Integration of a small biofuel refinery in a rural context

chemical engineering research and design 8 7 ( 2 0 0 9 ) 1191–1205

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Integration of a small biofuel refinery in a rural context M. Simone a , M. Bientinesi a,∗ , C. Nicolella a , L. Petarca a,b a b

Dipartimento di Ingegneria Chimica, Chimica Industriale e Scienza dei Materiali—Università di Pisa—via Diotisalvi 2, 56122 Pisa, Italy Consorzio Polo Tecnologico Magona—via Magona, 57023 Cecina (LI), Italy

a b s t r a c t In this work three scenarios of biomass production, conversion and utilization of different biofuels (sunflower crude oil, sunflower refined oil and sunflower methyl-ester) in a rural context are compared. The analysis is referred to the district of Pisa, in Italy. Technical feasibility was analysed by comparing process schemes and safety issues, while environmental impacts were studied by applying the methodology of life cycle assessment. Scenarios involving upgrading of crude sunflower oil (refined oil and biodiesel) require complex plants and the management of dangerous materials, and they produce considerable amounts of wastewater. These scenarios need larger plant size, more complex organization (farm cooperatives) and higher costs than the simple mechanical operations associated with crude oil production. On the other hand the use of low-quality fuels in internal combustion engines can lead to short engine lifetime and high pollutant emissions. The life cycle analysis shows that the biofuel upgrading processes (refining and transesterification) and oil transport have a low influence on the environmental impact, compared to seed cultivation, which is the most impacting step. However fuel upgrading allows a significant reduction in polluting emission during combustion; as a consequence biodiesel results the most sustainable biofuel. © 2009 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

1.

Introduction

Biomass is expected to become one of the major renewable resources for the production of food, feed, materials, chemicals, fuels, power and/or heat. The process plant where biomass is transformed in these products is seen as an evolution of a traditional petrochemical refinery and it is called biorefinery. A biorefinery may include different technology platforms (Ragauskas et al., 2006; Fernando et al., 2006) such: 1. Sugar platform for the production of ethanol from sugar, starch and cellulosic plants by fermentation; 2. Thermochemical platform for the production of syngas by gasification of ligno-cellulosic biomass, forestry and agricultural residues; 3. Biogas platform for the production of methane by anaerobic digestion of cellulosic biomass and manure; 4. Oil platform for the production of vegetable oil and biodiesel from oilseeds. Large scale installations give the best opportunities for process integration in a biorefinery. On the other hand, due to the

∗

low energy density and the uneven distribution of biomass, biorefineries at industrial scale require feed biomass to be transported from long distances for processing (Wu et al., 2002). In these cases transportation costs and environmental impacts become critical factors in planning new installations (Shi et al., 2008). As an alternative to large installations, the delocalization of small biorefineries in rural and near-rural contexts gives the opportunity of exploiting local biomass, while reducing the transportation of raw materials (Bernesson et al., 2004), but it requires careful considerations of operation, safety and environmental issues. These issues are routinely addressed in an industrial context, but they may become critical when small plants in non-industrial contexts are considered. In these cases, the interactions of a process plant and its products with the local economic and environmental framework are key factors for the choice of suitable products and plant size, even for established technologies, such as those included in the production of biofuels. High-grade fuels (i.e. biodiesel) guarantee high efficiency, low emission and long operating life to engines, but they require a more complex plant and higher operating and cap-

Corresponding author. Tel.: +39 0 502217891; fax: +39 0 502217866. E-mail address: [email protected] (M. Bientinesi). Received 3 October 2008; Received in revised form 14 May 2009; Accepted 24 May 2009 0263-8762/$ – see front matter © 2009 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.cherd.2009.05.007

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ital costs (which may not be afforded by a small farm) than low-grade fuels (i.e. vegetable oil). The choice of the most suitable biofuel production and plant size in a given context can be supported by process analysis and life cycle assessment (LCA). LCA has been widely employed to characterise biodiesel production. Different biodiesel process options (Janulis, 2003; Stephenson et al., 2008; Zhang et al., 2003) and plant sizes (Stephenson et al., 2008; Bernesson et al., 2004) are compared, also with diesel production (Kaltschmitt et al., 1997). The final utilization considered in published LCA works on biofuels is mainly automotive traction. These LCA works generally do not consider the utilization of vegetable oils as biofuels nor they include combined heat and power generation. The aim of this paper is to asses some aspects of feasibility in a rural context for an oil refinery, a well-established technology platform, based on the extraction of oil from oilseeds and a sequence of physical and chemical operations to produce a fuel suitable for use in internal combustion engines.

2.

Methodology

The background for the production of three different biofuels (Crude Oil, Refined Oil and Biodiesel) from oilseeds was derived from commercial technologies and existing plants, leading to the design of the flow-sheet for each process. Consequently three scenarios were defined. The biofuel type and the plant size were chosen according to preliminary considerations on plant complexity and costs of each process. The scenarios were related to a specific geographical area to consider reliable data on land use, biomass yield and agricultural practises, as well as defining a realistic rural context. Finally the performance of the scenarios were compared taking into account technical and safety issues, process analysis (material and energetic balances) and life cycle assessment, in order to provide information for the choice of the best option in a given context in relation to the environmental impact.

3.

Vegetable oil based biofuels background

Biofuels such as vegetable oil and biodiesel are produced from oilseeds of plants such as sunflower and rapeseed. The first step of the process is the oil extraction from the seeds. There are two types of extraction: mechanical pressing and solvent extraction. In the former the seeds are pressed in a screw press to release oil. In solvent extraction the seeds are crushed and then an organic solvent (usually hexane) is brought into contact with them to dissolve the oil; the oil and the solvent are then separated through distillation. The choice between mechanical and solvent extraction is based on the plant productivity. Typically plants that process less than 100,000 kg/day use mechanical pressing and plants that process more than 300,000 kg/day use solvent extraction (Williams, 1997). Therefore mechanical pressing is suitable for a small farm. The oil produced by the extraction step can then be processed in three different ways, as described in the following.

3.1.

Crude oil

Filtering of the oil mechanically extracted from seeds is the minimum process requirement for the production of a biofuel (hereafter called crude oil) suitable for use in engines.

Fig. 1 represents the flow diagram of this process. The oilseeds are fed to the screw press (PM1) which operates at nearly 75 ◦ C. The released oil (nearly 30% of the amount of the processed seeds) is collected in a drum (D1). During the pressing the moisture is released due to the temperature. The solid residue produced from the extraction can be used as fodder, provided that the residual oil content is reduced to the desired limits. To this end, solids from the first extraction are fed to a second press (PM2) which produces a little amount of oil, which is collected in a drum (D2), and leads to a solid residue in the form of pellets, used as animal fodder. The oil produced through mechanical pressing contains nearly 2% of solids which must be separated. Therefore the oil is filtered on a filter-press (F1). The filter-press usually needs to be precoated to form a filter cake. Between the pressing and the filtration the oil is momentarily stored in a heated tank (D3). The filtered oil is stored in a large tank (D5) equipped with a heating system that maintains the temperature of the oil high enough for it to be pumped. The crude oil contains compounds which may damage the engine as phosphorus (derived from phospholipids) and acids (free fatty acids) and its use may lead to short engine life and high pollutant emissions. On the other hand, the crude oil is obtained through a simple process involving mechanical operations only. There is no need for chemicals and the requirements of the plant are limited to electric power and heat for oil storage.

3.2.

Refined oil

The quality of the crude oil can be enhanced through a refining process to improve the engine performance and lifetime. Oil refining is similar to that of an edible oil producing plant. Fig. 2 represents the flow diagram of the process. The crude oil is heated up to nearly 60 ◦ C in a plate heat-exchanger (E1) and it is mixed with a solution of phosphoric acid (water and H3 PO4 3% and 0.85% by weight of the feed, respectively) through a static mixer (MX1) to remove phospholipids (degumming process). Oil neutralization is carried out by adding NaOH to the oil stream before a static mixer (MX2). The neutralization removes free fatty acids producing soaps. Two heated mixers (D1, D2) provide the residence time to carry out the reactions. Gums and soaps are separated in a centrifuge (PC1) and the oil is momentarily stored in a heated tank (D3). Oil is further purified by washing it with warm (nearly 50 ◦ C) water (20% by weight), which is added through a static mixer (MX3) in order to dissolve residual soaps and impurities. Oil and water are separated in another centrifuge (PC2). Finally the residual water in the oil is removed in a vacuum tower (C1). Oil is heated up to 70 ◦ C through a plated heat-exchanger (E2) and it is fed to the tower which is kept at 0.1 bar by removing continuously moisture and non-condensable gases through a liquid ring pump. Dried oil is extracted from the bottom of the tower and is stored in a large heated storage tank (D5). The refining process involves the use of chemicals, management of chemical reactions and physical separations.

3.3.

Biodiesel

The physical properties of vegetable oils are significantly different from to those of a traditional diesel fuel, and they may lead to low engine efficiency and high pollutant emissions, as well as short engine life. To overcome these problems vegetable oil can be converted through a transesterification reaction in biodiesel, which has physical properties similar

chemical engineering research and design 8 7 ( 2 0 0 9 ) 1191–1205

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Fig. 1 – Flow diagrams of crude sunflower oil production process.

Fig. 2 – Flow diagrams of refined sunflower oil production process. to those of a diesel fuel (Altin et al., 2001). Fig. 3 reports the production process of biodiesel from refined vegetable oil. Refined oil is heated up to 70 ◦ C in the heat-exchanger E1 and mixed with methanol and KOH as catalyst (22% and 1% by weight respect to the feed, respectively) in the heated reactor D1 to perform the transesterification reactions. This reaction

breaks the triglycerides of the oil to form methyl-esters and glycerine. The reaction takes almost 2 h to reach completion (Rashid and Anwar, 2008). The products are removed from the reactor and the catalyst action is blocked by the addition of acetic acid before the static mixer MX1. The mixture is then moved to a vessel (D2) kept at low pressure (nearly

Fig. 3 – Flow diagrams of refined sunflower methyl-ester production process.

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Table 1 – Data of each scenario. Scenario

1 (CSO)

2 (RSO)

3 (SME)

Sunflower surface Sunflower seeds yield Product Production rate Utilization rate Production period and hours Utilization period and hours Biofuel PCI (MJ/kg) (Altin et al., 2001) Thermal input to engine (kW)

50 ha 2500 kg/ha Crude oil 98 kg/h 30 kg/h September–November (420 h) Winter (1360 h) 39.6 330

4000 ha 2500 kg/ha Refined oil 270 kg/h 270 kg/h Year (6500 h) Year (6500 h) 39.6 5340

4000 ha 2500 kg/ha Biodiesel 270 kg/h 270 kg/h Year (6500 h) Year (6500 h) 40.6 5472

0.1 bar) to strip and recover the methanol which is added in excess. The following step is the removal of the heavy phase, which is composed of glycerine, residual methanol and salts, from the methyl-esters. This is carried out by centrifugation in PC1. The methyl-esters free of glycerine and methanol are further purified by washing them with warm water (50 ◦ C) in a static mixer (MX2) to dissolve any residual salt or methanol. Methyl-esters and water are separated in the centrifuge PC2. Methyl-esters are then heated up to 70 ◦ C through a plated heat-exchanger (E2) and fed to a tower (C1), which is kept at 0.1 bar by removing continuously through a liquid ring pump moisture and non-condensable gases. Dried biodiesel is extracted from the bottom of the tower and is stored in a large tank (D4). Another section of the plant is dedicated to methanol removal from the glycerine phase, which is carried out through a low pressure distillation process. The management of the transesterification process is more complex than the refining process because it involves the use of methanol, which is flammable and toxic, and the low pressure separation of glycerine and methanol.

4.

Scenarios

Three scenarios related to the production and utilization of three biofuel products (crude vegetable oil, refined oil, biodiesel) were defined. The district of Pisa was considered as the geographical context. Sunflower, the most common among oilseed cultures in this area, was chosen as biomass. Mass and energy balances were set for each defined scenario, in order to compare the performance from an energetic and environmental point of view. Electric consumptions (oil press, centrifuges, pumps, impellers et cetera) were calculated from datasheet of commercial equipments.

4.1.

Definition

4.1.1.

Scenario 1

burned in a CHP (combined heat and power) engine in winter. This solution allows the farm to reduce its energetic and thermal requirements in the cold season. The output of the CHP engine is not integrated in the production process of crude oil because the two operations are neither simultaneous nor continuous. The CHP engine has a thermal input of 330 kW and it is not considered as a significant polluting source subjected to emission limitations according to the Italian legislation (D.Lgs. 152/06, art. 269).

4.1.2.

4.1.3. The first scenario represents a single farm in the district of Pisa, which produces crude oil. Table 1 reports data related to this production. The farm has a relatively wide cultivable surface (200 ha) compared to the average value (50 ha) in the district of Pisa (ISTAT, 2002). Only 25% of the surface is cultivated with sunflower (a 4-years rotation is considered). The farm harvests sunflower seeds at the end of summer and it produces oil from September to November. The crude oil is

Scenario 2

The second scenario represents the production of high quality vegetable oil, requiring higher technology level and plant complexity than the crude oil. The oil quality is enhanced by removing phosphorus (degumming), acids (neutralization) and moisture. The refining process involves the use of chemical substances, chemical reactions management and complex physical separation. The plant is made up of chemical operations which are not suitable to be operated in a farm. For this reason, we referred this process to a consortium of farms located in the Pisa district. Table 1 reports data related to this production. The consortium is formed by nearly 100 farms similar to that of Scenario 1. This assumption is based on the farms distribution in the considered geographical area (ISTAT, 2002). Each farm produces sunflower seeds that are transformed in crude oil in situ. The crude oil is then transported to the consortium refining plant. A mean distance of 50 km between each farm and the refining plant is considered, according to the territory conformation of the district. The plant operates almost continuously during the year and produces refined oil which is fed to a CHP engine with a thermal input of about 5 MW. The thermal and electrical outputs are destined to local networks and partially used in the refining process.

Scenario 3

In the third scenario, the same consortium described in Scenario 2 performs the crude oil refining and it transforms the refined oil in sunflower methyl-ester (biodiesel) according to the data reported in Table 1. The plant is more complex than in Scenario 2, due to the management of methanol and to glycerol refining. Methanol recovery and glycerol refining are complicated and energy intensive processes, therefore they are usually not performed by small-scale producer. At the small scale, glycerol is usually treated as a waste (Stephenson

Table 2 – Energetic input for each process. Scenario Total electrical input Total thermal input

1 (MJ/kgcrudeoil ) 0.854 2.254

2 (MJ/kgrefinedoil ) 0.018 1.818

3 (MJ/kgbiodiesel ) 0.151 0.923

Table 3 – Streams description. Material

Quantity

Proc. 2

Material

Quantity

Proc. 3

Material

Quantity

1

Oilseeds

100 kg/h

1

Crude oil

100 kg/h

1

Refined oil

100 kg/h

2

Meal Oil

52.5 kg/h 7.8 kg/h

2

H3 PO4 Water

0.085 kg/h 3 kg/h

2

Methanol

22 kg/h

3

Meal Oil

52.4 kg/h 5.3 kg/h

3

NaOH Water

0.075 kg/h 0.225 kg/h

3

KOH

1 kg/h

4

Moisture

9 kg/h

4

Wastewater Solids

5.04 kg/h 1.332 kg/h

4

Esters Glycerine Methanol KOH

100 kg/h 10.3 kg/h 11.7 kg/h 1 kg/h

5

Oil Solids

30 kg/h 0.6 kg/h

5

Oil

97 kg/h

5

CH3 COOH

1 kg/h

6

Oil Solids

2.5 kg/h 0.1 kg/h

6

Water

20 kg/h

6

Methanol

9.98 kg/h

7

Oil Solids

32.5 kg/h 0.7 kg/h

7

Oil Water

7

Esters Glycerine Methanol Impurities

100 kg/h 10.3 kg/h 1.72 kg/h 2 kg/h

8

Solids

0.7 kg/h

8

Wastewater

18.36 kg/h

8

Glycerine Methanol Impurities

10.3 kg/h 1.72 kg/h 1.58 kg/h

9

Oil

32.5 kg/h

9

Oil Water Water Refined Oil

96.67 kg/h 2 kg/h 2 kg/h 96.67 kg/h

9

Esters Impurities Water Esters Water Impurities Wastewater Esters Water Water Esters

100 kg/h 0.42 kg/h 20 kg/h 100 kg/h 20 kg/h 0.42 kg/h 18.42 kg/h 100 kg/h 2 kg/h 2 kg/h 100 kg/h

10 11

97 kg/h 20 kg/h

10 11

12 13 14 15

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Proc. 1

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Table 4 – Engines performance. Scenario

1

2

3

Engine electric output (kW) Electric efficiency (%) (Altin et al., 2001) Thermal efficiency (%) Engine lifetime (h) Abatement system

100 30.9 37.3 15000 Cat. ox.

1600 30.9 37.3 30000 SCR Denox + Cat. ox.

1600 33.5 37.3 60000 SCR Denox + Cat. ox.

Major pollutants concentration in dirty flue gases NOx (g/N m3 ) CO (g/N m3 ) Cx Hy (g/N m3 ) PM (g/N m3 ) O2,ref. (%)

2.85 0.30 0.15 0.15 5

2.85 0.17 0.115 0.13 5

2.51 0.134 0.098 0.111 5

Abatement efficiencies for major pollutants NOx (%) CO (%) Cx Hy (%) PM (%)

– 50 50 50

95 50 50 50

95 50 50 50

et al., 2008). So the consortium option seems suitable for this process. The produced biodiesel is then used in a CHP engine with a thermal input of about 5 MW. As in the previous scenario, the thermal and electrical outputs are destined to local networks and partially used in the refining and transesterification process.

4.2.

Biomass production

this plant. This process requires energy due to centrifuges, reactors impellers and cooling cycle. The thermal requirements of the process are oil and reactants heating up to reaction temperatures and storage of crude oil. Table 3 reports the material balance related to the streams represented in Fig. 2 on the basis of 100 kg/h of crude oil fed. The overall yield in refined oil from crude oil is nearly 97%. Despite this high conversion level, this process may produce wastewater for more than 20% of the feed.

The management of the sunflower cultivation in a 200 ha farm is common to each scenario. We assumed a 4-years rotation culture, so the surface destined to sunflower is 50 ha. The typical sunflower cultivation in Tuscany does not involve irrigation, so we considered not-irrigated land. A dry matter yield of 2500 kg/ha was considered, assuming a low intensive cultivation in Tuscany. The product is sunflower seeds with a content of 9% moisture. This low moisture level is obtained delaying the harvest until September. This solution avoids the need of drying the seeds before they are processed to extract oil. No green manure is taken into account for this cultivation.

The biodiesel production in Scenario 3 has refined oil and reactants as inputs. Table 2 reports the energetic requirements of this plant. Table 3 reports the material balance related to the streams represented in Fig. 3, referred to 100 kg/h of refined oil in input. The amount of biodiesel produced is almost equal to the amount of refined oil fed. However there are big concerns about side streams of the process, such as the methanol recovery and the wastewater production from esters washing.

4.3.

Biomass conversion

4.4.

Biomass utilization

4.3.1.

Scenario 1

4.4.1.

Scenario 1

In Scenario 1 we considered to process sunflower seeds with 9% of moisture. The process involves the mechanical pressing of the seeds to extract the oil and the oil filtration in order to remove suspended solids. Table 2 reports the energetic requirements of this plant. The overall energy consumption of the process is dominated by the mechanical pressing. The heat requirements of the process are due to temporary oil storage between pressing and filtration, and to oil storage before the utilization in the engine. Table 3 shows the material balance related to the streams represented in Fig. 1, on the basis of 100 kg/h of oilseed fed. The overall oil yield from oilseeds is nearly 33% and less than 1% of the seeds form a solid waste. Noteworthy about 52.5% of the seeds is transformed into pellets that can be sold as animal fodder. The economic sustainability of this process depends on the economic value of this by-product.

4.3.2.

Scenario 2

The production process in Scenario 2 has crude oil and reactants as inputs. Table 2 reports the energetic requirements of

4.3.3.

Scenario 3

In Scenario 1 the crude oil is burned in a CHP engine to produce electric power and heat (as hot water at 90 ◦ C). As far as the pollutant control is concerned only a catalytic oxidation of the flue gases is taken into account. As mentioned in Section 4.1.1, it is assumed that a 330 kW CHP engine produces non-significant emissions according to the Italian legislation, therefore it does not require any control system. Catalytic oxidation is considered as a standard available technology for this scenario. Table 4 reports the engine performance and emission factors of the engine. Emissions and engine lifetime were assumed on the basis of personal communications of a CHP diesel engine manufacturer, for this as well for the other two scenarios. The main problems associated to the low quality of the crude oil are a short engine lifetime (15,000 h) and high emission levels from combustion. For instance the concentration of NOx is higher than the limit reported in the Italian legislation (D.Lgs. 152/2006, P.V, All. I, P.3, 1.2). The presence of the catalytic oxidation is assumed to provide a 50% abatement efficiency of carbon monoxide, hydrocarbons and particulate matter (Heck, 2007).

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Table 5 – Comparison of performance indicators of the three scenarios. Performance indicator

Scenario 1 (CSO)

Scenario 2 (RSO)

Scenario 3 (SME)

Mass conversion efficiency

(kgfuel /kgseed ) (kgfuel /kgplant )

0.314 0.105

0.303 0.101

0.305 0.102

Waste production

Solid (kg/kgfuel ) Wastewater (kg/kgfuel )

0.022 –

0.036 0.242

0.052 0.426

Power requirements

(MJel /MJfuel )

0.022

0.023

0.027

Energy yield

Biofuel yield (MJ/ha yr) Electric yield (MJel /ha yr) Thermal yield (MJth /ha yr)

3.40 1.05 1.27

3.29 1.02 1.23

3.38 1.13 1.24

4.4.2.

Scenario 2

The refined oil produced in Scenario 2 is used in a 1600 kWel CHP engine. Again the CHP engine is assumed to produce electric power and hot water at 90 ◦ C. In this case the power installed does not allow considering these emissions as non-significant, so we considered, in addition to catalytic oxidation, a Selective Catalytic Reactor (SCR) fed with urea for NOx abatement. The management of an SCR unit is more complex than the simple catalytic oxidation unit, due to the dosage of reagents. However the oil refinery plant is a suitable scenario for this technology. Table 4 reports the performances and emission factors of the engine. The refined oil is assumed to ensure a longer engine lifetime (30,000 h) and lower emissions level, except for NOx , than the crude oil. The SCR unit is assumed to provide a 95% abatement of NOx and the catalytic oxidation is assumed to provide a 50% abatement efficiency of carbon monoxide, hydrocarbons, particulate matter, according to Heck (2007).

4.4.3.

Scenario 3

The sunflower methyl-ester (biodiesel) produced in Scenario 3 is used in a 1600 kWel CHP engine similar to that of Scenario 3. Again the CHP engine is assumed to produce electric power and hot water at 90 ◦ C and the engine is equipped with SCR and catalytic oxidation units. Table 4 reports the performances and emission factors of the engine. Biodiesel is assumed to ensure the longest engine lifetime (60,000 h) and the lowest emissions level, thank to its low viscosity and the absence of impurities. Moreover the electrical efficiency of the engine is higher than in the other scenarios because of the better combustion features of sunflower methyl-ester (Altin et al., 2001; Lapuerta et al., 2008; Ramadhas et al., 2004). The SCR unit is assumed to provide a 95% abatement of NOx and the catalytic oxidation is assumed to provide a 50% abatement of carbon monoxide, hydrocarbons, particulate matter.

5.

Analysis and comparison

The three processes were compared in terms of issues related to plant complexity and costs. The three scenarios were compared through performance indicators such as mass yields, waste production, power requirements, power conversion and the representations of the energetic flows of each process. Furthermore some specific environmental impacts are calculated according to the technique of life cycle assessment.

5.1.

Process comparison

Plant complexity and cost increase moving from the crude oil to the biodiesel production. However it is worthy to note some aspects which can indicate the contexts where each process

can be suitably located. Four aspects are taken into account: 1. 2. 3. 4.

process management; utilities; safety; wastes management.

(1) The crude oil production plants comprise exclusively mechanical operations (pressing, filtration). These operations can be readily performed on a farm site and they do not require the management of chemicals. The refined oil and biodiesel production plant comprise chemical operations (i.e. chemical reactions) and complex separation processes (distillation), which involve the management of chemicals and the control of variables such as temperatures, flow rates, pressures and pH. (2) The plant for crude oil production needs as input electrical power only and hot water to provide heat to the oil storage. The refined oil and the biodiesel processes require also steam to provide heat in the process, a vacuum system, compressed air, nitrogen and refrigeration loops. (3) The crude oil plant can be considered intrinsically safe, since no chemicals are involved in the production of crude oil. In the refining plant the management of acids and bases implies precautions and safety measures. Finally the biodiesel production is subjected to the ATEX regulation due to the use and storage of methanol, particular measures must be adopted in the management of this substance (for instance inert reaction environment). (4) Since the pellets obtained from the mechanical pressing are used as animal fodder, the only waste of crude oil production is the cake filter, a solid waste which can be easily disposed. On the other hand oil refining and biodiesel production generate wastewaters, which must be treated before being discharged or reused. Moreover in the biodiesel plant the glycerine phase produced from the transesterification must be distilled to recover methanol and to obtain a product which meets the requirements to be sold to glycerine refineries.

5.2.

Performance indicator

Table 5 reports some performance indicators of each biofuel scenarios. As far as the yield in kg of fuel per kg of seeds processed is concerned, Scenario 1 shows the highest value. The result is that the higher is the quality of the fuel, the lower is the conversion of seeds (and consequently of plants) into fuel. Scenario 3 is not an exception. The higher conversion of seeds in fuel than Scenario 2 is due to the fact that biodiesel is produced not from seeds only but also from methanol. Another consequence of the fuel upgrading is the

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Fig. 4 – Sankey energy flow diagrams for (a) Scenario 1, (b) Scenario 2, (c) Scenario 3.

Table 6 – Allocation criteria for LCA. Process

Products

Allocation factor

Allocation criteria

Sunflower seed, at oil mill

Crude sunflower oil Sunflower meal

77.2% 22.8%

Economic

Refined sunflower oil, at transesterification plant

Sunflower methyl-ester Crude glycerine

91.3% 8.7%

Economic

CSO, at cogeneration plant, 100 kWel

Electric Power Heat (Hot water 90 ◦ C)

82.2% 17.8%

Exergetic

RSO, at cogeneration plant, 1600 kWel

Electric Power Heat (Hot water 90 ◦ C)

82.2% 17.8%

Exergetic

SME, at cogeneration plant, 1600 kWel

Electric Power Heat (Hot water 90 ◦ C)

83.4% 16.6%

Exergetic

chemical engineering research and design 8 7 ( 2 0 0 9 ) 1191–1205

higher production of wastes (solid waste and wastewater) than the simple crude oil production. On the other hand Table 5 shows that the fuel upgrading involves a small increase in the power requirements per MJ of fuel produced compared to Scenario 1. The reason is that the power consumption of the mechanical pressing is large compared to the power requirements of the upgrading processes. Finally Table 5 compares the energetic yield of the three scenarios in terms of MJ per ha yr. The requirement of agricultural soil per year is similar for Scenario 1 and Scenario 3 if the comparison is based on the energetic content of the fuel, but as far as the conversion in electrical power is concerned the major fuel quality leads to a higher efficiency in the use of agricultural soil to energetic purposes. Fig. 4 represents the Sankey diagram with mass and energy flows referred to the production of 1 MJ of electrical energy for each considered scenario. The diagrams were drawn assuming the following lower heating value (LHV) for the different materials: • 27.2 MJ/kg for sunflower seeds (DM, dry matter) (Venturi and Venturi, 2003); • 39.6 MJ/kg for crude and refined sunflower oil (Altin et al., 2001); • 40.6 MJ/kg for sunflower methyl-ester (Altin et al., 2001); • 19.9 MJ/kg for methanol. Energy flows associated with mass fluxes were calculated by multiplying the material flow by its LHV. It can be observed that Scenario 1 and Scenario 2 exhibit similar Sankey diagrams, except for the loss of energy associated with waste by the refining process for Scenario 2. On the other hand Scenario 3 saves the highest amount of energy due to the higher engine efficiency, which in turn allows a minor requirement of raw materials (first of all the seeds) and a minor production of heat waste than the former scenarios.

5.3.

LCA

Life cycle assessment is a technique for assessing the environmental aspects associated with a product over its life cycle, i.e. from the extraction of raw materials to the final disposal. According to the ISO normative on LCA (ISO 14040:2006 and 14044:2006), it consists of four phases: goal definition and scoping, inventory analysis, impact assessment, and interpretation.

5.3.1.

1199

• Scenario 4. Electricity, at cogeneration unit 200 kWel , diesel. The functional unit chosen for referring balances and LCA results was 1 MJ of electrical energy produced by the CHP engine. Mass and energy balances were performed on every defined scenario, in order to compile the inventory, which contains all of the inputs and outputs of the processes. Life cycle assessment was then carried out with the software SimaPro 7.1.8 (PRé Consultants, Holland). The system boundaries include a series of process units: primarily the biomass production, conversion and utilization, which were directly designed and modelled; they also include processes like fertilizer and chemical reagent production, waste disposal, electric power and heat generation and delivery, material transport, infrastructure production, associated with non-elementary flows1 entering or leaving the main processes. The data about this last series of processes were taken from the database Ecoinvent Data v2.0 (Frischknecht et al., 2007), which is already implemented in Simapro. Different allocation criteria were used, which are summarized in Table 6. • For the co-production of crude sunflower oil (CSO) and sunflower meal at the oil mill, economic allocation was used, considering 900 D /t and 150 D /t, respectively, the price of the oil and of the meal in Italy (http://borsa.granariamilano.org, August 2008). • Economic allocation was performed even for the coproduction of sunflower methyl-ester (SME) and glycerine at the transesterification plant. The price of SME was assumed to be 1000 D /t (mean price of biodiesel), while for crude glycerine a value of 700 D /t was taken (http://www. icispricing.com/il shared/Samples/SubPage99.asp, August 2008). • Finally, electric power and heat (hot water at 90 ◦ C) were both produced by the cogeneration processes. In this instance allocation was executed on exergetic basis. The exergy flow is equal to the electricity flow, while for the ˙ of hot water at 363 K it can be calculated by heat flow (Q) the following expression, where T0 is 298 K and TH is 363 K.



T0 E˙ = Q˙ · 1 − TH



• In all the preceding cases, allocation for inputs and emissions of carbon dioxide from and to the air was done according to carbon balance for CO2 emissions. Any different approach would indeed lead to coarse mistakes in the evaluation of the environmental indicator “climate change”.

Goal definition and methodology

The goal of this LCA was to evaluate the environmental viability of the three scenarios described in paragraph 3 and compare them with a scenario of cogeneration that use fossil diesel as fuel. The defined scenarios were named as: • Scenario 1. Electricity, at cogeneration unit 100 kWel , CSO (crude sunflower oil), at farm. • Scenario 2. Electricity, at cogeneration unit 1600 kWel , RSO (refined sunflower oil), at refinery plant. • Scenario 3. Electricity, at cogeneration unit 1600 kWel , SME (sunflower methyl-ester), at transesterification plant. In addition, a fourth scenario was considered for comparison with the others:

Life cycle impact assessment was performed using the method Impact 2002+ (Jolliet et al., 2003). The damage assessment factors for the impact categories “aquatic acidification” and “aquatic eutrophication” (still in development by the author of the method) were set to 1.04 PDF2 m2 yr/kgSO2eq and

1 In LCA an elementary flow is: (1) Material or energy entering the system being studied, which has been drawn from the environment without previous human transformation; (2) Material or energy leaving the system being studied, which is discarded into the environment without subsequent human transformation. 2 PDF (potentially disappeared fraction) is calculated as PDF = 1 − POO, where POO (probability of occurrence) is the

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Table 7 – Weighting set for impact 2002+. Damage category

Weight

Human health Ecosystem quality Climate change Resources

250 200 300 250

Table 8 – Cultivation management data. Operation Harrowing Ploughing Fertilizing Weed and pest control Sowing Combine harvesting

Frequency (yr−1 ) 2 0.25 1 1 1 1

1.04 PDF m2 yr/kgPO4-Plim , respectively. The weighting set used is reported in Table 7.

5.3.2.

Data and hypotheses

The Ecoinvent process “Sunflower IP, at farm/CH U” is adopted and modified, according to the hypotheses mentioned in Section 3.2, to model the sunflower seeds production step and compile the inventory. In addiction to what we described in Section 3.2, we made other assumptions. We summarize below the major ones. • The land occupation (in kg/ha yr) was calculated assuming a dry matter yield of 2500 kg/ha (typical of cultivations with low intensification in Tuscany) and the whole year, because sunflower is an annual plant (Bonari et al., 1992; Venturi and Venturi, 2003). • The input “energy, gross calorific value, in biomass” was calculated by multiplying the dry matter content of the functional unit by the gross calorific value of the grains, which is 30.25 MJ/kgDM (Nemecek and Kägi, 2007, p. 39). • The uptake of CO2 by the vegetation was calculated using a factor of 2.34 kgCO2 /kgDM (Nemecek and Kägi, 2007, p. 39). • For the ground working operations we considered the steps and frequencies reported in Table 8, and multiplied these for the amount of land occupied by the cultivation of the functional unit. Ploughing is a very expensive and energy-consuming operation, which moreover leads to ground deterioration in the long-term. So we considered that ploughing was carried out once every four years, while a simple harrowing was executed twice a year. • As far as soil fertilizing is concerned we took into account urea and triple super-phosphate, respectively, as nitrogen and phosphorus suppliers, while no potassium were provided, as is usual in Tuscany if the cultivation is rotated every four years. We calculated the amount of fertilizers fed using the input factors reported in Bonari et al. (1992), corrected in order to consider the difference in dry-matter yield (63.5 kg/ha of N and 32.5 kg/ha of P2 O5 ). • For the sowing we considered an input of seeds of 4 kg/ha. • For the airborne emissions deriving from the cultivation step:

probability that a plant species still exists in the considered area after the transformation involved by the assessed scenario (Goedkoop & Spriensma, 2001).

Fig. 5 – Comparison of resources consumption of the four scenarios. - We used for NH3 the emission factors for mineral fertilizers given by Asman (1992); - Fossil CO2 is emitted following the degradation of urea (produced from fossil resources). A factor of 1.57 (kg of CO2 emitted for kg of N-urea fed) was used on the basis of the mass balance; - Emissions of N2 O were calculated according to the model described in Nemecek and Kägi (2007, pp. 35–36). The nitrogen contained in the crop residues was fixed at 50 kg/ha, which is a mean value for the selected yield; - Emission of NOx were estimated applying a multiplicative factor of 0.21 to the emissions of dinitrogen monoxide, according to Nemecek and Kägi (2007, p. 36). • For the waterborne emission deriving from the cultivation step: - Nitrate leaching to groundwater, phosphorus and phosphate leaching to river and groundwater were calculated by the models described in Nemecek and Kägi (2007, pp. 29–35). The soil depth was fixed at 2 m, the soil erosion at 1 t/ha yr and the P content of soil surface at 20 ppm. - Heavy metal emissions in river and in groundwater of the original inventory “Sunflower IP, at farm/CH U” were corrected by considering the different amount and type of fertilizers and seeds fed, according to Nemecek and Kägi (2007, pp. 37–39). The main assumptions for the other processes involved are described in paragraph 3. Values from similar processes of the Ecoinvent 2.0 database were used wherever not otherwise specified. Scenario 4 is completely taken by Ecoinvent (process “Electricity, at cogen. 200 kWel diesel SCR, allocation exergy/CH U” retrievable in the section Energy/Cogeneration/Oil).

5.3.3.

Life cycle inventory

The comparative analysis of the life cycle inventory (LCI) of the four scenarios gives a first indication of the processes sustainability. All results refer to the production of 1 MJ of electrical energy.

5.3.3.1. Resources. Fig. 5 reports a comparison of the major resources consumption by the four scenarios. The five resources taken into account are crude oil, coal, natural gas, iron and water. As far as the crude oil consumption is concerned, Scenario 4 exhibits the highest value due to the direct use of this resource in the production of the diesel fuel. The scenarios related to biofuels require about 25% of the crude oil consumed

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Fig. 6 – Comparison of major airborne emissions of the four scenarios. by Scenario 4. This consumption is mainly due to heat production needed for oil storage. Noteworthy the integration of heat produced by CHP engine in Scenario 2 and Scenario 3 leads to minor demand of crude oil respect to Scenario 1, which does not involve heat recovery. The coal consumption is almost equal for the three biofuel scenarios and it is nearly a double of the requirement of Scenario 4. The mechanical pressing of oilseeds at a small scale leads to a high electrical demand. As a consequence the biofuels scenarios show higher coal consumption than Scenario 4. The utilization of natural gas is mainly due to urea (used both as fertilizer and reactant in the SCR unit) and methanol production, which both involve methane steam reforming to produce synthesis gas. Biofuels have thus a higher demand than Scenario 4 because of the use of urea in the biomass production. Moreover Scenario 3 (SME) exhibits the highest value because of the use of methanol in the methyl-ester production. The iron consumption can be considered an indicator of the materials requirement due to equipment and infrastructure

fabrication. The major need of this resource is in Scenario 1 (CSO) and it decreases with the enhancement of the quality of the fuel. This is due to the lower engine lifetime associated with a poor fuel quality. The last resource considered is the water demand. Noteworthy no water is needed for sunflower cultivation. This value, which is mainly associated with “upstream” energy and chemicals production processes, overcomes water consumption by crude oil upgrading processes. Therefore water demand does not change much among the analysed scenarios.

5.3.3.2. Airborne emissions. The major airborne emissions from the four scenarios are compared in Fig. 6. Emissions can be classified according to the major sources that originate them. Several compounds (CO, CO2 , NOx , PAH, Particulates total, SO2 , total hydrocarbons) are mainly produced by combustion, both directly in the considered CHP unit and during other “upstream” energy production processes. NH3 and N2 O are mainly due to the use of fertilizers on agricultural soil. Finally CH4 emissions derive from several processes which contribute to the scenario, including methanol and fer-

Fig. 7 – Comparison of major waterborne emissions of the four scenarios.

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Fig. 8 – Weighted scores for impact categories, method Impact 2002+. tilizers production, crude oil extraction, natural gas transport in pipeline. The higher amount of CH4 emission of Scenario 2 and 3 respect to Scenario 1 is due to the higher amount of solid waste produced, which has to be landfilled, while methane emissions for Scenario 4 arise mainly from natural gas venting during oil extraction. The emissions related to combustion show a similar trend among the three biofuels scenarios: the emission level decreases from Scenario 1 (CSO) to Scenario 3 (SME). The reason is that higher emission factors are associated to a poor fuel quality. It is worthy to note that the NOx emission from Scenario 1 (CSO) is pretty much higher than the others because of the absence of the SCR unit. The use of biofuels improves the abatement of CO, CO2 and SO2 respect to diesel, while Scenario 4 exhibit lower NOx , PAH, Particulates and Hydrocarbons emissions. It is important to observe that, for instance, the combustion of biodiesel leads to smaller emissions of all the aforementioned pollutants but NOx (Altin et al., 2001). Therefore the performances of Scenario 3 are worse than those of Scenario 4 because this emission must be ascribed to “upstream” processes.

Scenario2 (RSO) exhibits the highest NH3 and N2 O emissions, followed by Scenario 1 and Scenario 3. The lower efficiency of the whole process in producing 1 MJ of electricity (as mentioned in Section 4.1) leads to higher seeds consumption and use of fertilizers and therefore to higher emissions of such nitrogen compounds.

5.3.3.3. Waterborne emissions. Fig. 7 shows the major waterborne emissions from the four scenarios. There are three major sources for these pollutants: the use of fertilizers on the soil (NO3 , PO4 , P, Cr, Ni), the disposal (landfilling) of solid wastes (Cd, Cu, Pb, Hg, Ni, Zn), and the production of triple-super-phosphate (Cd, Hg). As far as the emissions produced from the use of fertilizers on soil are concerned a clear trend related to the overall efficiency of the scenario can be identified. Thus Scenario 2 (RSO) exhibits the higher emissions, followed by Scenario 1 and Scenario 3. Obviously such emissions cannot be found in Scenario 4. The trend is very similar for the emissions related to waste disposal, in this case Scenario 1 (CSO) exhibits

Fig. 9 – Percentage comparison for major impact categories, method Impact 2002+.

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Table 9 – LCIA weighted scores (E+03) for damage categories, method Impact 2002+. Damage category

Scenario 1 (CSO)

2 (RSO)

3 (SME)

4 (Diesel)

Human health Ecosystem quality Climate change Resources

12.8 11.1 3.3 2.2

5.7 11.5 3.2 2.0

4.9 9.7 2.9 2.3

1.9 0.2 6.0 4.9

Total

29.4

22.4

19.7

13.0

very low emission values due to the small production of wastes.

5.3.4.

Life cycle impact assessment

As previously outlined, the life cycle impact assessment (LCIA) was carried out using the method Impact 2002+. Fig. 8 shows the results of the weighting step of the LCIA for each scenario, based on 1 MJ of electrical energy production. The scores for all categories are non-dimensional. It can be noted that only seven categories affect significantly the total environmental impact of the four scenarios: “non-carcinogens”, “respiratory inorganics”, “terrestrial eco-toxicity”, “terrestrial acidification/nutrification”, “land occupation”, “global warming”, “non-renewable energy”. The impact in these categories is then better compared in Fig. 9, in terms of percentage of the highest score in each category. The impact in the category “non-carcinogen” is mainly due to the fertilizers production and utilization and to the extraction and refining of metals in upstream processes. Therefore the three biofuels scenarios have a similar impact in this category, which is largely higher respect to Scenario 4. The pollution from respiratory inorganic compounds and terrestrial acidification are dominated by the emission of NOx already mentioned in paragraph 4.2.3, thus Scenario 1 shows the worst performance in these categories, followed by Scenario 2 and Scenario 3. As far as “terrestrial eco-toxicity” and “land occupation” are concerned Scenario 2 exhibits the worst performance followed by Scenario 1 and Scenario 3. This trend is due to minor overall efficiency, which leads to a higher use of soil and fertilizers. Scenario 1 is the biofuel scenario with the worst performance in “global warming”, followed in order by Scenario 2 and Scenario 3, as a consequence of the thermal requirement (oil storage) within the process, while Scenario 3 has the highest demand of “nonrenewable energy” (due to the methanol production). Generally speaking, the production and use of biofuels give better results in term of contribution to the global warming and use of non-renewable sources than Scenario 4. However the diesel production and use show better performances in terms of land occupation, terrestrial pollution and production of respiratory inorganics. In Table 9 we report the results of the weighting step for the four damage categories and the global impact indicator of the method Impact 2002+. It is not recommendable to use these results to compare directly the use of fossil diesel with the use of biofuels: the LCIA method and the weighting step chosen affect the aggregated results in a definitive way, and above all scenarios are too much different to be compared by a single indicator. For instance, Scenario 4 certainly does not contain an agricultural step, so that the impact category “Land occupation”, which has a relative important weight in the method, has an irrelevant score. The aggregated results can be more properly used to compare in a direct and simple way similar scenarios, like sce-

Fig. 10 – Process contribution to global environmental impact, method Impact 2002+. narios 1, 2, and 3. Among these, Scenario 3 turns out to be the less impacting in all of the damage categories but “Resources”, due to the use of methanol of fossil origin. Moreover, Scenario 3 is the more environmentally convenient even according to the global indicator.

5.3.5.

Process contribution

Fig. 10 shows the percentage contribution to global environmental impact of the main process units for the biofuels scenarios. The absolute contributions are also reported in the labels in order to compare different scenarios. The sunflower seed cultivation impact varies from 55% to 75% of the total, with an additional 5–10% arising from the industrial production of fertilizers, Scenario 2 exhibits the greatest value. Among the biomass transformation processes, pressing requires a noticeable amount of energy, resulting in a relatively high impact (5–8%). It is worthy to note that only a slight impact arises from the processes of fuel upgrading, namely oil refining, accounting for about 2%, and the transesterification processes, accounting for 5%, including 3.5% for methanol production. On the other hand the upgrading itself, along with the use of SCR, leads to a noticeable lower impact in the combustion step, which goes from about 30% in Scenario 1 to about 5% of Scenario 3. As far as equipment and infrastructure fabrication is concerned, we observe that chemical plants such as the transesterification plant, which require a large amount of material and energy to be build, have though a very long lifetime (about 50 years). As a consequence they do not significantly affect the impact referred to the functional unit. On the contrary, CHP engines have limited lifetime and the impact of their production can be significant. This is in agreement with the fact that the impact of Scenario 1 due to equipment production is higher than those of Scenarios 2 and 3. The former, using a low-quality fuel, considers an engine lifetime that is, respectively, 50% and 25% of the engine lifetime in Scenarios 2 and 3. It can be noted that the process of transport by truck of crude oil from farms to the transformation plant in Scenario 2 and Scenario 3 has a negligible influence on global environmental impact.

5.3.6.

Sensitivity analysis

In order to evaluate how the assumptions made in the scenario definition step and in the calculations affect the final results, a sensitivity analysis was performed, studying how the single score associated with Scenario 1, 2, 3, change when we vary parameters with the highest uncertainties. The first parameter investigated was the mean distance between farms and the biorefinery plant, which was changed

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Table 10 – Single impact indicator × 103 (SI) and variation respect to the base case (between brackets) varying some main parameters. Scenario

1 (CSO)

2 (RSO)

3 (SME)

SI (Base case)

294

224

197

Mean transport distance 200 km 1000 km

Base case 50 km 294 294

228 (+2.47%) 251 (+11.2%)

201 (+2.36%) 220 (+10.8%)

Engine lifetime 60,000 h

Base case 15,000 h 287 (−2.4%)

Base case 30,000 h 221 (−1.3%)

Base case 60,000 h 197

Meal price 75 D /t (−50%) 300 D /t (+100%)

Base case 150 D /t 318 (+8.2%) 259 (−11.9%)

249 (+10%) 188 (−16.1%)

218 (+10.7%) 167 (−15.2%)

Glycerine price 0

Base case 700 D /t 294

224

215 (+9.1%)

Engine emissions +20% −20%

311 (+5.8%) 277 (−5.8%)

226 (+0.8%) 222 (−0.8%)

199 (+1%) 196 (−0.5%)

SCR in Scenario 1

220 (−25%)

224

197

from 50 km in the base case to 200 km or 1000 km (see Table 10). Obviously the global impact increases with increasing distance for Scenario 2 and 3, while it remains constant for Scenario 1, since no transport step is involved. However, until 200 km the percentage impact of the oil transport is poor, and even for 1000 km Scenario 2 and Scenario 3 still have far better environmental performances than Scenario 1. Engine lifetime was considered to vary strongly with fuel quality (see Table 4). In the sensitivity analysis it was set at 60,000 h for all the scenarios. Noteworthy even in this case the global impact for Scenario 2 and 3 reduces only of 1–2%. The price of by-products such as sunflower meal and glycerine considered in the LCA is another important parameter, since it can be subjected to significant market variation. Considering a large fluctuation in meal price (−50%, +100%) we found that LCA results change considerably, but in a similar way for all the three scenarios. About the glycerine, which is a by-product of sunflower methyl-ester production, we considered the situation in which its value turns to zero (representing the saturation of the market). As a consequence, the impact of the third scenario grows of about 10%, and become really similar to that of Scenario 2. Noteworthy the variation of these by-products prices influence strongly the economical sustainability of the biofuel production processes. Finally, the analysis focused on the biofuel combustion step, and we tried both to increase and to reduce the emission level by 20%. Only slight changes resulted in the global impact of scenarios 2 and 3, while a bigger change turned out for Scenario 1. This result is related to the absence of an NOx abatement system only for this scenario; this point was further assessed considering an SCR unit even for Scenario 1: a reduction of 25% in the global impact was obtained, and Scenario 1 became better than Scenario 2. We must remember, however, that the conduction of an SCR for a really small engine (100 kWel ) in a rural context is unlikely, mainly due to the necessity of an urea or ammonia feeding system. However, several studies are currently focusing on the application of urea-SCR even for automotive engines, and in the next future SCR could become a standard technology even for small-size engine (Gabrielsson, 2004).

6.

Conclusions

Scenarios involving upgrading of crude sunflower oil (Scenarios 2 and 3) require complex plants and the management of dangerous materials, and lead to the production of considerable amounts of wastewater. These in turn need greater plant size, more complex organization (farm cooperatives), higher capital and operational costs than the simple mechanical operation associated with crude oil production (Scenario 1). On the other hand the use of low-quality fuels in internal combustion engines can lead to short engine lifetime and high pollutant emissions. So the trade-off is between the fuel production cost and complexity and the engine performance. In the LCA the three defined biofuel scenarios were compared with the use in CHP engines of fossil diesel. LCIA method used was Impact 2002+. Main results were: • The use of all the three types of biofuel allows a reduction of fossil CO2 emissions of 400–460 g/MJ of produced electricity, i.e. about 60%, respect to diesel (Scenario 4); a connected reduction of about 60% in the category “fossil fuels” was recorded; • On the contrary all biofuel scenarios have a higher impact than diesel in the categories “respiratory inorganics”, “terrestrial ecotoxicity”, and “terrestrial acidification/nutrification”; this is not due to lower combustion performance, but to polluting emissions deriving from seed cultivation step; • As shown by the analysis of process contributions, the most impacting step in producing all the three types of biofuels is the seed cultivation, as found also by Bernesson et al. (2004) and Stephenson et al. (2008). In the present work we found it is responsible for 60–80% of the global impact; • Oil transport from farms to transformation plant has a non-significant weight on global emission, even if we considered relatively long mean distances (>200 km); this result is in agreement with the findings of another recent work (Stephenson et al., 2008); • Influence on environmental impact of biofuels upgrading processes (refining and transesterification), as well as that of oil transport, is low compared to seed cultivation; on the

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other hand fuel upgrading allows a significant reduction in polluting emission during combustion; as a consequence LCA results show that Scenario 3 (biodiesel) is the most sustainable biofuel scenario, because of the high efficiency of fuel utilization (minimum seeds requirements for produced energy unit) and high fuel quality (minimum emission respect to oil and even to fossil diesel). Further benefits could be obtained by considering as the reagent in the transesterification reaction bio-methanol (biomass gasification plus Fisher-Tropsch) or bio-ethanol (fermentation), so reducing fossil carbon dioxide emissions due to Scenario 3.

Acknowledgement The authors thank Dr. Giorgio Ragaglini for the precious information about sunflower cultivation.

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