Streamlined life cycle assessment of residue utilization options inTongkat Ali (Eurycoma longifolia) water extract manufacturingprocess

Choon Keat Kuan Æ Dominic Chwan Yee Foo ÆRaymond R. Tan Æ Sivakumar Kumaresan ÆRamlan Abdul Aziz

Received: 18 May 2006 / Accepted: 26 January 2007 / Published online: 22 February 2007� Springer-Verlag 2007

Abstract Life cycle assessment (LCA) is often used

to compare alternative process options in terms of their

overall impact on the environment to easily identify

the most environmentally friendly alternative. In this

work, a streamlined LCA study was conducted to as-

sess three different residue utilization schemes for

Tongkat Ali (Eurycoma longifolia) extract production.

The case study was firstly simulated using a batch

process simulation software. The results of mass and

energy balances obtained from the simulation software

were then subjected to life cycle analysis. By evaluating

the different schemes for using the fibrous residue from

the extraction process, the potential for environmental

process improvement was identified. Overall, use of

the residue as process fuel was found to be the most

environmentally friendly option. It produces the least

emissions and reduces resource usage per unit of

product than the other options evaluated.

Keywords Life cycle assessment � Life cycle

inventory � Phytochemicals � Tongkat Ali � Herbal

water extract production

Introduction

The herbal-based phytochemical industry is a new and

upcoming industrial sector in Southeast Asian countries

such as Malaysia. One of the important phytochemicals in

the Malaysian market is Eurycoma longifolia (more com-

monly known as Tongkat Ali), which is traditionally used

for its aphrodisiac, anti-pyretic and anti-malarial effects; it

is also consumed as a general tonic (Kuo et al 2003; Aziz

et al. 2003, 2005). The decoction of its long, woody root is

taken orally to achieve these effects; it is also mixed with

conventional food and beverage products as a nutritional

additive. The benefits of the roots of Tongkat Ali include

restoring energy and vitality, and enhancing blood flow

and functioning after child birth (Ismail et al. 1999). The

leaves are used as a cure for malaria, ulcers, syphilis and

gonorrhea, gum diseases, and insect bites (Adenan 2003).

Due to the high market demand and these medicinal

effects, this phytochemical product has a high commercial

value in the Malaysian market (Aziz et al. 2003).

C. K. KuanChemical Engineering Department,Universiti Teknologi Malaysia,81310 Skudai, Johor, Malaysiae-mail: ckkuan83@yahoo.com

D. C. Y. FooSchool of Chemical and Environmental Engineering,University of Nottingham Malaysia, Broga Road,43500 Semenyih, Selangor, Malaysiae-mail: dominic.foo@nottingham.edu.my

R. R. Tan (&)Chemical Engineering Department,De La Salle University-Manila,2401 Taft Avenue, 1004 Manila, Philippinese-mail: tanr_a@dlsu.edu.ph

S. KumaresanChemical Engineering Programme,School of Engineering and Information Technology,Universiti Malaysia Sabah, Locked Bag 2073,88999 Kota Kinabalu, Malaysiae-mail: shiva@ums.edu.my

R. A. AzizChemical Engineering Pilot Plant,Universiti Teknologi Malaysia,81310 Skudai, Johor, Malaysiae-mail: ramlan@cepp.utm.my

However, a common pitfall associated with the

phytochemical sector is that the production of phyto-

chemicals (including Tongkat Ali water extract) is

mainly carried out through various traditional pro-

cesses, which often lead to high losses and low product

yield. This also leads to the common perception that

phytochemical processing is technologically backward

industrial sector. Hence more effort is needed to de-

velop this industry into a viable and profitable eco-

nomic sector (Aziz et al. 2005). In the area of process

design, some efforts in phytochemical processing have

been explored recently using flowsheet synthesis

(Harjo et al. 2004), as well as process modelling and

optimisation (Athimulam et al. 2006).

In addition to optimizing the profitability of the

production process, environmental considerations are

becoming increasingly important as the scale of phy-

tochemical production grows. Life cycle assessment

(LCA) is a systematic method for assessing the

environmental impacts of a product through all of its

life cycle stages, from extraction and processing of

raw materials, to manufacturing, transportation, dis-

tribution, maintenance, reuse and recycling, and the

final disposal (Curran 1996; ISO 1997, 1998, 2000a, b).

In recent years LCA has been commonly accepted for

analysing the environmental impacts of products

(Bishop 2000). The LCA methodology has four

components: goal and scope definition, life cycle

inventory analysis (LCI), impact assessment (LCIA),

and interpretation (previously known as improvement

analysis). A full life cycle assessment includes each of

the four components (Curran 1996). Streamlined or

simplified LCA has also become a commonly used

tool in many practical applications where full LCA is

deemed too time-consuming to implement (Graedel

1998).

In this paper, a streamlined LCA study was con-

ducted to quantify and compare the comprehensive

sets of environmental flows over three different

schemes for utilizing the residues of Tongkat Ali water

extract production. Mass and energy balances of the

process streams used for the LCI were extracted from

process simulations. The database for different manu-

facturing alternatives was collected and then used as

inputs in an LCA model. The assessment focuses on

alternatives for the utilization of the fibrous residue

from the water extraction process.

Case study

Figure 1 shows the process flow diagram of a semi-

industrial scale production of Eurycoma longifolia

water extract at Chemical Engineering Pilot Plant

(CEPP), Universiti Teknologi Malaysia (UTM). The

two main processing steps in this water extract pro-

duction consist of the two-stage counter-current solid–

liquid extraction (leaching) process and the spray

drying operation. The current process is operated with

a batch size of 40 kg of ground Tongkat Ali root, which

is supplied in chip form.

In the first processing step, the two-stage counter-

current solid–liquid extraction (leaching) process,

freshly ground Tongkat Ali root chips are sent to the

extraction vessel to be extracted using the hot water as

solvent. The ratio of water volume to the root chips

weight is maintained at 6 l/kg. In the first stage of

extraction, Tongkat Ali chips are boiled with fresh

water or recycled water at a temperature range of 110–

120�C. This elevated temperature is maintained for 2 h

to provide sufficient time for the phytochemicals in the

root chips to be leached into the extraction solvent.

Upon the completion of the first stage of extraction,

the extracted liquid is pumped out of the extractor and

stored in a holding tank, to be sent later for spray

drying. The leftover chips are then extracted using

fresh solvent in the second stage of extraction, fol-

lowing the same operating conditions as in the first

extraction stage. After the second extraction stage, the

solvent is removed and stored for reuse in the sub-

sequent batch; the leftover chips are then discharged.

Approximately 35% of the solvent water is trapped in

the discharged wet chips; this entrained liquid is rich in

phytochemicals and thus constitutes a significant

process loss.

The liquid extract is then spray dried at 170�C to

yield a powdered concentrate. Due to the limitation of

the existing spray drier capacity, which has a liquid

feed rate of 7 l/h, the drying operation for one batch

takes approximately 22 h to complete. Spray drying is

widely used in most herbal-based phytochemical pro-

cessing to produce extract powders, mainly due to its

relatively shorter process time and favourable process

economics, as compared to other product drying

techniques such as freeze drying. In the current pro-

duction scheme, the spray dried extract powder is sold

as the final product in bulk form.

In this semi-industrial scale production, the overall

process-yield of Tongkat Ali extract is approximately

3% of the raw material feed by weight. Hence, signif-

icant quantities of fibrous residues are generated,

which at the moment present disposal difficulties.

Utilization of the residue can potentially make the

process more economically viable, either by generating

additional products or by displacing the demand for

external resources during operation. Rigorous simula-

tion studies have been performed based on the pilot

scale production with three scenarios to enable a

comparative LCA study to be carried out.

Methodology

Goal definition

The scale and boundaries of the system have been set

according to data availability, time constraints and le-

vel of accuracy of the analysis as shown in Fig. 2. The

purpose of this LCA is to:

• Generate environmental information on the base-

line Tongkat Ali water extract production process.

• Identify improvement potentials for all alternative

processes through the use of the residues.

• Compare alternative processes and identify the best

environmental option.

Scope definition

The scope of the LCA is limited as follows:

• The functional unit in this study is 1 kg of Tongkat

Ali extract capsules.

• The system excludes raw material acquisition,

waste treatment and the impacts arising from the

packaging of the final product. This assumption is

justified since the process yields remains the same

throughout the three scenarios considered, and thus

the contributions of these stages cancel each other

out in the comparative analysis. Focus is placed on

the effect of utilising the extract residue as process

fuel (Scheme 2) or raw material for the generation

of ethanol by-product (Scheme 3).

• The following impact categories are considered:

resource depletion, global warming, acid rain,

photochemical oxidant formation and human tox-

icity. These categories were identified since pre-

liminary analysis of the TA process indicated that

most environmental impacts arise indirectly from

energy use in the plant.

Assumptions and data sources

There are several assumptions made in this work for

the simulation modelling and matrix calculation of LCI

(Heijungs and Suh 2002). There are as follows:

• Energy and emissions data were obtained from

LCA software tools such as greenhouse gases,

regulated emissions, and energy use in transporta-

tion (GREET v1.5a) (Wang 1999) and missing

inventory estimation tool (MIET v2.0) (Suh 2001).

• The energy mix for power generation is based on

recent data in Malaysia: residual oil (14.6%),

Fig. 1 Process flow diagram of pilot scale Eurycoma longifoliawater extract production (Athimulam et al. 2006)

RawMaterial Aquisition

TA Production

Electricity Steam

Emissions to Air

Releases to Water

Solid Waste

System Boundary

Fig. 2 Scale and systemboundaries for performingLCA (adapted from Svoboda1995)

natural gas (56.5%), coal (17.5%) and others

(11.4%), and transmission losses are estimated at

10.0% (Energy Commission of Malaysia 2003).

• The model assumes 100% Tongkat Ali residue

utilisation for steam generation (Scheme 2).

• Energy consumption and environmental air and

water emissions are the only consideration of the

inventory.

• Mean values for conversion efficiencies, heating

values and other inputs used in the model were

based on SuperPro Designer v6.0 (Intelligen 2005),

technical publications and industry average values

from literature.

LCA model

The general equations for LCIA as described by Hei-

jungs and Suh (2002) are as follows:

P ¼ A

B

� �ð1Þ

s ¼ A�1f ð2Þ

g ¼ Bs ð3Þ

where:

P Process matrix

A Technology matrix indicating the flow of economic

commodities

B Intervention matrix indicating the flow of natural

resources or emissions

s Scaling vector

f Final demand vector indicating the functional unit

of the system

g Inventory vector indicating the environmental

flows per functional unit.

The impact characterisation equation (Heijungs and

Suh 2002) is:

h ¼ Qg ð4Þ

where:

Q Characterisation matrix indicating the relative

strengths of the environmental flows with respect

to each impact category

h Impact vector indicating the environmental

impacts per functional unit.

This generic LCA model can be implemented in

different software environments, such as the purpose-

built LCA program CMLCA (Heijungs and Suh 2002).

In this study, the model was developed entirely in a

spreadsheet environment using Excel.

Results and discussion

Figure 3 shows the simulation model for a combination

of three schemes for the case study. Due to the batch

operation of the process, a batch simulator software,

SuperPro Designer v6.0 (Intelligen 2005), was used to

model the process. The modelling of each scheme is

described next.

Scheme 1 is adapted from Athimulam et al. (2006)

as the optimal production scheme of the original pro-

cess. A grinder P-1 (with grinder GR-101) is used to

reduce 40 kg of Tongkat Ali root (denoted as ‘TA

roots’) into chips which are the feed of the extract

production. The extraction procedure in P-2 using the

charging of ground TA chips, deionised water as

extraction solvent (consists of recycle water, i.e., ‘R.

water’ from the second extraction stage and 30 l of

fresh water) and heating of mixture to 110�C. This is

followed by an extraction operation that runs for 2 h.

Based on the product yield of 3.0 wt%, Tongkat Ali

extract produced in the extraction vessel was deter-

mined as 1.2 kg per batch. About 150 kg of fibrous

residue is produced at the same time; the utilization of

this waste is studied in Schemes 2 and 3, which are

discussed in subsequent sections.

Upon the completion of the extraction process, the

resulting mixture is sent to the bowl centrifuge (P-3/

BC-101) where all Tongkat Ali fibre (‘TA fibre’) are

removed. The remaining extract–water mixture (de-

noted as ‘Ext. water’) is transferred to storage tank P-6

(in vessel V-103). The separated solids from P-3 are

transferred into P-4/V-102 to undergo the second

extraction stage (same operating condition as in P-2/V-

101) with 240 l of fresh water feed. Product yield at this

stage is assumed at 1% of original feed. The effluent

from vessel procedure P-4 is separated by P-5 (same

operating condition as in P-3/BC-101). The extract

water leaving P-5 is recycled to P-1 while the solid

content leaves as process residue.

In the drying section, the stored extract–water mix-

ture in P-6/V-103 is sent to an evaporator (P-7/EV-101)

prior to two parallel spray-drying processes (P-9/SDR-

101 and P-10/SDR-101). Ambient air is heated to

170�C before it is used as drying medium in the spray

dryers. Hot air and evaporated water vapour is emitted

with 1% extract loss; while TA powder leaves at the

bottom at 70�C.

In the packaging section, the Tongkat Ali extract

powder from the spray driers is mixed with maltodex-

trin (in P-12/MX-102) and made into capsules with

450 mg extract powder each. The capsules produced

are then put into plastic bottles (P-14/BX-101) and sent

to the box packaging operation (P-15/BX-102). De-

tailed modelling is found in (Athimulam et al. 2006).

The simulation model for Scheme 2 is also shown in

Fig. 3. This scheme is extended based on Scheme 1. A

new steam generation section is introduced in this

scheme via a closed-loop recycling process of the res-

idue, while the operating condition of other units re-

main the same as in Scheme 1. As a result, it is possible

to quantify the effect of changing combustion-related

emissions and impacts from replacing fuel oil with the

process residue. The latter must be pretreated prior to

combustion to remove excess moisture. The closed-

loop recycling process consists of a tray drying (P-16/

TDR-101) and a boiler. The main function of this

section is to generate steam for use in the product

system processes, i.e., extraction and drying. After the

centrifuge operation ends (P-5/BC-101), the residue is

sent to P-16/TDR-101, where 77% of the water content

Fig. 3 Simulation model forSchemes 1, 2 and 3

in the TA fibre is removed. Residue leaves the tray

dryer with a moisture content of approximately 40%.

TA fibre calorific value is taken as 10.4 MJ/kg based on

values for biomass such as wood chips; thus, the fuel

energy available in the 150 kg of residue per batch is

about 1,500 MJ.

Last section of Fig. 3 shows the model for Scheme 3.

This scheme is also extended based on Scheme 1. In-

stead of recycling residue for stream co-production in

Scheme 2, Tongkat Ali waste from the centrifuge is

used as feedstock in the newly introduced ethanol

production section. Each batch generates 150 kg of

residue, from which 15.8 kg of ethanol can be pro-

duced be decomposing the cellulose into fermentable

sugars and subsequently fermenting these into alcohol.

There is considerable interest in ethanol as a gasoline

additive or substitute, as demonstrated by a large

number of assessments done on its life cycle in recent

years (von Blottnitz and Curran 2006). The main aim

of this scheme is to produce value-added product while

minimising the solid disposal. The second product

considered is ethanol, which can displace usage of

imported ethanol. Potential reductions in emissions

and impacts are possible through displacement of

conventional, external ethanol production processes,

which is assumed to use grains such as corn (Heijungs

and Suh 2002). Inventory data for the displaced etha-

nol production process are derived from the GREET

1.5a model (Wang 1999). This section consists of four

unit processes, i.e., storage vessel (P-16/V-104), fer-

mentation (P-17/V-105), centrifugation (P-18/BC-102)

and batch distillation (P-19/V-106). The product of this

new section is ethanol of 95% purity, produced via the

fermentation of yeast in a bioreactor.

After the centrifuge operation ends in the bowl

centrifuge (P-5/BC-101), the residue is transferred

into the vessel procedure (P-16/V-104) to be heated to

140�C prior to the acid hydrolysis reaction with sul-

phuric acid (H2SO4). It is next cooled to 37�C before

neutralisation with lime (CaOH) takes place. The

vessel mixture is then sent to a fermentation proce-

dure (P-17/V-105) with yeast. Upon completion of the

fermentation process, the slurry content of procedure

P-17 is passed through a bowl centrifuge (P-18/BC-

102) where it is separated into ethanol and water

mixture from the process residue (mainly consists of

CaOH, CaSO4, hydrolyzate, water and yeast). The

ethanol and water mixture is sent for batch distillation

(P-19/V-106) while the process residue leaves as solid

waste. In the batch distillation, the distillate produced

is ethanol of approximately 95% purity. Liquid waste

effluent consists of water with trace amounts of

CaOH and ethanol.

LCA results and discussion

The mathematical model previously described is coded

in MS Excel for LCA computations. LCI is used to

quantify resources and environmental flows for the

entire life cycle of a product. The method creates a

basis to evaluate comparative environmental impacts

or potential improvements of different alternative

manufacturing routes. Table 1 shows the inventory

vectors (matrix g) of Schemes 1, 2 and 3. Values en-

closed in parentheses indicate negative flows, which are

interpreted either as inputs of resources, or as avoided

emissions from displaced processes (Heijungs and Suh

2002). Tables 2, 3 and 4 show the contributions of the

process or life cycle stages in Schemes 1, 2 and 3,

respectively, to the total inventory results. In all cases,

the drying and packaging processes do not contribute

to any direct emissions, so these processes are excluded

from the table. Their indirect effects are, however,

reflected as additional energy consumption in the

electricity and steam generation processes. Note that

the main benefit derived from Scheme 2, which uses

the fibrous residue as process fuel, lies in displacing

emissions that would otherwise result from burning

fuel oil in an industrial boiler. These displaced emis-

sions are reflected by negative values in the column

‘‘Steam generation’’ in Table 3 for most of the air

emissions. As a result, Scheme 2 generates reduced

total air emissions compared to Scheme 1, except for

N2O. In comparison, Scheme 3, which utilizes the fi-

brous residue for cellulosic ethanol production, dis-

places emissions resulting from conventional (grain-

based) ethanol production, found in the last column

labelled of Table 4. This benefit is achieved at the ex-

pense of added steam demand for the entire process,

Table 1 Inventory results of each scheme

Resource or emission Scheme 1 Scheme 2 Scheme 3

Fresh water (kg) (32.55) (50.43) (171.92)Residue (kg) 13.52 0 0Root (kg) (3.56) (3.56) (3.56)Oil (MJ) (34.71) 3.18 852.10Coal + gas (MJ) (47.32) (47.32) 1,676.13VOC (g) 0.12 0.40 (3.97)CO (g) 1.30 2.85 (10.87)NOx (g) 9.50 6.14 26.61PM10 (g) 0.47 0.65 0.92SOx (g) 7.27 2.72 16.34CH4 (g) 0.16 0.26 (22.59)N2O (g) 0.05 0.27 (1.93)CO2 (kg) 5.96 2.99 20.74Solid waste (kg) 0 0 25.41Liquid waste (kg) 0 0 151.73

with corresponding increases in internal fuel oil con-

sumption. However, the added fuel usage within the

plant is offset by the corresponding reductions in fuel

inputs for the energy-intensive production of grain-

based ethanol. Hence, there are mixed results with

respect to air emissions, with some increasing and

others decreasing. It should be noted, however, that

such results remain highly dependent on the assump-

tions regarding conventional ethanol production. In

Scheme 3, the major environmental disadvantage ap-

pears to be the increased consumption of fresh water,

coupled with large amounts of wastewater and solid

residue from the ethanol production process. This re-

sult may be particularly critical in locations where

water availability is a problem, or where government

effluent regulations are particularly stringent. The re-

sults imply that the choice between Schemes 2 and 3

depends on the prioritization between air and liquid

emissions, which will vary depending on plant location.

Characterisation factors for air emissions are given

in Table 5; the impacts arising from these air emissions

from the system are given in Table 6. It can be seen

that both Schemes 2 and 3 significantly reduce impacts

on the environment compared to the baseline case.

Significant emissions are avoided by displacing exter-

nal power generation in Scheme 2 and conventional

ethanol production in Scheme 3. Scheme 2 is the best

in terms of acidification (AP), eutrophication (or

nitrification or EP) and human toxicity (HTP), while

Scheme 3 is the best in terms of global warming

(GWP) and photochemical ozone formation (POFP)

impacts. However, Scheme 3 is not fully optimized,

and further reductions in impact are possible by using

unfermented residue as fuel to meet the energy de-

mands of ethanol distillation; such a scenario can be

explored further in the future. Furthermore, a scenario

combining Schemes 2 and 3 can be explored as well.

For the resource usage, a positive value indicates

generation where as a negative value indicates con-

sumption. No residue is observed in Scheme 2 because

the residue has been burned to produce steam. Positive

values for oil flows indicate the amount of oil saved

from avoided energy use due to biomass utilization.

Fresh water consumption in Scheme 2 is higher than

that in Scheme 1. Overall, Schemes 2 and 3 both gen-

erate significant reductions in most emissions and im-

Table 2 Contribution ofprocesses in Scheme 1 toinventory results

Resource or emission Electricityproduction

Steamproduction

Preprocessing Extraction

Fresh water (kg) 0 (8.60) 0 (23.95)Residue (kg) 0 0 0 13.53Root (MJ) 0 0 (3.57) 0Oil (MJ) (10.71) (24.01) 0 0Coal + gas (MJ) (47.32) 0 0 0VOC (g) 0.11 0.02 0 0CO (g) 0.94 0.37 0 0NOx (g) 5.45 4.06 0 0PM10 (g) 0.34 0.14 0 0SO2 (g) 4.32 2.95 0 0CH4 (g) 0.09 0.07 0 0N2O (g) 0.05 0.01 0 0CO2 (kg) 4.08 1.88 0 0

Table 3 Contribution ofprocesses in Scheme 2 toinventory results

Resourceor emission

Electricityproduction

Steamproduction

Preprocessing Extraction Steam generationfrom residue

Fresh water (kg) 0 7.04 0 (23.95) (33.52)Root (MJ) 0 0 (3.57) 0 0Oil (MJ) (10.71) 13.89 0 0 0Coal + gas (MJ) (47.32) 0.00 0 0 0VOC (g) 0.11 (0.01) 0 0 0.30CO (g) 0.94 (0.21) 0 0 2.13NOx (g) 5.45 (2.35) 0 0 3.04PM10 (g) 0.34 (0.08) 0 0 0.40SO2 (g) 4.32 (1.71) 0 0 0.11CH4 (g) 0.09 (0.04) 0 0 0.22N2O (g) 0.05 0 0 0 0.23CO2 (kg) 4.08 (1.09) 0 0 0

pact categories. Use of the residue as either process

fuel or feedstock for ethanol production addresses

residue disposal problems; these schemes also reduce

emissions by displacing conventional processes for

steam generation and ethanol production, respectively.

Both residue utilization schemes increase the fresh

water usage, and production of ethanol results in added

liquid waste from the fermentation process. LCIA of

the gaseous emissions shows that use of the residue for

process heating has the lowest AP, EP and HTP while

ethanol production is the best in terms of GWP and

POFP. Tables 7, 8 and 9 show the contributions of the

different processes within the life cycle to impacts from

air emissions. It is evident that the major benefits ac-

crue mainly from the displacement of steam generation

using oil (in Scheme 2) and production of ethanol from

grain (in Scheme 3).

Conclusions

Three alternative Tongkat Ali process residue utiliza-

tion schemes were evaluated using streamlined LCA.

In addition to the baseline production scheme, use of

the fibrous residue as process fuel or feedstock for

ethanol production was simulated to determine the

most environment-friendly scheme. Each of the two

modified schemes presents its own environmental

Table 4 Contribution ofprocesses in Scheme 3 toinventory results

Resourceor emission

Electricityproduction

Steamproduction

Preprocessing Extraction Ethanolproductionfromresidue

Ethanolproduction byconventionalmethod

Fresh water (kg) 0 (17.59) 0 (23.95) (130.38) 0Root (MJ) 0 0 (3.57) 0 0 0Oil (MJ) (53.15) (48.45) 0 0 0 953.71Coal + gas (MJ) (234.96) 0 0 0 0 1,911.10VOC (g) 0.54 0.04 0 0 0 (4.55)CO (g) 4.66 0.74 0 0 0 (16.28)NOx (g) 27.04 8.18 0 0 0 (8.62)PM10 (g) 1.68 0.28 0 0 0 (1.04)SO2 (g) 21.46 5.95 0 0 0 (11.06)CH4 (g) 0.44 0.15 0 0 0 (23.18)N2O (g) 0.24 0.02 0 0 0 (2.19)CO2 (kg) 20.26 3.80 0 0 0 (3.31)Solid waste (kg) 0 0 0 0 25.42 0Liquid waste (kg) 0 0 0 0 151.74 0

Table 5 Characterisationfactors (Wenzel et al. 1997;Guinee 2002)

GWP (g CO2

eq. per g)AP (g SO2

eq. per g)POFP (g C2H4

eq. per g)EP (g NO3

–

eq. per g)HTP (m3 airper g)

VOC 3 0 0.5 0 2,500CO 2 0 0.03 0 830NOx 0 0.7 0.028 1.35 8,600PM10 0 0 0 0 6,667SOx 0 1 0.048 0 1,300CH4 21 0 0.007 0 0N2O 310 0 0 2.82 2,000CO2 1 0 0 0 0

Table 6 LCIA of each scheme

Scheme 1 Scheme 2 Scheme 3

GWP (g CO2 eq.) 29.73 99.37 (1,087.97)AP (g SO2 eq.) 13.92 7.03 34.97POFP (g C2H4 eq.) 0.72 0.59 (0.94)EP (g NO3

– eq.) 12.99 9.05 30.46HTP (m3 air) 95,881.76 64,616.72 233,402.42

Table 7 Processes contributing to impacts from air emissions inScheme 1

Electricityproduction

Steamproduction

GWP (g CO2 eq.) 22.96 6.77AP (g SO2 eq.) 8.13 5.79POFP (g C2H4 eq.) 0.44 0.28EP (g NO3

– eq.) 7.49 5.50HTP (m3 air) 55,861.99 40,019.77

advantages, as a result of emissions and impacts avoi-

ded by displacing fuel oil combustion in a boiler (for

Scheme 2) or ethanol production by conventional

means (for Scheme 3). Thus the final choice of optimal

utilization of the process residue will depend on the

priority placed on key environmental impact indicators

by plant management. For Scheme 2, the main benefits

lie in displacing the usage of fuel oil for steam gener-

ation, leading to potential direct emission reductions

within the plant itself. For Scheme 3, the advantage lies

in displacing ethanol production process emissions

outside the Tongkat Ali plant. As the commercial

production of ethanol from grains is highly energy-

intensive, this scheme also gives significant environ-

mental benefits. Its main drawback is the increase in

direct process wastes from producing ethanol from the

fibrous residue. These liquid and solid wastes may be a

significant limitation in many candidate plant locations

for Tongkat Ali processing. Thus Scheme 2 offers the

best environmental benefits among the alternatives

considered. However, it is technically possible to con-

sider additional schemes combining the best features of

the options studied thus far; and, economic consider-

ations will also play a role in determining the final

decision for a full-scale plant in the future.

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Table 8 Processescontributing to impacts fromair emissions in Scheme 2

Electricityproduction

Steamproduction

Steam productionusing residue

GWP (g CO2 eq.) 22.96 (3.92) 80.33AP (g SO2 eq.) 8.13 (3.35) 2.24POFP (g C2H4 NO3

– eq.) 0.44 (0.16) 0.31EP (g NO3

– eq.) 7.49 (3.18) 4.75HTP (m3 air) 55,861.99 (23,155.44) 31,910.18

Table 9 Processescontributing to impacts fromair emissions in Scheme 3

Electricityproduction

Steamproduction

Conventionalethanol production

GWP (g CO2 eq.) 113.99 13.66 (1,215.62)AP (g SO2 eq.) 40.39 11.68 (17.09)POFP (g C2H4 eq.) 2.20 0.56 (3.70)EP (g NO3

– eq.) 37.18 11.09 (17.81)HTP (m3 air) 277,360.96 80,757.82 (124,716.36)

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