Life Cycle Analysis of Ethanol

Life cycle analysis for Bio-ethanol production

Fahmi Taufik Kresmagus

Chemical Engineering and Energy, Otto-Von-Guericke University,Magdeburg, Germany

Abstract

Shortage in supply and high price of petroleum, oil reserves depletion global

warming, and urban pollution has created concern and forces to the use of

alternative energy sources recently. Bio-fuels deriving from biomass are

expected to be an alternative-renewable energy that will replace petroleum-

based fuels. This study also included how ethanol is produced from different

feedstocks and processes based on some published journals. Nowadays

many methods and environmental assessment have been conducted to

assess the environmental benefit of biofuel. Some recent works describe

carbon and environmental assessment into details unlike the previous 10 - 15

years that only concerned only on energy assessment. These LCAs typically

report that bio-ethanol results in reduction in resource use and global

warming, however, impacts on acidification, human toxicity and ecological

toxicity occurring mainly during the growing and processing of biomass, were

more often unfavourable than favourable.

1. Introduction

Shortage in supply and high price of petroleum, oil reserves depletion

global warming, and urban pollution has created concern and forces to the

use of alternative energy sources recently. Bio-fuels deriving from biomass

are expected to be an alternative-renewable energy that will replace

petroleum-based fuels. Ethanol derived from biomass is often assumed as a

tremendous contributor to the potential solution for a sustainable transport

fuel.

The European Commission report for 2030 vision notes that dependent on

fossil fuel is around 98% imported from outside the EU and 30% is consumed

by the transport sector in the community. The EU has defined ambitious

targets to reduce its dependency in fossil fuels since less than 2% of overall

fuel consumption is derived from bio-fuel. It is estimated between 4 and 13%

of the total agricultural land in the EU would be needed to produce the amount

of bio-fuels to reach the level of liquid fossil fuel replacement required for the

transport sector in the Directive 2003/30/EC [9].

Bio-fuels originate from plant oils, sugar beets, cereal, organic waste and

the processing biomass [7]. This biomass has a certain amount of sugar that

can be converted (fermented) into bio-ethanol. Based on their chemical

composition, these raw materials are classified under three categories: sugar

(e.g. sugar beet and sugar cane), starches (e.g. wheat, corn, and barley), and

lignocelluloses materials (e.g. trees, processing residues and grasses) [7,8].

Fermentation processes is an ancient tradition, using microorganism like

yeast to convert sugar into ethanol (e.g. in wine production). The most

suitable feedstock for producing ethanol is from is from high sugar content

such as sugarcane, sugar beets, molasses, and fruits because their main

component is glucose, a simple sugar that can be readily converted to ethanol

[8].

Several methods have been suggested to perform analyses of biomass-to-

fuel conversion with useful indicators about system behaviours. The primary

tools are the life cycle assessment method, the thermo-economic theory,

further expand to include the cumulative exergy costing accounting (CExC),

the extended exergy accounting (EEA) and energy accounting [1]. A life cycle

approach involves a cradle-to-grave assessment, where the product is

followed from its primal production stage involving its raw materials, through

its end use [2]. There has recently been a substantial development of life-

cycle methodologies to assess the energetic and environmental performance

of product system from “cradle-to-grave”, namely life cycle energy analysis

(LCEA) and environmental life cycle assessment (LCA) [4].

2. Approach used in this study

2.1Objective

The objective of the study was to review recent evaluations of bio-ethanol,

made from varying feedstock on a life cycle basis. The effort consisted of a

literature search, followed by an analysis of the methods and assumptions

used, and findings obtained to detect if any trends could be identified in the

results when viewed by the type or location of the feedstock.

2.2 Scope of the search

An online search of publicly available papers and reports was conducted

to find studies that have been published in recent years (2005 – 2012). The

focus of the search was the life cycle of ethanol from biomass). Cost analyses

were not part of the main focus of the study. Only those reports that are

available in English were subjected to further analysis; 13 reports were

included in the analysis.

3. Production process of Bio-Ethanol

The selection of regional biomass-based ethanol is based on the regional

prevalent agricultural crops. The dominant biomass-based fuel ethanol

feedstock in Brazil is sugar cane, while it is corn in America and lower-value

grains such as barley, corn and feed wheat in Canada [5]. Meanwhile in some

area in China use cassava, wheat and corn as their feedstock, which all are

starch-based crops.

High sugar-content crops such as sugarcane, sugar beets, molasses and

fruits are the most suitable feedstock for ethanol production, because their

main components are sugars that easily fermented into ethanol. Starch-based

crops such as corn, grains, and potatoes contain carbohydrates and its

carbohydrates fist must be fermented into simple sugar before fermented into

ethanol. Likewise, lignocelluloses feedstock deriving from agricultural forestry

residues, industrial waste, trees, grasses, and sugar chains into simple sugars

prior to fermentation, lignocellulose feedstock contain cellulose and

hemicellulose, and lignin which are more difficult to breakdown than starch [6].

In lignocellulose feedstock, both hemicellulose and cellulose components are

sugar-based chains that can be fermented into ethanol where as lignin is a

structural component to the plant that cannot be fermented into alcohol [8].

The production process of biomass-

based fuel ethanol as in fig.1 has

numerous similarities to that of edible

ethanol, differing primarily in the

addition of dehydration facilities similar

to the one used in industrial-grade

ethanol production [5]. Like in China

where most of the feedstock is using

starch-based crops, the technology

employed to produce ethanol is based

on the hydrolysis of starch and

fermentation of sugar. Starch-based

ethanol can be produced in two ways,

either in wet milling or dry milling. Wet

milling involves separating the

feedstock into its component parts

(e.g. germ, fibre, protein and starch),

meanwhile in dry process the

feedstock is screening to remove

debris and then directly ground into flour. The feed feedstock is mixed with

process water and enzyme and then the mixture is heated and then held at

high temperature so that the enzyme converts starch into short-chain dextrin.

Glucoamylase is added to the mixture after temperature and PH is adjusted

and pumped into fermentation tanks. In the fermentation pots the short-chain

dextrin in the mash is broken into monomeric sugars for suitable fermentation.

To convert sugar into ethanol yeast is added, creating carbon dioxide and

distiller’s grain. After fermentation, low-concentration ethanol passes onto

distillation, where it is concentrated to 95.6% w/w ethanol [1]. Molecular

sieves usually follow, which recover 99.5% w/w ethanol suitable for blending

with gasoline [1].

Fig. 1. Production process of BFE from strach-containing feedstock [5]

In tropical countries like Brazil and Columbia, banana is chosen as

biomass to produce bio-ethanol. Banana fruit is composed 73.4% w/w banana

pulp with banana skin as a balance [6]. The pretreatment for banana after

harvesting are washing, shattering, and crushing for hydrolysis preparation.

During the hydrolysis the complex carbohydrates such as starch and cellulose

is converted into fermentable sugar using the help of enzyme and inorganic

acids, as we can see in the following reaction:

(C6H10O5)n + H2O catalyst n(C6H12O6) [6]

Yeast or bacteria under the anaerobic conditions are carried out the

fermentation process, converting (sugar) fermentable sugar into ethanol as

we can se in the following reaction

C6H12O6 yeast 2C5H5OH + 2CO2 [6]

The CO2 produced during fermentation does not contribute to global

warming because it originates from biomass and is recycled by the banana

tree during cultivation. The maximum reaction efficiency during the

fermentation process is 51%. However, other compounds are produced such

as : aldehydes, heavy alcohols, fatty acids, residual biomass, etc. Therefore, it

is only possible to reach about 90% of this theoretical conversion [6].

Ethanol at 96% w/w is produced at the distillation process. Normally, two

distillation columns are used and some by-products such as aldehydes and

heavy alcohols are recovered. After separation, about 70% w/w of the bottom

fraction of the distillation columns (water together with other by-products) is

recycled for the fermentation process. The other 30% w/w of the bottom

fraction is processed in a plant where water is treated and solids are

separated and sent to the composting plant where they are mixed with ashes

and other biomass residues to obtain an organic fertiliser.

Fig 2. Schematic block diagram of ethanol production process using starch and cellulose as feedstock [6]

Ethanol can be also produced from sugar beet, it comprises two steps: (i)

green juice and green syrup (GS) at the sugarhouse, by subjecting biomass to

a sequence of processes, namely washing and diffusion and purification,

evaporation and crystallisation afterwards; (ii) ethanol is produced both from

green juice and green syrup at distillery though: fermentation using yeast,

followed by distillation to increase ethanol concentration and, finally,

dehydration to obtain anhydrous ethanol. According to current industrial and

commercial practices in France 50% of the bio-ethanol produced comes from

green juice and the other half comes from GS. The commercial feasibility of

producing ethanol from sugar beet involves a comparison of alternative

revenue streams from sugar beet with ethanol or sugar product forms [4].

Fig 3. Flow chart illustrating the bio-ethanol production from sugar beet [7]

Fig 4. Flow chart illustrating the bio-ethanol production from wheat [6]

Production of ethanol from wheat can be divided in two main stages,

which include chemical and mechanical processes. The first stage are

grinding of grains, liquefaction and saccharification, in this stage enzymes are

introduced to break down the starch in the wheat into fermentable sugar.

Fermentation of sugar juice using yeast to produce ethanol at 10-15 % are the

next stage, distillation to recover the ethanol to get higher concentration (95%)

and to obtain anhydrous ethanol used as fuel.

Table 1. First generation of bio-fuels based on feedstock and processes used [9]

Table 2. Second generation of bio-fuels based on feedstock and processes used [9]

4. Methodology: life cycle analysis

4.1 Defining the life cycle

A comprehensive environmental assessment of an industrial system

needs to consider both upstream and downstream inputs and outputs

involved in a delivery of functionality. LCA is based on system analysis,

treating the product process chain as sequence of sub-system that exchanges

inputs and outputs approach involves a cradle-to-grave assessment, where

the product is followed from its primal production stage involving its raw

material, through to its end use. The results of an LCA quantify the potential

environmental impacts of a product over the life cycle, help to identify

opportunities for improvement and indicate more sustainable option where a

comparison is made. A reliable LCA performance is crucial to achieve a life-

cycle economy. The International Organisation for Standardisation (ISO) has

standardised this framework within the ISO 14040 series on LCA [2].

LCA addresses the environmental aspects and potential environmental

impacts (e.g. use of resources and environmental consequences of release)

throughout a product’s life cycle from raw material acquisition through

production, use, end-of-life treatment, recycling, and final disposal (i.e. cradle

to grave). LCA does not predict absolute or precise environmental impacts

due to the relative expression of potential environmental impacts to a

reference unit, the integration of environmental data over space and time, the

inherent uncertainty in modelling of environmental impacts, and the fact that

some possible environmental impacts are clearly future impacts.

Figure 6. Stages on LCA [14]

The LCA methodology consists of 4 major steps. The first component of

an LCA is the definition of goal and scope of the analysis. This includes the

definition of reference unit, to which all the inputs and outputs are related.

This is called functional unit, which provides a clear, full and definitive

description of the product or service being investigated, enabling subsequent

results to be interpreted correctly and compared with other results. The

functional unit should enable the comparison of the energy used throughout

the alternative bio-fuel product system [7]. The second component of LCA is

identification and quantification of environmental loads involved; e.g., the

energy and materials consumed, the air emission, water effluents, and wastes

generated (inventory) [2]. The inventory analysis, also Life Cycle Inventory

(LCI), which is based on primarily on systems analysis treating the process

chain as a sequence of sub-system that exchange inputs and outputs

includes setting system boundaries between economy and environment, and

with other product system [7]. The third component is evaluation of potential

environmental impacts of impact assessment loads [2]. The “end point”

defined for this life cycle study is the final (bio)-fuel product, quantified by the

energy content (MJ/kg). In LCA, the selection of the final product as an “end

point” is often designated by the “cradle-to-gate” approach instead of the more

metaphoric “cradle-to-grave”. The choice of the “cradle-to-gate” approach is

appropriate because it enables LCI results and (bio)-fuels’ energy efficiencies

to be analysed in a variety of different ways, namely concerning allocation,

enabling optimisation or comparison with fossil fuel displaced [7]. Life cycle

interpretation is the final phase of the LCA procedure, in which the result of an

LCI or LCIA, or both are summarised and discussed as a basis for conclusion,

recommendation and decision-making on accordance with the goal and scope

definition [14,15].

4.2 System boundary

LCA is conducted by defining product systems as models that describe of

physical systems. The criteria used in setting the system boundary are

important for the degree if confidence in the result of a study and the

possibility of reaching its goal. When setting the system boundary, several

cycle stages, unit processes and flows should be taken into consideration, for

example, the following [14]:

Acquisition of raw material;

Inputs and outputs in the manufacturing / processing sequence;

Distribution / transportation;

Production and use of fuels, electricity and heat;

Use and maintenance of product;

Disposal of processes wastes and products;

Recovery of used products (including reuse, recycling and energy

recovery);

Manufacture of ancillary materials;

Manufacture, maintenance, and decommissioning of capital equipment

Additional operation, such as lighting and heating

4.3 Life cycle inventory analysis (LCI)

Inventory analysis involves data collection and calculation procedures to

quantify relevant inputs and outputs of a product system. Data for each unit

processes within the system boundary can be classified under major

headings, including [14]:

Energy inputs, raw material inputs, ancillary inputs, other physical

inputs

Products, co-products, and waste

Emission to air, discharges to water and soil, and

Other environmental aspects

4.4 Life cycle ipact assessment (LCIA)

The impact assessment phase of LCI is aimed at evaluating the

significance of potential environmental impacts using the LCI results [14]. It

shall be determined which impact categories, category indicators, and

characterisation within the LCA study [15]. For each impact category, the

necessary component of the LCIA include:

Identification of the category endpoint(s)

Definition of the category indicator for given category endpoint(s)

Identification of appropriate LCI results that can be assigned to the

impact category, taking into account the chosen category indicator and

identified category endpoint(s) and

Identification of the characterisation model and the characterisation

factors

Impact categories that normally assessed within LCA studies are following

[11,12,13]:

Abiotic depletion potential

Global warming potential

Ozone depletion potential

Figure 7. Concept of category indicators [15]

Photochemical oxidation potential

Acidification potential

Eutrophication potential

Human toxicity potential

Ecotoxity potential

Energy consumption / Energy demand

Land competition (for solid wastes)

4.5 Life cycle interpretation

Interpretation is the phase of LCA in which the findings from the inventory

analysis and the impact assessment are considered together or, in the case of

LCI studies, the findings of the inventory analysis only. The interpretation

phase should deliver results that are consistent with the defined goal and

scope and which reach conclusion, explain limitation and provide

recommendations [14]. The life cycle interpretation comprises several

elements, as follows [15]:

Identification of the significant issues based on the result of the LCI and

LCIA phases of LCA

An evaluation that considers completeness, sensitivity and consistency

checks

Conclusion, limitation, and recommendation.

Interpretation phase finely described in the Figure 8

Figure 8. Relationship between elements within the interpretation phase with the other phases of LCA [15]

5. Result

From several reviewed studies we can see assessment and impact of the

production of bio-fuel for alternative-renewable energy. Assessment

categories are mainly on energy balance, greenhouse gasses and

environmental impact.

I. Yu (2008). Energy efficiency assessment by life cycle simulation of

cassava-based fuel ethanol for automotive use in Chinese Guangxi

context

Feedstock: Cassava

Location: Guangxi, China

Basis: 267,000 ha of wasteland in southwest china to produce

100,000 ton/yr 95.6% ethanol and 95,360 ton/yr 99.5%

fuel ethanol

System description:

The study assesses energy efficiency of the cassava-based fuel

ethanol as replacement transportation fuel. The study chose a “vehicle

fuelled by cassava-based E10 (a blend of 10% ethanol and 90%

gasoline by volume) to simulate energy efficiency.

Impacts:

Energy consumption

Findings:

Based on the result of simulation-based life cycle energy assessment

with Monte Carlo method in terms of total energy coefficient (TECff),

net energy values (NEV) as well as energy consumption of vehicles

fuelled by the cassava-based ethanol E10. Simulation results show

TECff is lower than zero and positive NEV, which means E10 fuel

Cassava-ethanol based, can save energy compared with running

gasoline fuel.

Table 3. The NEVs and lifecycle TECff s of cassava-based ethanol [1]

II. Gabrielle (2007). Life-cycle assessment of straw use in bio-ethanol

production: A case study based on biophysical modelling

Feedstock: Cereal straw

Location: France

Basis: 96 x 103 Mg (dry matter basis) annual straw. The study

area comprises cropland, of which 45 % planted with

cereals in an area 22000 km2.

System description:

Two systems in two different soils (places) are used in the analysis.

The so-called S1 (reference system) the plant is powered only by

natural gas. In the straw-to-energy system (S2) half of energy is

supplied by a straw-fuelled combined heat and power (CHP) unit.

Impacts:

Non-renewable energy consumption

Global warming

Acidification

Eutrophication

Ozone creation potential

Findings:

From this study, the author concluded from two soil differences the

deep loam (in Abbeville) emitted more nitrate than rendzina (in

Fagnieres) by an order of magnitue, three times more nitrous oxide and

similar lever of ammonia whilst achieving 25% of higher yields. The

author also added that the substitution of natural gas with straw

resulted in a significant reduction in global warming impact, along with

non-renewable energy consumption. Each etanol produced, the

reference and straw-based system amounted to 20% for those two

impact categories. Compared to the S1, addification was 8% higher in

the S2 system in Fafnieres and 5% lower in Abbeville, whereas

eutrophication was 3% lower in Fagnieres and 0.2% higher in

Abbeville.

Table 4. LCA results for the reference (S1) and straw-based (S2) systems, for the selected agronomic scenarios involving the rendzina soil at Fagnie` res and the deep loam at Abbeville [3]

III. Dale (2005). Life cycle assessment of various cropping system unitized

for producing bio-fuels: Bio-ethanol and bio-diesel

Feedstock: corn and soybean

Location: France

Basis: 0.3 kg ethanol per kg of dry corn grain

System description: the author specified the cropping site and study

the effects of cropping system and corn stover removal. There are four

cropping system scenarios. The first scenario is corn-soybean rotation,

continuous corn without residue removal, continuous corn with 50%

residue removal and the last one continuous corn with 70% residue

removal.

Impacts:


Global warming

Acidification

Eutrophication

Findings:

All the cropping systems from the biomass, which are studied, have

negative environmental impact in terms of non-renewable energy

consumption and global warming impacts. However, the utilisation of

biomass for bio-fuels would increase acidification and eutrophication

particularly because of nitrogen and phosphorus related burdens from

the soil during cultivation.

Table 5. Cradle-to-grave environmental impacts in the different cropping systems for a 40-year cultivation period with the environmental burdens of DDGS estimated by the mass allocation approach [4]

IV. Yu (2009). Simulation-based life cycle assessment of energy efficiency

of biomass-based ethanol fuel from different feedstocks in China

Feedstock: wheat, corn, cassava

Location: China

Basis: The study assesses energy efficiency of the biomass-

based fuel ethanol as replacement transportation fuel

from different feedstock types. The study chose a “vehicle

fuelled by cassava-based E10 (a blend of 10% ethanol

and 90% gasoline by volume) to simulate energy

efficiency.

System description:

The study assesses energy efficiency of the three different feedstocks

fuel ethanol as replacement transportation fuel. The study chose a

“vehicle fuelled by E10 (a blend of 10% ethanol and 90% gasoline by

volume) to simulate energy efficiency.

Impacts:


Findings:

Based on the result of simulation-based life cycle energy assessment

with Monte Carlo method, net energy values (NEV) as well as energy

consumption of vehicles fuelled by the all the biomass (wheat, corn,

cassava)-based ethanol E10 has positive NEV, which means E10 fuels

biomass-ethanol based are viable for energy security concerns.

Furthermore, cassava-based could save up to 5% fossil energy

demand and 2% less for corn-based and 1% less for wheat-based.

To convert ethanol from biomass consumes so much energy and by

using grid electricity from hydraulics and biogas integration for steam

and power it reduces the usage of fossil energy use, especially in KFE

(cassava bio-ethanol production) because it produces more biogas

compare to two other feedstocks.

Technology, which is used to produce fuel ethanol, should be one of

main concerns especially concerning high temperature process.

Saccharification with traditional high-pressure cooking consumes more

energy comparing with the help of enzyme, which is lowering

temperature condition and distillation with pressure distillation is 35%

uses less energy than that of the normal atmospheric. At the end this

technology concerns improve energy efficiency in producing bio-fuel.

Table 6. Respective NEVs and life cycle energy coefficients of CFE, BFE, and KFE [5]

V. Velasque-Arredondo (2010). Ethanol production process from banana

fruit and its lignocellulosic residues: Energy analysis

Feedstock: banana pulp, banana fruit, banana skin, flower stalk

Location: Colombia

Basis: 4000 kg per day banana fruit and its residual biomass

(flower stalk)

System description:

The objective of this work is to apply an energy analysis to evaluate the

behaviour of a pilot plant to produce ethanol. The study takes account

into the stages of banana tree cultivation, feedstock transport,

hydrolysis, fermentation, distillation, dehydration, utility plant and

residue treatment. Four production routes were considered to use

biomass as feedstock, acid hydrolysis of amylaceous material (banana

pulp and banana fruit) and enzymatic hydrolysis of lignocellulosic

material (flower stalk and banana skin)

Impacts:


Findings:

Table 7. Performance indicators [6]

From the four production routes analysed, banana pulp and banana

fruit material submitted to acid hydrolysis showed a better perormance

with higher mass performance, higher NEV (Net Energy Value) and

higher energy ratio compare to two another material submitted to

enzymatic hydrolysis. All of the four materials show a positive energy

balance; therefore, it can be considered for renewable energy sources.

VI. Freire (2006). Renewability and life-cycle energy efficiency of bio-

ethanol and bio-ethyl tertiary butyl ether (bioETBE): Assessing the

implication of allocation

Feedstock: sugar beet and wheat

Location: France

Basis: 400,000 tonnes production of bio-ethanol

System description:

Two feedstock types are used to produce bio-fuel, sugar beet and

wheat to produce bio-ethanol (bio-fuel). The study compares energy

renewably efficiency of producing bio-ethanol from wheat and three

sugar beet cases (case #A for bio-ethanol production, case 50%A and

50%B and case #B which is mainly dedicated to sugar production) and

as direct blended with gasoline. Efficiency of energy input (natural gas,

oil, coal, electricity) to convert the biomass is also considered.

Impacts:


Findings:

Table 8. Bioethanol ‘‘cradle-to-gate’’ primary energy requirement (Ereq) using mass allocation [7]

If mass allocation is used, the percentage of energy use assigned to

bio-ethanol is 42.7% of the total energy requirements. For case #A of

sugar beet 89.7% energy is needed since the contribution of the co-

product is not relevant. Energy renewability efficiency (ERenEf) values

for bio-ethanol (wheat) can vary more than 50%, ranging between -

10% (replacement method) and 48% mass allocation, with 31% for

energy allocation and 46% for allocation based on market values. In

particular, a maximum ERenEf value using mass allocation, meaning

that approximately 50% of the bio-ethanol energy content is indeed

renewable energy. However, when replacement is used as the

allocation procedure, wheat based ethanol shows a negative ERenEf

value, which due to low energy credits from co-products substitution.

However the energy renewability efficiency of ethanol from sugar beet

(case #A) varies only between 33% and 37%. Thus, case #B presents

low ERenEf value between -12% and 15.

VII. Tilley (2009). Integrated energy, environmental ad financial analysis of

ethanol production from cellulosic switch grass

Feedstock: switch grass (panicum virgatum L.)

Location: U.S.A

Basis: 30,000 joules of solar energy for its transformation and

delivery to an ecosystem for use in transpiration.

System description:

Objective of this study is to estimate the ultimate amount of energy

required to produce ethanol from switchgrass by integrating all

environmental, fossil fuel, and human-derived service inputs used

throughout the production chain from crop field to processing facility

Impacts:


Findings:

Table 9. Emergy indicators for ethanol production from switchgrass. [8]

The transformity of switchgrass production was estimated to be 21,200

sej/joule, while the transformity for switchgrass-ethanol was 110,000

sej/joule. The emergy yield ratio decrease from 1.55 for the crop

biomass to 1.29 for ethanol, indicating that most of the resources

added during the industrial transformation were purchased from the

economy. It is estimated energy return on energy invested to be 2.62

based on a production of 80.2 mega joules (MJ) of ethanol that

required 30.6 MJ of fuel. However, from the sensitivity analysis of

producing ethanol from switchgrass, it is determined the EROI was

1.02 and EYR was 0.57.

VIII.Roy and Shiina (2011). Evaluation the life cycle of bio-ethanol

produced from rice straws

Feedstock: rice straws

Location: Japan

Basis: 15,000 kL/ year under rice cultivation area of 1,702,000

ha and total land area of 37,750,000 ha

System description:

This study evaluated the life cycle of bio-ethanol produced by

enzymatic hydrolysis of rice straw. This study used two varieties of rice

straw (Koshihikari and Leafstar), three energy scenarios (F-E-RH: Fuel-

Electricity-Residual used to generate Electricity) and three types of

primary energy (heavy oil, liquefied natural gas, agri-residues).

Impacts:


Global warming (CO2 Emission)

Findings:

Figure 9. Energy consumption breakdown in the life cycle of bioethanol produced from different feedstocks and Effect of energy scenarios and the source of primary energy on CO2 emissions (F-E-RH: Fuel-Electricity-Residues used for Heat; F-E-RE: Fuel-Electricity-Residues used forElectricity; F-RE: Fuel-Residues used for Electricity) [10]

From the energy consumption in each stage and energy output from

the residues, the net energy consumption was estimated to be 10.0

and 17.6 MJ/L for Leafstar and Koshihikari. Atmospheric emissions are

directly related to energy and CO2 emission was estimated to be -0.48

to 0.93 and -0.47 to 1.58 Kg/L for Leafstar and Koshihikari. The CO2

emissions are depent on the source of primary energy. Carbon neutral

of agri-residual (biomass) used as a primary energy source results in

negative emission.

IX. Fu (2003). Life Cycle Assessment if Bio-ethanol Derived from Cellulose

Feedstock: cultivated, waste biomass

Location: Canada

Basis: E10 (10% ethanol and 90% gasoline) on new vehicle with

no engine modification

System description:

Main focus of this study is to determine the potential of reducing

greenhouse gas emission in a 10% blend of this bio-ethanol with

gasoline as transportation fuel. Bio-ethanol is produced by enzymatic

hydrolysis of cellulosic biomass.

Impacts







Ecotoxity potential


Land competition (for solid wastes)

Findings:

Based on the LCA study, the author concludes that Ethanol fuel as a

blend in gasoline may help to reduce overall life-cycle greenhouse gas

emission only if the energy required to generate the process steam

derives from biomass. Replacing traditional gasoline with E10 may

save energy, lead to less summer fog and ozone depleting substances

and lower discharge of heavy metals. However, it may results in

increased eutrophication, acidification, winter smog, and generate

more solid waste.

Figure 10. : Characterization result - distribution of life-cycle environmentalperformance of E10 [11]

The author also concludes that use of biomass waste as a feedstock

could avoid these impacts as feedstock cultivation contributes

significantly to environmental impact in almost all categories

X. Bai, Luo and van der Voet (2003). Life Cycle Assessment if Bio-ethanol

Derived from Cellulose

Feedstock: cultivated, waste biomass

Location: Netherland

Basis: E100, E85, E10 and gasoline on 1 km driving

System description:

Main focus of study is to determine the potential of reducing

greenhouse gas emission in a 10% blend of this bio-ethanol with

gasoline as transportation fuel. Bio-ethanol is produced by enzymatic

hydrolysis of cellulosic biomass.

Impacts:







Ecotoxity potential


Findings:

Figure 11. : Overall comparison results of the environmental impact of gasoline, E10, E85, and E10 [12]

The result of this study indicates driving with E10 produces lower GHG

(green house gases) compare to that of with gasoline but E85 has the

lowest GHG compare to that of E10 and gasoline. The difference in

fuel efficiency is also described: for driving 1 km with E85, 0.099 kg of

fuel is required, which is much larger than 0.0665 kg of gasoline. With

regard to abiotic resource depletion, replacing gasoline by fuel ethanol

reduces the use of crude oil and emission from crude oil production is

renounced, causing a significant decrease ODP for ethanol-fuelled

driving. On the contrary, emissions in other environmental impacts are

substantially higher.

XI. Gonzalez-Garcia (2011). Life Cycle Assessment of two alternative bio-

energy systems involving Salix spp. biomass: Bio-ethanol production

and power generation

Feedstock: willow biomass

Location: Spain

Basis: biomass chips from 1 ha of SRC willow (Salix spp.)

System description:

Two energy production systems using short rotation coppice (SRC)

willow chips were evaluated: bio-ethanol production via enzyme-

catalyzed hydrolysis and electricity production following a biomass

integrated gasification combined cycle scheme.

Impacts:

Abiotic depletion (ADP)

Global warming potential (GWP)

Ozone depletion potential (ODP)

Acidification potential (AP)

Eutrophication potential (EP)

Energy consumption / Energy demand (CED)

Land competition (LC)

Findings:

Fig. 12. Percentage contributions to each impact category under assessment in the biofuel scenario [13].

From the bio-fuel scenario, it shows: the production of the willow chips

as the main source of impact concerning with ADP (62%), EP (90%),

ODP (62%), and CED (62%) due to machinery demand for the

cultivation activities, the production of nitrogen-based fertiliser and the

emission related to diesel combustion. The occupation of agricultural

land for SRC, road network and industrial area occupation contributed

to 72% of LC. The 49% contribution of bio-fuel scenario to AP mainly is

derived from the pre-treatment and conditioning. 75% POFP is linked

to fugitive acetic acid emission during hemicellulose hydrolysis. In

order to compare the environmental performance of the willow-based

bio-ethanol with the environmental profile of conventional fossil fuel,

energy density for E100 and petrol are 26.8 MJ/kg and 44.4 MJ/ kg. In

addition to the lower heating value of each fuel, the efficiency of the

engines was considered 35% in the case of E100 and 30% for petrol.

79% GHG emission was approximately saved from the use of bio-

ethanol.

6. References

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Life Cycle Analysis of Ethanol

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