Chapter 3 Methodology
3.1 Goal and Scope Identification
3.1.2 Scenario Description
3.1.2.2 Scenario 2 – Self Ethanol production in Taiwan
The second scenario analyze that the self bioethanol production in Taiwan. The second scenario is based on the policy already set by Energy Bureau. This scenario will assume that if farmers contracted to produce sugarcane for bioethanol use, the amount of water, fertilizer, chemicals, pesticide, energy, machinery, sugarcane and labor required will be assumed (Figure 3.2). Transportation of sugarcane to alcohol production plant will be assessed with materials of input and output as well as energy required. Then after transported to production process plants (subsystem 3).
Figure 3.2 Scenario 2 of this study
3.1.3 Functional Unit
Functional unit used in this study is considering the amount 1 L of E3 required to run 12.835 km by a passenger car.
(1) Calculation basis
Calculation basis is defined in this section. These bases are very important to interpret the result after the analysis. Differences in functional output that is performance of product system and consequence need for adjustments can often be avoided by choosing broader function-based perspective (Rebitzer et al., 2004).
Calculation basis of this study is shown as the following Table 3.1:
Table 3.1 The calculation basis of this study
Sugarcane Mass 3.3 × 104 ton sugar
(Daishou, 2004)
Ethanol Volume 3,000 kL
E3 Volume 108 L (Su, 2006)
Gasoline Volume 97,000 kL
Land Hectare 468.75 ha
(Whitemer, G. 2008)
According to Daishou (2004), the amount of ethanol produced by 1 ton of sugarcane is 91 L. Currently, bioethanol is mainly imported from Brazil and not produced at
Whitmer, G. (2008) has stated 6400 L of ethanol can be produced per hectare by using Brazilian sugarcane. The area of land requirement can be calculated as following:
3000 kL ethanol ×
468.75 ha of land are required to produce 3000 kL of ethanol in the studied scenario.
3.1.4 System Boundary
Variables evaluated in system boundary of this study is agriculture of sugarcane, transportation of sugarcane to ethanol industrial production factory, industrial production of ethanol, blending of ethanol and gasoline, transportation for E3 to distributor and distribution at petrol station then use of E3. System boundary of this study is shown in Figure 3.3.
Figure 3.3 System boundary of this study
3.2 Life Cycle Inventory Analysis
Life cycle inventory analysis was conducted to calculate the inflow and outflow of materials at each subsystem. There are six subsystems: agriculture, industrial conversion of ethanol, transportation, blending and transportation, distribution and fuel use.
The inventory data was classified by data sources and quantities. In this study, majority of data sources are from literatures. Local data was mainly found in subsystem of agriculture and production of ethanol in Taiwan.
In order to complete LCA study the data from different data sources are integrated.
The data sources and the parameters were listed in Table 3.2.
Table 3.2 Data source for subsystems
Local Data Literatures
Agriculture (Scenario 1) V
Agriculture (Scenario 2) V V
Transportation (Scenario 1) V
Transportation (Scenario 2) V V
Industrial production of ethanol (Scenario 1) V
Industrial Production of ethanol (Scenario 2) V
Blending and Transportation (Scenario 1) V V
Blending and Transportation (Scenario 2) V V
Distribution of E3 (Scenario 1 and 2) V V
Use of E3 (Scenario 1 and 2) V
3.2.1 Agriculture
Material inflow and outflow in agriculture was analyzed in this section. Inputs of material and energy are referred to the data from de Oliveira (2005) and Omette et al.
(2004). Approximate input parameters at the agricultural stage were agricultural operations, cane transportation, fertilizers, lime and fertilizers, seeding and equipment.
There are four activities in agriculture. These activities are soil preparation, sugarcane plantation, pesticide application and harvesting. Amount of material as inflow: water, pesticide and sugarcane bud, fertilizers, lime and fuels are examined based on de Oliveira (2005).
The system boundary and concerned input and output from the agriculture of sugarcane are listed in Figure 3.4.
Figure 3.4 The system boundary of the agriculture of sugarcane
Subsystem1: Agriculture Soil Preparation Sugarcane plantation Pesticide application Harvest
Fuels
Energy Loss
Material Outflow
Sugarcane Water
Pesticide Fertilizers Sugarcane
The input and output of resources and energy of the agriculture can be represented in Table 3.2.
Table 3.3 Parameters for subsystem of agriculture
Parameter Process References
Up = La × Cp seeds Cs, La of land require
de Oliveira (2005), Taiwan Sugar Corporation (1997)
Uf = La × Cf
Total fertilizers use of Uf.
La of land are required. Cf of
3.2.2 Transportation
Cropped sugarcanes are transported from farms to the ethanol production plants. The travelling distance of sugarcane from farm to the ethanol plants was assumed to be Scenario 1 and 2. The travelling distance from farm to the ethanol plant was assumed 30 km.
Amount of fuel consumption was calculated by the equation adapted by the Japan Institute of Logistics Systems (2006).
Weight of sugarcane (ton) × energy coefficiency in litre per ton kilometre × Travelling distance (3.2.2.1)
3.2.3 Industrial Production of Ethanol
Process of producing ethanol was examined with inputs of materials: water, lime, diesel and electricity. Ethanol production plants have outputs of energy and material of bagasse and molasses which are the by prodcut of sugar production and necessary to produce ethanol.
For Scenario 1, due to the data availability, it was considered that Brazil produce ethanol from sugarcane juice and electricity is co-generated by bagasse as a byproduct at the ethanol plant.
On the other hand, Scenario 2 produces ethanol from sugarcane juice and molasses.
Molasses are the byproduct of sugar products. Not like Scenario 1, Scenario 2 cannot self produce electricity at ethanol plants in Taiwan and electricity was provided by electricity companies.
3.2.4 Blending and Trasportation
After ethanol was produced at ethanol production plants ethanol were blended with gasoline. Ratio of the mixture is 3 % of ethanol to 97% of gasoline, then this will be E3.
This blended E3 will be delivered from CPC Kaohsiung blending site to the Taipei.
Parameters were considered in this subsystem were Amount of gasoline blended with ethanol to be E3, diesel to transport E3 to the distribution site by truck as input. As outputs, energy loss from diesel consumption for transporting E3 and fugitive ethanol and gasoline was assumed. Produced E3 was also considered as output and this was flow into the next subsystem of distribution of E3 stage.
3.2.5 Distribution
Blended E3 arrives at petrol station in Taipei. This delivered E3 is distributed customers in Taipei.
In this subsystem electricity used in petrol stations and amount of E3 provided to customers in Taipei are parameters of input. Output is material outflow of fugitive loss in E3 and energy loss from electricity used in petrol stations and E3 distributed to customers.
3.2.6 Vehicle Use of E3
Distributed E3 at subsystem of Distribution was assumed to be an input in this subsystem. Output was the energy loss of consuming E3 and material loss of pollutants to the air.
3.3 Life Cycle Impact Assessment Method
As one of life cycle impact assessment methodology, IMPACT 2002+ is and attractive implementation combined midpoint/damage approach. Jolliet et al, 2003 proposed a feasible implementation of a combined midpoint/damage approach that link all types of life cycle inventory results through 14 midpoint categories to four damage categories as shown in Figure 3.5. IMPACT 2002+ has developed new concepts and methods especially for the comparative assessment of human toxicity and ecotoxicity.
For human damage factors were calculated for carcinogens and non-carcinogens that employ intake fractions, best estimates of dose-response slope factors as well as severities. Both human toxicity and ecotoxicity effect factors are reflected from mean responses rather than the assumptions.
Figure 3.5 Overall scheme of the IMPACT 2002+ framework, linking LCI results via the midpoint categories to damage categories, adapted from Joliet (2003)
Mineral extraction
As a scope of this assessment, E3 gasoline literatures ethanol from sugarcane in purpose of a transportation fuel will be assessed. Past literatures published in recent years and local data will be assessed then applied on the case in Taiwan. The final goal of this LCA is to model all potential impacts to the environment and energy issues of bioethanol. Air emissions will be analyzed followed by the methodology proposed by Bernesson et al (2004). Considered emissions are CO2, CO, HC, methane, CH4, NOx (nitrous oxides), SOx (sulphur oxides), NH3, N2O and HCl. These emissions will be classified in to different environmental impact categories: global warming potential, acidification potential, eutrophication potential, carcinogens, respiratory organics and inorganic, ionizing radiation, ozone layer depletion, ecotoxicity and land occupation.
These impact categories are able to be analyzed by LCA software like SIMAPRO.
3.4 Life Cycle Exergy Analysis of Biofuel
Dewulf et al (2005) has stated that the cumulative exergy values were calculated by tracking back input materials to the raw materials extracted out of the ecosystem to deliver them. The whole production of sugarcane and transport of raw materials and ethanol are therefore accounted. Values of exergy, cumulative exergy consumption (CExC) and cumulative degree of perfection (CDP) are already given by Szargut, (1987), Szargut et al, (1988), Tsatsaronis & Moran, (1997), Mulder, (2002) and Dewulf et al., (2005). These values are adapted into this study.
Assessment of a boundary requires calculating total exergy and cumulative exergy consumptions. These parameters were required to calculate exergy breeding factor (BFex) and non-renewable exergy ratio.
Total Exergy = Quantity × Exergy (3.4.1) CExCtotal = Quantity × CExC (3.4.2)
The CExC-index expresses the sum of exergy values of natural resources fraction to the system delivered in all the link of the chain of production processes, per unit of the product under consideration. Dewulf et al., 2005 analyzed the CExC-index adapting the method of Szargut, 1987 by correcting the exergy consumption in three production chain. The reference state of Szargut, (1987) was chosen with its reference temperature (298 K), pressure (1 atm), and composition.
In this study, it adapted from Szargut (1987) when the reference state was not available by calculating from lower heating value-to-exergy rations. Solar irradiations were calculated by taking into account the geographical position of the different production sites. This study however assumes the solar irradiation is the same in any geographical position. Functional unit of the land is already decided therefore the solar
radiation was considered to be the same in Taiwan and Brazil. Exergy of solar radiation can be calculated from the exergy-to-energy ratio being 0.933 (Szargut, 1987).
With respect to system boundaries, the whole production chain, including extraction, transport and storage of raw materials and the pesticides were taken into account.
Firstly, exergy of the bagasse and sugarcane was calculated. For the determination of bagasse exergy, an exergy value has given by Patzek and Pimentel (2005) in Table 3.18. The data has been directly adopted. Patzek and Pimentel (2005) stated the bagasse at the reference environment conditions, its total exergy is equal to its chemical exergy.
The following composition of the bagasse in mass and dry base was assumed:
C(47.0%), H(6.5%), O(44.0%) and Ash(2.5%) (Patzek and Pimentel, 2007). The exergy of the sugarcane was assumed from 1 metric ton of harvest sugarcane stem (Patzek and Pimentel, 2005). It is assumed on the dry basis of 140 kg bagasse, 160 kg of fermentable sugars and starch and 92 kg of attached tops and leaves, 188 kg detached leaves and 608 kg of water (Figure 3.6).
Figure 3.6. The mass fraction of sugarcane structure
Exergy value of bagasse and trash were referred to Patzek and Pimentel (2005) (Table 3.4)
Table 3.4 Exergy of bagasse and attached trash.
Item Exergy value Unit
Dry bagasse exergy 179.9 GJ/ha-yr
Dry attached trash exergy 47.5 GJ/ha-yr
Exergy analysis was conducted and the method used in here is adapted from Szargut, (1987) and Dewulf et al., (2005). The same system boundary from LCA was applied in this section. The functional unit used is kg of sugarcane or ethanol to the hectare of land use. Resource use is quantified and also the data was adapted from Szargut (1987) and Dewulf et al., (2005) then the quantity of each parameter was adapted from the LCA inventory data.
3.4.1 Exergy analysis of E3 use
Dincer (2000) defined exergy as the maximum theoretical work that can be obtained from a system as it comes to equilibrium with a reference environment. To improve energy source utilization by determining the order of exergy destructions and losses in the processes and components of the system and then by reducing them, the exergy analysis of thermal system is performed. In the exergy calculation it is assumed by Canakcki and Hosoz (2006) and Sayin et al., (2007) that the reference environment has a temperature (T0) of 298.15 K and a pressure (P0) of 1 atm. The reference environment is considered a mixture of perfect gases with the following composition of a molar basis: N2, 75.67%: O2, 20.35%; CO2, 0.03%: H2O, 3.12%: other, 0.83%.
The specific flow exergy of a fluid stream can be found as
ch
where h and s denote the specific enthalpy and entropy of the fluid, respectively while h0 and s0 stand for the corresponding values of these properties when the fluid comes to equilibrium with the reference environment.
The following expression on a unit mass basis can evaluate the specific chemical exergies of liquid fuels (Kotas, 1995)
echF = [1.0401 + 0.1728
where h, c, o, and s are the mass fractions of H, C, O, and S, respectively. The chemical
exergies of the fuels were calculated using the equation (3.4.1.3) and the table adapted from Sayin et al. (2007).
After calculating all the formulas, Sayin et al., (2007) showed the result as Table 3.5.
Table 3.5 Properties of the fuel
Research octane number 95
Typical formula C6.97H14.02
Average molecular weight (kg kmol_1) 97.842 Lower heating value (kJ kg_1) 43 961 Specific exergy (kJ kg_1) 47 011 (calculated from Equation (3.4.1.3) by
Sayin et al., 2007)
After calculating all the total exergy and cumulative exergy consumption, the production manners can be assessed in terms of exergy breeding (BFex). BFex assesses how much renewable resources are bred from nonrenewable resources. In order to calculate it, renewable inputs have to be subtracted from the total input. In this study solar radiation is considered as renewable exergy. However the solar radiation value is quite high and assumed to be overwhelming the system when compare to the other inputs fertilizers. Concept of this exergy study is defining renewable and non-renewable exergy. Furthermore, there is no reason that the solar radiation value to be neglected as renewable exergy and cumulative exergy consumption even the value will be extremely high. Biofuel production assessment of exergy study must be consuming higher amount of non-renewable energy. Therefore at the final stage, it was assumed that the solar radiation exergy value will be depleted at the end of the system. Below formulas are the BFex and overall BFex stated by Dewulf et al., 2005. BFex was calculated by dividing the amount of biofuel delivered by allocated non-renewable resources consumed in the agricultural and industrial biofuel production:
Breeding Factor (BF) =
Overall BFex was calculated by dividing biofuel exergy amount by all non-renewable resources consumed in the overall industrial metabolism as follows:
Overall Breeding factor (overall BF) =
metabolism
Chapter 4 Results and Discussion 4.1 Environmental Performance
Environmental performance of E3 gasoline in Scenario 1 and 2 was discussed in this section. Results calculated by SimaPro 7.1 were also discussed in this section.
Environmental impact of sugarcane to produce ethanol, industrial production of ethanol, and use of E3 gasoline of use were analyzed. The environmental performance of E3 gasoline in Scenario 1 and 2 is only distinct in these stages, namely agricultural activities, industrial ethanol production and transportation.
4.1.1 Agriculture 4.1.1.1 Scenario 1 1. Material inflow (1) Rainfall
Amount of rainfall into subsystem of agriculture was assessed. According to the US Library of Congress: Climate, the amount of averaged rainfall in Brazil per year is 1500 mm/year (US Library of Congress: Climate, http://countrystudies.us/brazil/23/htm) Total amount of rainfall input = (density of rain water) × (rainfall/area/year) × area × time
= 103 kg/m3 × 1500 yr
mm ×468.75 hectares ×
hectares m2 10000
× mm
m 103
1
= 7.03 × 109kg/yr (4.1.1.1)
(2) Pesticide
The amount of insecticide and herbicides used for agriculture of sugarcane in Brazil is assessed in this section. Data is directly adapted from de Oliveira (2005).
According to de Oliveira (2005), insecticides used for sugarcane production were 0.5 kg
The amount of herbicides into agriculture subsystem was calculated.
Herbicides used for production of sugarcane were 3.0kg per hectare according to de Oliviera (2005). In this study, 468.75 ha were used as calculation basis therefore:
ha
According to de Oliveira (2005), fertilizer applied the farm land was 217 kg/ha. Within this amount fertilizer use, the amount of nitrogen used was 65 kg/ha, then 52 kg of P2O5 and 100 kg of K2O.
According to de Oliveira (2005) sugarcane seed used per hectare was 215 kg.
This is the amount of sugarcane seed required per hectare.
Calculating the total amount of sugarcane bud to produce 1.0 × 108 L of E3 is:
ha
bud sugarcane kg
215 × 468.75 ha = 1.01 × 105 kg sugarcane bud (4.1.1.5)
According to de Oliviera (2005), the energy consumption per hectare of sugarcane bud was 3.35 GJ/ha.
(6) Diesel
For agricultural activity, the used amount of diesel is 600 L per hectare (de Oliveira, 2005). Converting this amount :
468.75 ha × ha
L
600 = 2.81 × 105 L diesel/year (4.1.1.6)
(7) Lime
According to de Oliveira (2005), amount of lime used per hectare was 616 kg.
468.75 ha × ha
kg
616 = 2.89 × 105 kg (4.1.1.7)
2. Energy Loss
Energy outflow at agricultural stage estimated in fuels considered to be energy loss.
This is calculated by:
Amount of water contained in soil is calculated by assumption. Intensity of rainfall in Brazil is 1500 mm. Runoff coefficient was assumed 0.1 as sandy soil with 2% slope.
0.1 × 1500 mm × 468.75 ha ×
ha m2 10000
= 7.03 ×108 m3 (4.1.1.9)
(2) CO2
Amount of CO2 emitted from diesel use was calculated. 0.284 kg CO2/kL of CO2
emission factors was adopted from Daishou (2006).
2.81 × 105L diesel/year × 0.284 kg CO2/kL = 7.98 × 104 kg CO2/year (4.1.1.10)
It should be noted that soil loss would not be count based on the consideration of little amount of soil was lost during sugarcane production.
(3) Sugarcane
According to the calculation basis in this study, amount of sugarcane required was given. The sugarcane production was 3.30 × 104 ton
4.1.1.2. Scenario 2
Inputs of material and energy are referred to the data from Omette et al. (2004).
Subsystem 1, have four subsystems in this system. Amount of material: water, pesticide and sugarcane; fuels and labor are examined based on local data. Subsystem 1 has outputs of energy loss, material outflow and sugarcane.
1. Material inflow (1) Rainfall
According to the Central Weather Bureau, the amount of averaged rain water in Taiwan per year is 2400 mm/year (Central Weather Bureau, http://www.cwb.gov.tw/) Total amount of rainfall input = (density of rain water) ×(rainfall/area/year) × area × time
= 103 kg/m3 × 2400 used because the soil condition and the land use.
Therefore, the total amount of pesticides used for the 465.75 ha of a sugarcane field is:
yr
②. Herbicides used for production of sugarcane were 3.0kg per hectare according to de Oliviera (2005). 0.80 GJ per hectare of energy is used. With the same
Amount of fertilizer used on 268.75 ha land in Taiwan was calculated. According to Taiwan Sugar Corporation (1999), fertilizer applied to per hectare of farm land was 684 kg/ha from 1989 to 1999. Within that amount Nitrogen was117 kg/ha, then 19.45 kg of P2O5 and 40 kg of K2O (Table. 4.1).
Table 4.1 Fertilizers used for sugarcane field kg/ha (data provided by Taiwan Sugar Corporation, Taiwan sugar Statistics 1999)
Year Fertilizer Contents per ha
N P2O3 K2O
According to Taiwan Sugar Corporation (1999) averaged planted area for sugarcane was 53,305 hectare (Table. 4.2). The estimation used in here is assumed that the sugarcane is planted for sugar production cane rather than for eating fresh. Then sugarcane production to the harvested area was 10,252 ha/year, yield of 63,502/ha and production of 651,041 ton has shown by Agricultural Statistics Yearbook 2006.
Table 4.2 Cane planted area (Ha). (Taiwan Sugar Corporation, 1999) Year Cane planted area (Ha)
1998-1999 40,709
According to National Agricultural Research Center for Kyusyu and Okinawa Region (2007), 1 kg of sugarcane grows about 4 to 5 m. When the sugarcane is planted about 30 cm of stem is planted. Then the assumption of sugarcane bud is carried by calculating 1 kg of 450 cm grown sugarcane from 30 cm sugarcane bud is:
1kg ×
Therefore it can be assumed the weight of sugarcane bud would be 0.07 kg. From this value the total amount of sugarcane bud can be calculated. According to Agricultural Statistics Yearbook (2006), the amount of produced grown sugarcane was 651,041 ton.
The amount of sugarcane will be:
area
Then the sugarcane bud per hectare is calculated:
ha
This is the amount of sugarcane bud required per hectare.
This is the amount of sugarcane bud required per hectare.