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Reduction of CO
2
emission by INCAM model in Malaysia biomass power
plants during the year 2016
Nor Aishah Saidina Amin
a,b,
⇑
, Amin Talebian-Kiakalaieh
b
a
UTM-MIT Sustainability City Program, Institut Sultan Iskandar (ISI), Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia
b
Chemical Reaction Engineering Group, Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia
article info
Article history:
Received 15 February 2017
Revised 4 October 2017
Accepted 8 November 2017
Available online xxxx
Keywords:
Renewable energy
Oil palm
Climate change
Carbon emission
Biomass
abstract
As the world’s second largest palm oil producer and exporter, Malaysia could capitalize on its oil palm
biomass waste for power generation. The emission factors from this renewable energy source are far
lower than that of fossil fuels. This study applies an integrated carbon accounting and mitigation
(INCAM) model to calculate the amount of CO
2
emissions from two biomass thermal power plants.
The CO
2
emissions released from biomass plants utilizing empty fruit bunch (EFB) and palm oil mill efflu-
ent (POME), as alternative fuels for powering steam and gas turbines, were determined using the INCAM
model. Each section emitting CO
2
in the power plant, known as the carbon accounting center (CAC), was
measured for its carbon profile (CP) and carbon index (CI). The carbon performance indicator (CPI)
included electricity, fuel and water consumption, solid waste and waste-water generation. The carbon
emission index (CEI) and carbon emission profile (CEP), based on the total monthly carbon production,
were determined across the CPI. Various innovative strategies resulted in a 20%–90% reduction of CO
2
emissions. The implementation of reduction strategies significantly reduced the CO
2
emission levels.
Based on the model, utilization of EFB and POME in the facilities could significantly reduce the CO
2
emis-
sions and increase the potential for waste to energy initiatives.
Ó2017 Elsevier Ltd. All rights reserved.
1. Introduction
The rise in energy demand and the corresponding rise in green-
house gas (GHG) emissions are causing climate change
(Kerdsuwan and Laohalidanond, 2011). Fig. 1 illustrates CO
2
emis-
sions by region from 1990 to 2030. CO
2
emission levels are esti-
mated to increase drastically for some regions of the world
within 40 years. One key approach to addressing climate change
is to replace fossil fuels with renewable energy for electricity pro-
duction. Thus, reliance on fossil fuels without any conservation
effort or increase in renewable energies to fulfill our energy
demand will eventually lead to catastrophic global impacts.
The development of non-fossil fuel energy sources is essential
for reducing GHG, avoiding fossil fuel resource depletion and cop-
ing with fluctuating fossil fuel prices (Talebian-Kiakalaieh et al.,
2013; Maceiras et al., 2011; Santori et al., 2012). CO
2
emissions
can be substantially reduced if biomass replaces fossil fuels for
power generation. Indeed, unlike fossil fuels, burning renewable
biomass is considered neutral in GHG emissions (Ibrahim, 2016).
Trees take in carbon dioxide from the atmosphere and convert it
into biomass; whether trees are burned or decompose naturally,
they release the same amount of carbon dioxide (Cho, 2011). Also,
the carbon that is released when biomass is burned is re-absorbed
by other plants in their growth cycle. However, when fossil fuels
are burned, they release CO
2
that has been trapped for centuries,
adding carbon to the atmosphere (Biomass Power Association,
2011). Fig. 2 illustrates that renewable energies generate signifi-
cantly lower GHG emissions compared with fossil fuels including
natural gas, oil and coal.
Given Malaysia’s tropical biodiversity, conversion of waste (bio-
mass) to energy is a promising approach to establishing sustain-
able energy production. Waste management was originally
adopted for the purposes of waste volume reduction and maintain-
ing high levels of public hygiene. However, over the years, waste
management concept has evolved to include the concepts of waste
prevention, waste recycling and waste to energy (Hadidi and Omer,
2017; Chen, 2016; Schwarzbock et al., 2016). Malaysia is ranked as
the world’s second largest palm oil producer, next to Indonesia. In
fact, Malaysia’s palm oil production exceeded 21.25 MMT in 2014,
and has been increasing annually since 2009. Malaysia’s palm
plantation area and amount of crude palm oil production
https://doi.org/10.1016/j.wasman.2017.11.019
0956-053X/Ó2017 Elsevier Ltd. All rights reserved.
⇑
Corresponding author at: Chemical Reaction Engineering Group (CREG), Faculty
of Chemical and Energy Engineering, Universiti Teknologi Malaysia (UTM), 81310
Skudai, Malaysia.
E-mail address: noraishah@cheme.utm.my (N.A.S. Amin).
Waste Management xxx (2017) xxx–xxx
Contents lists available at ScienceDirect
Waste Management
journal homepage: www.elsevier.com/locate/wasman
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
significantly increased from 4.7 to 5.4 million hectares and 17.6 to
19.8 million tonnes, respectively, between 2009 and 2014 (Aditiya
et al., 2016).
The oil palm industry yields a tremendous amount of biomass
waste such as frond, trunk, mesocarp fibres, palm kernel shell,
empty fruit bunches (EFB), and palm oil mill effluent (POME).
These wastes are a potential source for energy generation. How-
ever, only a small portion of this waste is currently utilized for
steam and electricity generation (Mahlia et al., 2003; de Souza
et al., 2010). A large fraction is simply burned or used as landfill
(Lahijani and Zainal, 2011). Thus, the government and industry
alike are seeking ways to utilize this massive oil palm industry
wastes. For instance, heat from EFB combustion can be captured
in a boiler to produce steam. POME, the voluminous liquid waste
from the oil palm industry, is retained in ponds to reduce its toxi-
city and releases methane gas. If harvested properly the valuable
methane fuel can be used for electricity, steam or heat generation.
In accordance with global efforts to produce renewable energy
and reduce CO
2
emissions, Malaysia has developed strategic plans
for increasing its share of renewable energy sources. Iskandar
Malaysia, an innovative economic development zone in Johor has
developed a Low Carbon Society Blueprint, called IM 2025, with
a target to reduce carbon intensity by 58% by 2025 from 2005 car-
bon level. The Malaysian government designed a roadmap to make
this economic development zone a ‘‘strong sustainable metropolis
of international standing” by 2025, producing only 18.9 MtCO
2
qe
GHG emissions, 40% lower than the projected amount (Low
Carbon Society Blueprint for Iskandar Malaysia 2025, 2014).
Life cycle assessment (LCA) is a common tool used to study
environmental impacts associated with all stages of a manufac-
tured product’s life cycle, from raw material extraction through
materials processing, manufacture, distribution, use, repair and
maintenance, and disposal or recycling. For example, the environ-
mental impacts in the different parts of the palm oil supply chain
have been identified using LCA in nurseries (Halimah et al.,
2010), fresh fruit bunches (Zulkifli et al., 2010), crude palm oil
(Vijaya et al., 2010a), and bio-char from empty fruit bunches
(Harsono et al., 2013). LCA is also used for palm kernel oil (Vijaya
et al., 2010b), refined palm oil (Tan et al., 2010), bio-
hydrogenated diesel from palm oil (Boonrod et al., 2017), GHG
emission of palm biodiesel (Abdul-Manan, 2017), and impact of
palm oil feedstock on products (Martinez et al., 2017). Alterna-
tively, a simpler integrated carbon accounting model (INCAM) con-
siders direct and indirect carbon emissions (Hashim et al., 2015).
The main objective of this paper is to apply the INCAM model to
determine the amount of CO
2
emissions from two biomass thermal
power plants that use oil palm waste to produce energy. In this
paper, two case studies are analyzed. The first case study investi-
gates the CO
2
emission from Bio-Xcell company, a central utility
facility situated in Iskandar Malaysia which uses EFB to produce
steam. The other company, Kulim Group Oil Palm Mill use POME
as an alternative fuel for firing gas turbines to produce electricity.
From the model, various innovative strategies are proposed to
reduce CO
2
emissions. The findings from our study provide basic,
useful data for developing renewable energy policies to lower
CO
2
emissions from the industrial sectors in Iskandar Malaysia
region.
2. Methods
The steps to determine the reduction in CO
2
emissions levels
with the INCAM model are illustrated in Fig. 3. Initially, each pro-
cess is divided into smaller scoping units known as carbon
Fig. 1. World CO
2
emission levels by region between 1990 and 2030.
2N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
accounting centers (CACs) for easy monitoring of the CO
2
emission
levels. Next, a carbon checklist is developed to identify the carbon
emission source for each division, and a plant audit is performed.
Most importantly, the average amount of CO
2
emission throughout
the year 2016 is reported in this study. In fact, there is a small dif-
ference in CO
2
emission levels in different seasons, thus application
of average amount was selected as the most logic choice. Five main
emission contributors-fuel, water, and electricity consumption,
waste water and solid-waste generation are identified as Carbon
Performance Indicators (CPI). The Carbon Emission Index (CEI) for
each CPI is based on CO
2
emission factors (Hashim et al., 2015;
The Climate Registry, 2014). The CPI with the highest emissions
is identified as the hotspot based on the Carbon Emission Profile
(CEP). After the hotspot is identified, innovative strategies are sug-
gested to reduce carbon emissions. The carbon emissions are again
calculated after the implementation of innovative strategies to
reduce carbon emissions. Finally, the carbon emission reduction
in each plant is measured and then compared to identify the plant
with the highest reduction.
3. Case studies
The effectiveness of the INCAM methodology is evaluated for
the two companies, namely Bio-Xcell and Kulim Group Oil Palm
Mill. Bio-Xcell, located in Nusajaya, Iskandar Malaysia uses EFB
as fuel for steam production. The steam is supplied to other nearby
power plants for generating heat and electricity. The Bio-Xcell
plant has three divisions: steam generation, waste water treatment
and chiller plants. At 500 °C temperature and 42 bar pressure,
7135 tonnes/month output rate steam was produced. The Kulim
Group Oil Palm Mill is situated in Kulai, Johor. In this facility, POME
retained in ponds releases methane gas and electricity is generated
from combusting methane in a gas engine. Biogas or methane from
the POME pond is trapped, conditioned and scrubbed before com-
bustion. The production output for this company is 160,000 m
3
/-
month (67,680 tone/month) of methane gas. The data for both
case studies are based on monthly average in 2016.
3.1. Process description for Bio-Xcell
Fig. 4a depicts the process flow of the Bio-Xcell facility. The
main divisions are the steam generation plant (boilers, biomass
storage, and LPG farm), water pre-treatment plant and chiller
plant. Two bi-water tube boilers are fueled by biomass and a fire
tube boiler uses LPG. Raw water is pre-treated in the water pre-
treatment plant to insure high-quality steam. In the LPG farm,
the liquefied petroleum gas is treated and vaporized before enter-
ing the boiler. The biomass is stored in a storehouse and carried on
a conveyer belt into the boiler. Three types of fuel consumption
data were collected—diesel (on-site transportation), LPG (fire-
tube boiler) and EFB (water-tube boiler). The electricity generation
data for each section was not available, but the general electricity
consumption data for the entire plant is assumed to be from the
chiller plant. The feedstock supplied to Bio-Xcell is wet EFB with
about 5–7% moisture (Abdullah and Sulaiman, 2013). Based on cal-
culations, an estimated 5% of water and solid fuel consumption
were wastewater and solid waste. As per observations and discus-
sions with the plant engineers, a 5% solid waste generation was
assumed since EFB could combust well and a relatively small
amount of ash and coke remained at the end of each process.
3.2. Process description for Kulim Group
The process flowchart of the Kulim Group plant is described in
Fig. 4b. The main two sections considered in this study are the
Fig. 3. Integrated carbon accounting and mitigation (INCAM) framework steps.
Fig. 2. Lifecycle GHG emissions of renewable energy, nuclear energy, and various
fossil fuels.
N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx 3
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
methane gas production (CAC 1) and electricity production (CAC
2). In details, the raw effluent is fed to the mixing tank for pre-
treatment and then sent to the anaerobic tank for microbiological
process which includes:
1. Hydrolysis (complex molecules are broken down into simple
molecules).
2. Acidogenesis (production of various types of acids, and
ammonia (NH
3
), CO
2
,H
2
S, and H
2
).
3. Acetogenesis (production of acetic acid (CH
3
CO
2
H), CO
2
,
and H
2
).
4. Methanogenesis (the last stage for methane (CH
4
) gas
production).
3.3. Assessment of carbon in each unit
The steps to identify the carbon accounting centers, determine
the total monthly carbon emissions, calculate the CEIs and reduce
CO
2
emissions are described here. Several strategies are considered
to reduce the carbon emissions across the CPIs.
3.3.1. Step 1: Identification of CAC
3.3.1.1. Bio-Xcell central facility. Three CAC breakdowns are used in
this study; CAC1 represents the steam-generation process, which
includes three sub-CACs of biomass storage, along with the LPG
farm and boilers. CAC2 and CAC3 represent the water pretreatment
and chiller plants.
3.3.1.2. Kulim Group bio-gas facility. For this case study, two CAC
breakdowns were performed. CAC1 represents the methane pro-
duction process and CAC2 for electricity generation process.
3.3.2. STEP 2: Carbon checklist development and plant audit
The carbon emission sources in each CAC are identified in this
step. Table 1 lists the various carbon emission sources for each
CAC. The audit process involved a site visit and data collection of
the companies’ utility bills, procurement reports and domestic
waste reports. The audit process provided significant information
about the monthly consumption and generation of five carbon per-
Fig. 4. The process flow diagram of (a) Bio-Xcell and (b) Kulim plants.
4N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
formance indicators (CPI) fuel, water, electricity consumption,
wastewater, and solid waste generation. The values, listed in
Table 2, are subsequently used for carbon emission analysis in
the next step.
3.3.3. STEP 3: Establish carbon emission profile (CEP) and carbon
emission index (CEI)
Table 3 summarizes the carbon profile (CP) and carbon index
(CI) of each CAC subsection. The highest total monthly CO
2
emis-
sion is released by the boilers and POME consumption in the EFB
and POME utilization processes, respectively. Thus, the steam gen-
eration in the boilers and methane gas generation process are iden-
tified as the hotspots in these case studies. The first and most
important information needed was the amount of CO
2
emissions
for each CPI. The emission factors related to each CPI were col-
lected from the literature (Hashim et al., 2015; The Climate
Registry, 2014). Meanwhile, the monthly carbon emission equiva-
lent (MCEE) was calculated by multiplying the CO
2
emissions and
monthly amount of each CPI’s consumption or generation (Eq.
(1)). The carbon profile (CP), and carbon index (CI) for each CAC
are determined by Eqs. (2) and (3). The CEP and CEI for each CPI
are calculated by Eqs. (4) and (5).
Table 3
Carbon profile (CP) and carbon index (CI) for each Carbon Accounting Center (CAC).
Carbon Performance
Indicators (CPI)
Monthly carbon emission equivalent (MCEE) (t CO
2
e)
BIO-XCELL KULIM
CAC1 CAC2 CAC3 Total CAC1 CAC2 Total
Steam
Generation
Water Pre-
treatment plant
Chiller
plant
Methane
Production
Electricity
Generation
Fuel POME (m
3
)– – – – 710
7
–710
7
EFB (Tone) 2.5 10
6
– – 2.8 10
6
––
Diesel (Liter) 2.6 10
3
–– ––
LPG (kg) 2.8 10
5
–– ––
Methane (m
3
) – – – – – 3.2 10
5
3.2 10
5
Water (m
3
) 2.2 10
6
1.8 10
6
1.5 10
6
5.5 10
6
4.1 10
6
– 4.1 10
6
Electricity (kWh) – – 1.5 10
6
1.5 10
6
8.7 10
4
– 8.7 10
4
Waste Water (m
3
)– 510
5
4.2 10
5
9.2 10
5
15 10
6
–1510
6
Solid Waste (kg) 1.1 10
5
– – 1.1 10
5
610
6
–610
6
Total monthly CO
2
e
(tCO
2
e)
5.1 10
6
2.3 10
6
3.4 10
6
10.8 10
6
9.5 10
7
3.2 10
5
9.532 10
7
% Carbon Profile, CP 47.1 21.3 31.6 100 99.7 0.3 100
Carbon Index (tCO
2
e), CI 714.8 322.4 479.3 1516.5 1406.6 4.7 1411.3
Table 2
Monthly consumption and generation in each Carbon Accounting Center (CAC).
Carbon Performance
Indicators (CPI)
Emission Factor
(kgCO
2
e/unit)
Monthly consumption or generation
BIO-XCELL KULIM
CAC1 CAC2 CAC3 CAC1 CAC2
Steam
Generation
Water Pre-
treatment plant
Chiller
plant
Methane
Production
Electricity
Generation
Fuel POME (m
3
) 292 – – – 2.4 10
5
–
EFB (Tone) 1100 2.25 10
3
––––
Diesel (Liter) 2.7 9.73 10
2
––––
LPG (kg) 1.53 1.82 10
6
––––
Methane (m
3
) 2 – – – – 1.6 10
5
Water (m
3
) 300 7.27 10
3
5.98 10
3
510
3
1.35 10
4
–
Electricity (kWh) 0.727 – – 2.06 10
6
1.2 10
5
–
Waste Water (m
3
) 1670 – 3 10
2
2.5 10
2
910
3
–
Solid Waste (kg) 997.9 1.12 10
2
––610
3
–
Table 1
Carbon checklist for Bio-Xcell and Kulim plants.
Carbon Performance
Indicators (CPI)
BIO-XCELL KULIM
CAC1 CAC2 CAC3 CAC1 CAC2
Steam Generation Water Pre-treatment plant Chiller plant Methane Production Electricity Generation
Fuel POME – – – p–
EFB p––––
Diesel p––––
LPG p––––
Methane – – – – p
Water pp pp –
Electricity – – pp –
Waste Water – ppp
–
Solid Waste p––
p–
N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx 5
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
Monthly carbon emission equi
v
alent ðMCEEÞ
¼Monthly consumption orgeneration Emission factor ð1Þ
CAC carbon profile ðCPÞ
¼Total monthly CO
2
of each CAC
Total monthly CO
2
equi
v
alent ðtCO
2
eÞ100 ð2Þ
CAC carbon index ðCIÞ
¼Total monthly CO
2
of each CAC
Total monthly of production ðtoneÞin a month ð3Þ
Carbon emission profile ðCEPÞ
¼Total monthly CO
2
of each CPI
Total monthly CO
2
equi
v
alent ðtCO
2
eÞ100 ð4Þ
Carbon emission index ðCEIÞ
¼Total monthly CO
2
of each CPI
Total amount of production ðtoneÞin a month ð5Þ
3.3.4. STEP 4: Recommended strategies for carbon emission reduction
Table 4 summarizes the recommended strategies for reducing
CO
2
emissions in two cases. At Bio-Xcell, we recommended
decreasing fresh water intake to reduce CO
2
emissions. Recycled
water could be utilized in boilers, water treatment, and chiller
plants in CAC1, CAC2, and CAC3, respectively. Next, we preferred
using natural gas instead of diesel fuel in the biomass storage sec-
tion (CAC1) to significantly reduce the CO
2
emissions.
We also recommended using higher-efficiency cooling tools to
reduce electricity consumption (Hashim et al., 2015). Utilization
of briquette EFB as a solid fuel instead of shredded and pellet
EFB could increase the energy content of EFB by increasing the fuel
calorific value (C
V
)(Yuhazri et al., 2012). Also, the furnace design
and the draft calibrations were improved to help ensure complete
combustion of the biomass (Olisa and Kotingo, 2014). The differ-
ence between monthly carbon emissions of each CPI before and
after implementation of reduction strategies is reported in Table 4
as ‘‘CPI reduction (%)”. In fact, about 18.2–25% of emission reduc-
tions across the CPIs were achieved due to the implementation of
the recommended strategies.
In the Kulim plant, the target was to use as much POME as pos-
sible to generate a steady supply of methane. Thus, the amount of
POME consumption should not be decreased when implementing
the CPI reduction strategy. However, application of a highly effi-
cient anaerobic reactor could increase methane production. In
addition, the other main factor that significantly effect on the
amount of electricity production is the gas-turbine efficiency for
combusting methane gas. Thus, the first strategy to reduce current
CO
2
emission was to decrease fresh and wastewater consumption
by utilizing recycled water (Hashim et al., 2015). Next, application
of cooling tools, which require less energy was suggested to reduce
the electricity consumption significantly. The Kulim plant pro-
duced sludge as solid waste. Since about 98% of the sludge is water,
water recycling could have an impact in reducing the amount of
solid waste. Table 4 shows the difference between monthly carbon
Table 4
Carbon emission reduction strategies and Carbon Performance Indicator (CPI) reduction percentage.
Carbon Performance
Indicators (CPI)
BIO-EXCELL KULIM
CAC Strategy CPI reduction (%) CAC Strategy CPI reduction (%)
Fuel POME + Methane – – – 1, 2 – –
EFB + Diesel + LPG 1 Natural gas utilization instead of
diesel
1–– –
Water consumption 1, 2, 3 Recycle water utilization in all the
process
25.0 1 Recycle water utilization in all the
process
25.0
Electricity consumption 3 High efficiency equipment 20.0 1 High efficiency equipment 20.0
Waste water generation 2 & 3 Recycle and pre-treatment 18.5 1 Recycle and pre-treatment 50.0
Solid waste generation 1 Application of briquette EFB instead
of shredded and pellet EFB
18.2 1 Separation and recycling of sludge
water and re-use in the process
90
Table 5
Carbon Index (CI) for each Carbon Accounting Center (CAC) after reduction strategy implementation.
Carbon Performance
Indicators (CPI)
Emission
Factor
(kgCO
2
e/unit)
Monthly carbon emission equivalent (MCEE) (t CO
2
e)
BIO-EXCELL KULIM
TC or
TG
a
CAC 1 CAC 2 CAC 3 Total TC or
TG
a
CAC1 CAC 2 Total
Steam
Generation
Pre-treatment
plant
Chiller
plant
Methane
Production
Electricity
Generation
Fuel POME (m
3
) 292 – – – – – 2.4 10
5
710
7
–710
7
EFB (Ton) 1100 2.25 10
3
2.5 10
6
– – 2.78 10
6
–– – –
Natural Gas (Liter) 0.002 9.74 10
2
2– – ––––
LPG (kg) 1.53 1.81 10
6
2.8 10
5
–– ––––
Methane(m
3
)2 –– – ––1.610
5
– 3.2 10
5
3.2 10
5
Water (m
3
) 300 1.37 10
4
1.64 10
6
1.35 10
6
1.13 10
6
4.12 10
6
110
4
310
6
–310
6
Electricity (kWh) 0.727 1.65 10
5
– – 1.2 10
6
1.2 10
6
9.6 10
4
710
4
–710
4
Waste water (m
3
) 1670 4.49 10
2
– 4.1 10
5
3.41 10
5
7.51 10
5
4.5 10
3
7.5 10
6
– 7.5 10
6
Solid Waste (kg) 997.9 92 9.2 10
4
– – 9.2 10
4
600 6 10
5
–610
5
Total Monthly CO
2
e (tCO
2
e) 4.51 10
6
1.76 10
6
2.67 10
6
8.94 10
6
– 8.1 10
7
3.2 10
5
8.132 10
7
Carbon Profile (%) 50.47 19.7 29.86 100 – 99.61 0.39 100
Carbon Index (tCO
2
e) 632.58 246.7 374.21 1253.49 – 1196.8 4.73 1197.19
a
Total consumption/generation of each fuel/material in a month.
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Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
emissions of each CPI before and after implementation of reduction
strategies as ‘‘CPI reduction (%)”. In fact, about 20–90% reduction of
various CPIs are attributed to the implementation of the recom-
mended strategies.
Data for CI of each CAC following the reduction strategies are
summarized in Table 5. Initially, the CO
2
emissions in the Bio-
Xcell and Kulim plants were 10.82 10
6
and 9.552 10
7
tCO
2
e,
respectively; however, after emission reduction strategies
were implemented, CO
2
emissions decreased to 8.94 10
6
and
8.15 10
7
tCO
2
e, respectively. The total monthly CO
2
emissions
related to the two case studies before and after reduction strategies
were implemented appear in Fig. 5, with 17.4% and 15% reduction
for Bio-Xcell and Kulim, respectively.
The bar charts in Fig. 6 compare the CEIs of the two plants
before and after the implementation of reduction strategies. CEI
is the main indicator of whether the strategies to reduce CO
2
emis-
sions are successful. In general, all the CEIs across the CPI for the
two companies decreased. For example, in Bio-Xcell, the CEI for
fuel and water significantly decreased after the reduction strate-
gies were implemented.
Fig. 7 presents four pie charts of the CEP of the two cases before
and after the reduction strategies. The hot spot in each case study
is highlighted in the pie charts. Fuel and water consumption are
the hot spots for the Bio-Xcell companies due to the largest CEP
while POME consumption and waste water generation are the
hot spots for Kulim. Nonetheless, the CEP for fuel consumption sig-
nificantly increases from 47.7% to 80.7%. Notably, the solid waste
generation declines from 40.9% to 6.9% (90% reduction), which sug-
gest that the reduction strategies are effective.
4. Comparison of CO
2
reduction: EFB and POME vs. coal and
diesel
The CO
2
emissions from the different fuels are compared in this
section. According to the EU Directive, CO
2
or GHG emissions
reduction savings is calculated by Eq. (6) (Zutphen and Wijbrans,
2011):
Percentage of CO
2
reduction
¼CO
2
emission of fossil fuel consumptionCO
2
emission of POME consumptionÞ
CO
2
emission of fossil fuel consumption
ð6Þ
Fig. 5. Total monthly CO
2
emission before and after implementation of reduction
strategies.
Fig. 6. Carbon Emission Index (CEI) of each Carbon Performance Indicator (CPI) before and after reduction strategy implementation; (a) Bio-Xcell and (b) Kulim plants.
N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx 7
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
CO
2
emissions from palm oil waste are lower compared to fossil
fuels. Table 6 reveals that EFB and POME combustion could reduce
CO
2
emissions by 57–65% and 85.8–89.2%, respectively, compared
to coal and diesel. Olisa and Kotingo (2014) compared the utiliza-
tion of EFB and natural gas in power generation and confirmed that
EFB utilization was more economical and had significant advan-
tages. Agricultural waste materials such as EFB or POME are abun-
dantly available as renewable fuels for power generation.
Utilization of these wastes translates into cheaper feedstock for
power generation. Furthermore, significant reduction of capital
costs, landfills, GHG emissions from EFB composting and POME
ponds suggest that investment in renewable energy is economi-
cally viable (Aditiya et al., 2016; Sivasangar et al., 2015).
5. Effect of oil palm biomass power on Malaysia’s economy
The amount of available oil palm biomass in Malaysia from the
stated fresh fruit bunch (FFB) is reported in Table 7. The total pro-
duction of oil palm biomass is about 114 Mt (Ng et al., 2012;
Aditiya et al., 2016). Consequently, the potential energy that can
be generated is equal to 48.2 Mt/y of oil equivalent based on the
amount of available biomass. Although the value could provide
sufficient electrical energy for Malaysia, huge amount of that is
wasted due to the inefficient utilization of the available biomass.
Recently, the Malaysia’s government has set a target to increase
its biomass power capacity to 800 MW by 2020 and 500 MW is to
be generated from oil palm biomass (KeTTHA, 2011; Ng et al.,
a)
b)
BEFORE AFTER
BEFORE AFTER
Fig. 7. Carbon Emission Profile (CEP) of each Carbon Performance Indicator (CPI) before and after reduction strategy implementation; (a) Bio-Xcell and (b) Kulim plants.
Table 6
Percentage of CO
2
reduction when fossil fuels are substituted with EFB and POME.
Fuel EF (CO
2
e/unit) Consumption Monthly carbon emission
equivalent (t CO
2
e)
CO
2
reduction by EFB or
POME combustion (%)
Bio-Xcell EFB 1100 kg/t 2250.3 tone 2.5 10
6
–-
Coal
a
2566 kg/t 2250.3 tone 5.8 10
6
57.0
Diesel
b
2.7 kg/liter 2250.3 tone (2647.4 10
3
l) 7.15 10
6
65.0
Kulim POME 292 kg/m
3
2.4 10
5
m
3
710
7
–-
Coal
a
2566 kg/t 2.4 10
5
m
3
(1.92 10
5
tone) 4.93 10
8
85.8
Diesel
b
2.7 kg/liter 2.4 10
5
m
3
(2.4 10
8
l) 6.5 10
8
89.2
a
Bituminous Coal (C
137
H
97
O
9
NS), C = 89.06 wt%; O
2
= 6.72 wt%; S = 0.74 wt%.
b
Diesel Fuel (C = 82.5% (ASTM D5291); H = 12.75% (ASTM D5291); S = 15 ppm (ASTM D240/516))”.
8N.A.S. Amin, A. Talebian-Kiakalaieh / Waste Management xxx (2017) xxx–xxx
Please cite this article in press as: Amin, N.A.S., Talebian-Kiakalaieh, A. Reduction of CO
2
emission by INCAM model in Malaysia biomass power plants dur-
ing the year 2016. Waste Management (2017), https://doi.org/10.1016/j.wasman.2017.11.019
2012). Thus, production of 500 MW electricity from oil palm bio-
mass will lead to huge financial saving as well as significant reduc-
tion of CO
2
emission level in Malaysia. In fact, Malaysia’s electricity
generation cost from fossil fuel in 2017 is equal to 15.2 RM per
MW h (The Star Online, 2017). Therefore, based on the current rate
6.7 10
7
RM equivalent to 1.7 10
7
USD will be saved if oil palm
biomass as a free feedstock is used instead of fossil fuel (coal or
diesel).
6. Conclusions
The carbon accounting and mitigation method (INCAM) is uti-
lized to assess ways to reduce CO
2
emissions from two Malaysian
power plants. By utilizing EFB or POME in their power plants the
two firms clearly lower their CO
2
emissions. The total monthly
CO
2
emissions decrease by 17.4% and 15% for Bio-Xcell and Kulim,
respectively. The power plants could decrease their fuel and water
consumption expenses by replacing fossil fuels with oil palm waste
namely EFB and POME biomass. The carbon emission indexes
across the carbon performance indicators are substantially reduced
by replacing fossil fuels with biomass fuels. The findings from this
study could improve the regional position of Malaysia in the
renewable energy technology market, considering that oil palms
tree, the raw materials for EFB and POME, are abundant and a
major agricultural crop in Malaysia. Investment and utilization of
one of the most valuable local waste products in the energy gener-
ation process not only could eliminate various environmental con-
cerns in Iskandar Malaysia, but also potential to improve the local
economy.
Acknowledgements
The authors would like to express their sincere gratitude to the
MIT-UTM Sustainable City Program under the Institute Sultan
Iskandar, Universiti Teknologi Malaysia. We would also like to
thank both Bio-Xcell and Kulim Group Oil Palm Mill for providing
us with the data of the power plants.
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Table 7
The amount of available oil palm biomass in Malaysia.
Palm biomass Quantity
(Mt/y)
a
Net calorific
value (MJ/t)
b
Potential energy
(MTOE/y)
c
EFB 22.1 18795 9.9
Mesocarpfibre 13.6 19055 6.2
Palm kernel shell 5.5 20093 2.6
POME 72.8 16992 29.5
Total 114 48.2
a
Aditiya et al. (2016).
b
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c
1 Mt of oil equivalent (MTOE) = 41868 MJ.
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2
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