Greenhouse gas emissions and energy balance of palm oil biofuel

Renewable Energy 35 (2010) 2552e2561

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Greenhouse gas emissions and energy balance of palm oil biofuel Simone Pereira de Souza a, Sergio Pacca a, *, Márcio Turra de Ávila b, José Luiz B. Borges b a b

Graduate Program on Environmental Engineering Science, School of Engineering of São Carlos, University of São Paulo, Rua Arlindo Bettio, 1000 Sao Paulo, Brazil Brazilian Agricultural Research Corporation (Embrapa e Soja), Brazil

a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 September 2009 Accepted 23 March 2010 Available online 7 May 2010

The search for alternatives to fossil fuels is boosting interest in biodiesel production. Among the crops used to produce biodiesel, palm trees stand out due to their high productivity and positive energy balance. This work assesses life cycle emissions and the energy balance of biodiesel production from palm oil in Brazil. The results are compared through a meta-analysis to previous published studies: Wood and Corley (1991) [Wood BJ, Corley RH. The energy balance of oil palm cultivation. In: PORIM intl. palm oil conference e agriculture; 1991.], Malaysia; Yusoff and Hansen (2005) [Yusoff S, Hansen SB. Feasibility study of performing an life cycle assessment on crude palm oil production in Malaysia. International Journal of Life Cycle Assessment 2007;12:50e8], Malaysia; Angarita et al. (2009) [Angarita EE, Lora EE, Costa RE, Torres EA. The energy balance in the palm oil-derived methyl ester (PME) life cycle for the cases in Brazil and Colombia. Renewable Energy 2009;34:2905e13], Colombia; Pleanjai and Gheewala (2009) [Pleanjai S, Gheewala SH. Full chain energy analysis of biodiesel production from palm oil in Thailand. Applied Energy 2009;86:S209e14], Thailand; and Yee et al. (2009) [Yee KF, Tan KT, Abdullah AZ, Lee KT. Life cycle assessment of palm biodiesel: revealing facts and benefits for sustainability. Applied Energy 2009;86:S189e96], Malaysia. In our study, data for the agricultural phase, transport, and energy content of the products and co-products were obtained from previous assessments done in Brazil. The energy intensities and greenhouse gas emission factors were obtained from the Simapro 7.1.8. software and other authors. These factors were applied to the inputs and outputs listed in the selected studies to render them comparable. The energy balance for our study was 1:5.37. In comparison the range for the other studies is between 1:3.40 and 1:7.78. Life cycle emissions determined in our assessment resulted in 1437 kg CO2e/ha, while our analysis based on the information provided by other authors resulted in 2406 kg CO2e/ha, on average. The Angarita et al. (2009) [Angarita EE, Lora EE, Costa RE, Torres EA. The energy balance in the palm oil-derived methyl ester (PME) life cycle for the cases in Brazil and Colombia. Renewable Energy 2009;34:2905e13] study does not report emissions. When compared to diesel on a energy basis, avoided emissions due to the use of biodiesel account for 80 g CO2e/MJ. Thus, avoided life cycle emissions associated with the use of biodiesel yield a net reduction of greenhouse gas emissions. We also assessed the carbon balance between a palm tree plantation, including displaced emissions from diesel, and a natural ecosystem. Considering the carbon balance outcome plus life cycle emissions the payback time for a tropical forest is 39 years. The result published by Gibbs et al. (2008) [Gibbs HK, Johnston M, Foley JA, Holloway T, Monfreda C, Ramankutty N, et al., Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology. Environmental Research Letters 2008;3:10], which ignores life cycle emissions, determined a payback range for biodiesel production between 30 and 120 years. Crown Copyright Ó 2010 Published by Elsevier Ltd. All rights reserved.

Keywords: Palm biodiesel Energy balance GHG emission Carbon stock Land use change

1. Introduction The use of biofuels has been supported by various nations through plans and goals calling for greater shares of these fuels and other renewable energy sources [7].

* Corresponding author. E-mail address: [email protected] (S. Pacca).

The energy balance, the reduction potential of greenhouse gas (GHG) emissions, and the biomass yield, which is a proxy for the conversion efficiency of solar radiation per hectare, are important factors that need to be considered in biofuels assessments. In addition, the effect on carbon stocks, because of direct and indirect land use change, has been discussed in recent articles focusing on biofuels’ GHG emission reduction potential [8e11]. These studies have demonstrated that the type of vegetation in place before the land is converted to a biofuel plantation exerts

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S.P. de Souza et al. / Renewable Energy 35 (2010) 2552e2561

a significant effect on the ecosystem’s carbon stock and overall biofuel GHG budget. Usually, the carbon stock in degraded soils is low (1e2 tC/ha) [11,12]. However, the carbon stock of a degraded soil could be enhanced by the decomposition of carbon sequestered by palm trees. Thus, the production of biodiesel from palm trees in degraded soils may add carbon to the soil and reduce overall GHG emissions. Fargione et al. [10] assessed a palm tree plantation directly displacing a tropical forest ecosystem and a peatland, and they found that the carbon payback time was respectively 86 and 423 years. Such difference is explained because of the high carbon stock of peatland. In contrast to recent terrestrial carbon budget studies, the evaluation of energy inputs and outputs in the production of biofuels is not new. However, few studies have dealt with the energy balance of palm oil biodiesel. Nevertheless, because of its high yields, the use of palm oil as a biodiesel source is increasing [13]. Based on this brief discussion, the objective of this work is identifying and evaluating the net GHG emissions and the energy balance of palm oil biodiesel in Brazil and compare the results with studies carried out in other countries. 2. Palm oil biofuel The production of palm oil and palm kernel oil accounts for 36% of the world’s vegetable oil production [14]. In comparison, 28% of the vegetable oil comes from soybeans. Malaysia and Indonesia are responsible for 86% of the world’s palm oil production [14]. The largest producer in the American continent is Colombia, responsible for 62% of the continental production. In Brazil, the largest production is located in Para State, in the Amazonian region. This State is responsible for 93% of the palm oil produced in the country [13,15]. Although it is possible to use both fruit’s oil and kernel’s oil to produce biodiesel, the biodiesel production in Brazil is based on fatty acids extracted from palm oil fruit through the refining process, adopted by the Agropalma Group in Tailandia, Para State [16]. Fresh fruit bunches (FFB) are composed of 20e21% of palm oil and 1.7% of palm kernel oil. In addition other co-products are produced: 3.5% of kernel oil cake, 22e23% of empty fruit bunches, 12e15% fibers, 5e7% of shells, and 50% of palm oil mill effluent (POME) [17,18]. Empty fruit bunches (EFB), which are abundant, may be used to produce steam and power, and the remaining ashes are used as fertilizers [12]. However, usually EFBs are applied as organic fertilizer [19]. The kernel cake is a co-product of the kernel oil extraction, which is used as animal feed. Shells and fibers are usually used as fuel in cogeneration schemes. Thus, palm oil refining is self sufficient with respect to energy consumption, and the use of fossil inputs and their respective GHG emissions is negligible [20,21]. The POME, which is rich in organic matter, may be used in anaerobic digesters to produce methane (CH4), which is a fuel. The remaining sludge may be used as fertilizer, and therefore, reduces the need for inorganic fertilizers [12]. On average, one metric ton of FFB yields 14 m3 of POME or 25 kWh of electricity [22,23]. 3. Methods A Life Cycle Assessment (LCA) method according to ISO 14044/ 2006 was used in this study to determine the energy balance and GHG emissions of biodiesel from palm oil. Our results are part of a meta-analysis, in which they are compared to results of three other studies on palm oil biodiesel. Other studies such as ERG Biofuel Analysis Meta-Model (EBAMM) [24] have used meta-analysis to compare biofuels production processes.

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3.1. Meta-analysis We adjusted part of the data presented by other authors as part of the meta-analysis. Thus, the use of co-products for power production, the production of organic fertilizers, and the allocation procedures were normalized for the other studies based on the scope of our study. Angarita et al. [3] determined the energy balance of the palm oil biodiesel produced in Colombia and Brazil based on different scenarios. We adopted the average for Colombia’s conventional biodiesel production in our meta-analysis. Because the study by Angarita et al. [3] lacks detailed information on inputs for the agricultural phase, it was not possible to verify either the GHG emission nor the reduction in fertilizers use due to the use of EFB. We considered that fibers and shells were used as fuel. The mass of each co-product (glycerin, palm kernel cake, and crude kernel oil) was not disclosed by the studies in our meta-analysis. Therefore, for mass allocation we applied the same values as of our study. For consistency reasons, the inputs for machinery and building were excluded of the analysis. In addition, the values for labor and construction were not considered either. Finally, the energy content of surplus shells was converted into electricity through steam turbines. Yusoff and Hansen [2] present a life cycle assessment of palm oil in Malaysia. The study comprises the use of fibers and shells for steam production, the use of POME for biogas production, the use of EFB and POME as organic fertilizers, and mechanical harvesting. Because the study does not present information on the industrial phase, we have completed the analysis with data from other sources [25,26], as shown in Table 1. Because the accessed studies do not report life cycle energy and emission factors for pesticides, we adopted the average of insecticides and herbicides from Simapro 7.1.8 software. The energy content of palm kernel cake and palm kernel oil was allocated based on its mass.

Table 1 Adopted values for this study. Variable

Application Energy and yield intensity (kg/ha yr) (MJ/kg)

Nitrogen (Production) 41.20 Nitrogen (Use) Phosphorus 80.37 Potassium 147.76 Magnesium 11.54 Herbicide 2.50 Insecticide 1.20 Boron 5.72 Methanol 396 Calalyst (NaOH) 24 Diesel 74.4 Electricity (Brazilian mix) e 143 Palm densitya 180 Palm seedsb Pueraria phaseoloides 5 c Biodiesel 3963 Fresh fruit bunch 20,350 Crude palm oil 4172 Crude kernel oil 346 Palm kernel cake 712 Empty fruit bunch 4579 Fiber 2747 Shell 1221 d 14 Biogas *kg CO2e/kWh (Brazilian mix). a Tree/ha. b unit/ha life time; MJ/ha. c Conversion rate: 0.95. d m3/t FFB; kWh/m3.

Source Emission (kg CO2e/kg)

67.60

3.26 18.60 34.70 2.01 9.64 0.51 2.85 1.05 407.00 15.50 405.00 13.70 308.25 1.60 37.60 0.79 33.13 1.20 54.10 3.90 e 0.07* e e 18.40 e 5.52 e 37.13 e e e e e Allocated e Allocated e Fertilizer e 7.70 e 11.91 e 1.80 e

[27,38,45] [27,46,47] [16,38,41,42]

[48]

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Wood and Corley [1] also evaluate the energy balance of palm oil in Malaysia. Fibers, shells and POME are combusted to produce power, which fuels the industrial process. The EFB are used as organic fertilizer and the nutrient content of this material was presented by these authors. Harvesting is mechanical and energy consumption due to transport and irrigation is considered. The energy content of inputs and outputs is disclosed in the paper. Energy consumption and oil extraction efficiencies of the industrial phase [25] and other inputs such as methanol and catalysts [27], are based on previous studies. Pleanjai and Gheewala [4] have assessed the palm oil biodiesel chain in Thailand. Fibers are utilized for cogeneration (stem and electricity). In addition, our meta-analysis considered electricity production using POME. In their study, the EFB are used as fertilizer. Harvesting is manual and fossil fuels are consumed only for transportation of FFB between the field and the refinery. They do not take into account labor, equipment, and constructions as inputs. The use of insecticides rodenticides, magnesium, and Boron are not considered in their study. Yee et al. [5] assessed the life cycle of palm oil biodiesel in Malaysia. Fibers and shells are used for cogeneration (steam and electricity). In addition, our meta-analysis considered electricity production using POME. In their study, the EFB are used as fertilizer. Their study takes into account diesel for traction and fertilizers transport. They do not take into account labor, equipment, and constructions as inputs. The use of pesticides, magnesium, and Boron is not considered in their study either. 3.2. Life cycle assessment In this work we adopted the life cycle assessment method according to ISO 14044/2006, which is recommended to evaluate the potential impact of products and processes. However, the LCA norms are outdated and their application does not result in good biofuels LCA because land use change effects over time are not necessarily included in the assessments. Moreover, several biofuels LCA present conflicting results because of scope differences and other issues that challenge the comparison between studies [28]. This highlights the need for a revised LCA method for biofuels [29], which also facilitates the proposition of certification schemes and public policies. 3.2.1. Goal and scope The objectives of this work are identifying and evaluating the net GHG emissions and the energy balance of palm oil biodiesel in Brazil and compare the results with studies carried out in other countries: Wood and Corley [1], Malaysia; Yusoff and Hansen [2], Malaysia; Angarita et al. [3], Colombia; Pleanjai and Gheewala [4], Thailand; and Yee et al. [5], Malaysia. The study is based on a “seedto-factory gate” approach and uses the methodology described by the ISO 14044:2006. Therefore, the study includes the nursery stage, the production and use of fertilizers and pesticides, harvesting, transport, oil extraction, transesterification, and finally, the combustion of neat biodiesel. We have not assessed energy consumption for biodiesel distribution because most of the biodiesel is locally consumed and displaces diesel, and still, there is no special infrastructure in place for biodiesel distribution in Brazil. Most of the biodiesel commercialized in Brazil is mixed with diesel in the oil refinery and sold at the gas station. This study’s LCA considers palm oil biodiesel, and its co-products such as kernel oil, kernel cake, fibers, shells, empty fruit bunches, glycerin, and POME. The latter is used to produce biogas. In this study, the functional unit (FU) is one hectare of palm trees, and the reference flux is 4.17 tons of crude palm oil, or 4 tons of

biodiesel. We used three sustainability metrics in our evaluation: life cycle energy balance, life cycle GHG emissions, and carbon payback time. The scope of this work encloses biodiesel production and the utilization of its co-products (fibers, shells, and POME) for power production so that the production units are self sustained in terms of energy consumption. Besides that, EFB are used as organic fertilizer, reducing the fossil fuel input in the agricultural phase. Fertilizer application rates are based on low fertility soils and the utilization of green manure (Pueraria phaseoloides). The application rate of pesticides is based on values observed by the Brazilian Agricultural Research Corporation (EMBRAPA) in Western Amazonia [34]. When dealing with multiple products that result from a single process, it is necessary to allocate the inventoried inputs and outputs [30]. Allocation is usually proportional to market value, mass or energy content of each co-product. In our analysis, inputs and outputs were allocated to kernel oil and kernel cake on a mass basis, considering the whole fresh bunch. The total mass of these 2 co-products corresponds to 5.2% of the bunch mass. For glycerin the allocation corresponds to 7.9% (mass basis) of the products of the transesterification phase (biodiesel and glycerin). The remaining co-products were not allocated because they are consumed during the biodiesel production process. For Wood and Corley [1] and Yusoff and Hansen [2], the total mass of kernel oil and kernel cake corresponds to 8.2% and 12.1% (mass basis) of the bunch mass, respectively. In the meta-analysis we have applied the glycerin allocation share of our case study to Wood and Corley data [1]. In the case of Pleanjai and Gheewala [4] and Yee et al. [5], the allocation corresponds to 5.4% and 5.2% of the total FFB mass. Glycerin was allocated to the transesterification phase that corresponds respectively to 15% and 10% of the resulting total mass of this phase. Fertilizer, pesticides and diesel use rates and conversions were based on data collected from various sources (Table 1). Because various GHG emission factors are based in international studies, it is important highlighting that GHG LCA emissions of these inputs could be overestimated for the reason that 73.4% of the Brazilian electricity comes from hydropower, which is a renewable energy source [31]. Throughout the calculations we adopted a conversion efficiency of 95% (mass basis) for palm oil into biodiesel [32] and biodiesel density equals 0.92 kg/l [33] and the average yield is 20.35 t fresh bunches/ha yr [16]. For the remained studies we adopted the same conversion efficiency, except for Yee et al. [5] because a 0.99% efficiency is explicit in this study. All values used in our metaanalysis are listed in Table 1. 3.3. Life cycle energy balance Energy quantification was based on the input inventory for the nursery, agricultural phase (nitrogen, phosphorous, potassium, and manganese), palm seed’s production, and green manure’s seed production. These mass values were further multiplied by their respective energy and GHG intensities. In addition we also determined the energy input for transport. The energy demand for the industrial phase was reduced in half because the process is powered by the combustion of co-products, cogeneration, and uses methane from POME. We used data from Embrapa [18,34] and Agropalma [16] to determine the amount of palm tree seeds, green manure seeds, fertilizer and pesticide rates. All values emulate a plantation in the Amazon. Based on the local climate, irrigation is required only at the plant nursery stage. Energy intensity of 1 m3 of water is 0.01 MJ/l of water [35].

S.P. de Souza et al. / Renewable Energy 35 (2010) 2552e2561

These data plus energy intensities presented in Table 1 were used to determine the energy required per hectare of palm trees, including transportation needs between the field and the processing facility. Except for Yusoff and Hansen [2] all the other studies presented their own energy input values. We have assumed a 10 metric ton capacity truck with a 5 km/l mileage unloaded and a 2.5 km/l mileage loaded, and a trip distance of 20 km between the field and the processing facility. Large transport distances should be avoided in order to prevent the acidification of the fruits, which usually takes place 24 h after harvesting [13]. The transportation to the refinery is done by truck and on its way back to the field the truck is loaded with empty bunches that return to the field as bio-fertilizer. The industrial phase inventory was based on data from the palm oil extraction [25] and palm oil transesterification (methyl route) [27]. We have not considered the energy associated with labor to allow the comparison with other studies. The LCA energy output includes biofuel energy reported on a low heating value basis (LHV) [36], electricity generation potential in the co-products such as shells and fibers [21] and biogas [12] (Table 1). Energy flows are presented in terms of net energy ratio (NER), in which the sum of the net energy output, which includes biofuel and its electricity surplus, is divided by the net input, which includes the energy for palm production (agricultural phase), transportation, and palm biodiesel production (industrial phase). These inputs exclude the energy from steam and electricity from power plant which is fuelled by co-products. The equation was adapted from Macedo et al. [37] (Equation (1)).

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study we adopt the method presented by Gibbs et al. [11], which was defined as the ecosystem carbon payback time (ECTP) that corresponds to the years required to compensate for the carbon stock of the displaced ecosystem adding the annual avoided emissions due to the fossil fuel displaced by the biodiesel (Equation (2)).

ECTP ¼

Carbonland source  Carbonbiofuel crop Biofuel carbon saving=ha yr

In our study, land use change corresponds to direct displacement of natural vegetation by palm tree plantations. The carbon stock content of both a natural forest and a palm tree plantation is considered. According to Gibbs et al. [11], these values are 197 and 71 tC/ha, respectively. The difference between these two values is the numerator of equation (2). This information represents generic values for the Americas. For the other authors we also adopted the values of Gibbs et al. [11]. In order to determine the avoided carbon due to biodiesel use, it is necessary to know the emissions associated with fossil fuel based diesel production. The LCA carbon emissions of diesel production is 0.21 kg C/kg of diesel [42] and the carbon emitted during diesel combustion equals 0.85 kg C/kg of diesel [41]. The sum of these two values is subtracted by the LCA emissions of the palm oil biodiesel to render the denominator of equation (2). This value corresponds to the avoided carbon per hectare per year and is calculated by equations (3) and (4).

 Biofuel carbon saving

tC $yr ha

P

NER ¼ P

Total output net Total input net allocated

 GHGdiesel;LCA

Based on the input data, corresponding to the mass of inputs (diesel for transport, fertilizers and pesticides) utilized for each hectare of palm oil, and appropriate conversion factors [38], it was possible to estimate GHG emissions in terms of CO2e. Emissions of different GHGs are compared based on the global warming potential (GWP) for 100 years [39]. The same conversion factors were applied to all results with the exception of the study published by Angarita et al. [3], which does not provide the level of the detail needed to carry out this analysis. For the industrial phase, in which palm oil is extracted and biodiesel is produced, GHG emissions correspond to chemicals, electricity from the grid, and diesel for start-up of the turbines. Other GHG emissions are nonexistent because all energy inputs are supplied by co-products from palm oil processing. For electricity from the grid, we adopted the GHG emission for the electricity mix production in Brazil, Malaysia, and Thailand, they are respectively 0.073, 0.62, and 0.790 kg CO2e/kWh [40]. In our study we have not considered emissions due to the manufacturing of equipment and construction of the facilities. To quantify emissions due to fossil fuels consumption, the production [38] and use [41] phases were considered. 3.5. Carbon payback time The carbon payback time is used to assess and compare the environmental performance of biofuels with respect to land use change effects and the overall carbon balance. Different studies applying this method have been recently published [8e11]. In this

 ¼ GHGdiesel;LCA  GHGBiodiesel;LCA

(1)

3.4. Life cycle greenhouse gas emissions

(2)

(3)

  tC $yr ¼ GHGdiesel;production ha

 þ GHGdiesel;combustion   hO/B  YCPO

1 PClBiodiesel ð4Þ

where the first term is given in kg C/MJ of diesel; the LHV is given in MJ of fuel per kg of diesel; hO/B is the conversion efficiency of palm oil to biofuel, given in kg biodiesel/kg crude palm oil; and YCPO is the crude palm oil yield, given in kg CPO/ha. 3.6. Sensitivity analysis A sensitivity analysis was carried out to assess the effect of some of the inputs e for example, bunches yield per ha, nitrogen, phosphorus, potassium, and magnesium application rate per ha on the NER and GHG emissions presented by all considered studies and our study. The effect of pesticides was not assessed because the information was absent in other studies, and probably this is not a relevant impact in terms of energy and GHGs. The equipment and transportation was not evaluated because the approach in each study was different. Data were independently analyzed; that is, each input varied and the others were held constant. In the case of Angarita et al. [3], the only variable included in the sensitivity analysis was yield. Palm oil, palm kernel cake and palm kernel oil are proportional to bunch yields. 4. Results and discussion In this section, LCA results are presented and discussed followed by a sensitivity analysis of the results.

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4.1. Energy input

to 170 MJ/ha. The values differ because of the approach used in the assessment. The values reported in the literature for energy input in the agricultural phase vary. Angarita et al. [3] reports the higher value, 14.3 GJ/ha and Yee et al. [5] the lower value, 6.5 GJ/ha. In our study, we estimate that 8.8 GJ/ha are consumed in the agricultural phase. Amongst the reasons for variance we highlight:

The total gross energy input in our study was 67 GJ/ha, without allocation, and 63 GJ/ha with the allocation of the kernel oil, kernel cake, and glycerin co-products. The industrial phase was responsible for 81% of the net energy consumption per hectare. Electricity and steam from power plant, which result from the combustion of co-products, are subtracted in the net input calculation, which equals to 29.5 GJ/ha, if allocation is considered (Table 2). The energy input corresponding to the production of the seedlings and young palm trees is accounted for once during the 27 year useful life cycle of the palm tree. This input is minimal compared to other life cycle inputs. According to our study this value corresponds to 18 MJ/ha while Pleanjai and Gheewala [4] this value corresponds

 In Wood and Corley [1], Yusoff and Hansen [2] and Yee et al. [5], nitrogen application rates are about 2 times higher than in our case study, which is responsible for about 50% to 60% of the overall agricultural energy consumption. In Pleanjai and Gheewala [4] nitrogen application rate is three times greater than in our case study; and thus nitrogen is responsible for 70% of all energy input in agriculture. This difference between the

Table 2 Energy input. This study

Wood and Corley (1991)

Yusoff and Hansen (2007)

Angarita et al. (2009)

Pleanjai and Gheewala (2009)

Yee et al. (2009)

Input (GJ/ha yr) 1. Agricultural phase Seeds (nursery phase) Pueraria phaseoloides

0.02 0.03

e e

e e

e e

0.17 e

0.02a e

1.1. Fertilizer Nitrogen (N) Phosphate (P2O5) Potassium (K2O) Magnesium (MgO) Boron (B) Total

2.79 2.79 1.42 0.03 0.18 7.25

5.90 0.54 2.83 0.25 e 9.52

6.49 0.97 1.66 0.14 e 9.26

e e e e 11.10

7.61 0.01 1.67 e e 9.45

5.29 0.66 0.76 e e 6.46

1.2. Pesticides Herbicide Insecticide Rondeticide Total

1.02 0.49 e 1.50

0.67 0.20 0.40 1.27

e e e 3.25

0.56 e e 0.56

1.72 e e 1.72

e e e 0.00

1.3. Irrigation Water

0.01

0.20

e

e

e

Total

8.81

10.79

12.50

14.32

11.17

6.46

Manual 0.76 3.05 3.81 e

1.75 e 2.33 e 0.05

3.25a e e 5.71 e

e e e e e

e e e 7.09 e

e e e 10.77b e

3.81

4.13

8.96

1.93

7.09

10.77

3. Industrial phase 3.1. Oil extraction Electricity from power plant Electricity from grid Steam from power plant Diesel for start-up Total

1.49 0.02 34.41 0.90 36.82

1.31 0.01 30.44 e 31.77

1.39 0.02 32.13 e 33.53

2.26 e 30.24 e 32.50

6.02 0.07 18.06 0.54 24.69

0.99 e 36.16 0.34 37.49

3.2. Transesterification Methanol Catalyst (NaOH) Electricity from grid Steam Total

14.90 0.79 2.37 e 18.06

13.82 0.73 2.20 e 16.75

14.29 0.76 2.27 e 17.32

19.96 e 0.85 6.58 27.38

13.37 0.44 0.02 e 13.84

0.07 0.01 0.42 4.95 5.45

Total Total Total Total Total

54.88 67.50 63.50 31.60 29.47

48.52 63.44 58.29 31.69 29.14

50.85 72.31 64.29 38.79 34.83

59.88 76.12 71.42 43.62 40.62

38.53 56.78 52.39 32.71 29.61

42.94 60.17 56.78 23.01 21.56

2. Fuel Harvesting (field) Transport (as far as field) Transport (as far as mill) Total transport (mill-field-mill) Personnel transport Total

input input input input

gross gross allocated net net allocated

The italic values refer to those used for net energy quantification. a Include electricity usage in administration, research, laboratory and nursery buildings. b Include diesel for traction and fertilizers transportation.

2.65

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application rates might be due to the use of green manure in the system analyzed in our case study; The energy intensity adopted by Wood and Corley [1] for potassium is 1.5 times as much the one from Simapro [38], which was adopted in our study. Besides this, the application rate is almost 2 times greater than our study; The magnesium application rates reported by Wood and Corley [1] and Yusoff and Hansen [2] are four times greater than the one adopted in this study. Besides that, the energy intensity adopted by Wood and Corley [1] is 2.5 times greater than the one from Simapro [38], which was adopted in this study. Magnesium application is not considered in Pleanjai and Gheewala [4] and Yee et al. [5] studies; In our study, the energy input for phosphate production is similar to nitrogen; For pesticides, the comparative assessment is difficult due to large variations between the local conditions and external influences. Beside this, Yee et al. [5] didn’t include the pesticide application. The high irrigation intensity presented in Angarita et al. [3] is due to the irrigation of palm trees in Colombia; The work by Angarita et al. [3] does not present details on the agricultural phase and therefore it is impossible to consider the use of EFB as organic fertilizers and its respective abatement potential.

The inventory of the agricultural phase allowed us to identify that potassium is the most important macronutrient for the palm trees (150 kg/ha year). However, nitrogen and phosphate are associated with the greatest energy intensities. Energy consumption as fuel is 3.8 GJ/ha, which is lower than Wood and Corley [1], Yusoff and Hansen [2] and Yee et al. [5] in which harvesting is mechanized. Although Angarita et al. [3] study refers to mechanized agriculture his values for diesel consumption are low. In manual harvesting schemes the workers carry bunches to the road to be loaded in trucks and transported to the processing units. In this case, energy consumption is associated with the truck trips between the field and the processing unit, which may also be significant. For example, Pleanjai and Gheewala [4] assumed that the fuel energy for transporting fresh bunches was 7 GJ/ha. The energy intensity of diesel fuel adopted in the analyzed studies varies. In our assessment and in the study done by Yusoff and Hansen [2], the life cycle energy intensity, which is greater than the heat content of diesel fuel, was adopted. Such an approach renders a negative energy balance for diesel fuel (1:0.77) [43]. In contrast, Angarita et al. [3], Wood and Corley [1] and Pleanjai and Gheewala [4] adopted the heat content of diesel. This approach reduces the total energy input of diesel fuel from 3.81 to 2.93. Yee et al. [5] account for a greater diesel energy input than the other authors because they add the life cycle energy intensity of diesel to its heat content. The industrial phase, which includes oil extraction and transesterification, is responsible for about 60% of the total net energy consumption, ignoring the energy content of the co-products (this study). The study done by Yee et al. [5], reports the lowest share associated with the industrial phase (25%). The largest net energy demands are related to methanol which is 43%, on average for all studies. According to our study, methanol was responsible for 47% of the total energy consumption of biodiesel production. 4.2. Energy output Including energy from biodiesel (low heating value) and surplus energy, the energy output equals to 158 GJ/ha, out of which 147 and 11 GJ/ha corresponds respectively to biodiesel and surplus energy. Surplus energy is the difference between the heat content of the co-

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products (fiber, shells, and biogas) and the electricity from the power plant (Table 3). In the work by Wood and Corley [1], the heating content of the fibers is 3 times greater than the one considered in our work, in which the conversion efficiency of the fibers into useful energy was considered. In our assessment we determine the heat content of fibers and shells separately. The heat content of fibers and shells are respectively 8 and 12 MJ/kg, considering 68% boiler efficiency [21]. In contrast, Yee et al. [5], consider fibers and shells together with a heat content of 19.89 MJ/kg. Because Angarita et al. [3] consider a higher energy input than the other studies its NER is lower than the other studies. The higher value of surplus energy from the combustion of coproducts is reported by Wood and Corley [1], around 18% of the net energy output, which is delivered to the grid. Their study does not consider boiler efficiency. Angarita et al. [3] do not mention values for fibers and biogas. The NER ratio in our study resulted in 5.4 (biofuel plus electricity surplus). This result has demonstrated that the energy yield from biodiesel production is around 5 times greater than the energy input in its production. The energy balances for all the assessments are presented in Table 3. 4.3. Greenhouse gas emissions Biodiesel production results in low emissions due to the use of co-products to produce power, and the use of green manure, which prevents the use of fossil fuels. Amongst the inputs, nitrogen is associated with the highest contribution to overall GHG emissions (3.3 kg CO2e/kg of upstream emissions [38] and 18.6 kg CO2e/kg of soil emissions [44]). Due to the manual harvesting, the diesel consumption during the transportation of bunches to the processing unit was responsible for 14% of the total GHG emissions. The industrial phase and agricultural phase contributed with 21% and 64%, respectively of the total LCA emissions. In the industrial phase, the most significant contribution is attributed to methanol production, which is derived from fossil fuel. This input is responsible for up to 16% of the life cycle emissions of palm oil biodiesel. In the agricultural phase, the highest emission comes from nitrogen, which is responsible for 47% of the total life cycle emission.  According to Wood and Corley [1], Yusoff and Hansen [2], Pleanjai and Gheewala [4] and Yee et al. [5] emissions associated with the agricultural phase were respectively 75%, 61%, 74% and 71% of the total emissions. This reflects high nitrogen use related emissions. Emissions from the industrial phase are mainly due to methanol use. We have not considered emissions due to equipment production. Consequently, the total life cycle emissions in our study were 1437 kg CO2e/ha.year if allocation is considered and 1900 kg CO2e/ ha.year if allocation is not considered. According to Wood and Corley [1], Yusoff and Hansen [2], Pleanjai and Gheewala [4] and Yee et al. [5], emissions were respectively 1259, 2219, 3623, and 2521 kg CO2e/ha (Table 4). In comparison to results based in studies done in other countries, the combustion of co-products in high-efficiency boilers and turbines for power production, which is delivered to the grid, reduces life cycle GHG emissions even if most of the displaced electricity comes from hydroelectric power plants, as is the case in Brazil. 4.4. Carbon payback Despite low life cycle GHG emissions, when compared with diesel and another cultures for biofuels [6], soil carbon loss, due to

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Table 3 Energy output and gross energy balance. This study

Wood and Corley (1991)

Yusoff and Hansen (2007)

Angarita et al. (2009)

Pleanjai and Gheewala (2009)

Yee et al. (2009)

Output (GJ/ha yr) Biodiesel Fiber Shell Effluent (biogas) Electricity surplus

147.15 21.16 14.54 1.85 11.03

136.51 64.27 19.11 9.38 29.60

141.09 24.03 18.10 1.72 13.23

185.99 e e e 4.60

93.40 e 20.73 1.54 7.42

144.27 e 71.89 1.72 23.54

Total output net (biofuel þ electricity surplus)

158.18

166.11

154.32

190.59

100.82

167.81

Total output net (only biofuel)

147.15

136.51

141.09

185.99

93.40

144.27

NER ratio (biofuel þ electricity surplus)

5.37

5.70

4.43

4.69

NER ratio (only biofuel)

4.99

4.68

4.05

3.40

4.58

7.78

3.15

6.69

The italic values refer to those used for net energy quantification.

the displacement of a natural ecosystem by palm trees, poses a significant effect. The carbon debt associated with the forest displacement equals to 126 tC/ha and this deficit is only compensated after 39 years by means of the annual displacement of diesel and its respective avoided emissions (3.6 tC/ha year). Consequently, up to the 39th year the biodiesel plantation will be a net GHG

source. However, as we have observed one way to reduce the payback time is increasing the yield per ha of the plantation. Besides that, the land use change assessment may differ if site specific information is considered [12]. For Wood and Corley [1], Yusoff and Hansen [2], Pleanjai and Gheewala [4] and Yee et al. [5] the ECTP is 43 years on average.

Table 4 Greenhouse gas emission balance.

Output (kg CO2e/ha year) 1. Agricultural phase 1.1. Fertilizer Nitrogen (N) Phosphate (P2O5) Potassium (K2O) Magnesium (MgO) Boron (B) Total 1.2. Pesticides Herbicide Insecticide Rondeticide Total

This study

Wood and Corley (1991)

Yusoff and Hansen (2007)

Pleanjai and Gheewala (2009)

Yee et al. (2009)

903.76 161.83 74.69 12.14 9.15 1165.08a

1651.06 62.23 104.41 36.75 e 1854.45

1399.04 32.16 30.30 29.40 e 1490.90

2896.57 1.73 123.77 e e 3022.07

1661.36 172.86 60.10 e e 1894.32

e e e

e e

38.75 16.44 e

52.70 13.70 e

99.98

e e e

55.19

66.40

23.71

99.98

0.00

Total

1220.27

1920.85

1514.61

3122.05

1894.32

2. Fuel Harvesting (field) Transport (as far as field) Transport (as far as mill) Total transport (mill-field-mill) Personnel transport

Manual 54.91 219.63 274.54 e

136.39 e 181.86 e 3.79

233.36b e e 411.81 e

e e e 661.68 e

e e e 764.27 e

274.54

322.04

661.68

764.27

Total 3. Industrial phase 3.1. Oil extraction Electricity from power plant Electricity from grid Steam from power plant Diesel for start-up Total

e

e 0.01

e 65.07 65.08

645.17

e 0.07

e e

e 0.07

e e

0.30 e

0.07

0.07

50.23 50.53

24.16 24.16 3.22 0.25 1.94

3.2. Transesterification Methanol Catalyst (NaOH) Electricity from grid Steam Total

311.50 28.53 1.30 e 341.34

288.97 26.47 10.21 e 325.66

298.68 27.36 10.56 e 336.60

372.44 31.59 0.10 e 404.13

Total Total GHG emission Total GHG emission allocated

406.42 1901.23 1436.51

325.72 2568.61 1258.70

336.67 2496.45 2218.87

454.65 4238.38 3623.05

a b

Nursery phase correspond with 3.51 kg CO2e/ha. Diesel use for machinery.

e e e

e 5.42 29.57 2688.16 2521.76

S.P. de Souza et al. / Renewable Energy 35 (2010) 2552e2561

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Fig. 1. Net energy ratio sensitivity analysis.

According to Gibbs et al. [11]; when a forest is displaced by palm trees and biodiesel displaces diesel, the corresponding annual carbon savings vary between 1.1 and 2.1 tC/ha year, without taking into account life cycle emissions. Therefore, if the life cycle emissions are considered, the denominator of equation (2) is lower, and therefore, the carbon payback time is greater. According to Fargione et al. [10], the annual carbon payback associated with the displacement of tropical forests in Malaysia and Indonesia by palm trees is 1.93 tC/ha.year. The main discrepancy with the result of their study is due to the life cycle emissions. Life cycle emissions reported by Fargione et al. [10] correspond to 2800 kg CO2e/ha year whereas in our assessment they correspond to 1437 kg CO2e/ha year. The difference might be justified by distinct fertilizers application rates, use of co-products as green fertilizers and as an energy source. The payback time estimated by Fargione et al. [10] was 86 years. Besides their low annual replacement value, the value adopted for the carbon stock of the

palm tree plantation is half of the one considered in this study, 36 tC/ha and 71 tC/ha, respectively. 4.5. Sensitivity analysis The results for sensitivity analysis are presented in Figs. 1 and 2. On each figure the horizontal axis demonstrates the variation of each parameter based on the value adopted in this study. The vertical axis represents the NER variation (Fig. 1) and the GHG emissions variation (Fig. 2) change due to the variance in the selected input parameter. For all the considered parameters, the greatest variation was due to nitrogen application which is 2.3 higher for Wood and Corley [1], Yusoff and Hansen [2], Pleanjai and Gheewala [4] and Yee et al. [5], on average, than our study. This resulted in a 9% reduction in the energy balance and increased GHG emissions by 78%. Besides the large variation on the application rate of this fertilizer, the energy

Fig. 2. GHG emission sensitivity analysis.

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content and GHG emissions associated with nitrogen are also high (Table 1). This variance might result from the use of green manure and the corresponding reduction of inorganic fertilizer demand. The application rate of phosphorous considered by the other authors, excluding Yee et al. [5], is 75%, on average, lower than the one in our study, which causes a 8% reduction in the GHG emissions and 7.2% increase in the NER ratio. The potassium rate in our study is 16%, 40% and 66% lower in comparison to the reported by Yusoff and Hansen [2], Wood and Corley [1] and Pleanjai and Gheewala [4], respectively. These amounts could decrease the NER by 1% to 3% and increase the GHG emissions by 1% to 3%. The application rate presented by Pleanjai and Gheewala [4] is 66% higher than the value adopted in our case study, which explains the reduction of 3% in the NER and the increase of 3% in the GHG emissions. In the case of magnesium, due to the small mass applied, in this study this nutrient was almost supplied by the return of the EFB to the field. In the other studies, the magnesium application rate is around 4 times greater. Despite increasing the fertilizer’s demand, the use of EFB to power production would enhance the energy balance. This results because energy produced from the combustion of co-products is greater than energy required to produce fertilizers. However, this scenario would contribute with increasing GHG emissions since the surplus energy does not displace a considerable amount of GHG emissions because of the characteristics of the Brazilian energy mix. 5. Conclusions Biodiesel production from palm oil has its largest energy input in industrial phase. The divergence between the authors was critical in the agricultural phase. The sensitivity analysis showed that nitrogen causes a large influence on the NER ratio and GHG and its application is significantly reduced by the use of Pueraria phaseoloides. Despite manual harvesting, in our study, fuel consumption is responsible for 18% of the GHG emissions in palm biodiesel life cycle, including diesel for boiler start-up. ECTP is affected by land use change carbon budget and life cycle emissions. These two assessments are required to portray the actual performance of biodiesel as a GHG emission reduction option. References [1] Wood BJ, Corley RH. The energy balance of oil palm cultivation. In: PORIM intl. palm oil conference e agriculture; 1991. [2] Yusoff S, Hansen SB. Feasibility study of performing an life cycle assessment on crude palm oil production in Malaysia. International Journal of Life Cycle Assessment 2007;12:50e8. [3] Angarita EE, Lora EE, Costa RE, Torres EA. The energy balance in the palm oilderived methyl ester (PME) life cycle for the cases in Brazil and Colombia. Renewable Energy 2009;34:2905e13. [4] Pleanjai S, Gheewala SH. Full chain energy analysis of biodiesel production from palm oil in Thailand. Applied Energy 2009;86:S209e14. [5] Yee KF, Tan KT, Abdullah AZ, Lee KT. Life cycle assessment of palm biodiesel: revealing facts and benefits for sustainability. Applied Energy 2009;86: S189e96. [6] Gibbs HK, Johnston M, Foley JA, Holloway T, Monfreda C, Ramankutty N, et al. Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology. Environmental Research Letters 2008;3:10. [7] Hunt S, Esterly J, Faaij A, Flavin C, Moreira JR, Lynd L, et al. Current status of the biofuel industry and markets. In: Biofuels for transport global potential and implications for energy and agriculture. 1st ed. Earthscan Publications; 2007. p. 3e9. [8] Searchinger T, Heimlich R, Houghton RA, Dong F, Elobeid A, Fabiosa J, et al. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land use change. Science 2008;319:1238e40. [9] Gallagher E. The Gallagher review of indirect effects of biofuels production, England. Renewable Fuels Agency; 2008.

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