THE BIOMASS REAL POTENTIAL TO REDUCE GREENHOUSE GAS EMISSIONS: A LIFE-CYCLE ANALYSIS. Abstract

Transcription

1 THE BIOMASS REAL POTENTIAL TO REDUCE GREENHOUSE GAS EMISSIONS: A LIFE-CYCLE ANALYSIS by Bruna de Barros Correia, , brunabc@fem.unicamp.br State University of Campinas (Unicamp) Tiago de Barros Correia, , tiago.correia@mme.gov.br Brazilian Ministry of Mines and Energy Arnaldo César da Silva Walter, , awalter@fem.unicamp.br State University of Campinas (Unicamp) Abstract As the debate surrounding the sustainability of social development based on a heavily oildepended economic growth unfolds and increases, alternative energy sources and energy efficiency become the protagonists in the global effort to limit greenhouse gas emissions. Moreover, biomass becomes more and more important as a supply-side option to accomplish a low carbon stabilization strategy, mainly because biomass is a general-purpose energy carrier which can be converted into liquid fuel, electricity, heat and hydrogen and because biomass presents a high potential to remove carbon dioxide from the atmosphere, reducing greenhouse gas (GHG) concentration. This paper gives an outline of the controversy surrounding the use of sugar-cane and corn as bio-energy sources and its contribution to mitigate global warming and offers a synthesis of a life-cycle analysis methodology to measure the biomass potential to reduce GHG emissions. 1. Introduction The imminence of climate change has exacerbated the need to reduce GHG emissions and has raised questions related to the energy sector and energy sources. Intensive fossil fuel burning in the transport sector and in power generation is a major factor in the global warming. Increase bioenergy share in the energy supply portfolio can be the fasted trail to achieve low carbon stabilization because ethanol can be easily used in spark ignition engines, without many technical and logistics changes, and its production from biomass, especially sugar-cane and cellulose, can co-generate expressive amounts of electricity. Furthermore, bio-energy sources are important because they can provide environmental benefits when compared to conventional energy (converting atmospheric CO2 to organic C in crop biomass and soil), and can contribute to energy supply security and, as consequence, help sustainable economic growth and social development. Analyses from the International Energy Agency (IEA, 2008) indicate that it is possible to reach a sustainable energy sector. For that, huge investments are necessary on research and technologies development related to energy efficiency, carbon capture and storage, and renewable and nuclear energy. According to data from IEA these technologies are able to contribute with energy supply security and also help reducing GHG emissions. Disclaimer: This paper presents the authors own personal opinions only and do not necessarily reflect the positions or opinions of their employers. All comments are based upon their current knowledge and their own personal experiences.

2 On the transportation sector, IEA (2008) points out that it represents the largest investment area and that the best options to reduce carbon emissions are conventional vehicles efficiency, biofuels, hybrid vehicles, electric batteries and fuels cells. The large scale use of bio-energy is, however, controversial. The literature reports widely different conclusions about the possible contribution of biomass in the future global energy supply. The first reason for the controversy is the uncertainty on the future land availability and yield levels in crop production and over the detrimental effects on world food production, biodiversity and water availability. The second reason is the difficulty in establishing a general methodology, based on a given technology and on a standard productivity level, to measure and to certificate the total (or relevant) GHG emissions during the entire bio-energy s life-cycle, especially concerning the indirect impact from land use change. In fact the bio-energy net energy value is highly sensitive to assumptions about both system boundaries and key parameter values. In addition, Farrell et. al. (2006) alert that many net energy calculations ignore vast differences between different types of fossil energy. Also energy ratios are extremely sensitive to specification and assumptions and can produce incomprehensible values in some important cases. Table 1: Different results for corn ethanol energetic balance Study Yield Energy input Co-product credit Energy output Energy ratio (L ha -1 ) (MJ L -1 ) (MJ L -1 ) (MJ L -1 ) (MJ MJ biofuel -1 ) Shapouri et. al. (2002) 3, Pimentel and Patzek (2005) 2, Farrell et. Al. (2006) 3, Patzek (2004) 2, The present paper aims to analyze the bio-energy real potential to reduce GHG emissions, presenting a synthesis of a life-cycle analysis methodology, including agricultural process, industrial production and transportation. 2. Bibliographic review Quantifying whether the use of a specific feedstock to produce bio-energy can reduce GHG emissions is, to say a minimum, a complex task. Biomasses capture CO2 by converting atmospheric CO2 to organic C in crop biomass and soil, but they also emit nitrous oxide and vary in their effects on soil oxidation of methane. Growing the crops requires energy (e.g., to operate farm machinery, produce inputs such as fertilizer) and so does converting the harvested product to usable fuels (feedstock conversion efficiency). Quantify all these factors and determine the final net effect means making choices, as well as choosing approaches and assumptions. The controversy surrounding the use of bio-energy as a supply-side option to accomplish low carbon stabilization involves analytical choices related to three key factors: i. The real bio-energy net GHG emissions. ii. The consequences of large scale bio-energy production on land use and food production. iii. The consequences for other environmental issues such as water scarcity and biodiversity. According to Macedo et. al. (2008), the extent to which bio-energy can reduce GHG emissions depends on the way in which it can be produced. All processing technologies involve (directly

3 and/or indirectly) the use of fossil fuels; the benefit of biofuels displacing their fossil fuel equivalents depend on the relative magnitude of fossil fuels input to fossil fuel savings resulting from the biofuel use. Additionally, Macedo et. al. (2008) emphasizes that significant difference in the GHG emissions are also expected in biomass production. Essentially because of the multiplicity in defensives and chemical applications and the incorporation of N2O emissions from agriculture and from industrial residues that are returned to soil and CO2 emissions from mineral fertilizers, but also because of differences in trash disposal alternatives (from simple burning to power generation). In short, the bio-energy net contribution to GHG emissions reduction can be measured only by an adequate life-cycle analysis. Bio-energy cropping varies with respect to the length of the plant s life-cycle, yields, feedstock conversion efficiencies, nutrient demand, soil carbon inputs, nitrogen losses, and other characteristics, all impacting management operations. These factors affect the magnitude of the net GHG release and N loss vectors. N2O emissions and NO3 leaching vary with amount of N fertilizer applied and the integration of rainfall, soil temperature and texture, and crop rotation. Soil organic carbon sequestration is affected by crop management decisions, which impact the quantity and quality of crop residue added to the soil and rate of decomposition. Crops have different requirements for farm machinery inputs from crop planting, soil tillage, fertilizer and pesticide application, and harvest (Adler, et. al., 2007). Standard life-cycle studies compare emissions from the separate steps of growing or mining the feedstocks (such as corn or crude oil), refining them into fuel, and burning the fuel in the vehicle. In these stages alone, bio-energy emissions may exceed or match those from fossil fuels, and therefore produce no GHG benefits. But because growing bio-energy feedstocks removes CO2 from the atmosphere, the net balance can reduce GHG emissions relative to fossil fuels. However, this is only part of the problem. To produce bio-energy, farmers may directly plow up more forest or grassland or may increase the production efficiency. In a deregulated economy, this is only a matter of price, cost and opportunity. However, the loss of maturing forests and grasslands also forgoes ongoing carbon sequestration as plants grow each year, and this foregone sequestration is equivalent to additional emissions (Searchinger et. al., 2008) According to Kim et. al. (2009), GHG released from land use change (carbon debt) has been identified as a potentially significant contributor to the environmental profile of biofuels. The time required for biofuels to overcome this carbon debt due to land use change and begin providing cumulative greenhouse gas benefits is referred to as the payback period and has been estimated to be years depending on the specific ecosystem involved in the land use change event. Two mechanisms for land use change exist: direct land use change, in which the land use change occurs as part of a specific supply chain for a specific biofuel production facility, and indirect land use change, in which market forces act to produce land use change in land that is not part of a specific biofuel supply chain, including, for example, hypothetical land use change on another continent. Because existing land uses already provide carbon benefits in storage and sequestration (or, in the case of cropland, carbohydrates, proteins and fats), dedicating land to bio-energy can potentially reduce GHG only if doing so increases the carbon benefit of land. Proper accountings must

4 reflect the net impact on the carbon benefit of land, not merely count the gross benefit of using land for bio-energy. Besides global warming aspects, Campbel et. al. (2008) emphasizes that the agricultural land dedicated to bio-energy crops growth will produce multiple consequences for ecosystems, and food security. These consequences are closely tied to the land that is used for bio-energy crops. Using food agriculture lands for bio-energy agriculture could increase the cost of the food commodities that are critical to the diets of food-insecure people worldwide. Clearing forest land for new bio-energy crops could result in CO2 emissions from terrestrial carbon pools that are much greater than any greenhouse gas benefits provided by biofuels. Therefore, it is inappropriate to use native forest land for bio-energy production. On the other hand, raising bio-energy crops on agriculturally degraded and abandoned lands or even on pasture, grassland and temporary crop land could be a sustainable alternative to bio-energy, providing acceptable environmental impacts and climate change mitigation. The question is how to delineate the area available for bio-energy crops and how to certificate its environmental sustainability? Global energy and environmental concerns are potent elements behind international trade of biomass and feedstock. Government s certification programs are used to link certifications with fiscal incentives, along renewable energy use obligations. Certified biofuels may be more acceptable to consumers than non-certified biofuels (UNCTAD, 2008) and certification is expected to turn into a crucial factor for both domestically produced and imported biofuels. However, because of the complexity in the concept of sustainability, there is no global standard on the sustainability criteria used by certifications programs. As a consequence, there are multiple types of criteria, which can foster the creation of trade barriers without providing coherent environmental benefits. Therefore, certificating environmental, social and economic sustainability of biofuels is a complex task and requires a delicate and fair work, which has to cover individual production aspects as well as rules from World Trade Organization (WTO) and Climate Regime. Bio-energy certainly plays a critical role in scenarios that aim for low GHG concentrations. On the other hand, large-scale use of bio-energy is still controversial. While some authors find that it is an essential element for GHG reduction, others emphasize the possible trade-offs with production of food and protection of biodiversity. In the bottom-line, large-scale bio-energy will demand some expansion of land use for bio-energy cropping and this will partly offset the final net bio-energy contribution to reduce GHG concentration. But if we allocate bio-energy only on abandoned agricultural land and natural grasslands, the impacts on remaining land use should be small. (van Vuuren, et. al.,2010b) 3. Life-cycle analysis methodology The evaluation of avoided emissions depends on the equivalences between the renewable fuel and the fossil fuels replaced and, mostly, on their respective GHG emissions during their entire lifecycle, including energy consumption on production, harvesting and transportation. Therefore, the total renewable energy produced in biofuel life-cycle was considered as the sum of the thermal energy contribution of ethanol and co-products (food and electricity surpluses, for example).

5 On this paper we adopt a seed-to-wheel analysis, which comprehends the biomass production and processing, coming to biofuel at the mill gate and, finally to it s end use as a fossil fuels substitute. This approach involves three levels of energy flows: i. The direct consumption of external fuels and electricity (direct energy inputs). ii. The energy required for the production of chemicals and materials used in the agricultural and industrial processes (seeds, fertilizers, herbicides, fuel, heat, lubricants, etc.). iii. The energy necessary for the manufacture, construction and maintenance of equipment and buildings. Figure 1 Life-cycle Diagram Photosynthesis GHG Emissions Biomass harvesting and transportation Biomass processing and biofuel production and transportation Final use - fuel burning - co-products Fuel and electricity Machinary Buildings and equipments Fertilizers, defensives, and materials Heat, fuel and electricity Machinary Buildings and equipments Others industrial inputs Primary Energy Source Oil/Coal/Natural Gas/Others Estimating the energy input for determining the Net Energy Value (NEV) of bio-energy involves adding up all the nonrenewable energy required to grow biomass and to process it into ethanol. Most studies include only primary energy inputs in their NEV estimates. Secondary inputs, such as energy embodied in building ethanol facilities, farm vehicles, and transportation equipment are difficult to quantify. Moreover, energy embodied in fixed inputs would have to be distributed over total production during the lifetime of the plant, including crops not used for ethanol production and ethanol co-products. Therefore, secondary inputs related to the ethanol plant would account for very little energy on a final volume production basis (Shapouri et. al., 2002). However, this little difference may be decisive on the final energy balance, especially on corn ethanol production. This study aims to describe a general life-cycle analysis methodology to measure the biomass potential to reduce GHG emissions. Therefore, the data referenced here is merely illustrative, but

6 all basic data used, as well as the most important coefficients (energy conversion, efficiencies, energy to produce materials, energy for chemical inputs) are detailed so that the results can be compared to other biomass-based energy systems. 3.1 Estimating energy requirement for transportation The amount of GHG emissions from fossil fuels used in feedstock transport to the biorefinery, conversion to biofuel, and subsequent distribution can be estimated based on: i. The specific consumption values to each type of truck, tractor and implement used in bioenergy life-cycle; ii. The mean harvested area distance; iii. The average distance from the biorefinary to the harvested land and to the distribution centers and fuel stations; and iv. The average distance from supplier centers (machinery, seeds, chemicals ) to the biorefinary and to the crop land. 3.2 Estimating embodied energy in farm inputs Bio-energy cropping systems vary with respect to length of the plant life cycle, yields, feedstock conversion efficiencies, nutrient demand, soil carbon inputs, nitrogen losses, and other characteristics such as soil carbon sequestration and nitrogen fixation. These factors affect the magnitude of the components contributing to net GHG balance. Moreover, crops have different requirements for farm machinery inputs from crop planting, soil tillage, fertilizer and pesticide application, and harvest (Adler et. al., 2007). The estimation of energy requirements and associated emissions in fertilizer, herbicides and pesticides production were based on general information of the chemical industry. The evaluation of the GHG emissions included the emissions due to fossil fuel utilization and those not related to fossil fuels. The most important emissions that are not derived from use of fossil fuels are: i. Methane and N2O emissions from the burning of crop residues; ii. N2O and CO2 emissions from soil by fertilizers and lime application and crop residues returned to soil. Table 2 Embodied energy and GHG emissions in defensives Energy demand a Emission factor (MJ kg -1 ) (kgco2 eq (kg -1 )) Brazil a USA a Nitrogen (N) Phosphorus (P2O5) Potash (K2O) Lime Herbicide Insecticide a Macedo et. al. (2008), b Farrell et. al. (2006)

7 3.3 Estimating embodied energy in ethanol conversion Energies embodied in the manufacture of equipment (field and industry) and construction of buildings/structures are expected to be small compared to the energy flows in the systems dedicated to energy generation. They can, therefore, be estimated in a simplified way based on the weight and type of material used in the equipment (steel, iron, aluminum) and in some cases, such as tractors and trucks, with some specific considerations (Macedo et. al., 2004). For buildings and others facilities the estimate is made based on the covered area and type of construction (industrial building, warehouse, office). It must be pointed out that for each piece of building and equipment there are two components in the energy cost: i. The energy required for the production of the raw material (steel, iron) and to manufacture the equipment. ii. The energy required to maintain the building and equipments in operational conditions during their useful life-time. To estimate the emissions, it would be adequate to separate electricity from others types of energy since, in many countries, renewable sources, nuclear and hydro power plants already have an expressive share in the electricity supply. At this point, it is important to notice that many sectors involved (steel, iron) generate most of the electric energy they need, partly in a renewable way. For the same reason, the estimation of energy requirements and associated emissions in chemicals production must be based on general information from the local chemical industry. (Macedo et. al., 2008). Table 3 Embodied fossil energy in buildings, chemicals and lubricants Brazilian average Fossil energy Fossil energy BULDINGS (GJ m -2 ) CHEMICALS (kj (L ethanol) -1 ) Industrial Buldings 1.8 NaOH 98.6 Offices 2.4 Lime 64.9 Labs, restore shops 2.4 Sulfiric acid 48.0 Yards 1.2 Cyclohexane 5.2 Antifoam 2.6 Lubricants 1.6 Others 2.0 Macedo et. al. (2008) 3.4 Estimating energy credits for co-products The literature presents basically four ways to estimate energy credits for co-products (Shapouri et. al., 2002): i. Estimate co-products energy credits by its caloric energy content. ii. Allocate energy used during ethanol conversion proportionally among multiple products based on each product s mass. iii. Assign energy used proportionally among multiple products based on each product s value or price.

8 iv. Assume that energy credits are to be equal to the energy required to produce a substitute for the ethanol co-product The problem with the first method is that calories are a measurement of food nutritional value and are not a good proxy for energy in a fuel context. The second and third methods have a similar disadvantage, given that the weight of a product or its price is not always a good measurement of its energy value. The fourth method has the appeal of measuring co-product credit by energy units. However, properly estimating energy value by the embodied energy in possible substitutes would demand a life-cycle analysis as much complex as the bio-energy analysis itself and, if the substitute has co-products as well, such approach could be trapped in endless processes of circular references. According to Farrell et. al. (2006) additional complications arise because many studies fail to specify whether the energy credit associated with co-products should be subtracted from the input energy or added to the output energy. While neither of these choices is a priori conceptually superior, the value of the net energy ratio is sensitive to this choice, particularly when co-product credits are large in comparison to input and output energies. Therefore we understand that there is no consensual method to estimate co-products energy credits and we gave zero energy credit to any non-energetic co-product that cannot be used in the feedstock production or in the ethanol conversion, and the remaining leftovers should be returned to the field to replenish soil humus and micro-elements. 3.5 CO2 debits from former land use Growing bio-energy feedstock is a land intensive activity, and, because diverting land from its existing uses can releases to the atmosphere much of the carbon previously stored in plants (forests, grasslands or crops) and soils through decomposition or fire. Therefore, a proper GHG net balance should account the impact of direct land use change, in which the land use change occurs as part of a specific supply chain for a specific bio-energy production facility, and indirect land use change, in which market forces act to produce land use change in land that is not part of a specific bio-energy supply chain. Additionally, because GHG emissions from land use change are likely to occur indirectly, the adoption of environmental regulation that focus only on direct land use change would have little effect. Barring bio-energy feedstock produced directly on forest or grassland would increase the demand for fertile lands and encourage others farmers to look-for new croplands by plowing up new lands removing native plants. GHG emissions associated with land use change, however, are very difficult to quantify, and the estimated amount will depend strongly on assumptions regarding economical, social and environmental aspects, among other issues. Higher bio-energy production will result on more demand for land and fertilizers, increasing their prices, and on a bigger energy supply, with the associated price reduction (including in bio-energy prices). These combined effects will produce changes in people income, consumption and investments resulting on a combined effect very difficult to anticipate. There is no effective method to estimate with accuracy GHG debit from indirect land use change and such effect should not be considered in comparative analysis between bio-energy feedstock

9 and energy sources. On the other hand, we strongly recommend that bio-energy production certification fully evaluates GHG debit from direct land use change and that governments compute GHG releases from land use to accomplish international emissions goals. 3.6 Estimating energy in human labor Some life-cycle studies, such as Shapouri et. al., (2002), Patzek (2004) and Pimentel and Patzek (2005) include energy input from human labor in the total energy requirement during the crop plowing. In these studies the human labor share varies from 4% to 6% of the total energy consumption during agriculture activity. However, the chosen assumptions are vaguely described, which make difficult to use similar methodology in studies worldwide. For this study, the energy in labor is not considered as an energy cost. 3.7 Estimating GHG emissions In bio-energy production significant difference in the emissions pattern are expected, essentially due to the large diversity on plowing system, on crop and industrial yield and on primary energy inputs. Table 4 GHG emissions factors (kgco2e MJ -1 ) USA a Brazil b Gasoline Diesel Natural Gas LPG Emissions from irrigation energy Electricity Buldings Equipements Nitrogen (N) Phosphorus (P2O5) Potash (K2O) Lime Herbicide Insecticide a Farrell et. al. (2006), b Macedo et. al. (2008) 4. Ethanol production chain Ethanol is generally produced from the fermentation of sugar (mainly glucose) and it can be produced from any biomass that contains substantial amounts of sugar or materials that can be converted into sugar such as starch or cellulose. The key steps in the feedstock-to-ethanol conversion process are shown in Figure 2.

10 Figure 2 - Ethanol production chain. Sugary biomass Starchy biomass Cellulose Crushing Milling Hydrolysis Milling Hydrolysis Fermentation Distillation Hydrous Ethanol Dehydration Anhydrous Ethanol 4.1. Ethanol from sugar-cane The complete sugar-cane crop cycle is variable, depending on local climate, varieties and cultural practices. In Brazil, the major sugar-cane ethanol production is usually a 6 year-cycle, in which five cuts, four ratoon cultivation treatments and one field reforming are performed. Generally, the first harvest is made 12 or 18 months after planting. The following ratoon cane harvests are made once in a year, during 4 consecutive years (Macedo et. al., 2008). The average sugar-cane productivity in Brazil is about 87 tons of cane per hectare (tc ha -1 ), considering a complete cycle with five cuts (BNDES, 2008). The sugar-cane ethanol production chain begins with cane cleaning and crushing, when the juice is separated from bagasse (which is sent to a power island section to produce steam and electricity). The treated and slightly concentrated juice follows to fermentation, producing the wine, which will result in hydrous ethanol after the distillation. The hydrous ethanol may be sold as final product to be used in ethanol-only or flex-fuel vehicles or may be dehydrated to produce the anhydrous ethanol.

11 Table 5 Basic data for sugar-cane production, harvesting and transportation Brazilian average Productivity (kg ha -1 ) 87,100.0 Nitrogen (N) (kg ha -1 ) 60.0 a Phosphorus (P2O5) (kg ha -1 ) 8.3 a Potash (K2O) (kg ha -1 ) 13.3 a Lime (kg ha -1 ) 1,900.0 Herbicide (kg ha -1 ) 2.2 Insecticide (kg ha -1 ) 0.2 Seeds (kg ha -1 ) 6.9 Irrigation (stillage) (m 3 ha -1 ) Filtercake application (kg ha -1 ) 5.0 Machinary (MJ ha -1 ) 0.08 Harvesting (MJ ha -1 ) 0.38 Cane transportation (MJ ha -1 ) 0.42 Transportation of inputs (MJ ha -1 ) 0.13 Other activities (MJ ha -1 ) 0.44 Macedo et. al., (2008). a with filtercake mud and stillage application. Figure 3 Sugar-cane ethanol processing. Filtercake CO2 Waste Heat Yeast Sugar-cane Juice Crushing Fermentation Wine Bagasse Steam & Electricity Power Island CO2 Waste Heat Electricity Stillage CO2 Waste Heat Hydrous Ethanol Distillation Dehydration Anhydrous Ethanol The main co-products of sugar-cane ethanol are bagasse and electricity surpluses. Nowadays, most of the energy generation in mills is based on pure cogeneration steam cycle systems (at pressure of 2.2MPa), which are capable to attend whole mill energy demand and still produce small amounts of bagasse (5 10% of biomass) and electricity surpluses (0 10 kwh tc -1 ). However, new mill units are already equipped with high-pressure steam systems (e.g. pressure of 6.5MPa and 9.0MPa), besides the utilization of more efficient equipment and better process

12 integration designs. The implementation and evolution in cane trash recovering will enable the production of electricity surplus that easily overcomes 100 kwh tc -1. The main residues are filtercake mud and stillage, which are very important for their use as fertilizers, reducing the need for agricultural inputs (Macedo et. al., 2008). Table 6 Basic data for sugar-cane ethanol processing Brazilian average Unit Transportation of feedstock to refinery (MJ L -1 ) 0.27 a Surplus electricity (MJ L -1 ) a Equipments (MJ L -1 ) 0.01 a Buldings (MJ L -1 ) 0.05 a Cyclohexane (kg (m anhydrous) -3 ) b Lime (g t -1 ) b Sulfuric acid (g L -1 ) 9.05 b Lubricants (g t -1 ) b Anhydro Ethanol yield (L t -1 ) 86.3 a a Macedo et. al., (2008), b Macedo et. al., (2004) 4.2. Ethanol from corn Because corn is cold-intolerant, in the temperate zones it must be planted in the spring, while the harvesting season usually occurs in the fall. Rotations with soybean and alfalfa are common to reduce nitrogen applications rates. Corn production has a significant requirement for nitrogen fertilizer (12-15 g N m -2 yr -1 ) 1 and Nitrogen fixed in the soil supplements the first year corn requirement of Nitrogen. In corn following soybean rotation, up to 4 g N m -2 was assumed to come from soybeans and in corn following alfalfa rotation, about 8 g N m -2 was assumed to come from alfalfa. Table 7 Basic data for corn production, harvesting and transportation USA average Input Unit Productivity (kg ha -1 ) 8,740.0 Nitrogen (N) (kg ha -1 ) Phosphorus (P2O5) (kg ha -1 ) 64.0 Potash (K2O) (kg ha -1 ) 99.0 Lime (kg ha -1 ) Herbicide (kg ha -1 ) 2.8 Insecticide (kg ha -1 ) 0.2 Seeds (kg ha -1 ) 24.0 Irrigation (MJ ha -1 ) 49.0 Transportation of inputs (MJ ha -1 ) Machinary (MJ ha -1 ) Electricity (MJ ha -1 ) Diesel (MJ ha -1 ) 2,719.0 Gasoline (MJ ha -1 ) 1,277.0 LPG (MJ ha -1 ) Farrell et. al. (2006) 1 Based on Adler et. al. (2007), Patezk (2004), Farrell et. Al. (2006) and Shapouri et. al. (2002)

13 The corn ethanol production process starts by separating, cleaning and milling (grinding up) the starchy feedstock. Milling can be wet or dry, depending on whether the grain is soaked and broken down further either before the starch is converted to sugar (wet) or during the conversion process (dry). In both cases, the starch is converted to sugar, typically using a high-temperature enzyme process. From this point on, the process is similar to the sugar crops, where sugars are fermented to alcohol using yeasts and other microbes. A final step distils (purifies) the ethanol to the desired concentration and removes water (IEA, 2004). Figure 4 Corn ethanol processing. CSL Corn oil Corn gluten Corn meal Wet Milling Corn Milling/Mashing Water Enzimes Heat Dry Milling Corn Milling/Mashing CO2 Waste Heat Protein Mash Fermentation Beer Distillation Hydrous Ethanol Yeast Heat Heat Mash Fermentation Beer Distillation Hydrous Ethanol DDGS CO2 Waste Heat Dehydration Heat Dehydration Anhydrous Ethanol Anhydrous Ethanol The wet milling process also yields several co-products, such as corn steep liquor (CSL), corn oil, corn gluten and corn meal and the dry milling process yields distillers dried grain with soluble (DDGS), which can be used as an animal feed ingredient. The heavy steep water can also be sold as a feed ingredient or be used as an environmentally friendly alternative to salt in the winter months. Table 8 Basic data for corn ethanol processing USA average Transportation of feedstock to refinery (MJ L -1 ) 0.59 Electricity (MJ L -1 ) NR Coal (MJ L -1 ) 8.31 Natural gas (MJ L -1 ) 5.54 Bulding and equipment (MJ L -1 ) 0.13 Process water (MJ L -1 ) 0.38 Anhydro Ethanol yield (L t -1 ) Farrell et. al. (2006) Unit

14 One important difference between sugar-cane and corn ethanol production is the energy source used to drive the conversion process. In current corn ethanol production processes, especially in North America and Europe, virtually all process energy is provided by fossil inputs, such as coal and natural gas used to power boilers and fermentation systems. For sugar-cane ethanol conversion, nearly all process energy is provided by biomass, in particular the unused bagasse and leaves. This difference has important implications for the associated net energy balances and for net GHG emissions. Other relevant remark is that sugar-cane ethanol yields 7,516 L per hectare, which is 2.17 times bigger than the corn ethanol average yield of only 3,463 L per hectare. Table 9 Average yield in bio-ethanol production Corn ethanol - USA Sugar-cane ethanol - Brazil Crop yield (t ha -1 ) Ethanol yield per crop weight (L kg -1 ) Ethanol yield per land area (L ha -1 ) 3, , Fuel energy yield per land area (MJ ha -1 ) 73, , Reported HV of ethanol (MJ L -1 ) Values based on Tables 5, 6, 7 and Results Using the data found in the literature, the offered life-cycle methodology demonstrated that corn conversion into ethanol is energetically inefficient. The energy ratio is only 1.03, e.g. to produce a unit of renewable energy corn ethanol requires units of fossil energy. Moreover, without considering credits for co-products, the net GHG emissions balance is actually negative. The total emission for a MJ corn ethanol is 3.93 gco2 bigger than the GHG released from gasoline. Considering total sugar-cane energy output (ethanol and electricity), the energy ratio is 10.2 times bigger than the corn ratio and the total avoided emissions is about 115 gco2e MJ -1, or 122% of the equivalent emissions per gasoline. Table 10 Net GHG balance in bio-ethanol production gco2 MJ -1 Corn bio-energy Sugar-cane bio-energy Seeds, fertilizer and defensives Fossil fuel in feedstock Ethanol processing Ethanol distribution Total emissions Gasoline avoided emissions Electricity avoided emissions Total avoided emissions Values calculated with data from Tables 4 and 11. A comparative analysis between corn and sugar-cane energy yield per land area shows that corn conversion into ethanol produces 2,283 MJ ha -1 of renewable energy; sugar-cane ethanol

15 produces 144,205 MJ ha -1 of renewable energy; and combined electricity and ethanol from sugarcane yields 220,816 MJ ha -1 of bio-energy. Table 11 Net energy balance in bio-ethanol production Corn ethanol - USA Sugar-cane ethanol - Brazil (kj L -1 ) (Energy share %) a (kj L -1 ) (Energy energy %) a Seeds, fertilizer and defensives 3, , ,1 Transportation of inputs , ,5 Farm machinery , ,6 Gasoline ,7 NA NA Diesel , ,8 LPG ,0 NA NA Natural gas ,9 NA NA Electricity ,1 NA NA Energy used in irrigation ,1 NA NA Total Agricultural Phase 5, ,0 2, ,9 Transportation of feedstock , ,7 Buldings and equipment , ,2 Chemicals ,7 Process water ,8 NA NA Effluent restoration (BOD) ,4 NA NA Coal 8, ,2 NA NA Natural gas 5, ,1 NA NA Total Refinery Phase 15, , ,6 Total Fossil Energy Input 20, ,9 3, ,5 Biofuel output 21, , Electricity output 11, Total Energy Output 21, , Energy ratio Values based on Tables 2, 4, 5, 6, 7, 8 and 9. a Fossil energy input (MJ L -1 ) per total energy output (MJ L -1 ). These results are merely illustrative, since the data used are based on others studies and are strongly sensitive to the assumptions and systems boundaries chosen by the authors. It is important to remark that we used average values which can be misleading, especially regarding to energy inputs and GHG emissions related to transportation and distribution. We also identify limitations to the life-cycle analysis, especially when the impacts are more qualitative than quantitative, as well as the need for further discussion about the relevance of regulatory restrictions and certification systems to mitigate detrimental effects from variables not included in the quantitative analysis. These limitations are particularly relevant in corn ethanol production, since its energetic and environmental feasibility relies on the inclusion of co-products credits.

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