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Environmental and energy assessment of smallscale hydrous ethanol production (SSEP) Flávio Dias Mayer, Michel Brondani, Ronaldo Hoffmann, Electo Eduardo Silva Lora, and Bruno Carlesso Aita Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.5b01358 • Publication Date (Web): 11 Sep 2015 Downloaded from http://pubs.acs.org on September 17, 2015

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Energy & Fuels

Environmental and energy assessment of small-scale ethanol fuel production (SSEP)

Flávio D. Mayer1*, Michel Brondani1, Bruno C. Aita1, Ronaldo Hoffmann1, Electo E. S. Lora2 1

Department of Chemical Engineering, Federal University of Santa Maria, Cidade Universitária,

97105-900, Santa Maria, Brazil. 2

NEST – Excellence Group in Thermal Power and Distributed Generation, Institute of Mechanical

Engineering, Federal University of Itajubá, 37500-903, Itajubá, Brazil

KEYWORDS: ethanol fuel; small-scale; life cycle; energy balance.

ABSTRACT Rio Grande do Sul (RS) State edaphoclimatic conditions are suitable only to produce ethanol in small-scale. However, small-scale ethanol production (SSEP) was not proved to be feasible because of its lower process efficiency compared to large scale, and its environmental impacts were not assessed. The objective of this study is to evaluate SSEP through Life Cycle Assessment (LCA) and Energy Efficiency Analysis (EEA), showing potential scenarios of improvement in SSEP efficiency. Eco-Indicator 99 and CML 2 Baseline 2000 were the assessment methods, and the results demonstrated that nitrogen- and phosphorus-rich fertilizers, along with herbicides and limestone, were responsible for the highest environmental impacts in agricultural sector, while the use of equipment and electricity had the highest impacts in industrial sector. In the overall analysis, the industrial sector showed the highest environmental impacts. The SSEP Global Warming 1 ACS Paragon Plus Environment

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Potential is 0.128 kg CO2eq/MJethanol, almost 20 times higher than in large scale ethanol production, demonstrating the negative impact of lower SSEP efficiency. The EEA results were given in terms of Net Energy Balance (NEB) and Net Energy Ratio (NER) considering four scenarios (Cases1 to 4). Agricultural sector showed high NER (19.59), while the industrial stage showed an NER of 0.20 and 2.08 for the baseline scenario (Case 1) and for the improved scenario (Case 4), respectively. The overall process showed a NER of 0.69 for Case 1, in which the bagasse was not considered as co-product. When bagasse energy was accounted, the NER rises to 4.82 (Case 4), showing the importance of co-products in the process energy efficiency. The higher environmental impact of industrial stage is an incentive to develop and use more efficient technologies in SSEP.

1. Introduction

Most countries satisfy a large amount of it energy demand through non-renewable fuels, especially by coal and petroleum utilization. To modify energy production profiles and performance, changes in the political, economic, social, and environmental sectors are necessary to increase the use of renewable energy sources. Small scale distributed energy units can have a large influence on efforts to reach sustainability, and renewable energy sources are key to achieving this goal 1. Brazil can be cited as an example in renewable energy utilization, as a growing proportion of its energy is derived from renewable sources, reaching 48% in 2011, which is significantly higher than the world average of 10.9% 2. Although the share of renewable energy sources in Brazil is projected to decrease to 42% by 2035, as the increase in per capita energy consumption in the next years is foreseen to be supplied mainly by fossil fuels. In 2010, the ethanol and sugar sector accounted for 19.1% of the Brazilian primary energy supply 3, indicating the importance of sugarcane biomass for energy generation in Brazil, resulting in sugarcane being the second-largest source of energy in the country. Ethanol fuel, including both 2 ACS Paragon Plus Environment

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hydrous and anhydrous, responded for approximately 15% of Brazilian transportation energy matrix in 2012 3. The use of biomass for energy production, mainly in the production of ethanol, is politically and economically justified as it reduces oil imports 4 and social inequality 5, and also it’s a basis for green chemistry

6

. Furthermore, biomass is recognized for its environmental benefits, its

contributions to reducing air pollution, and the promotion of social benefits by creating jobs, as well as improving live conditions in rural communities

7,8

. Regarding the socioeconomic impacts of

small-scale agribusiness, the most important impact is job and income creation 5, with the flexibility to support local industries 9. It should also be reminded that agroenergy fosters substantial foreign currency savings by avoiding oil imports and enables the business and technological development of a major equipment industry 10. Also, decentralized production of energy, specifically biofuels, has several advantages, as follows: •

Utilization of local and low-cost feedstock, with lower transportation cost;

•

Operational flexibility and high reliability;

•

Production of energy near the consumer, because the market is decentralized. This reduces transportation costs;

•

Local production of energy assures self- sufficiency to the producer and local community.

Although Brazil is a major producer of ethanol, some states, such as Rio Grande do Sul (RS), produce small volumes of this biofuel. RS produces less than 2% of the ethanol fuel that it currently consumes, and this state pays a high price to “import” ethanol from other states. Edaphoclimatic conditions, as well as the predominance of small family farms, limit ethanol production to small-scale units in this region. Therefore, it is necessary to stimulate the ethanol production in RS, considering local specificities, especially the sugarcane cultivation and

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processing in small farms (which differ from the current scenario of the existing extensive sugarcane agribusiness in Brazil). However, the fact that ethanol is a renewable fuel does not means that it not cause environmental impacts arising from biomass cultivation, industrial processing, and/or its use, that must be evaluated in its life cycle. In fact, ethanol production could be more damaging to the environment than gasoline depending on the feedstock and land utilization

11

. Life Cycle

Assessment (LCA) and Energy Efficiency Analysis (EEA) are affordable methodologies to evaluate environmental impacts of a productive process, including the production of biofuels 12–16. The aims of this study are to identify the major potentially polluting flows within each process step of ethanol production in small scale, and verify the steps that have greatest potential for environmental impact using LCA. Also, it is intended to assess via EEA if the process is energetically feasible. This is an academic research in order to provide more information for the ethanol production process in small scale.

1.1 Small-scale ethanol production

Sugarcane conversion into ethanol fuel in large plants or in SSEP occurs through a two main stages - agricultural and industrial, both equally important for the efficient production. Sugarcane industrial processing can be divided in three major steps as follows: sugarcane crushing; fermentation; and distillation. Table 1 shows the process efficiencies for large and small-scale ethanol production. Global efficiency of SSEP process reaches a maximum of 65% of the large scale one, demonstrating the necessity of a higher feedstock input to produce the same amount of ethanol fuel, which will lead to greater environmental impacts and lower energy efficiency. In small-scale process, the preliminary washing of sugarcane is not necessary; that´s reduces water consumption and wastewater generation. Sugarcane harvest is usually manually performed without burning sugarcane straw, thus reducing pollutant emissions and allowing straw to be used 4 ACS Paragon Plus Environment

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as fertilizer and/or livestock feed 17,18. SSEP technology enables the small farmer to produce brown sugar, sugarcane spirit, and sugarcane syrup, resulting in a diversified sugarcane based industry. Most of the energy losses in SSEP are due to lower efficiency and could be reduced if coproducts are utilized

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, that can also raise SSEP profits. Bagasse, the main co-product in ethanol

production, could be used in energy generation or as animal feed (after hydrolysis and nutrient enrichment). Fuel ethanol production in small-scale jointly with dairy products could raise the income of small farmers by tenfold 8. Other study suggest that dairy production replaced by sugarcane cultivation may not generate satisfactory profits

20

. In the same way, the production of

ethanol and food in small-scale farms could be an alternative to ethanol production in large scale when supported by governmental policies and instruments 5. Ethanol fuel standard is an important issue to be considered in SSEP. In Brazil, ethanol fuel is required to have a concentration of ethanol between 92.5 and 93.8 by mass, according to regulation by National Agency of Oil, Natural Gas and Biofuels (ANP)

19

. This standard is not

applicable if ethanol is produced for self-consumption, which means that ethanol fuel could have a higher concentration of water, significantly reducing the energy consumption in distillation step.

1.2 LCA studies of biofuels System boundaries definition is important in a study related to a biofuel life cycle considering two perspectives: i) physical boundaries of the production system; and ii) regression levels of the considered flows. For biofuels produced from crop products, it is necessary to consider the impact of fertilizers, pesticides, and water consumption, as well as the impact on biodiversity, in order to delimitate system boundaries

12

. The LCA should consider the energy contained in and

necessary for the production of fuels for agricultural tractors, trucks, and other vehicles. Physical boundaries refer to the stages of the product’s life cycle. The cradle-to-gate analysis considers every stage, from obtaining and processing feedstock to attaining the desired product; in this case, biofuel analysis would be restricted only to the agricultural and industrial 5 ACS Paragon Plus Environment

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21–23

, not including the fuel distribution network and it utilization in vehicles. Most analyses

of biofuel production are cradle-to-gate, considering only the energy consumed in the cultivation of biomass, its processing, and, in some cases, the distribution of fuel 21. Some authors reported that the most widely used software is SimaPro® 24–27; and impact assessment method commonly chosen is Eco-Indicator 99 24. Energy flows within the physical boundaries of the system are related to flows regression levels

21,28

, that can be classified mainly in direct and indirect ones. The system can thus be

classified into four levels 29: •

Level 1: Considers only the energy inputs used directly to the process, usually in terms of electricity and steam.

•

Level 2: In addition to level 1, it also considers the energy intake related to indirect inputs. In biofuel production systems, this includes the embodied energy in fertilizers and pesticides, diesel consumption and the fuels used in boilers that produce the steam used in the process.

•

Level 3: Includes the energy used in the manufacturing of the production process equipment.

•

Level 4: Considers the energy used to obtain raw materials for the manufacturing of equipment, materials, etc.

There are several studies related to LCA of biofuels. Cherubini and Strømman

30

evaluated

94 LCA studies of bioenergy systems, including review articles and papers. Results indicated a focus on the study of biofuels such as biodiesel and ethanol derived from lignocellulose; the study of ethanol production from sugarcane was more developed in countries with favorable geographic and climate conditions, and an increasing number of studies, particularly of biorefineries, were expected in countries such as Brazil. Another interesting result from

30

is related with the

methodologies used for the qualitative interpretation of the LCA results, that generally includes the 6 ACS Paragon Plus Environment

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energy balance, the balance of greenhouse gases or carbon footprint, and other indicators based on impact categories such as eutrophication, acidification, etc. In fact, only 20 to 40% of the studies used software to express environmental analysis results, and these results, evaluated in terms of impact categories. Most of the studies have chosen the output product unit as the system functional unit. Emmenegger et al. 31 reported that bioenergy is not environmentally friendly per se. In many cases, energetic use of biomass allows a reduction of greenhouse gas and fossil energy use. However, there is often a trade-off with other environmental impacts linked to agricultural production, such as eutrophication or ecotoxicity. Methodological constraints still exist, such as the assessment of whether direct and indirect land use change emissions and their attribution to the bioenergy production, or the influence of heavy metal flows on the bioenergy assessment. In the production of sugar from sugarcane, the greatest impacts correspond to cultivation, mainly because of harvest technologies and agrochemical (fertilizer and herbicides) consumption 32,33

. Rocha et al.

34

informs that agriculture implies the most impacting activity, considering all

categories assessed in large scale ethanol production. As presented in the study by Contreras et al. 33

, utilization of byproducts (bagasse combustion and utilization of molasses and agricultural wastes

as livestock feed) has the potential to reduce environmental impacts in the sugar production process. In large scale ethanol production, agricultural sector is also reported to be responsible for most of the environmental impacts due to the application of fertilizers, sugarcane burning before harvesting, and the use of diesel fuelled machinery 35. In Brazil, studies performed by Luo et al.

36

and Cavalett et al.

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evaluated, both

economically and environmentally, ethanol production in large facilities considering both their agricultural and industrial stages. The latter study compared autonomous ethanol facilities with ethanol distilleries annexed to sugar facilities, both of which used basic and optimized technology, using SimaPro® to show the results of environmental assessment (conversion of inputs into


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environmental impacts categories). The best feasibility and lower environmental impacts were obtained using technologies with higher efficiency. Therefore, LCA is increasingly being applied to renewable energy production, particularly productions on a large-scale. Accordingly, the environmental and energy LCA of the SSEP using SimaPro® is an original study because of the production scale, and related characteristics, and the local conditions in RS state.

1.3 EEA studies of biofuels

Energy balance aims to quantify all energy flows within the process, in order to inform the net energy gain and the output/input energy ratio. This energy efficiency will determine whether the production system is energetically positive, that is, whether more energy is resulting than consumed. Efficiency of energy utilization measured by the energy balance or by the output/input ratio is calculated by determining the amount of energy obtained from the product in relation to the energy used in the system to produce it, according to 37. The criteria to assess the sustainability of a biofuel production process (in large or small scale) include positive energy balance or energy efficiency, energy footprint, emission reduction on its life cycle, economic feasibility, and the minimum impact over food supply

38–41

. Different

studies assessed the sustainability of biofuels production considering net energy balance methodology 38,39,42–46. Muench and Guenther (2013) cited that 32 out of 58 studies used energetic indicators to assess bioenergy production systems. In energy assessment, there are different indicators to calculate the net energy from a biofuel production system. A relation commonly found is the allocation criteria, used when the production process provides both biofuel and co-products47. In this case, the EEA can consider the whole system (biofuel + co-product) or the biofuel production only. In the later case, an allocation criterion (commonly mass or energy) should be defined. 8 ACS Paragon Plus Environment

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Indicators as Net Energy Ratio (NER) and Net Energy Production (NEP) or Balance (NEB) are the most important sustainability indicators in the EEA. NER is the energy output and the energy input ratio (including fossil and non-fossil fuels) 48, and NEB refers to the net energy output of the system 49. These indicators can be used considering allocation criteria. Some authors do not clearly point out the equations used when allocation is considered 42, while others precisely indicate if the assessment refers to the system (no allocation) or to the biofuel (with allocation) 34,38,39. Equation (1) and (2) are used in NEB and NER assessment

39,42

, respectively, when co-product is

not considered.

= −

=

(1)

(2)

Where, - energy output (MJ or MJ ha-1) - energy input (MJ or MJ ha-1)

When the energy output includes biofuel and co-product, allocation criteria should be used and, therefore, Equations (3) and (4) are used in NEB and NER calculations, respectively.

= − ( . + . + . )

!"# $ .$ % . % . )

= (

(3)

(4)

Where, 9 ACS Paragon Plus Environment

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- energy output from biofuel (MJ or MJ ha-1) , , - energy input of agricultural, transportation, and industrial stages, respectively (MJ or MJ ha-1) , , - allocation factor for agricultural, transportation, and industrial stages, respectively.

In Equations (1) to (4), solar energy and human workforce inputs are not included, according to Kamahara et al. 42 and Pradhan et al. 48.

2. Methodology

This study data were obtained in the small-scale distillery located at the Federal University of Santa Maria (UFSM), Rio Grande do Sul state. Ethanol fuel produced is consumed by the institution’s vehicles. Analyses of SSEP consider agricultural, transportation, and industrial production stages, covering regression levels 1, 2, and 3 from section 1.2, that is, the process boundaries represent a “cradle to gate” approach.

2.1 Life cycle boundaries and inventory allocations

Figure 1 shows the overall system boundaries, represented as the agricultural (sugarcane production), transportation (sugarcane transportation), and industrial (ethanol production) stages. The mapped and quantified flows were allocated in the SimaPro® software, using the Eco-Indicator 99 as a method of impact assessment to obtain the environmental impact percentage of each flow. Global warming potential (GWP) environmental impact was assessed using CML 2 Baseline 2000, developed and published by the Institute of Environmental Sciences (CML) of the Leiden University 34. 10 ACS Paragon Plus Environment

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2.1.1 Agricultural stage

An estimative of the amount of harvested sugarcane was performed considering the daily ethanol production of 320 L (minimum of 92.6% mass of ethanol and 7.4% mass of water), resulting in 48,000 L of ethanol annually. Sugarcane productivity was estimated in 80.0 t ha-1 and small-scale ethanol productivity was 56.5 L per tonne of sugarcane, requiring a cultivation crop area of 10.6 ha to harvest 850.0 tonnes of sugarcane per year. Sugarcane cultivation involves soil preparation and fertilization, using tractor for soil grading. Mass and energy coefficients for energy inputs calculations are shown in Table 2.

2.1.2 Transportation stage

Transportation sector involves transporting sugarcane from field to the small-scale distillery using a wagon pulled by a tractor, considering consumption of 0.45 liter of diesel per km and average distance of 2.0 km. Life cycle inventory is presented on Table 3. Sugarcane transportation was an intermediary step, that is, a step connecting the agricultural and industrial stages. Transportation stage was considered in the overall LCA, and in the EEA, this stage was evaluated as belonging to the agricultural stages.

2.1.3 Industrial stage

As stated in item 2.1.1, LCA was based on the production of 48,000 L of ethanol fuel per year, aiming self-consumption. Nevertheless, ethanol fuel was produced to attend legal standard (92.6% of ethanol by mass). This concentration was obtained using a batch distillation system with partial condenser, operating under condition of varying reflux ratio, described in Mayer et al.

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.


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Equipments, buildings, and mass and energy inputs were therefore calculated considering this production. As in distillation, batch production system was used in all other industrial steps, given the operational nature and scale of the process. Figure 1 shows the flowchart describing the production process of ethanol fuel in small-scale. The inventory of industrial stage was developed by monitoring the process and the mass coefficient is presented in Table 4. Water consumption was quantified based on sugarcane juice dilution, steam generation, and steam used for washing and cleaning, estimated at 5% of the steam generated for distillation. The amount of steam required in distillation was estimated in 3.25 kg of steam per liter of ethanol fuel. The process heat was considered to be generated from firewood or bagasse when specified. Only a fraction of bagasse is consumed as fuel, resulting in a large amount of bagasse output (dashed line of bagasse stream in Figure 1). When firewood is specified, all bagasse is considered to be an output.

2.2 Inventory energy efficiency analysis

Energy inputs and outputs of each stage were calculated by multiplying each flow by its energetic coefficient, according to Tables 2, 3, and 4. EEA of each stage and of the overall process was calculated considering four (4) cases, assessed using Equations (1) to (4), as follow: •

Case 1: Includes inputs and outputs in Equations (1) and (2), and consider firewood as the fuel to supply heat energy in industrial stage. Bagasse has no utilization in this scenario, therefore no allocation criterion was considered. This is the baseline scenario (“business as usual”).

•

Case 2: Includes inputs and outputs in Equations (1) and (2), and consider bagasse as the fuel to supply heat energy in industrial stage. No allocation criterion was used;

•

Case 3: Includes inputs and outputs in Equations (2) and (4), and consider firewood as the fuel to supply heat energy in industrial stage. The surplus of bagasse is 12 ACS Paragon Plus Environment

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considered to have energetic value according to its LHV and, therefore, an allocation criterion was used. •

Case 4: Includes inputs and outputs in Equations (2) and (4), and considers bagasse as fuel to supply heat energy in industrial sector. An allocation criterion was also used in this case. This is the improved scenario, because all bagasse has utilization and no firewood is consumed.

In Cases 3 and 4, the allocation criteria were based on mass fluxes, resulting in 0.53 for agricultural and transportation stages, and 0.1075 for industrial stage. Energy for equipments manufacture was also included in this analysis despite its low contribution to energy inputs, generally less than 10% 29. In Cases 1 and 3, firewood was the fuel used to provide heat energy to industrial stage because it is easier to handle and burn in small boilers, despite its higher cost. This is the case of SSEP at UFSM. Bagasse was not used as fuel due to its high moisture (50 %) making it difficult to burn in small scale boiler. Therefore, all the bagasse is used as soil amendment and as animal feed in Case 1. Energy analysis also considered the useful life of the tractor and furrowers, assuming to be 9 and 10 years, respectively 21. For the industrial stage, the following assumptions were considered, according to Macedo et al. 50 and Santos 51: •

Buildings (small-scale distillery) have a useful life of 50 years;

•

Heavy machinery and equipment (sugarcane crusher and boiler) have useful life of

25 years; •

Other (light) equipment have a useful life of 10 years;

•

The lifetime of the distillation column was assumed to be 15 years.


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The energy used for the maintenance of manufacturing machinery, equipment and buildings was estimated at 4% of the total energy of these items 50.

3. Results and Discussion

As discussed above, the LCA and EEA results consider agricultural, transportation, and industrial production stages.

3.1 LCA results

Table 2 shows the mass and energy inputs in agricultural stage. A preliminary study demonstrates that the use of farm tractors for land preparation is responsible for the greatest environmental impacts in the agricultural stage (see Table 5). It is important to note that this preliminary study considers the manufacture of farm tractors (raw materials and utilities). Thus, an LCA was performed excluding the use of farm implements, allowing identifying the major contribution inputs to each impact category. These results are shown in Table 6. According to Table 6, the major environmental impacts are resulted from the consumption of fertilizers and herbicides. The use of herbicides affects mainly the ozone layer, contributing to 89.5% of the overall impact in this category. Among fertilizers, nitrogen-rich fertilizer had the greatest potential for environmental impact. The mass and energy inputs and outputs of the industrial sector are presented in Table 4. Electricity and firewood were the major energy input, accounting for 60 and 36%, respectively, while bagasse and ethanol were the major energy output, representing 76 and 24%, respectively. Equipment utilization below its minimum capacity implies low production with higher specific energy consumption; in other words, it is necessary to work close to the design capacity to avoid wasting energy. Equipments and buildings have a negligible contribution in energy input 14 ACS Paragon Plus Environment

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compared to electricity and firewood, although these inputs have a more significant contribution than the corresponding ones of the agricultural stage. Industrial equipment (e.g. sugarcane crusher, batch distiller, tanks, etc.) could not be allocated directly in the SimaPro® software to perform environmental assessment; instead, it was allocated by its mass components, including cast iron, stainless steel, and iron. The construction of buildings consumes a large amount of materials such as cement, iron, and energy (electrical, mechanical, and human work), resulting in a high impact in all environmental categories except carcinogens, but especially on climate change and land use. Table 7 shows the contributions of the various inputs to environmental impacts in eleven categories, excluding buildings. In this analysis, the use of cast iron, mainly in industrial equipment such as sugarcane crusher, provides an important contribution to the impacts in all categories except land use. Electricity input resulted in small environmental impacts, despite its important contribution to energy input. Electricity major contributions were climate change and land use as it was assumed that the electric energy was generated by hydroelectric technology, resulting in large flooded areas. A higher contribution of industrial sector inputs was observed in the respiratory inorganics category, because of the emissions from industrial processes, mainly gaseous emissions from firewood combustion.

3.2

EEA analysis

The results of EEA analysis, considering NER and NEB for each stage for Cases 1 to 4 are shown in Table 8. NER of agricultural stage demonstrated a very positive energy balance for all cases assessed, resulting in an NER of 19.6. Excluding equipments (tractor and furrower) from this analysis, NER reached 22.14. NER of transportation sector for Cases 1 to 4 were near the unity because the only energy input was diesel. 15 ACS Paragon Plus Environment

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The NER from industrial stage proved to be small if bagasse was not totally used as energy source (Cases 1 and 2). Otherwise, NER for Cases 3 and 4 were higher than 1.0, proving the importance of bagasse in the energy balance of the process. Figure 2 show the standardized NER, considering input and output for Cases 1 to 4. It is clear that the energy consumption in industrial stage is the major input in Cases 1, 2 and 3. In Case 4, where firewood was replaced by bagasse, the farm inputs (fertilizers, herbicides, insecticide, water and limestone) become the major energy input. In terms of NEB assessment, it was revealed that Case 1 presented the worst scenario with a very negative energy balance (-463.0 GJ). Case 4 is in turn the best alternative to SSEP, with the most positive energy balance (+808.0 GJ). From the energy and environmental analysis, it is possible to conclude that the use of machinery and farm implements implies in greater influence from the point of view of environmental impacts than from energy consumption (11.5%). Utilization of three types of fertilizers in addition to herbicides resulted in a large contribution to various impact categories; therefore, utilization of these materials should be assessed attempting to reduce their harmful effects on the environment. Alternative fertilizers sources or production process

52

could help to mitigate

the impact of these inputs in biofuel production. This could also be achieved by replacing fertilizers by vinasse in some extent or using bioherbicides instead chemical products. This analysis demonstrates low energy balance indicators when by-products (bagasse were not included in the process (see assumptions 3 and 4 from Table 8). In Case 1 (business as usual), firewood is considered as fuel for the process heat generation. In this case, electricity and firewood represents around 81% of total energy input, and about 370 tonnes of bagasse are produced, representing 3,290 GJ of energy with no direct use. When bagasse is used as fuel replacing firewood in steam generation (Case 2), around 52 tonnes of bagasse are consumed, resulting in a surplus of 320 tonnes of bagasse (2,840 GJ of energy) which has no particular use. This suggests the need to use all the bagasse (as demonstrated in Case 4), which could be achieved by 16 ACS Paragon Plus Environment

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cogeneration (CHP), which may be difficult to accomplish in small scale. A possibility is the implementation of small scale advances technologies such as ORC engines

57–59

or radial steam turbines

53–56

, screw expander steam

60,61

. LHV of firewood (30% moisture) is 12.98 MJ·kg-1, that

is, 3.2 MJ·kg-1 higher than bagasse (50% moisture); however, the logging and transportation of firewood causes a greater environmental impact, while the bagasse is a residue, sometimes with negative price, that favors its utilization.

3.3 LCA and EEA results discussion

Figure 3 shows the eleven environmental impacts categories results obtained from SimaPro®, demonstrating a difference between the production stages. Industrial stage has the highest contribution in most of the impact categories (5 of 11), whereas agriculture stage showed the highest contribution in 3 of 11 categories, and the second-highest contribution in 6 of 11 categories. In addition, industrial and transportation stages had second-highest contribution in 2 and 3 of 11 categories, respectively. These results show that the environmental impacts of the agricultural stage should not be disregarded, even though the industrial one seemed more relevant. The GWP environmental impact from this study is presented in Figure 4. The GWP for SSEP was 0.128 kgCO2eq/MJethanol. This value is 20 times higher than other studies, demonstrating the low energetic efficiency of SSEP compared to large scale ethanol production. Agricultural, transportation, and industrial stages accounted for 26.0, 20.0, and 54.0% of CO2eq. emissions, respectively. Electricity consumed in industrial stage is responsible for 24% of CO2eq. emissions from the SSEP process, because no electricity is generated from the residual biomass, as opposed to large-scale, where cogeneration is used. Similarly, the use of two tractors in agricultural and transportation accounts for 28% of total CO2eq. emissions, resulted from their large idle utilization period, which does not occur in large scale. Furthermore, sugarcane is not burned before harvest, which contributes to partially reduce CO2eq emissions. 17 ACS Paragon Plus Environment

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Energy efficiency of the overall system was low, as shown in Table 8. Batch system leads to a reduction in efficiency compared to a continuous process, as stated in Table 1. Data in Table 8 show that SSEP is only energetically viable when bagasse energy is included as output. Bagasse represents a significant share in the energy balance, because it’s high production. A process that aims only to produce ethanol fuel will waste the energy contained in the bagasse, especially in SSEP, where the bagasse could be used for soil amendment or in livestock feed 8. If the surplus bagasse in Case 4 is used as animal feed, the NER certainly will lower than 4.82. Equipment utilization has little influence on the energy efficiency, accounting for 11.5% and 0.87% of energy input of agricultural and industrial sectors, respectively. Globally, equipments represents only 5.6% of total direct energy input – in accordance with IFIAS 29. However, the use of equipment (considering its manufacturing) has an important effect on environmental impacts, as evidenced by data from Tables 5 and 7. Furthermore, the use of bagasse as a solid fuel should be considered, thereby decreasing the consumption of firewood, reducing environmental impacts, and increasing the energy efficiency of the overall process. Another issue is related to industrial equipment, as a batch process implies in large idle equipment. It is necessary to determine the suitable dimensions of the process equipment in order to optimize its capacity, because its inefficient use of such equipment results in high energy consumption. Issues such as minimum production capacity, feedstock availability, and operating below optimum capacity are mentioned as an issue to be evaluated to obtain a positive energy balance in ethanol production 62, which can also be applied to SSEP. Table 9 summarizes the main results in energy consumption from different studies compared to the present study. Studies by Triana ethanol production, while dos Santos

51

63

, Macedo et. al.

50

, and Turdera

64

refer to large scale

and the present study refer to production of ethanol in

small-scale. Data from Table 9 evidence the major share of agricultural sector in energy consumption in large scale ethanol production. All studies present similar information regarding 18 ACS Paragon Plus Environment

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energy demand in sugarcane cultivation, but its share on the total energy demand is lower in smallscale process. Figure 5 show the agricultural and industrial share on energy inputs from several references, considering different feedstocks. From Figure 5 is evident that large-scale ethanol production has a smaller share of industrial stage on energy input because it’s higher efficiency. Additionally, largescale production uses bagasse as a fuel to generate steam and electricity in a combined heat and power system, thus increasing the process energy output. In fact, the use of bagasse is as important as ethanol in sugarcane processing energy balance. Where bagasse is considered, NER was around 8.0; in other cases, the NER remains between 0.7 and 5.0, excepting the study by de Oliveira 65. The higher share of agricultural sector on energy input in ethanol production is also verified in processing other feedstock, as agave (93%)

66

and switchgrass (99.9%) 67, because these feedstock

provide bagasse and lignin to be used in CHP generation in the industrial processing, as occurs in large-scale sugarcane ethanol production. Moreover, starchy feedstock produces no energetic byproduct to be used as fuel in CHP in industrial stage, generally demanding an external source of heat and/or electricity, resulting in a larger share of industrial stage on energy input and, relatively, reducing the share of agricultural stage. Therefore, the share of agricultural stage on energy input for ethanol production is 32% in the case of corn 38, 24% in the case of wheat 68, and 27% in the case of cassava 69, similar to Case 1 from this study. As stated by Luk et al. 70, the coproduction of ethanol and electricity can enhance the overall efficiency of the production process, considering both economical end environmental perspective. Production of ethanol in small-scale is highly energy intensive in industrial sector because its lower process efficiency, specifically in sugar extraction, fermentation, and distillation steps, resulting in higher energy consumption ratio per liter of ethanol. Therefore, industrial sector’s share of energy demand is higher, notably because of electricity and firewood consumption, as showed in Table 4. Industrial energy consumption in Case 1 and 4 are the same in both cases. The difference


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between the values presented in Table 9 for these cases refers to the allocation criteria, because bagasse is considered as co-product only in Case 4. In order to explain the difference between the results from this study and those from the study by dos Santos 51, a deeper comparison is necessary. Although both studies were on the smallscale process – both using batch distillation –, annual ethanol production of small-scale distillery assessed by dos Santos

51

is more than two times greater than that of this study, indicating a

reasonable answer to this divergence. Additionally, system boundaries and mass and energy coefficients should also be compared because they are not the same. Comparison among different studies regarding environmental impacts of ethanol production is also difficult because of divergences in methodology (system boundaries, process coefficients, and impact assessment methodology) and uncertainties in data used, although some general and relevant information can be obtained from these meta-analysis studies15. As stated by Granda et al. 14

, comparison among different data (as shown in Table 9) do not clearly reveal economical

feasibility nor environmental impacts from ethanol production. The present study informs that the major impact is in industrial sector – 5 of 11 categories. If transportation is enclosed in the agricultural sector, as stated in Table 9, the latter causes a higher impact – 6 of 11 categories. In any case, the industrial sector causes a higher impact in small scale than in large scale, because sugarcane cultivation on a large scale is more intensive in agricultural inputs (machinery, fertilizers, insecticides and fungicides), while the industrial sector on a small scale is less efficient. In general, it was demonstrated that lower efficiency in small-scale industrial process results in lower NER. This work also confirmed that a positive energetic balance depends on both process optimization and total use of co-products, thus confirming the importance to use allocation criteria. Feasibility of SSEP is linked directly with energetic issues, because electricity and firewood increase the production costs, affecting the competitiveness of the ethanol produced in small scale. This situation highlights the impact of economy of scale, which favors large-scale ethanol 20 ACS Paragon Plus Environment

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production. In Brazil, the ethanol fuel production is tightly regulated by National Agency of Oil, Natural Gas and Biofuels (ANP), which imposes several standards and restrictions to biofuels commercialization. As example, the producer of ethanol is not allowed to sell directly to the final consumer, raising the costs of ethanol (transportation, taxes, and markup), increasing the effects of SSEP inefficiencies. Therefore, a governmental program to develop more efficient technologies and also tax exemption on this should be used as public policy to encourage SSEP. It is clear that SSEP is not related only to biofuel production, but it is an economic activity which can produces several goods taking advantage from co-products, while ensuring energy security to the country.

4. Conclusions

Environmental impacts in sugarcane cultivation resulted mainly from the use of nitrogenand phosphorus-rich fertilizers, followed by herbicides. High electric energy use accounts for the largest percentage in four impact categories in industrial sector, accounting for the highest percentage in six impact categories. The SSEP Global Warming Potential is 0.128 kg CO2eq/MJethanol, almost 20 times higher than in large scale ethanol production, because no electricity is generated in the process and the inefficient utilization of tractors. Agricultural stage showed a NER equals to 19.59 units of energy, higher than NER for the industrial stage (0.20), considering the baseline scenario (Case 1). Industrial stage also showed the highest contribution to environmental impacts in five of eleven categories, while the agricultural stage had the highest contribution in three categories, confirming that the industrial stage has the highest potential environmental impacts. The overall process was energetically inefficient (NER of 0.69) considering only ethanol as output in Case 1. The NER rise to 4.82 if bagasse is used to replace firewood and considering other energetic uses of bagasse surplus.


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Results indicate the importance of a qualitative and quantitative analysis of the process, highlighting LCA and EEA as important tools for the assessment and identification of environmental impacts and energy balance of a process. This study also demonstrated the negative impact of lower SSEP efficiency in LCA and in EEA. Therefore, it is important to find solutions that take advantage of co-products, e.g. utilization of bagasse in cogeneration, in animal feed or as soil fertilizer. In these solutions, it should be considered credits from substitution of grid electricity, chemical fertilizers, and industrialized animal food. Without these improvements, SSEP will not become an alternative to large-scale ethanol production. Such improvements depend mainly from technological development (equipment and process efficient in small-scale) and from public policies, such as tax exemption or other subsidies, in way to ensure energetic security to local rural communities.

Corresponding Author *Tel.: +55 3220-8841. E-mail: [email protected].

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Pimentel, D.; Patzek, T. W. Ethanol Production Using Corn, Switchgrass, and Wood; Biodiesel Production Using Soybean and Sunflower. Nat. Resour. Res. 2005, 14 (1), 65–76. 27 ACS Paragon Plus Environment

Energy & Fuels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Odum, H. T. Environmental Accounting Emergy and Environmental Decision Making; J.Wiley & Sons, Inc.: New York, 1996.

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Macedo, I. C.; Nogueira, L. A. H. Avaliação da Expansão da Produção de Etanol no Brasil (Assessment of ethanol production expansion in Brazil); Brasília, 2004.

(80)

Hannon, B. M.; Stein, R. G.; Segal, B. Z.; Diebert, P. F.; Buckley, M.; Nathan, D. Energy use for building construction; 1977.

(81)

Tavares, S. F. Analysis methodology of the energy life cycle of Brazilian residential buildings (in Portuguese), PhD Thesis,Universidade Federal de Santa Catarina, 2006.

(82)

Environmental Product Declarations of the European Plastics Manufacturers. Polypropylene (PP); 2008.

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Nogueira, L. A. H. Analysis of energy use in the production of alcohol from sugarcane (in Portuguese), PhD Thesis, Universidade Estadual de Campinas, 1987.

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Paoliello, J. M. M. Environmental and energy potential in sugar industry waste recovery (in Portuguese), Master Dissertation, Universidade Estadual Paulista, 2006.


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Energy & Fuels

Table 1 – Efficiency of ethanol production process in large and small-scale. Industrial step

Large scale Efficiency (%)

Reference

Small-scale Efficiency (%)

Reference

Sugarcane crushinga

95.7

Lobo et al.71

53-79

Mayer et al.19

Fermentationb

92.0

Basso et al.72

80-85

Mayer et al.19

Distillationc

99.7

Dias et al.73

85

Michel Junior74

a

Efficiency of sugar extraction from sugarcane in the milling process;

b

Batch fermentation yield;

c

Distillation efficiency considering the ethanol recovery from the feed stream.


Energy & Fuels

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Table 2 – Life-cycle inventory in agricultural stagea Mass coefficient Input

Energy coefficient

Specific consumption

Phosphorus pentoxide (P2O5)

160.0 kg·ha-1·yr-1

Potassium oxide (K2O)

225.5 kg·ha-1·yr-1

Nitrogen (N)

111.5 kg·ha-1·yr-1

Source

Calculated data

Specific energy

Nogueira75 Seabra76 Nogueira75 Seabra76 Nogueira75 Seabra76

Source

Amount

Total energy (E+10 J)

9.56 MJ·kg-1

Farrell et al.62

1,699.2 kg

1.63

7.1 MJ·kg-1

Farrell et al.62

2.394 kg

1.70

59.02 MJ·kg-1

Farrell et al.62

1,184.13 kg

6.99

Farrell et al.62 30,444.04 kg

3.53

34.52 kg

1.44

Dolomitic limestone

2,866.7 kg·ha-1·yr-1

Collected data

1.16 MJ·kg-1

Herbicide

3.25 kg·ha-1·yr-1

Collected data

418.6 MJ·kg-1

Pimentel and Patzek77

Insecticide

0.3 kg·ha-1·yr-1

Seabra76

358.0 MJ·kg-1

Nogueira75

3.2 kg

0.114

-1

Collected data

-1

78

5,841.0 kg

0.003

3,000.0 kg

Collected data

61.83 MJ·kg-1

Macedo et al.50

3,000.0 kg

2.06

200.0 kg

Collected data

71.71 MJ·kg-1

Macedo et al.50

200.0 kg

0.143

-1

Collected data

-1

50

212.4 L

1.02

2.0 t·ha-1

dos Santos51

Macedo et al.50

21,240.0 kg

0.56

4.43 MJ·kg-1

EPE3

850,000 kg

376.0

12,81 MJ·kg-1

Nogueira75

119,000 kg

152.4b

Water Rural tractor (one unit) Furrower (one unit) Diesel Sugarcane steam (propagation) Output Sugarcane

-1

550.0 L·ha ·yr

20.0 L·ha

80.0 t·ha-1

-

0.00494 MJ·kg

47.8 MJ·L 3% of total input energy

Odum

Macedo et al.

75

Nogueira Sugarcane straw 11.2 t·ha-1 Macedo and Nogueira79 a average values were used when two or more references were available. b

sugarcane straw was not considered as a energetic co-product because it is difficult to harvest and transport to be used in the facility.

30

ACS Paragon Plus Environment

Page 31 of 40

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Energy & Fuels

Table 3 - Life-cycle inventory in biomass transport stage Mass coefficient Input Sugarcane Tractor (one unit) Tractor wagon Diesel

Energy coefficient


Source

Specific energy

Calculated data Source

80.0 t·ha-1

-

4.43 MJ·kg-1

EPE3

3,018.0 kg

Collected data

61.83 MJ·kg-1

1,750.0 kg

Collected data

71.71 MJ·kg-1

20.0 L.ha-1

Collected data

47.80 MJ·L-1

Macedo et al.50 Macedo et al.50 Macedo et al.50

80.0 t·ha-1

-

4.43 MJ·kg-1

Amount


850,000 kg

376.0

3,018.0 kg

2.07

1,750.0 kg

0.126

276.7 L

1.32

Output Sugarcane

EPE3

850,000 kg

376.0

31


Energy & Fuels

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Page 32 of 40

Table 4 - Life-cycle inventory in industrial stage Mass coefficient Input

Energy coefficient


Electricity Water

208,889 kWh

Source

Calculated data

Specific energy

Collected data

Source


Amount

-

-

208,889 kWh

75.0

78

206,400 kg

0.10

EPE3

34,648 kg

45.0

Macedo et al.50

576 kg

0.08

Hannon et al.80 and Tavares81

103 m2

1.40

Macedo et al.50

2,500 kg

1.08

Environmental Product Declarations of the European Plastics Manufacturers82

30 kg

0.02

Macedo et al.50

30 kg

0.03

135 kg

0.10

306 kg

0.23

-1

206,400 kg

Collected data

0.00494 MJ·kg

34,648 kg

Collected data

12.98 MJ·kg-1

Yeast

576 kg

Collected data

1.39 MJ·kg-1

Building

103 m2

Collected data

6,548.40 MJ· m-²

2,500 kg

Collected data

108.37 MJ·kg-1

30 kg

Collected data

73.40 MJ·kg-1

30 kg

Collected data

108.37 MJ·kg-1

135 kg

Collected data

73.40 MJ·kg-1

306 kg

Collected data

73.40 MJ·kg-1

280 kg

Collected data

104.91 MJ·kg-1

Macedo et al.50 and Nogueira83

280 kg

0.20

2,000 kg

Collected data

135.20 MJ·kg-1

Macedo et al.50

2,000 kg

1.08

Firewood

Sugarcane crusher (one unit) Decanter tank (one unit) Pump (02 units) Fermentation tank (03 units) Storage tank (06 units) Distiller (one unit) Boiler (one unit)

Odum

Environmental Product Declarations of the European Plastics Manufacturers82 Environmental Product Declarations of the European Plastics Manufacturers82

Output 48,000 L

Collected data

21.37 MJ/L

EPE3

48,000 L

102.0

Bagasse

369,557.0 kg

Collected data

8.92 MJ/kga

EPE3

369,557.0 kg

329.0

Vinasse

624,000.0 L

Collected data

0.0238 MJ/L

Paoliello84

624,000.0 L

1.49

Ethanol fuel

Total a

-

-

-

433.0

Bagasse with 50% moisture.

32


Page 33 of 40

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Energy & Fuels

Table 5 - Contribution of tractor use for each impact category in agricultural stage. Impact category Carcinogens Respiratory organics Respiratory inorganics Climate change Radiation Ozone layer Ecotoxicity Acidification/Eutrophication Land use Minerals Fossil fuels

Contribution (%) 96.62 86.45 61.44 50.67 89.43 51.39 90.15 35.43 91.01 90.66 65.25

Table 6 - Major inputs in each impact category in agricultural.stage Impact category Carcinogens

Respiratory organics

Respiratory inorganics

Climate change Radiation Ozone layer Ecotoxicity Acidification/Eutrophication Land use Minerals Fossil fuels

Major input

Contribution (%)

Herbicides

55.0

Dolomitic limestone

34.7

Fertilizer (P2O5)

27.6

Fertilizer (N)

23.7

Diesel Fertilizer (P2O5) Fertilizer (N) Dolomitic limestone Fertilizer (P2O5)

16.9 32.7 43.0 12.9

Fertilizer (N) Herbicides Dolomitic limestone Herbicides Herbicides Dolomitic limestone Fertilizer (P2O5) Fertilizer (N) Herbicides Dolomitic limestone Herbicides Dolomitic limestone Fertilizer (P2O5) Fertilizer (K2O) Fertilizer (N)

73.5 22.9 71.0 89.5 37.6 54.0 25.2 64.4 26.2 52.1 46.0 48.4 20.1 17.8 47.4

11.7


Energy & Fuels

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Page 34 of 40

Table 7 - Major inputs in each impact category in industrial stage. Impact category

Major input

Contribution (%)

Stainless steel and iron

Carcinogens

Cast iron

85.9 8.9

Electric energy

44.3

Respiratory organics

Cast iron

14.8

Respiratory inorganics

Chemicals Industrial sector Cast iron Electric energy

14.6 75.3 12.9 77.5

Cast iron Cast iron Electric energy Chemicals Cast iron Chemicals Firewood Cast iron Stainless steel Cast iron Firewood Electric energy Electric energy Cast iron Cast iron Polypropylene Chemicals

9.6 61.5 19.4 10.4 33.4 27.1 20.2 51.0 27.5 32.0 21.8 95.6 56.1 26.8 29.9 21.8 21.2

Climate change

Radiation

Ozone layer Ecotoxicity Acidification/Eutrophication Land use Mineral Fossil fuels

Table 8 - Energy efficiency Analysis of the process. Stage

NER

NEB (GJ)

% of initial energy attributed to equipment (no allocation)

Case 1

Case 2

Case 3

Case 4

Agricultural

19.59

19.59

19.59

19.59

11.48

Transport

0.99

0.99

0.99

0.99

0.87

Industrial

0.20

0.22

1.90

2.08

0.83

Global

0.69

0.99

3.92

4.82

5.60

Global

-463,0

-13,6

760,0

808,0

-


Page 35 of 40

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Energy & Fuels

Table 9 – Comparison of energy efficiency of ethanol fuel production from sugarcane in large and small-scalea. Energy input (GJ·ha-1)

Reference

Triana 63c

Macedo et. al. 50 Turdera 64 dos Santos This study a

51k

Case 1

Output (GJ·ha-1)

NER (Eout/Ein)

43.98

135.44

3.08d

18.01

135.44

7.52e

15.32

135.44

8.84f

3.63

39.61

135.44

3.42g

16.60

4.06

20.67

158.13-172.01

7.65 - 8.30h

15.80

19.07 16.95

168.13-194.85 134.40

8.85 - 10.22i

13.32

3.28 3.63

18.55 22.50

7.32 117.00

25.88 139.5

129.54

5.01k

95.47

0.69

95.47

4.82

Agriculturalb

Industrial

Total

25.36

18.62

16.19 12.71

1.82 2.61

35.98

l

Case 4 11.90 8.07 19.97 Ethanol fuel distribution (after industrial sector) was not considered;

7.93j

b

Energy input in sugarcane transportation sector was allocated in agriculture sector;

c

Results compiled from Triana 63.

d

Pimentel e Patzek (2008) cited by Triana 63. Considering only ethanol as output;

e

Macedo et al. 43.

f

Boddey et al. (2008) cited by Triana 63 .

g

de Oliveira 65.

h

Scenario 1 – Average energy consumption values;

i

Scenario 2 – Using improved agricultural and industrial practices and techniques;

j

Considering only ethanol output. Considering results from five sugarcane distilleries in Brazil;

k

The author informs the production of 1,000 liters of ethanol per day, which is not so small as the SSEP considered in this study.

l

Considering energy from bagasse.

35


Energy & Fuels

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Page 36 of 40

Figure 1 - Overall system flowchart and boundary for Case 1 (functional unity is 48,000 L of ethanol per year). 36 ACS Paragon Plus Environment

Page 37 of 40

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Energy & Fuels

Figure 2 – Standardized NER of ethanol fuel (biofuel) production in small scale. Note: Input and output for Cases 1 to 4 were standardized considering the energy in biofuel.


Energy & Fuels

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Figure 3 - Comparison among the production sectors of SSEP, in terms of impact categories.

38


Page 39 of 40

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Energy & Fuels

Figure 4 – GWP in life cycle of ethanol production. The GWP values from Capaz (2009) and Macedo et al. (2004) were calculated in Rocha et al. 34 .


Energy & Fuels

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Page 40 of 40

Figure 5 – Share (%) of agricultural and industrial stage on energy demand in bioethanol production from different feedstocks. Legend: a Cassava69; b Wheat 68; c Corn 38; d Switchgrass 67; e Agave 66; f Sugarcane 63; g Sugarcane 50; h Sugarcane 51; i Sugarcane 64.


Environmental and Energy Assessment of Small ... - ACS Publications

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