycle has a timescale of one year and demand relatively more emergy investment per emergy delivered. Moreover, factors like high diesel use in machines, increasing fertilizer inputs and loss of topsoil in agricultural stage can negatively affect the efficiency of other biofuel production alternatives. Assessing the Emergy Yield Ratio (EYR) indices, it is possible to quantify the system s reliance on economic investment. In theory, the minimum value for EYR occurs when the quantity of emergy delivered by the system is equal to the emergy within the economic investment; in this case, EYR would be 1. For such a system, EYR=1 would indicate zero ability of capturing free local resources in the environment and also extreme dependence on economic investment to deliver energy. Table 2. EYR performance indice among different fuel options. As table 2 shows, the highest EYR values are observed for fossil fuel production systems, indicating higher economic competitiveness compared to biofuel production systems. Such difference is explained again by the timescale necessary for fossil fuel formation and accumulation. For fossil fuels, previous emergy investment has been made by natural processes during millions of years. Although oil exploration rely on economic investments on technology and infrastructure, when the oil stock is explored there is lower investment of emergy per emergy delivered as fuel. In the case of biofuel production, besides the technology and infrastructure expenditures, raw material (biomass) is not ready and rely on more economic investment to grow. Biomass has a short production timescale (usually one year) and although is a renewable environmental product, high productivity (mass per hectare) depends on previous inputs made by high economic inputs such as fertilizer, diesel, human labor and services. As a consequence, current biofuel production can be less competitive (in economical and environmental terms) than fossil fuel production. However, changes in the model of biofuel production and scarcity of fossil fuel can invert this situation in the future since EYR would increase for biofuel and decrease for diesel and gasoline. A basic indice to assess the system s sustainability using emergy theory is the Renewability (%R). Emergy analysis shows that certain energy production

5 systems considered as renewable don t have a complete renewable character and rely upon some non-renewable inputs, even in the case of biofuel production. As table 3 shows, fossil fuels such diesel and gasoline are completely non-renewable, which means 0% renewability since their rates of extraction are thousands or millions of times superior to its rate of production by natural processes. However, less obvious results regard biofuel production for Brazilian sugarcane ethanol, U.S. sugarcane ethanol and European corn ethanol which values correspond to 35%, 14.2% and 5.4%, respectively. For example, European Corn ethanol performance of 5.4% Renewability means that 94.6% of all inputs used up in corn ethanol production came from nonrenewable inputs. Table 3. Renewability (%R) performance indice among different fuel options. Such biofuel performance (see table 3 above) is mainly affected by the degree of soil erosion, fertilizer application, mechanization, diesel consumption, and other factors. Therefore, although biomass rely on environmental factors such as rain and sunlight (environmental renewable inputs), there are cases in which the non-renewable inputs heavily exceed the renewable inputs. Soil erosion is specially when assessing biofuel renewability (%R) because emergy assessments consider soil as a non-renewable input. Although soil is a good provided by the environment, the rate of soil use by modern agricultural can exceed a hundred times the rate of soil formation through natural processes. The fourth performance indice assessed is the Environmental Loading Ratio (ELR), which is calculated to measure the environmental stress caused by energy production systems. The best value would be zero, meaning zero ecosystem disturbances. According to Brown & Ulgiati (2004), values ranging from zero to 2 would indicate moderate level of environmental impact, but values superior to 10 would indicate high environmental stress. Table 4. Emergy loading ratio (ELR) performance indice among different fuel options.

6 As presented in table 4, soybean biodiesel and sugarcane ethanol production in Brazil have better performance than ethanol produced in other systems presented in this paper. As table 4 shows, Brazilian agro-ecosystems and mills cause moderate stress on the environment, three times inferior than those systems studied in other parts of the world. However, such results don t include the land-use-change effects when cropland systems eliminate ecosystems. ELR only measures the pressure on the environment derived from the temporary pattern of agricultural management practices, such as soil depletion, fertilizer use, machinery and diesel use, intensity of human labor, etc. Moreover, Pereira (2008) and Cavalett (2008) states that agricultural stage causes more impacts on environment than the processing and transportation stages. Because of that, such biofuel production systems focus on land practices in order to improve their performance indices. 3 Other renewable energy system s performance indices This section aims to expand the scope of the performance indices assessed and includes other energy production systems. Aiming an evaluation of other renewable electricity production systems, Brown and Ulgiati (2004) have studied and reviewed (Odum, 2000) some power plants performance indices, presented in table 5. The case studies include an oil-powered thermal plant, a wind powered field, a geothermal plant, an ocean thermal energy conversion (OTEC) and a hydro power plant, with the following characteristics: (i) The oil-powered thermal plant is a conventional power plant, with four 320 MWe boiler-turbine-generators cooled by seawater from the nearby of Mediterranean Sea, in Italy. This system was included just to compare it with other power plants based on renewable energy; (ii) The wind turbine consists of a 2.5 MW wind powered field, composed with ten M30-A single blade-250 kw wind turbines, located in Italy. This power plant has a distance between turbines of 150 meters, all of them located on the top of a 30 meters support tower. The operating wind speeds were between 4 and 25 m/s; for wind speeds out this range, the turbine automatically stops; (iii) The geothermal field is sited in central Italy and has a 20 MW power module to efficiently and cost-effectively installed. Geothermal fluids carry and release significant amounts of hydrogen sulfide, carbon dioxide, arsenic, mercury, nitrogen and boron that involves plant corrosion problems as well as pollution problems in the area. Therefore, many devices and equipments have been designed for the uptake and abatement of the most dangerous chemicals; (iv) The Ocean thermal energy conversion (OTEC) is and energy technology that is able to convert indirect solar radiation to electric power, using the ocean s natural thermal gradient to drive a power-producing cycle. The temperature of the warms surface seawater must differ about 20 ºC (or 36 ºF) from that of the cold deep water that is about 1000m below the surface. Electricity generated by plants fixed in one place can be delivered directly to a utility grid, and a submersed cable is required to transmit electricity from an

7 anchored floating platform to land. Such evaluation was based on a feasibility study and not on an actually existing plant (Odum, 2000); (v) The hydroelectric plant in southern Italy has a reservoir-dam of 1,000 cubic meters and is located at about 600m above sea level. Water flows out of the dam reaching the turbines located downstream, at about 50 m above the sea level. There are two 50 MW turbines with vertical axis converting the water energy into electricity, generating a total actual electrical power of about 85 MW. No labor is required for plant operation. Table 5 shows the performance indices for the case studies studied by Brown and Ulgiati (2004). Transformity (Tr) indices are process specific and range from the low value of about 1.1 E+05 sej/j for hydro and wind up to higher values around 3.5 E+05 sej/j for geothermal and oil-powered electricity, which means that, in terms of emergy invested per energy delivered, hydro and wind might be more efficient ventures than other ones showed in this table. Table 5. Emergy performance indices for different electricity power plants. For OTEC, the plant has very small inputs of solar energy via temperature gradient and a noteworthy input in the form of financial investment, labor and services to which a high emergy is associated. This explains the low EYR, almost equal to 1, which means that there almost all emergy delivered as electricity rely on emergy of economical investment and not on those ones from environmental inputs. Similarly, the oil plant has a low EYR, showing that even ventures based on fossil fuel depend on huge economic investment to produce electricity. For wind, geothermal and hydro, the EYR around 5 is satisfactory since these ventures are more reliant on environmental inputs and more competitive among the alternatives showed in table 5. OTEC has a high reliance on nonrenewable inputs, which reduces significantly the Renewability to 0.55%, even lower than oil plant %R, around 4 %. The best performance was observed at wind power plants, with almost 85% of renewable inputs, showing that such system has a high environmental sustainability. Geothermal and hydro had intermediate performance indices, around 60 %.

8 Finally, high ELRs characterize oil based plant and OTEC electricity, while very low ELRs are shown by processes very reliant on renewable inputs. OTEC shows a huge environmental stress. However, such evaluation was based on a feasibility study and not on an actually existing plant. Wind, geothermal and hydro show very low ELR, and probably causes low environmental stress compared with other options assessed. However, geothermal electricity load on environment due to the release of chemicals extracted with underground fluid increases the ELR of the process. 4 Conclusions Although biofuel is used as fuel in transport sector and not to generate electricity, we ll briefly compare the biofuel case studies performance indices with those ones observed in other renewable systems generating electricity and assessed by Brown and Ulgiati (2004). In case of Tr performance indice, its magnitude was around 1.00 E+05 sej/j, excluding the case study of Brazilian sugarcane ethanol, which had a better process efficiency, and the transformity was of 5.00 E+04. For EYR, the biofuel performance was around 1.5, very close to OTEC and oil power plants, but lower than geothermal, wind and hydro power performances. Therefore, among the case studies, biofuel production was more reliant on economic investment and probably less competitive than geothermal, wind and hydro in the long run. Moreover, if biofuel was converted into electricity through its combustion in turbines, EYR performance could be even lower due to the additional economic investment (infrastructure such as equipments, buildings, etc.) required transform one kind of energy in another. This would reduce its competitiveness even more as a source of energy. In case of renewability %R, the biofuel with the best performance was observed in Brazilian sugarcane ethanol (Pereira, 2008); although ethanol use is directed to the transport sector and not to generate electricity, its %R was lower than for wind, geothermal and hydro. Therefore, these last systems have higher performance in terms of sustainability than biofuel ones assessed in this paper. Assessing the stress caused in the environment, Brazilian ethanol and soybean biodiesel s ELRs were lower than those ones observed in the oil and OTEC power plants but higher than ELRs for geothermal, wind and hydro case studies. Among biofuel case studies assessed in this paper, Brazilian ethanol had a remarkable performance. However, results can vary depending on the region and, obviously on the production system because its inputs and outputs will change and, therefore, its performance indices. Consequently, more local research using emergy methodology would be necessary to enhance the quality of the discussion. Although fossil fuel production systems assessed require less economic investment to deliver one unity of emergy (high EYR), biofuel systems present higher sustainability performances (higher %R) and could contribute to sustainable development. Of course, changes in agricultural practices to reduce soil loss, diesel input and fertilizer use can improve biofuel performance indices.

9 References: Bastianoni, S., Campbell, Ridolfi, R., Pulselli, F.M. (2009): The solar transformity of petroleum fuels. Ecological Modelling v.220 p Bastianoni, S., Marchetinni, N. (1996): Ethanol production from biomass: Analysis of process efficiency and sustainability. Biomass and Bioenergy, v. 11, 5 p Brown, M.T, Ulgiati, S. (2002). Emergy evaluation and environmental loading of electricity production systems. J. Cleaner Production 10, Brown, M.T., Ulgiati, S. (2004). Emergy Analysis and Environmental Accounting. Encyclopedia of Energy, Vol. 2. Cavalett, O. (2008): Análise de ciclo de vida da soja (title in English: Soybean life cycle assessment). State University of Campinas, Brazil. Data available in: < Odum, H.T. (1996): Environmental Accounting. Emergy and Environmental Decision Making. J.Wiley & Sons. NY. Odum, H.T. (2000). Emergy evaluation of an OTEC Electrical Power system. Energy 25, Pereira, C.F. (2008): Avaliação de sustentabilidade ampliada de produtos agroindustriais. Estudo de caso: laranja e etanol. (title in English: Sustainability evaluation of agro industrial products. Case studies: orange juice and ethanol). State University of Campinas, Brazil. Data available in: < Ulgiati, S.(2001): A comprehensive energy and economic assessment of biofuels: when "green" is not enough. Critical Reviews in Plant Sciences, v. 20, p