Energy Efficiency 1

KXGM 6302 Energy Efficiency

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CHAPTER 1:

EMISSION PRODUCTION

Summary

Emissions in the process utilization produce adverse effects on the environment that

influent human health, organism growth, climatic changes and so on. The Kyoto

protocol by the United Nation Framework Convention on Climate change (UNFCC) in

December 1997, prescribed legally binding greenhouse gas emission target about 5%

below their 1990 level. About 160 countries including Malaysia now adopt this

protocol. The electricity generation is one of the main contributors for emission in the

country. In order to calculate the potential emission by this activity, the type of fuel use

should be identified. Malaysia has changes fuel use gradually from 70% of gas, 15% of

coal, 10% of hydro, and 5% of petroleum in year 2000 to 40% of gas, 30% of hydro,

29% of coal, and only 1% of petroleum in the year of 2020. The changes on fuel type

have changes the pattern of emission production. This study attempts to predict the

pattern of emissions from 2002 to 2020 due to these changes. The calculation is based

on emissions for unit electricity generated and the percentages of fuel use for electricity

generation. The study found that, the electricity generation company has contributed

huge emissions from their power plants in this country.

1. Introduction

Over the past decades, it has been observed that there is an increasing atmospheric

concentration of greenhouse gases such carbon dioxide (CO2) and other emissions that

give negative impact to the environment such as sulfur dioxide (SO2), nitrogen oxide

(NOx) and carbon monoxide (CO). One of the main contributors of these gases is

generated by power generation because a conventional power stations burn fossil fuels

to produce electricity. Burning fossil fuels is releases the emissions such as mentioned

gasses which known can cause greenhouse gas emission effect, acid rain and other

negative impact to environmental and humankind.

CO2 is a colorless, odorless gas and produced when any form of carbon is burned in an

excess of oxygen. Due to this reason, CO2 greenhouse effect in the world has been

enhanced. This means that the atmosphere is trapping more heat that has to escape to

space. This enhancement has linked the greenhouse effect is causing global warming.

CO2 is the largest contributor of greenhouse effect out of all the gasses produce by

human activities.

SO2 is a colorless gas, from the family of sulfur oxides (SOx). It reacts on the surface of

a variety of atmosphere solid particles and can be oxidized within atmosphere water

droplets. Fossil fuel combustion is the main sources of SO2 produce by human activities.


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NOx are a collective term used of two types of oxides of nitrogen namely nitric oxide

(NO) and nitrogen dioxide (NO2). NO is a colorless, flammable gas with a slight odor.

NO2 is a nonflammable gas with a detectable smell and in certain concentration will

highly toxic, which is in long time can cause serious lung damage. NO2 is plays a major

role in the atmospheric reactions that produce ozone or smog. In the atmosphere, NO2

will mix with water vapor producing nitric acid and deposited as acid rain.

CO is a colorless, odorless, poisonous gas. Exposure to CO reduces the blood's ability to

carry oxygen. CO is a product of incomplete burning of hydrocarbon-based fuels. CO

consists of a carbon atom and an oxygen atom linked together. During normal

combustion, each atom of carbon in the burning fuel joins with two atoms of oxygen

forming a harmless gas. When there is a lack of oxygen to ensure complete combustion

of the fuel, each atom of carbon links up with only one atom of oxygen forming carbon

monoxide gas.

Malaysia planning to reduce the production of CO2, SO2, NOx and CO in the country

but the data of production of these gasses is unavailable therefore the study attempts to

estimate potential production of these gases from electricity generation in this country.

With exact figure of these emissions, Malaysia can contribute to undermine the disaster

caused by these gases by maximizing of using renewable power plant.

2. Survey Data

The data used for this study are the electricity consumption data, percentage of fuel type

for electricity generation data and emissions of CO2. SO2, NOx and CO from fossil fuel

for a unit electricity generation data. These data are collected from the Refs. [1-3]. All

of the survey data are tabulated in Tables 1.1, 1.2 and 1.3.

Table 1.1

Electricity generation data

Year Total

(GWh)

1970 2175

1980 7912

1990 19 469

1991 21 442

1997 49 080

2000 52 300

2010 105 762

2020 195 253


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Table 1.2

Percentage of electricity generation based on fuel types

Year Coal

(%)

Petroleum

(%)

Gas

(%)

Hydro

(%)

2000 15.00 5.00 70.00 10.00

2010 18.00 2.00 50.00 30.00

2020 29.00 1.00 40.00 30.00

Table 1.3

CO2, SO2, NOx and CO emission from fossil fuel for a unit electricity generation

Fuels Emission (kg/kWh)

CO2 SO2 NOx CO

Coal 1.18 0.0139 0.0052 0.0002

Petroleum 0.85 0.0164 0.0025 0.0002

Gas 0.53 0.0005 0.0009 0.0005

Hydro 0.00 0.0000 0.0000 0.0000

Other 0.00 0.0000 0.0000 0.0000

3. Methodology

This study uses the scenario approach for the analysis. Schwartz [4], states that

scenarios are tools for ordering perceptions about alternative future environments and

the end result might not be an accurate picture of tomorrow, but can give a better

decision about the future. No matter how things might actually turn out, both the analyst

and the policy maker will have a scenario that resembles a given future and that will

help us think through both the opportunities and the consequences of that future.

This analysis is generally based on modeling methodologies to figure out the potential

emissions from electricity generation in Malaysia in the future. For this purpose,

initially, the electricity pattern and percentage type of fuel use for electricity generation

should be identified. Some of the data are already available but others have to be

calculated with respect to the county electricity consumption trend. The method used to

estimate the rest of the calculation data is polynomial curve fitting. The method is an

attempt to describe the relationship between variable x as the function of available data

and a response y. Which seeks to find some smooth curve that best fit the data, but does

not necessarily pass through any data points. Mathematically, a polynomial of order k in

x is expressed in the following form [5]:

k

k xcxcxccy ...2210 (1)


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The pattern of emission due to the fuel changes is potential production of emissions by

electricity generation in Malaysia. The common gasses are consisting CO2, SO2, NOx

and CO. Emission pattern of the electricity generation can be calculated by the

following equation:

)...( 332211 np

nipipipiii EmPEEmPEEmPEEmPEEPEM (2)

4. Data Analysis

There are two types of data to be analyzed i.e. electricity consumption data and

percentage of fuel type data that mainly used for electricity generation. These fuels are

coal, petroleum, gas and hydro. Based on the data shown in Table 1.1, using Eq. (1), the

total energy consumption in Malaysia from year 2002 to year 2020 can be predicted by

the following equation:

9941.0R , x x y 221 100.65 1333.25755.9 (3)

Based on the data shown in Table 1.2, using Eq. (1), the fuel mix of electricity

generation in Malaysia from the year 2002 to 2020 can be predicted. The percentage of

coal used for electricity generation in Malaysia can be predicted by the following

equation:

1 , 00040 0010 150 222 Rx. x. .y (4)

The percentage of petroleum used for electricity generation in Malaysia can be

predicted by the following equation:

1 , 00010 0.004 05.0 223 Rx.x y (5)

The percentage of gas uses of electricity generation in Malaysia can be predicted by the

following equation:

1 , 0.0005 0250 7.0 224 Rxx.y (6)

The percentage of hydropower uses of electricity generation in Malaysia can be

predicted by the following equation:

1 , 0010 0.03 0.1 225 Rx.x y (7)

The results of the predicted data based on Equations (3), (4), (5), (6) and (7) from the

year 2002 to 2020 are tabulated in Table 1.4 and illustrated in Fig. 1.1. The fuel

percentage trend will be used to predict future potential emissions. The emissions


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produced from fuel burden for generating electricity is calculated in term kg/kWh of

electricity generation.

Table 1.4

Predicted electricity consumption and percentage fuel mix of electricity generation in

Malaysia

Year Total

(GWh)

Coal

(%)

Petroleum

(%)

Gas

(%)

Hydro

(%)

2002 66159 14.96 4.24 65.20 15.60

2003 71368 15.06 3.89 62.95 18.10

2004 76779 15.24 3.56 60.80 20.40

2005 82390 15.50 3.25 58.75 22.50

2006 88203 15.84 2.96 56.80 24.40

2007 94217 16.26 2.69 54.95 26.10

2008 100433 16.76 2.44 53.20 27.60

2009 106850 17.34 2.21 51.55 28.90

2010 113468 18.00 2.00 50.00 30.00

2011 120287 18.74 1.81 48.55 30.90

2012 127308 19.56 1.64 47.20 31.60

2013 134530 20.46 1.49 45.95 32.10

2014 141954 21.44 1.36 44.80 32.40

2015 149578 22.50 1.25 43.75 32.50

2016 157404 23.64 1.16 42.80 32.40

2017 165431 24.86 1.09 41.95 32.10

2018 173660 26.16 1.04 41.20 31.60

2019 182090 27.54 1.01 40.55 30.90

2020 190721 29.00 1.00 40.00 30.00

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Hydro

Gas

Petroleum

Coal

Fig 1.1. Predicted

electricity consumption and percentage fuel mix for electricity generation in Malaysia


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5. Results

The changes of energy sources for electricity generation have contributed for emissions

pattern in Malaysia. To replace hydropower the utilities have to increase the use of coal.

This replacement can be avoided if Malaysian government plans from now. The utilities

should switch this replacement to another renewable energy sources such as geothermal,

photovoltaic, solar thermal, wind and biomass. This can help to reduce emission in the

future and also helps Malaysian utilities to survive in the global market. This is due to

high cost of conserving emissions in the future. Conducting life cycle cost analysis of

conserved emissions and investment is necessary. However, this analysis is not

discussed in this study. Detail explanation of cost of conserved emissions is discussed

by Ref [6].

The pattern of emissions is a function of the total energy consumption multiplied by the

percentage of fuel mix and the amount of emissions by the fossil fuel from every unit of

electricity generation. The pattern of emissions by electricity generation in Malaysia is

tabulated in Table 1.5 and illustrated in Fig. 1.2.

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

SO

2,

NO

x,C

O P

roduction

0

10000000

20000000

30000000

40000000

50000000

60000000

70000000

80000000

90000000

100000000

110000000

120000000

CO

2 P

roduction

SO2

NOx

CO

CO2

Fig. 1.2. Pattern of emissions production by electricity generation in Malaysia


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Table 1.5

Potential emissions production by electricity generation in Malaysia

Year Emissions production (Ton)

CO2 SO2 NO2 CO

2002 36 925 190 205 146 97 301 24 108

2003 38 853 310 217 390 103 264 25 168

2004 40 871 919 230 813 109 693 26 228

2005 42 999 341 245 625 116 664 27 292

2006 45 258 018 262 069 124 267 28 366

2007 47 670 787 280 395 132 593 29 457

2008 50 263 503 300 877 141 743 30 572

2009 53 062 992 323 804 151 821 31 718

2010 56 098 579 349 481 162 940 32 906

2011 59 401 570 378 236 175 220 34 143

2012 63 005 748 410 416 188 788 35 443

2013 66 945 895 446 377 203 775 36 814

2014 71 259 772 486 505 220 324 38 271

2015 75 985 624 531 189 238 577 39 825

2016 81 165 687 580 852 258 690 41 492

2017 86 842 673 635 925 280 822 43 285

2018 93 062 310 696 863 305 141 45 221

2019 99 871 266 764 132 331 819 47 316

2020 107 318 707 838 219 361 035 49 587

The results from Table 1.5 show that the total emissions production are about 1 216

862 891 ton of CO2, 8 184 313 ton of SO2, 3 704 479 ton of NOx and 667 212 ton of

CO. These are huge amount of emission for small developing country like Malaysia.

6. Conclusions

The emissions from electricity generation contributed the largest emission for the

country. Government intervention to abate this emission is urgently needed at the

present. The study also shows that emissions pattern from electricity generation of fossil

fuel to renewable fuel such as hydropower offers a solution and multiple benefits to

utility, society and most important to protect environment protection. Malaysian

government has to find ways to reduce these emissions, such as by introducing

emissions taxation which can be used to subsidies renewable energy power plant or for

replanting threes of the rain forest in the country. The data from the study can be a basis

for calculating cost benefit analysis for implementation of new renewable sources for

electricity generation and emission abatement program in Malaysia.


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Notation

c,k Constant value

iEM Total emission for a unit electricity generation (kg,

Ton) n

pEm Fossil fuel emission for a unit electricity generation of

fuel type n (kg)

iEP Electricity production in year i (GWh)

n

iPE Percentage of electricity generation in year i of fuel

type n (%)

x Year predicted – year start

y Predicted value

References

[1] Economic Planning Unit. Study on energy policy analysis and planning to the year

2020. Prime Minister Department, Kuala Lumpur, Malaysia, 1996. [2] Department of Electricity & Gas Supply. Statistics of electricity supply industry in

Malaysia. Kuala Lumpur, Malaysia, 1999.

[3] Jaafar MZ, Yusop YM. Malaysian energy sector and current energy supply and

demand forecasting, Kuala Lumpur, Malaysia, 1998.

[4] Schwartz P. The Art of the Long View: Planning in an uncertain world, Doubleday,

New York, 1996.

[5] Klienbaum DG. Applied regression analysis and other multivariable methods. ITP

co., USA, 1998.

[6] Krause F, Koomey J. Unit costs of carbon savings from urban trees, rural trees, and

electricity conservation: a utility cost perspective, Lawrence Berkeley Laboratory,

University of California, Berkeley. 1990,

Documents

Energy Efficiency 1