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ALTERNATIVE ANALYSIS OF THE TRANSBOUNDARY AIR POLLUTION
PROBLEMS IN NORTHEAST ASIA

By

Won Park

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Resource Development

1998

ABSTRACT

ALTERNATIVE ANALYSIS OF THE TRANSBOUNDARY AIR POLLUTION
PROBLEMS IN NORTHEAST ASIA

By

Won Park

The recently increasing industrialization and urbanization in Northeast Asia has
led to a large volume of air pollutants being emitted in this region. The growth rate of the
total emissions is still increasing alarmingly. China has been the major contributor to the
total emissions of air pollutants in Northeast Asia. Westerly winds, a unique regional
meteorological phenomenon, prevail throughout the year, and the long-range transport of
air pollutants is propelled by those winds. As a result, nations in Northeast Asia are very
concerned about potential problems with long-range transport of air pollutants from
foreign sources. This is because air pollutants emitted from one nation’s ground facilities
and mobile sources travel hundreds or even thousands of miles by the effects of air
pressure and wind drift, and can bring damage to other nations’ ecosystems and human
health. For example, Korea is located in the eastern part of the region and it can be
signiﬁcantly affected by the air pollutants transported from China.

This dissertation research deals with the transboundary air pollution problem
between China and Korea. Among many problems related to transboundary air pollution,
this study concentrates on the following two issues:

0 Firstly, the negative consequences of transboundary air pollution from China at

industrial sites in Korea; and

O Secondly, the prediction of the future impact of China's sulfur dioxide and nitrogen
oxide emissions on the air quality in Korea.

The results of the case study in Chapter 3 show evidence of the negative impacts of
the transboundary air pollution in Korea. The production loss in Korea is an example of
the negative impact brought about by transboundary movement of Chinese air pollutants.
The runs of the computer aided simulation model in Chapter 4 show projected emission
trends in China and Korea until the year 2010. The simulation results show that the total
amount of sulfur dioxide and nitrogen oxide emissions in China and Korea will continue
to increase at high rates, which means more and more of those air pollutants are projected
to be transported from China into Korea. The total amount of Chinese emissions was
more than ten times, in the case of sulfur dioxides, and one hundred times, in the case of
the nitrogen oxides, the amount of the Korean emissions during the years from 1990
through 1996. Therefore, a small portion of the Chinese emissions, if transported into
Korea, will cause a great increase of the concentration level of those air pollutants in
Korea. The simulation model shows several scenarios of policy options which are
effective in slowing down the growth rates of the Chinese and Korean emissions, and
thus the growth rates of the amount of air pollutants to be transported from China into
Korea.

The ﬁndings of this study will be useful in raising public awareness in China and
Korea, and will provide public policy makers with grounds for future environmental
policy generation and cooperation in order to control air pollution and the transboundary

air pollution problems in both nations.

Dedicated To My Dear Parents

ACKNOWLEDGMENTS

I am sincerely grateful to my major professor, Dr. George H. Axinn, for his
endless help, advice, support, and encouragement during all phases of my doctoral
program at Michigan State University. His great willingness to see me regularly with
eagerness has been the strongest driving force towards the fulﬁllment of the program.
His unique qualities as a scholar and mentor will always be remembered and appreciated.

I express my gratitude to Dr. Cynthia F ridgen, Dr. Tom Edens, and Dr. J ianguo
Liu for their guidance and support as Ph.D. guidance committee members. I will reﬂect
on the memories gained with them here for years to come.

I thank the faculty members and fellow graduate students who rendered their
services to me throughout my experience on and off campus. I also appreciate the ofﬁcer
at the TV/monitor bulb panel maker in Korea, who provided me limitless cooperation in
collecting invaluable data but wished to remain anonymous.

Embarking on this adventure in the US. was a difficult decision. Special
gratitude is expressed to Dr. Wan-Soon Kim for his motivation that led me to explore
environmental issues and earn the Ph.D. degree in sustainable development and
environmental policy studies in the United States.

I would like to express my special thanks to my parents for their moral support
and steadfast love, which has always been an inspiration to me. I also owe what I am
today to the encouragement and the sacriﬁce of my brother, and my sister and her
husband. Finally, I am deeply indebted to my dear wife, Seunghee Lee, for all the
achievement of the journey in Michigan. She married a dreamer, and the realization of

his dream is the mm of her help from behind in every aspect of his life.

TABLE OF CONTENTS

LIST OF TABLES. ............................................................................................................ ix
LIST OF FIGURES. ........................................................................................................... x
LIST OF ABBREVIATIONS ........................................................................................... xii
CHAPTER 1
INTRODUCTION ............................................................................................................... 1
CHAPTER 2
LITERATURE REVIEW .................................................................................................... 7
A. Air Pollution and Acid Rain ................................................................................ 7
1. Negative Effects of Air Pollution and Acid Rain ................................... 9
2. Beneﬁts of Controlling Air Pollution for Environmental Protection... 1 2
B. Measuring Beneﬁts and Costs Of Reducing Air Pollution ............................... l4
1. Some Concerns in Measuring Beneﬁts and Costs of Reducing Air
Pollution ............................................................................................... 14
2. Economic Analysis For The Comparison Of Costs And Beneﬁts ........ 16
3. Types of Non-market Beneﬁts: Use, Option, Existence, and Bequest
Values .................................................................................................. 19
4. Measuring the Beneﬁts and Costs in Economic Analysis .................... 20
a. Contingent Valuation Method (CVM) ............................................. 21
b. Travel-Cost Model (TCM) ............................................................... 21
c. Hedonic Pricing ................................................................................ 22
(1. Production Function Approach ........................................................ 22
C. Issues Involved in Measuring and Analysis of Air Pollution ............................ 23

1. Non-conventional Economics Approach: Pricing and Valuing the
Ecological System Services and the Beneﬁts of Air Pollution

Control ................................................................................................. 25
2. Ecological, Technological, Political, Socio-Economic, And Cultural
Factors .................................................................................................. 25
3. Paradigm Shift ..................................................................................... 28
D. Transboundary Air Pollution ............................................................................. 29
1. Deﬁnition ............................................................................................. 3O
2. Types of Transboundary Air Pollution ................................................ 31
3. Other Examples of Transboundary Air Pollution ............................... .32
4. Conventional Analysis Techniques of Transboundary Air Pollution..36
5. Principles of Stockholm Declaration ................................................... 37
CHAPTER 3
CASE STUDY: DETECTION OF THE TRANSBOUNDARY AIR POLLUTION IN
NORTHEAST ASIA ......................................................................................................... 39
A. Methodology .................................................................................................... 40

vi

B. Presentation of Data ......................................................................................... 41

C. Analysis of Data ............................................................................................... 42
l. Shrinkage Rates With and Without Yellow Sand Phenomenon
(January-May, 1995) ............................................................................ 43
2. Average Shrinkage Rates With and Without Yellow Sand
Phenomenon (January-May, 1995) ...................................................... 48
D. Ingredient Analysis of the Sample Particles from the Defect Selection .......... 50
CHAPTER 4
MODELING AND SIMULATION: FORECASTING TRANSBOUNDARY AIR
POLLUTION IN NORHEAST ASIA ............................................................................... 55
A. Methodology .................................................................................................... 57
B. Presentation of Data ......................................................................................... 57
C. Analysis of Data ............................................................................................... 61
1. Analysis of Chinese Data ..................................................................... 62
2. Analysis of Korean Data ...................................................................... 65
3. Comparative Analysis of Chinese and Korean Data ............................ 67
D. Modeling and Simulation Analysis .................................................................. 70
1. Introduction of Model Components ..................................................... 71
2. Assumptions ......................................................................................... 72
3. Process of Simulation Model Construction ......................................... 73
4. Model Validation ................................................................................. 76
a. Validation By Graphical Display and Tabulation ........................... 77
b. Validation By Statistical Analysis: t test and P-value ..................... 80
5. Results of Simulation: Prediction of the Future Emission Trend ........ 82
6. Sensitivity Analyses ............................................................................. 85
a. Magnitudes of Transboundary Air Pollution in Korea at Different
Transboundary Movement Fractions ............................................. 85
b. Economic Performance .................................................................. 91
c. Governmental Environmental Policies .......................................... 97
(1. International Agreement between China and Korea .................... 104
e. Sensitivity Indices ........................................................................ 107
CHAPTER 5
CONCLUSION ................................................................................................................ 1 1 l
A. Findings .......................................................................................................... 113
B. Limitations of This Study .............................................................................. 115
C. Opportunities for Future Research ................................................................. 118
APPENDICES ................................................................................................................. 121
BIBLIOGRAPHY ............................................................................................................ 141

vii

LIST OF TABLES

Table 3-1. Dates with Yellow Sand Phenomenon in the Spring of the Year 1995 ............ 42
Table 3-2. Comparison of Average Shrinkage Rates of Panel Forming Process Lines ...48

Table 3-3. Ingredients: Suspended Particles with and without Yellow Sand PhenomenonSl

Table 3-4. Ingredients of the Sample Particles .................................................................. 53
Table 4-1. Chinese Historical Data Used in Modeling and Simulation ............................. 59
Table 4-2. Korean Historical Data Used in Modeling and Simulation .............................. 60
Table 4-3. Calculated Ratios (China) ................................................................................. 62
Table 4-4. Calculated Ratios (Korea) ................................................................................ 65
Table 4-5. Comparison between China and Korea (Ratio: China/Korea) ......................... 67
Table 4-6. Validation of the Model (Unit: 1,000 tons) ...................................................... 80
Table 4-7. Summary: Results of Statistical Analysis for Model Validation ...................... 81
Table 4-8. Prediction of the Future Emission Generation Trend (Unit: 1,000 ton) ........... 84

Table 4-9. Sensitivity Analysis: Different Transboundary Movement Fractions (S02)....88
Table 4-10. Sensitivity Analysis: Different Transboundary Movement Fractions (NOX) .89

Table 4-11. Total S02 and NO, in Korea at 1% Transboundary Movement Fraction ....... 94

Table 4-12. Sensitivity Analysis: Utilization (Unit: 1,000 ton) ......................................... 97
Table 4-13. Sensitivity Analysis: Regulation (Unit: 1,000 ton) ...................................... 100
Table 4-14. Sensitivity Analysis: Air Pollution Tax (Unit: 1,000 ton) ............................ 104
Table 4-15. Sensitivity Analysis: International Agreement (Unit: 1,000 ton) ................. 107
Table 4-16. Sensitivity Indices: SO2 (Unit Except Indices: 1,000 ton) ........................... 109
Table 4-17. Sensitivity Indices: NOx (Unit Except Indices: 1,000 ton) ........................... 110
Table 4-18. Sensitivity Ranking ...................................................................................... 1 10

viii

LIST OF FIGURES

Figure l. Westerlies in Northeast Asia. ............................................................................... 3
Figure 3-1. Shrinkage Rates, January-May, 1995 (%) ....................................................... 44
Figure 3-2. Shrinkage Rates of Line (A), Small-Sized Products ....................................... 45
Figure 3-3. Shrinkage Rates of Line (B), Large-Sized Products ....................................... 45
Figure 3-4. Shrinkage Rates of Line (C), Mid-Sized Products I ....................................... 46
Figure 3-5. Shrinkage Rates of Line (D), Mid-Sized Products 11 ...................................... 46
Figure 3-6. Shrinkage Rates of Line (E), Mid-Sized Products 111 ..................................... 47
Figure 3-7. Shrinkage Rates of Line (F), Mid-Size Products IV ....................................... 47
Figure 3-8. Comparison of Average Shrinkage Rates ....................................................... 49
Figure 3-9. Pictures of Sample Particles of the Sample Defect Panels ............................. 52
Figure 4-1. Display of the Ratios of Chinese Data ............................................................ 63
Figure 4-2. Display of the Ratios of Korean Data ............................................................. 66
Figure 4-3. Comparative Display of Energy Intensity of China and Korea ...................... 69
Figure 4-4. Model Components ......................................................................................... 72
Figure 4-5. Simulation Model Construction Procedure ..................................................... 76
Figure 4-6. Validation of the Model: 802 in China ........................................................... 78
Figure 4-7. Validation of the Model: NOx in China ........................................................... 78
Figure 4-8. Validation of the Model: 802 in Korea ........................................................... 79
Figure 4-9. Validation of the Model: NOx in Korea .......................................................... 79
Figure 4-10. Prediction of the Future SO2 Emission Generation Trend ............................ 83
Figure 4-11. Prediction of the Future NOx Emission Generation Trend ............................ 84
Figure 4-12. Sensitivity Analysis: Amount of SO2 to Flow Into Korea ............................ 86

Figure 4-13.
Figure 4-14.
Figure 4-15.
Figure 4-16.
Figure 4-17.
Figure 4-18.
Figure 4-19.
Figure 4-20.
Figure 4-21.
Figure 4-22.
Figure 4-23.

Figure 4-24.

Sensitivity Analysis: Amount of NOx to Flow Into Korea ............................ 87
Total SO2 in Korea at 1% Transboundary Movement Fraction .................... 93
Total NO, in Korea at 1% Transboundary Movement Fraction ................... 93
Sensitivity Analysis (S02: 10% Utilization ) ................................................ 95
Sensitivity Analysis (N 0,: 10% Utilization) ................................................ 96
Sensitivity Analysis: SO2 Regulation ............................................................ 99
Sensitivity Analysis: NOx Regulation ......................................................... 100
Sensitivity Analysis: SO2 Air Pollution Tax Policy .................................... 102
Sensitivity Analysis: NOx Air Pollution Tax Policy ................................... 103
Sensitivity Analysis: SO2 An International Agreement .............................. 106
Sensitivity Analysis: NOx - An International Agreement ........................... 106
Sensitivity Analysis Index ........................................................................... 108

LIST OF ABBREVIATIONS

AP ............................................................................................................... Associated Press
Avg ........................................................................................................................... Average
BTU (Or Btu) ....................................................................................... British Thermal Unit
CFCs .................................................................................................... Chloroﬂuorocarbons
CH4 ............................................................................................................................. Methane
CO ............................................................................................................ Carbon Monoxide
CO2 ............................................................................................................. Carbon Dioxides
CVM ...................................................................................... Contingent Valuation Method
DT ....................................................................................................................... Delta Time
ECE ............................................................................... Economic Commission for Europe
ECE/UN ............................................... Economic Commission for Europe, United Nations
EIA ................................................................................ Energy Information Administration
EMEP .......................................................... European Monitoring and Evaluation Program
GDP ................................................................................................ Gross Domestic Product
HCFCs ......................................................................................... Hydrochloroﬂuorocarbons
HPS ..................................................................................... High Performance Systems, Inc
ILA ........................................................................................ International Law Association
MC ......................................................................................................... Methyl Chloroforrn
NIER ............................................................. National Institute of Environmental Research
NOx .............................................................................................................. Nitrogen Oxides
NSWS .................................................................................. National Surface Water Survey
O3 ................................................................................................................................ Ozone

xi

OECD ....................................... Organization for Economic Cooperation and Development

PEC ........................................................................................ Primary Energy Consumption
SO2 ............................................................................................................... Sulfur Dioxides
TCM ........................................................................................................ Travel-Cost Model
TSP’s ....................................................................................... Total Suspended Particulates
US. EPA .......................................... The United States Environmental Protection Agency
VOCs ...................................................................................... Volatile Organic Compounds
WRI .............................................................................................. World Resources Institute
WTA ................................................................................................. Willingness To Accept
WTP ....................................................................................................... Willingness To Pay
WWF ................................................................................. World Wide Fund for the Nature

xii

Chapter 1

INTRODUCTION

Recently, international interest in the environment has grown and become focused
on global environmental issues arising from anthropogenic emissions. These emissions
are known to originate frequently far from the site of impact, and bring about various
negative environmental consequences. Some of those consequences are global warming,
acidiﬁcation of the natural environment including soil and aquatic systems, toxicity to
terrestrial and aquatic ecosystems by the deposit of heavy metals, ozone-related forest
and crop damage, and visibility impairment by suspended particles in the atmosphere.
For example, acid rain has signiﬁcant negative inﬂuence on the ecosystem for a short
period, for which international policing of emission discharges presents a great problem.

In Northeast Asia, because of the increasing industrialization and urbanization in
countries including China, Korea, and Japan during recent years, a large volume of air
pollutants has been increasingly emitted. Particularly, a large proportion of the pollutants
have been emitted by China, which has been among the highest sulfur dioxide (80,)
emitting countries in the world.1 These are contributed by coal and heavy oil-ﬁred
sources concentrated on the Yellow Sea coastal area2 such as Shantung peninsula,

Shanghai region and Kangsao province centered in Peking. (N IER, 1991)

 

' World Wide Fund for the Nature reports, “China is the world's second largest producer of the greenhouse
gas, carbon dioxide (C02) - accounting for 10 per cent of the world's CO2 emissions.” (WWF, 1998)

2 The Yellow Sea lies between China and the Korean Peninsula. Therefore, Yellow-sea coastal region of
China refers to its eastern coast.

Additionally, there is a unique meteorological phenomenon to consider in
Northeast Asia. Westerly winds prevail in this region and the long-range transport of air
pollutants is inﬂuenced by this weather condition (Figure 1). As a result, countries in
Northeast Asia under the inﬂuence of westerly winds are very concerned about potential
problems with long-range transport of air pollutants originating abroad, and each country
is interested in dealing with these problems effectively. Air pollutants emitted from a
nation’s ground facilities and mobile sources travel hundreds or even thousands miles by
the effect of air pressure and wind drift, e. g. westerly wind, and can bring damage to
other nation’s natural environment and ecosystem, and human health.

It has been known that air pollutants and Yellow Sands are transported from the
west to the east in Northeast Asia. In particular, Korea, located in the easternmost part of
the region, can be signiﬁcantly affected by the air pollutants transported from China.
This includes the suspended particulates in the atmosphere brought by the dust storms.
This is known as the “Yellow Sand Phenomenon,”3 which occurs in early spring. Those
air pollutants and the dusts in the air, “Yellow Sands,” are transported by the westerly
winds that prevail in the region. Therefore, Korea is concerned about the growth of the
SO2 and nitrogen oxides (N 0,) emissions in China and their negative inﬂuences on the
air quality in Korea, as well as the concentration level of the total suspended particulates

(TSP’s) in the atmosphere in Korea.

 

3 The outbreak of dust storms (‘ Yellow Sands ') ﬁom Northern China and Mongolia is observed to occur
several times in spring. A dust cloud can travel to Korea and Japan in 1-4 days from the source region. In
Korea, as dust clouds invade, visibility less than 1 kilometer has been observed and atmospheric

Figure l. Westerlies in Northeast Asia4

 

 

 

 

 

According to research, long-range transport of air pollutants in Northeast Asia has
been detected, and can signiﬁcantly affect Korea, located to the far east of the Westerly
region in Northeast Asia. (N IER, 1991) Two relevant examples are as follows. The air
pollutants transported from China by dust storms, known as the “Yellow Sand
Phenomenon,” during early spring, are driven by the synoptic weather condition. Also
the average acidity level of the rainfall in Baekryung Island.s Findings of a study of the
relationship between the acidity level of the rainfall and the air pressure in the Island

show that it is more acidic than its counterpart in the inland peninsula. (N IER, 1987)

 

concentration of particulate matters including Yellow Sands up to 1.105 ug/m’ have been recorded. (NIER,
1991)

‘ This map was created by the author of this dissertation, based on the outlines that were copied from the
clip arts collection of Microsoﬂ‘ Oﬂice 95 and pasted into this Chapter. Grey colors, arrows, and letters
were added by the author.

’ Baekryung Island is located in Yellow Sea coastal region of Korea, which is its western coast. The Island
does not have any signiﬁcant emission sources.

These two examples clearly indicate that the acid deposition in Korea to a certain extent
originates from the west.

However, until recently, not much attention was paid to antecedent negative
consequences of the transboundary air pollution on the natural environment, economic
activities, and human health in Northeast Asia. In particular, there has been lack of
scientiﬁc research that deals with the economic and non-economic consequences of the
transboundary air pollution in the region.

Under these circumstances, it is appropriate to study the international
environmental problems arising from long-range transport of air pollutants in Northeast
Asia. Some of the major issues in Northeast Asia with regard to the transboundary air
pollution are:

0 If there are really transboundary air pollution problems;

0 If so, how much air pollution is transported in the region;

0 What the negative consequences on the natural environment and human health are;
and

0 How the problem should be solved.

Currently, government sponsored research projects are now being carried out in
Korea to investigate domestic and foreign emission sources, transboundary movement
routes of foreign emissions, and the amount of air pollutants transported into Korea. In
those projects, satellite monitoring, wind trajectory analysis,6 and ﬂight measurements"

are used as major methods. Observations have also been made focusing on the climatic

 

° Wind trajectory analysis is a useful analysis to provide information about the origin of foreign pollutants
deposited at a particular site. (Flinterman et al., 1986)

7 Flight measurements is used to observe the behavior of pollutants over long distances. (Flinterman et al.,
1986)

patterns during the period when the Yellow Sand Phenomenon takes place. Some
measurements of the air quality and the acid deposition, both dry and wet, have also been
carried out in Korea during recent years.

Among many problems related to the transboundary air pollution in Northeast
Asia, this dissertation research will concentrate largely on:

0 First, the impact of transboundary air pollution from China at industrial sites in
Korea (Chapter 3); and

0 Second, the amount of air pollutants transported into Korea from China by the
transboundary movement in terms of S02 and NOx (Chapter 4).

This study presents valid evidence of the negative impacts of the transboundary
air pollution at industrial sites in Korea by the case study in Chapter 3. This study also
tries to project the future emission trend in China and Korea and the amount of air
pollutants to be transported from China to Korea, by building a simulation model in
Chapter 4.

The outcome will provide public policy makers with grounds for future
international environmental policy cooperation in Northeast Asia. In future research by
other scholars or the author of this dissertation, policy cooperation or agreement in
Northeast Asia, especially between China and Korea, might be created based on the basis
of this research. This study may also contribute to avoiding potential environmental and
political conﬂicts between China and Korea, arising from transboundary movement of air
pollutants from China into Korea.

The next section, Chapter 2, presents the literature review. It explores: air

pollution and acid rain, negative effects of air pollution, costs and beneﬁts of air pollution

control, issues in measurement of beneﬁts and costs of air pollution, and transboundary

air pollution problems in general and in Northeast Asia.

Chapter 2

LITERATURE REVIEW

Air pollution has long been a problem in human societies throughout the world. It
was during and aﬁer the Industrial Revolution when air pollution began to be paid public
attention. Even in those times, various efforts were made to prohibit using coal in open
furnaces, unhealthy and noxious emissions from steam engines, smoke or odor from
manufacturing and so on.8

As human economic activities have increased rapidly, the air pollution problem
has become a more serious threat to human and natural environment and health. The
growth of economic wealth and welfare throughout the world has led to more and more
attention being paid to the air pollution problem. What is more, clean air, in both local
and global contexts, has become a critical factor in human welfare. This chapter attempts

to explore issues involved with air pollution and transboundary air pollution.

A. Air Pollution and Acid Rain

There can be different perceptions and deﬁnitions of air pollution according to a
person or a society’s experiences and social, cultural, and historical environment. One of
them is the one generally accepted in international law, according to the International

Law Association’s Montreal Rules of 1982. It states, “‘Pollution’ means any introduction

 

' Some of the efforts included ﬁnes, the demolition of pollution generating facilities, and the ultimate
punishment such as the death sentence to violators in England during the King Edward I era, in 1306.
(Flinterman, et al., 1982)

by man, directly or indirectly, of substance or energy into the environment resulting in
deleterious effects of such nature as to endanger human health, harm living resources,
ecosystems and material property and impair amenities or interfere with other legitimate
uses of the environment.” (ILA, 1982: 159) This deﬁnition can also be applied to the
atmospheric setting, and then it becomes the deﬁnition of air pollution. In a rather
technical approach, Frank and Brownstone argue, “Pure” air consists of a little under 21
percent oxygen, a little over 78 percent nitrogen, and small amounts of carbon dioxide,
argon, and other elements; water vapor is also present to some degree. Everything else is
a contaminant. Air pollutants may be gases, liquid droplets, solid particles . .. or a
combination of these. (Frank and Brownstone, 1992: 6) However, in a broad context,
when there are substances concentrated in the atmosphere that are not friendly with
environmental health, it may be considered to be air pollution.

The air pollutants in the atmosphere bring about various problems in the natural
environment and human health. One of the serious air pollution problems is acid rain, or
acid deposition. The air pollutants that cause acid rain are commonly known to be sulfur
dioxide (80,) and nitrogen oxides (N 0,), emissions of which react to form various acidic
compounds when they get mixed with water, oxygen, and oxidants in the atmosphere.

(U .S. EPA, 1998) Those compounds fall to the earth either in dry form, examples of
which are gas and particles, or in wet form, examples of which are rain, snow, and fog.
Acid rain causes various problems. (U .S. EPA, 1998) Some of them include acidiﬁcation
of lakes and streams, damage to trees, the decay building materials and paints and so on.

According to R. S. Scorer's deﬁnition, acid rain refers to “all the mechanisms

whereby acidity is deposited on objects on the ground. Acid rain has a signiﬁcant

negative inﬂuence on the ecosystem for a short period, such that international policing of
discharges presents a great problem.” (Rose, 1984: 1)

When there are prevailing winds, the acidic compounds formed in the atmosphere
are transported by then winds. They ﬂy sometimes over a far distance over national
borders, which causes conﬂicts between nations or between regions. Scorer argues “. .. it
is necessary to cope with the international environmental problems arising from Long-

range transport of air pollutants.” (Rose, 1984: 1)

1. Negative Effects of Air Pollution and Acid Rain

Various human economic activities such as running power stations for electricity,9
manufacturing products, running automobiles, building structures,'0 and running
appliances create air pollution. Sometimes natural phenomena such as eruption of
volcanoes also cause air pollution.

The air pollution coming from those human activities does not stay in the
atmosphere forever, but returns to the earth as acid rain.” Acid rain, due to the emissions
of air pollutants, brings about serious negative environmental impacts on forests and
lakes at a distance from pollution sources. However, it also results in some of the
important detrimental consequences such as accelerated corrosion of building materials,
deterioration of stone monuments, and crop damage. (Flinterrnan et. al., 1986) The
negative impacts of air pollution and acid precipitation on the natural environment and

human health can be categorized into the following ﬁve major areas.

 

9 Most of the power stations produce electricity by burning fossil fuels like coal, oil and gas
‘° Houses and other building structures use gas or coal ﬁres for heating.

Firstly, air pollution damages aquatic ecosystems by acidiﬁcation of surface
waters such as lakes or rivers. The acidiﬁcation of lakes, water in dams and rivers is
increased by acid rain and the death of aquatic life often takes place as a result.‘2 Acid
rain can damage the water and the wildlife in lakes.‘3 Besides, the transboundary
characteristics of acid rain can also cause acidiﬁcation of surface waters on a remote site.

Secondly, soils, forests, plants and crops get negative effects from air pollution.
Acid rain destroys many vital substances and washes away the nutrients, thus damaging
the soils. Damage to the soils is one of the most serious effects of acid rain, because
healthy soil is an essential factor for the growth of trees, plants, and crops. Acid rain
does not only damage the soils but can also do harm to the trees, plants and crops
directly.”

Thirdly, air pollution deteriorates man-made materials. Whether it is in wet or
dry forms, the acid precipitation and deposition is known to contribute to the corrosion or
deterioration of metals, stone and paint on buildings, historic structures, cultural objects,
cars, ordinary houses and other structures. The value of those objects affected by acid

rain gets depreciated seriously, and it means a loss to society. Increased maintenance

 

” Throughout this dissertation, the terms "acid rain" and "acid precipitation" include dry deposition.

‘2 A healthy lake has a pH of around 6.5 and a large number of plants, insects and ﬁsh can live there. In
addition, there are a number of animals and birds that feed on the plentiful food in a healthy lake. The
term, pH, is a chemistry term. It is “a measure of the acidity or alkalinity of a solution, numerically equal
to 7 for neutral solutions, increasing with increasing alkalinity and decreasing with increasing acidity. The
pH scale commonly in use ranges from O to 14.” (American Heritage Dictionary, l994)

'3 According to National Surface Water Survey (N SWS), acid rain has been determined to cause acidity in
75 percent of the acidic lakes and about 50 percent of the acidic streams of the 1,000 lakes larger than 10
acres and streams surveyed in the NSWS. What is worse, acidiﬁcation has completely eradicated ﬁsh
species in some vulnerable lakes and streams. (US. EPA, 1998)

“ Soils naturally contain small amount of poisonous minerals such as mercury and aluminum. Normally
these minerals do not cause serious problems, but when acid rain falls on the ground and soil and the
acidity of the soil increases, chemical reactions occur allowing the poisonous minerals to be taken up by the
plant roots. The trees, plants, and crops are then damaged and any animals eating them will absorb the
poisons, which will stay in their bodies. Pollutants can block or damage the little pores on the leaves
through which the plant takes in the air it needs to survive. (ECE/UN, 1992)

10

costs are inevitable when buildings and other structures are dirtied by dry deposition of
acidic compounds.‘s

Fourthly, low visibility becomes a problem when air pollution rises to a certain
degree. For example, emissions of sulfur dioxide bring about the formation of sulfate
particles in the atmosphere. Sulfate particles, then, cause signiﬁcant reduction of
visibility, thus ruining people’s enjoyment of natural views, national parks and so on.‘6

Finally, air pollution leaves people in health risk. People suffer from respiratory
problems when there are acid particles in the atmosphere. Automobiles and factories
produce air pollution, which results in acid rain, and can also risk human health. The
chemicals released by acid rain contaminate drinking water, and cause unfavorable or
serious health problems to people. (Forster, 1993) Sulfur dioxide (802) also causes a
serious health problem to people. They interact in the atmosphere to form sulfate
aerosols, and they may travel quite a long distance through the air. People can inhale the
particles of most sulfate aerosols. Recent studies at Harvard and New York Universities
warn of the close and positive relationship between higher levels of sulfate aerosols and
morbidity (sickness) and mortality from lung disorders, such as asthma and bronchitis.

(US. EPA, 1998)

 

'5 To reduce damage to automotive paint caused by acid rain and acidic dry deposition, some manufacturers
in the world use acid-resistant paints, at an average cost of $5 for each new vehicle (or a total of $61

million per year for all new cars and trucks sold in the US.) Famous buildings like the Statue of Liberty in
New York, the Taj Mahal in India and St. Paul's Cathedral in London have all been damaged by this sort of
air pollution. Much of the damage is caused by dry deposition. (ECE/UN, 1992)

‘6 According to a study, the visual range improvements expected at national parks of the eastern United
States due to the Acid Rain Program's SO2 reductions will be worth a billion dollars by the year 2010. (EPA,

11

2. Beneﬁts of Controlling Air Pollution for Environmental Protection

Air pollution causes various negative impacts on the natural environment and
human health. Therefore, it needs reducing and controlling. Air pollution control brings
people clean air for a better life. A whole nation can beneﬁt from reducing SO2
emissions by a signiﬁcant amount. For example, the reduction in SO2 emissions is
expected to signiﬁcantly relieve water bodies and forests from acidiﬁcation and stress.
By lowering levels of sulfate aerosol, the incidence and the severity of asthma and
bronchitis will decrease. Public health beneﬁts from air pollution control will also be
signiﬁcant, due to decreased mortality and health maintenance expenses. (ECE, 1994)

Decreased emissions of nitrogen oxides (N 0,) will also promise a positive impact
on human health. This is because the nitrate component of inhalable particulates is
expected to be reduced and nitrogen oxides, available to react with volatile organic
compounds (V OCs) and form ozone, will be reduced. A number of morbidity and
mortality risks associated with lung disorders is ascribed to the ozone impacts on human
health.‘7 (Han, 1998) Therefore, the reductions in pollution emissions will help to protect
public health.

Air pollution control will also reduce the cost of environmental quality and
objects maintenance signiﬁcantly. The beneﬁts will match, in part, the current costs of

damage repair or prevention.18 For example, the value that society places on the details of

 

1998)

‘7 On days following an ozone warning, mortality rates in Seoul, Korea rose to 7% while the number of
people admitted to hospital emergency rooms increased to 1.3 to 2.0 times the normal, according to a report
at the Seoul National University's Medical Institute submitted to the Ministry of Finance, Korea. (Han,
1998)

‘8 For example, repairing damaged buildings, using acid-resistant paints on new vehicles.

12

historic structures lost forever to acid rain is not to be represented in monetary terms, and
air pollution control can avoid the deterioration. (ECE, 1987)

Visibility can be improved by the reduction of emissions, which will allow people
to enjoy scenic vistas much better across a nation, particularly in natural sites such as
national parks. (Forster, 1993) The life span of building materials and important cultural
and historic structures will also be expanded.

By reducing the emitted amount of SO2 and NOx in the atmosphere, many
acidiﬁed lakes and streams will become healthier. The healthy surface water supports
ﬁsh life and wildlife better. Air pollution control will also reduce damage to crops as
well as stress to soils, forests and plants. (ECE, 1987)

Finally, controlling air pollution is expected to promote regional peace and
security. For example, throughout the history of intense interstate conﬂict in Northeast
Asia, there has not been much dialogue between those nations. (Hayes, Peter and Lyuba
Zarsky, 1994) Colonial and pre-colonial eras, World War II, the Korean War, and the
Cold War have encouraged antagonism, fear of one nations’ domination, and hostilities
until recently among the countries in this region. In this context, successful dialogues
between nations in this region to enhance environmental cooperation to combat
transboundary air pollution are expected to contribute subsequently to the promotion of

regional peace and security.

13

B. Measuring Beneﬁts and Costs of Reducing Air Pollution

Measuring costs and beneﬁts of reducing air pollution is not an easy task to
perform. This is primarily because it is difficult to measure the speciﬁc beneﬁts and
costs of reducing air pollution. It is also because knowledge concerning the adverse
physical impacts of a air pollution tends to be qualitative rather than quantitative.
(Freeman, 1984) However, if the beneﬁts of air pollution reduction program exceed its

cost, then it would be justiﬁed to implement that option. (ECE, 1987)

1. Some Concerns in Measuring Beneﬁts of Costs of Reducing Air Pollution

In order to measure the beneﬁts of reducing air pollution, Portney introduces a
four-step process for a comprehensive estimation under a certain air pollution reduction
program, and they are summarized as follows (Portney, 1992):

0 Translate regulations under the air pollution reduction program into reduced
air pollution or emissions by the affected sources.

0 Convert the reduced air pollution or emissions into reduced ambient
concentrations of total suspended particulates (TSP’s), 802, O3 (ozone), NO,
and other regulated pollutants.

0 Map the reduced ambient concentrations into, (or relate them to) enhanced
human welfare or well-being such as improved health, increased visibility, or

reduced damage to crops, forests, and exposed materials.

14

0 Finally, measure the beneﬁts in dollar terms in a formal beneﬁt-cost analysis,
ascertain individuals’ willingness to pay for these gains.

There are many difficult problems at each of the four steps above in estimating
beneﬁts. For example, the amount of the reduced air pollution or emissions will largely
depend on the air pollution control technology selected, the proper operation and
maintenance of the equipment used, and the degree to which natural forces surpass the
control of air pollution sources. (Portney, 1992) Secondly, meteorological, topographical,
biological and other factors as well as emissions control should be counted in measuring
ambient environmental condition. Thirdly, determining enhanced human welfare or well-
being may be most difﬁcult.'9 Therefore, it is greatly difﬁcult to measure the beneﬁts of
the reduced air pollution under a certain pollution reduction program.

Measuring the costs of reducing air pollution is relatively simpler, because it is
just the mere sum of the expenditures made by the regulatees for air pollution control.
However, in reality, Gittinger argues that it is much more complex to estimate the social
costs of regulation. (Gittinger, 1992) The social cost of an air pollution reduction
program is measured by the total compensation to be made to the affected consumers as
before the program goes into effect. Economic factors, the possible price increase of
products, which become the additional burden to consumers. should be taken into account.
There can also be some involuntary unemployment due to the air pollution control that
should be counted. Lastly, a supplier may stop producing a certain product because
producing the product becomes less proﬁtable due to the additional pollution control cost.

In this case, the supplier is likely to stop producing the product, which will become a loss

 

‘9 At the web site of World Resources Institute, they report, “. .. the health valuation accounts only for lost
productivity and treatment costs, while the estimate of health effects considers only acute effects and not

15

to consumers and will have to be counted when measuring the costs. However, the
producer may decide to invent a device to control the emissions more effectively in terms
of cost. This technology investment should, then, be also counted. By estimating the
costs of an air pollution reduction program in this fashion, it will be reasonable to

compare the costs with beneﬁts based on willingness to pay.

2. Economic Analysis for the Comparison of Costs and Beneﬁts

Economic analysis of the costs associated with reducing air pollution should be a
substantially easier task than measuring beneﬁts. As mentioned earlier, by simply adding
up all the expected expenditures by producers on air pollution reduction equipment and
personnel, we can obtain the costs. 2" At the same time, we can count as costs
governmental expenditures on pollution control efforts such as the drafting, monitoring,
and enforcing of air pollution control.

However, Goodstein points out this approach of measuring the costs may
overstate the true social costs, and argues that the reasons are (Goodstein, 1995):

o the efficiency in terms of resource use may be enhanced by Governmental
involvement; and

0 Regulation contributes to productivity increase through improving health or forcing
technological improvement.

On the other hand, true social costs may be underestimated, because the

governmental regulation (Goodstein, 1995):

 

cumulative and long-term effects.” (World Resources Institute, 1998)
2° Goodstein call this an engineering approach, compared to the approach that counts the opportunity costs

16

0 Causes the productivity to decrease by diverting investment;
0 Leads to structural unemployment;

o Discourages manufacturing investment; and

o Increases the chances of growing monopoly power.

The beneﬁts of reducing air pollution can be categorized into two in economic
analysis. One is market beneﬁts, and the other is non-market beneﬁts.

Market prices are convenient to use for those products that are directly bought and
sold, because they provide information to economic analysis of beneﬁts and costs.
Measuring these market values is a natural approach. In a competitive market, the prices
of goods represent the marginal value of the goods to consumers as well as the marginal
cost of producing the goods. However, Sugden and Williams state, “. .. market prices
sometimes need to be adjusted to take account of the inﬂuences of price and quantity
constraints and of taxes. Where a project causes market prices to change, further
problems were shown to arise, requiring the use of measures of producers’ and
consumers’ surplus.” (Sugden and Williams, 1990: 148)

In the agricultural sector, it is relatively easy to measure the costs and beneﬁts for
the comparison. For example, acid deposition could reduce cr0p yield by adversely
affecting above-ground environment or soil quality. It is relatively easy to measure the
impacts of air pollutants because agricultural goods are exchanged in markets. In
addition, there are quantity and price data readily available. What is required, then, is the
information about the impacts of air pollution, e. g. acid rain, on the crop production and

production costs of given agricultural goods. In the case of acid rain damage,

 

relevant. (Goodstein, 1995).

17

establishing an experimental design, e.g. dose-response function (Forster, 1993), will
demonstrate damage at current levels of acid deposition. By multiplying the damage (in
terms of the amount of agricultural goods damaged) and the price, the costs of air
pollution impacts can be estimated. The thing that makes it difﬁcult for measuring is that
there are side effects of the agricultural goods loss due to the air pollution impacts. For
example, decreased supply of a crop is like to cause the price increase of the crop, which
will turn as an additional burden to consumers. In contrast, acid deposition is also
beneﬁcial to the agricultural soil to a certain degree because of the nutritious sulfur and
nitrogen compounds for plants. (Evans et al., 1981) These side effects that are
contributing to the costs or the beneﬁts are not easy to measure.

There are many goods that are not directly bought and sold and do not have
certain market prices. Likewise, many effects of reducing air pollution bear non-market
values. Economists have also devised some methods to measure the non-market beneﬁts
and costs of reducing air pollution. Good examples include environmental resources and
common resources such as: recreational use of a river (e. g. boating, swimming, ﬁshing,
etc.), the enjoyment of the greater species diversity in the river, and so on, in the case of
rivers). We can measure non-market beneﬁts by inferring how much people are willing

to pay for these beneﬁts.

18

3. Types of Non-market Beneﬁts: Use, Option, Existence, and Bequest Values

In order to measure beneﬁts and costs measurements of reducing air pollution, it
is important to identify types of some non-market beneﬁts that should be counted. This is
because market beneﬁt, monetary value in other words, cannot represent the total value
of the beneﬁts that come from air pollution control. The total value of an environmental
resource is the sum of both market and non-market beneﬁts. Walsh et al. categorize the
non-market beneﬁts of environmental protection into three categories: option value,
existence value, and bequest value. (Walsh et al., 1984) These three categories are
combined into one and called as non-use value by Schweitzer, and he adds use value as a
different category (Schweitzer, 1991), which is also called preservation value. (Greenley
et al., 1981). Brief descriptions of use value and non-use value/preservation value
(option value, existence value, and bequest value) are as follows:

0 Use Value: The value of both consumptive and non-consumptive use of
environmental goods.21 Recreational activities in a cleaner river without paying for
the services become non-market use values. (Schweitzer, 1991)

0 Option Value: The value of future consumptive and non-consumptive use of natural
resources. (Schweitzer, 1991) One would be willing to pay something merely to

preserve environmental goods or services that might become valuable in the future.22

0 Existence Value: This is a value of an environmental good that is not for any actual or

potential recreational use (Schweitzer, 1991) or “the willingness to pay for the

 

2‘ Consumptive use involves the direct consumption of environmental goods, e.g. deer hunting, while non-
consumptive use doesn’t involve the reduction of the availability of environmental goods for others, e.g.
visit to recreational sites or national parks.

22 Walsh et al. deﬁne it as “the annual payment of . .. insurance premium” to protect possible future use.

19

knowledge that a natural environment is protected by wilderness designation even
though no recreation use is contemplated.” (Walsh et al., 1984: 14) The existence
value has much to do with moral concerns about environmental degradation.”

0 Bequest Value: It is related with the willingness to pay (WTP) for the satisfaction

coming from saving wilderness resources for future generations.“ (Walsh et al., 1984)

4. Measuring the Beneﬁts and Costs in Economic Analysis

The main interest of economic analysis falls on the consumer surplus increase
induced by the pollution reduction. Consumer surplus here means “difference between
what one is willing to pay and what one actually has to pay for a service or product.”
(Goodstein, 1995: 87) There are two measuring beneﬁts: indirect valuation and direct
valuation. Indirect valuation focuses on a dose-response relationship between pollution
and a non-monetary effect.” Once the relationship is determined, direct valuation26 is
used to measure the preference for the non-monetary effect. Direct valuation is meant to
measure the monetary value of an environmental change (e. g. improved visibility or
better air quality). The examples of direct valuation techniques include: contingent

valuation, hedonic pricing, the travel-cost model, and the production function approach.

 

(Walsh et al., 1984: 14)

23 such as such as empathy for other species.

2‘ The bequest value is somewhat similar to the option value, but it can be said that the bequest value is
‘intergenerational’ option value.

2’ Here, pollution is the dose, and the response is a non-monetary effect, of which an example can be health
impairment.

2° i.e. measuring willingness to pay or willingness to accept.

20

In one of his articles, Schweitzer describes these four techniques as follows.

(Schweitzer, 1991)

a. Contingent Valuation Method (CVM)

The criteria of ‘willingness-to-pay (WTP)’or ‘willingness-to-accept (WTA)’play a
signiﬁcant role in contingent valuation methods. In this method, surveys, questionnaires,
or experimental techniques are employed to ask individuals how much they are willing to
pay to receive a certain beneﬁt or how much they are willing to accept as compensation
for a certain cost. This method aims to elicit close values (of certain beneﬁts or costs) to
those in an actual market. In CVM, if people are willing to pay more than a certain cost,
assuming they are in an actually existing market, the difference between the market price
and what they are willing to pay becomes the consumer surplus. (Schweitzer, 1991) The
CVM method makes it possible to use values of those non-market beneﬁts in estimation

as alternatives.

b. Travel-Cost Model (TCM)

This approach is used “to measure the beneﬁts associated with recreational
resources such as parks, rivers, or beaches.” (Goodstein, 1995: 96) The TCM model is
meant to measure the amount of costs associated with travelling to the resources that
people spend to use. First, differences in travel cost data are treated as differences in

consumption to estimate a demand curve. Second, the demand curve for the resource can

21

be drawn as a distance decay equation for a certain recreational travel to a recreational

resource. Finally, thus, the consumer surplus is to be estimated.

c. Hedonic Pricing

This is a surrogate market technique of valuation, and it deals with the pleasure or
the utility ﬁ'om an improved or healthier environment. (Goodstein, 1995) The hedonic
method assumes that people will show how much they value environmental attributes,
both structural and aesthetic, in terms of their willing to pay for land, for example. Land
at a different location is likely to have different environmental qualities, in other words, a
different price for the land. Therefore, the hedonic pricing method focuses on the
relationship between land values and indicators of environmental quality. Once the
relationship is established,” the relationship becomes useful when we infer the social and

individual costs of environmental pollution or the beneﬁt of pollution reduction.

(1. Production Function Approach

In the production function approach, ﬁrstly, private goods and environmental
goods become inputs in the production process. Secondly, the individual’s utility is
considered as an output from a production process. If we get an measurable output, then
we can carry out sensitivity analyses to measure “changes in the supply of the

environmental input” (Schweitzer, 1991: 8) in monetary terms. With all the other inputs

 

27 A useﬁrl technique is multiple regression, for example, and this is why Goodstein calls it “hedonic
regression.” (Goodstein, 1995)

22

being constant, we can regard the value of the environmental input change same as the

value of the change in production.

C. Issues Involved in Measuring Beneﬁts and Costs of Reducing Air Pollution

1. Non-conventional Economics Approach: Pricing and Valuing the Ecological System
Services and the Beneﬁts of Air Pollution Control

One complication in measuring the beneﬁts against the costs of controlling air
pollution comes from the fact that it is never easy to prove what will happen if no
pollution control action is taken. In other words, there is an issue of uncertainties in
measuring the beneﬁts of air pollution control or valuing the ecosystem services. Those
uncertainties seem to stem from the lack of scientiﬁc proof, extemalities, and human
beings’ different world views.

According to Page’s argument, the antlrropocentric approach to valuing natural
resources is human-oriented in the sense that humans are those who do the valuing and
human values are what count. Page points out that valuation should be less human-
centered and should get other things counted as well as human interests. (Page, 1992) In
this regard, the ecological economics approach is different from the conventional
economic analyses on values of the natural resources, including both natural goods and
services.

The ecological economics approach is transdisciplinary and takes a holistic view
in considering the natural resources-economy interactions. It is different from both

conventional economics and conventional ecology, in terms of the breadth when it

23

perceives the problem and in terms of the degree of the attention it pays to the
interactions between natural resources (or the environment) and human economic
activities. The ecological economics approach to valuing natural ecosystem services
takes a wider and longer-term view “in terms of space, time and the parts of the system to
be studied Its domain is the entire web of interactions between economic and
ecological sectors.” (Costanza et al., 1991: 3)

Costanza et al. conducted a research to measure the values of ecosystem services
in a different way from conventional economics approaches. (Costanza et al., 1997)
They grouped the ecosystem services into 17 categories, with earth’s surface classiﬁed
into 16 biomes. To estimate each of the 272 combinations, ﬁrst, they estimated the
ecosystem service values per unit area by biome. Second, they multiplied the unit values
by the total area of each biome. Finally, all services and biomes were summed over.

Application of Costanza et al.’s approach to the estimation of the beneﬁts of air
pollution control can be viable. However, as Costanza et al. argue in their article that the
beneﬁts from nature are “inﬁnite,” the beneﬁts from air pollution control cannot be fully
measured in monetary terms that are used for economic goods and services. (Costanza et
al., 1997) If the contingent valuation and willingness to pay are employed in the
estimation of the beneﬁts of air pollution control, individuals’ subjective preferences will
be estimated. Those preferences are translated in the monetary terms, according to the
amount of money individuals are willing to pay for those beneﬁts. Although the prices
cannot indicate the true values, measuring the beneﬁts of air pollution control by these

approaches can be instructive and useful for policy makers and the public. This is

24

especially true where there is no valuation system developed to represent more realistic

or true values of natural resources and ecosystem services.

2. Ecological, Technological, Political, Socio-Economic, and Cultural Factors

Wenz argues that the translation of individuals’ preferences into prices is not as
just as giving people no right “to buy extra votes” in a democratic society. (Wenz, 1998:
217) It, then, brings us to the issues such as: ‘who decides the values of natural
resources?’ and ‘why do they put a high or low value on them?’ If the preferences should
be converted into prices, it will become a ‘one dollar, one vote’ matter, which can never
be a just way in dealing with natural resources.

Besides, those prices cannot be good indicators of values of natural resources
such as air, water, forests, and so on. Prices can also be only poor predictors of future
value. That is because there is no economic scale developed that can be used commonly
(like dollars) to represent values of ecosystem services. (Fiscus, 1997) Secondly, there is
a huge gap between the prices and values of ecosystem functioning, thus resulting in
uncertainties. Thirdly, as natural resources get more scarce and more stressed, their value
is expected to increase on a non-linear basis, and will also be accelerated by their
irreplaceability and irreversibility. The uncertainties tend to lead the beneﬁts to be under-
weighted when policy decisions are made, although air pollution control results in diverse
valuable beneﬁts to human beings and their society.

Some economic theorists assume that the market economy is based on efﬁcient

use of resources and, thus, reduces pollution. A relevant example for this study is the

25

case of resolution through negotiation between polluter and victim in pursuit of an
efﬁcient pollution level. According to the Coase theorem, if polluter and victim can
negotiate with ease and effectiveness, an efﬁcient outcome can be obtained. (Coase,
1960) Ronald Coase argues that an efﬁcient solution is obtained no matter who pays for
pollution from an efficiency perspective. (Tietenberg, 1992) However, in real-world
settings, fairness becomes an important factor that cannot be ignored. In fact, Goodstein
argues that “efficiency will in general be better served under a polluter pays principle.”28
(Goodstein, 1995: 53) Goodstein also argues that requiring the polluter to pay for the
pollution is more efﬁcient than requiring the victim to pay, because the former policy will
reduce “the free-riding and transactions costs associated with the latter policy.”29
(Goodstein, 1995: 53) However, the world industrialization path has shown us its failure
in terms of sustainable resource use and the reduction of pollution. This comes from the
fact that it has been unsuccessful in reﬂecting extemalities fully on production costs.
Ernest U. von Weizsacker states, “Bureaucratic socialism collapsed because it did not
allow prices to tell the economic truth. Market economy may ruin the environment and
ultimately itself if prices are not allowed to tell the ecological truth.” (as in Schmidheiny,
1992:14)

Another important aspect in valuing the natural resources and the beneﬁts of air
pollution control lies in their cultural, and/or moral values. Pimm argues that these
cultural values “could be very large and easy to estimate in theory, if not in practice.”

(Pimm, 1997) Schumacher also points out that if industrialization continues in the

 

2‘ According to the ‘Polluter Pays Principle,’ “the polluter should bear the expenses of carrying out
pollution prevention measures or paying for damage caused by pollution.” (OECD, 1995: 12) The
Principle was initially adopted by the OECD countries in the early 19705, when strict environmental
regulations began to be introduced.

26

current trend, without paying attention to religious and spiritual values, it is expected to
result in a disaster. (Schumacher, 1993) Rice and agricultural land in Korea are good
examples. Acid rain due to air pollution can result in an extensive damage to rice crops,
which is the major food source for people in Korea. The cultural and spiritual value of
rice and agricultural land exceeds far beyond monetary values derived from the grains or
agricultural products. Even though the outsiders or the market may only count their
monetary values, there are other signiﬁcant values besides those dollar values. The
cultural and spiritual importance of rice was a huge issue when the US. Government was
in a negotiation process with Japan and Korea for their rice markets.

As disciplines and their world views differ from each other, there are many
different approaches to the valuation of ecosystem services. Page summarizes those

different approaches brieﬂy for comparison:

The biologists have a connected view of ecological systems, but not a value theory to go
with it. The moral philosophers have value theories, but they seem too entity—oriented
(individuated) for valuing ecological system. The institutional approach has the virtue of
integrating valuation and implementation and they are decision-oriented, but they are
entity-oriented. And especially economic approach takes individual valuations as given
or exogenous. The approach from health is relational and has normative concepts built in,
but the concept must be developed more and integrated more with the other approaches in
order to become a more practical guide to making choices about ecological systems. The
approach from meaning goes a step further as a relational concept and integrates things
previously viewed as dichotomous. (Page, 1992: 118)

By placing an emphasis on “the approach from meaning,” where meaning is a
relational concept and a prerequisite to valuation, and collapses dichotomous views, Page
argues that we should pay greater attention to tomorrow’s values of ecological systems.

Incorporating tomorrow’s values of ecosystem services more ‘meaningfully’ into current

 

2’ The examples of the transactions costs are court time for the legal resolution, lawyers’ fees, and so on.

27

values, will make it possible to represent the more realistic values of the ecosystem

services. (Page, 1992)
3. Paradigm Shift

If beneﬁts from the air pollution control are compared with its costs, political
inﬂuence can be reduced substantially when policy decisions are made. This is because
numbers in the forms of prices “speak for themselves” to policy makers and the general
public. (Goodstein, 1995: 144) Nevertheless, this approach brings up an important issue
of the discord between the price and the value.

The industrialization in Northeast Asia has followed the similar path that the
Western world has preceded through during its economic growth in that they have not
paid careful attention to the costs of growth. Without full acknowledgement of the costs
of economic activities, our economy can never be sustainable. This is because the
economy is a subsystem of the ecosystem that does not grow. Daly and Cobb insist that
there should be something of a paradigm shift, in order to expect a shift from
“chrematistics” to “oikonomia.”30 (Daly and Cobb, 1989)

The holistic and ecocentric3| world view, systems approach, a paradigm shiﬁ, and
moral revolution need to underlie the valuation process of natural resources and their

services to human beings and other species.

 

3° These two concepts are based on Aristotle’s distinction. According to Daly and Cobb, “Chrematistics” is
deﬁned as “the branch of political economy relating to the manipulation of property and wealth so as to
maximize short-term monetary exchange value to the owner,” while “oikonomia” is deﬁned as “the
management of the household so as to increase its use value to all members of the household over the long
run.” (Daly and Cobb, 1989: 138)

3' People with ecocentric view see acts in terms of what effects they cause to the biosphere. People with
this ethic support environmental policies that beneﬁt ecosystems even though those policies require

28

D. Transboundary Air Pollution

The international air pollution problem is not also a recent problem. For example,
a transboundary air pollution problem, the so called Trail Smelter affair,32 brought about
environmental conﬂicts between Canada and the United States in 1920’s and resulted in
the Final Award in 1941. (Bodansky, 1998) However, it was only recently thatwhen the
international society initiated a multilateral cooperation to combat international air
pollution at regional level. It was done within the framework of 1979 Economic
Commission for Europe (ECE) Convention on Long-Range Transboundary Air Pollution
and it involved all the nations of Europe and North America.

Air pollution has increased tremendously as economic activities continue to
increase all over the world. However, it was relatively recently that the ensuing negative
effects of air pollution became many nations’ concern. More recently, there has been
growing public awareness of:

o the link between air pollution and the degradation of lakes, rivers, and oceans’ water
quality;

0 the link between the depletion of ozone layer in the stratosphere and the emission of
certain chemical substances;33

0 the link between global warming and so called greenhouse gases?“ and,

 

sacriﬁce from them. (Gardner and Stern, 1996)

’2 Trail is a province of British Columbia, Canada, and it is about twenty kilometers north of the territorial
boundary between Canada and the US. Between 1926 and 1937, Sulfur dioxide fumes were emitted by the
Canadian smelter, and caused damage to the agricultural lands and forests near the Northport township in
Washington, USA. Canada agreed to pay $428,000 for the damage caused up to 1937 and provide
remedial measures. (Bodansky, 1998)

’3 such as chloroﬂuorocarbons (CF Cs), halons, methyl chloroform (MC), and hydrochloroﬂuorocarbons

29

o long-range transboundary air pollution and acid rain.

Of the four issues above, this section deals with transboundary air pollution.

1. Deﬁnition

Types and levels of intensity of air pollution vary depending on places, regions,
and nations. One of the most typical types of air pollution comes from a combination of
smokestacks and the basic meteorological phenomenon of dispersal. Therefore, air
pollution seemed to be a problem in the urban or industrial areas, because most of the
pollution sources were located there.

When dilution seemed to be the solution of air pollution, the smokestacks were
built grew higher. However, it could never be a ‘solution.’ During the recent decades,
there has been a change in the dimensions of air pollution as pollution levels increased.”
Air pollution became no longer a local problem, but a transboundary one. The higher
pollution is sent into the atmosphere, the longer the pollution stays there. Likewise, the
longer the pollution stays in the atmosphere, the greater are the chances that the
pollutants are likely to form acid rain. (US. EPA, 1998)

Depending on the forms and weight of the pollutants, the length of the stay in the
atmosphere and the distance of travel vary. Heavier pollutants usually fall and are
deposited in relatively close area to the source. However, certain lighter pollutants such

as lighter particles, vapors and gases stay airborne for several days, travelling over

 

(HCFCs)

3‘ such as carbon dioxide (C02), carbon monoxide (CO), Methane (CH4), volatile organic compounds

(V OCs), nitrogen oxides (NOx), chloroﬂuorocarbons (CFCs) and surface ozone

3’ People thought if the pollution were sent high into the atmosphere, it would not be a problem any more.

30

several hundreds of thousand square miles until they get deposited on the surface of the
earth. Sometimes they reach even other continents. This is why there exist acid rain
problems at remote distances from pollution sources. (ECE, 1984)

Transboundary air pollution is not a precise term, and several different deﬁnitions
can be made according to the way transboundary air pollution is perceived. However, the
deﬁnition made by the 197 9 Economic Commission for Europe (ECE) Convention on
Long-Range Transboundary Air Pollution contains some important aspects of
transboundary air pollution in a comprehensive way. It deﬁnes transboundary air
pollution as “. . .air pollution whose physical origin is situated wholly or in part within the
area under the national jurisdiction of one state and which has adverse effect in the area
under the jurisdiction of another State at such distance that it is not generally possible to
distinguish the contribution of individual emission sources or groups of sources.” (ECE,

1979: 18)

2. Types of Transboundary Air Pollution Problem

If transboundary air pollution can be viewed with a combination of constituents
and effects considered, it can be classiﬁed into the following four types (ECE, 1991):
o acidiﬁcation of the natural environment;
0 visibility impairment due to suspended particulates of sulphate and dusts;
o toxicity due to heavy metals; and

o ozone layer depletion.

31

Acid rain is only one form of pollution, i.e. acidiﬁcation of the natural
environment, and it results from burning fossil fuels. (US. EPA, 1998) It is of particular
interest at local and international dimensions, however, due to the characteristics of its
transboundary movement over long distances. The difﬁculty to measure the amount and
effects of transboundary air pollution stems from its transboundary movement. When the
suspended particulates of sulphate and dusts stay in the air, visibility is impaired. Heavy
Metals in the air are deposited in terrestrial and aquatic ecosystems. Since they are
signiﬁcantly toxic, both natural environment and human health can get impaired to a
great extent. Ozone related problems are also transboundary. They include: ozone layer
depletion, and ozone-related human health risks as well as forest and crop damage. (U. S.

EPA, 1998)

3. Other Examples of Transboundary Air Pollution Problem

From January until June 1998, Mexico had about thirteen thousand ﬁres that

burned a million acres or so within its territory.36 (Price, 1998) A Mexican traditional

 

3" Since 1997, forest ﬁres in Indonesia have burned hundreds of thousands of acres and the smoke
spread out to cover most of the Southeast Asia. However, the Mexican ﬁres are known as more serious
than any ﬁres in the world. What is more, the loss of biodiversity in the Chimalapas, southern Mexico, is a
serious in a different dimension. Brian Atwood, head of Agency for International Development, states,
“About 1,500 of the world’s most-endangered species of plants grow in the Chimalapas reserve and 90
percent of the migratory birds that reach the United States stop there,” and that “About 130 of the most-
used pharmaceuticals in the United States contain ingredients from its forests.” (Price, 1998: 3A)

32

agricultural practice37 - farmers’ setting ﬁres to clear land for planting purpose - was the
major reason for the ﬁres as well as the drought caused by El Nine.” The haze drifted
into Texas, Louisiana, Arkansas, Missouri, Mississippi, and Oklahoma in the US. The
transboundary movement of the smoky haze, for example, caused people in Texas to
suffer from scratchy throats and watery eyes during while the entire State was under a
health watch. People in those states including Texas can also face long-term health
problems, due to the carcinogens in the smoke. Some health specialists recommend that
people should limit their physical exercise. (AP, 1998)

During summer, the prevailing winds carry so much Aﬁican dust across the
Atlantic Ocean. It reaches Florida and some other east-coastal states of the US, the
Caribbean islands, and South America. The long-range transboundary movement of

Aﬁican dust forces those states to violate the air quality standard of the US.

 

’7 “As long as the population ﬁgures remained low, traditional slash-and-burn agricultural practices were
sustainable. But the population has now almost doubled in 20 years and continues to grow by 1.8 per cent
annually in the prefecture and 5.7 per cent in the reserve. If . .. forests are to survive, their people have to
ﬁnd alternative methods of food production, using the forests sustainably, and of earning income in non-
destructive ways.” (WF, 1998)

3’ El Nino is an oceanic and atmospheric phenomenon that occurs in the Paciﬁc Ocean. El Ninb occurs
every third to seventh year, and appears along the western coast of Ecuador and Peru. During this
phenomenon, the ocean warms up unusually and causes climatic disturbances of varying severity around
the world for more than a year. The process of the phenomenon is “. .. sea surface temperatures in the
southeastern tropical Paciﬁc are unusually high, with temperatures more than 10 Celsius degrees (18
Fahrenheit degrees) higher than the eastern waters of coastal Peru and Ecuador. The air pressure is quite
low over the warmer waters. Moist air rises in the region, causing the clouds and heavy rainfall
characteristic of southeastern Asia, New Guinea, and northern Australia. In the eastern Paciﬁc, the water is
cold and air pressure is high, creating the typically arid conditions along coastal South America. The trade
winds blow from east to west, pushing sun-wanned surface waters westward and exposing cold water to the
surface in the east. During El Nino, however, the easterly trade winds collapse or even reverse. As the
slight weakening of the winds causes a modest change in sea surface temperatures, the change in wind and
pressure increases. The warm water of the western Paciﬁc ﬂows back eastward, and sea surface
temperatures increase signiﬁcantly off the western coast of South America. As this happens, the wet
weather conditions normally present in the western Paciﬁc move to the east, and the arid conditions
common in the east appear in the west. This brings heavy rains to South America and can cause droughts
in southeastern Asia, India, and southern Africa. It can also bring unusual weather to large parts of the
United States.” (Microsoft, 1998: Encyclopedia Articles)

33

Environmental Protection Agency (EPA).39 A few micrograms of dust per cubic meter of
air increase up to ﬁfty or one hundred micrograms during months when the African dust
is present. (R.M., 1997) The source of dust was identiﬁed by scientists, using satellite
images40 and collecting daily dust samples.

During the 1992 southern African drought, the worst in the twentieth century,
millions of tons of topsoil were lost as drought persisted, thus hurting people, animals,
and land across nine countries in Southwestern Aﬁica and the Americas across the
Atlantic. (Simons, 1992) Overuse and abuses of the land“ - - can easily damage
relatively less fertile soils such as the fragile arid and semi-arid soils. Although the
practices of those people may not be the direct cause of all the desertiﬁcation,“2 the
desertiﬁcation process is made largely by them and can be exacerbated by them.

Sometimes, dust storms are created by human overuse of natural resources, and
they change the ecosystem in the region affected. In 1983, Mono Lake in the US.“3 was
in “danger of being turned into a lifeless saline sump.” (Forstenzer, 1993: 29) The water
diversion that had been practiced for decades by the Department of Water and Power of

Los Angeles was its cause. The long-term consequences of the Lake water diversion

 

’9 The current standard for particles set by US. EPA are ‘smaller than 2.5 micrometers in diameter’ in
terms of size. Approximately half of the African dust meets the criterion. (R. M., 1997)

‘° Satellite images can show the progress of dust storms.

1' It includes, for example: overgrazing, the deforestation, the slash-and-bum and other agricultural
practices (leading to erosion), the planting of unsuitable crops, and improper irrigation (leading to
salinization).

‘2 Dessertiﬁcation is “the progressive reduction in an area’s ability to capture and store water, and therefore
to support plant and animal life.” (Frank and Brownstone, I992: 86) A good example of dessertiﬁcation is
that of, so called, “Dust Bowl,” the Portions of Oklahoma, west Texas, Arkansas, Nebraska, the Dakotas
and other Plains states in the US. during the Great Depression of the 19305. American farmers who had
hard times with multiple foreclosures due to the economic problem, could not afford to buying seeds to
plant, while suffering from a series of drought years. (Discover, 1997) Russel states, “Over stretched on
mortgage, overploughed and overcropped, the great drought of the 19305 produced the biggest disaster of
all.” (Russel, I988: 61) Without water or seeds, the top soil of those states was just blown away, creating
dust storms. (Discover, 1997)

‘3 This scenic lake lies on the east side of Califomia’s Sierra Nevada.

34

include: the drop of the water level of the Lake (by forty-ﬁve feet); the shrinkage of the
surface area of the Lake (from eighty-ﬁve to sixty—three square miles); the doubled saline
concentration of the Lake (threatening the food supply for about one hundred forty
thousand migrating birds); and, ﬁnally, a serious health hazard for people in the region
because of the alkali dust storms rising from the dried-up surface of the lake. (F orstenzer,
1993) In spite of all the efforts to turn it back into its original condition, Mono Lake has
not regained its own unique ecosystem.

For centuries, ﬁerce dust storms have caused problems in northern China. The
Westerly winds, cold and dry winds from Siberia, lift dusts (Yellow Sands) into the air
from the Gobi Desert and blow them from the west to the east. The dusts travel far away
and reach the Islands of Hawaii in the Paciﬁc and Alaska. The visibility in the areas
inﬂuenced by the dusts is reduced signiﬁcantly, up to zero making afternoon to appear as
if it were night time. Throughout history, the arid lands south of the Gobi have been
abused by humans’ environmentally-unfriendly activities such as deforestation,
overgrazing, and mining. Consequently, the dust-oriented problems have been
exacerbated. (Discover, 1994)

When it rains in Korea during the periods when Yellow Sands are present, one can
easily ﬁnd perceptible layer of yellowish northern Chinese dust on the bottom of the
buckets or in thick and yellowish dusty spots on the top of the cars. The particles of the
dust are also very small that they are hazardous especially when they are embedded in
people’s lungs. (Forstenzer, 1993)

These examples of transboundary air pollution show ecosystems depend on each

other regardless of their sizes and distance from each other. The message contained in

35

this fact is that the earth consists of many interconnected and interdependent systems,

which are ruled by powerful forces of nature that lie beyond the inﬂuence of man.

4. Conventional Analysis Techniques of Transboundary Air Pollution

Economic analysis in reducing pollution is based on the values, both market and
non-market. There are some non-economic analysis models that are widely used for
identifying and solving the problems of air pollution. Due to the extraordinarily complex
characteristics of actual atmospheric processes, many approximations and assumptions
need to be introduced in an air pollution model.

Techniques of analyzing transboundary air pollution are as follows:

0 Mass balance analysis - It accounts for all mass that enters and leaves a deﬁned
volume of the atmosphere above a particular region. This analysis provides a useful
qualitative estimate of whether a region is a net importer or exporter of an air
pollutant. (F linterman et al., 1986)

0 Wind trajectory analysis — This technique computes air trajectories backward from
the deposition site. It is a useful analysis to provide information about the origin of
foreign pollutants deposited at a particular site.“ This technique was used extensively
to assess the where the long-range transportation of sulphur originates from in Europe.

(OECD, 1979)

 

“ Considerably suitable “during a rainstorm or snowstorm, with the place of origin of the air mass bringing
the storm.” (Flinterman et al., 1986: 7)

36

Chemical tracer analysis - It analyzes “particular trace chemicals associated with
different sources of pollution” over a long distance (Flinterman et al., 1986: 9).“5 The
source of pollution at a location of interest can be identiﬁed by analyzing the
chemical characteristics of the air or the deposition there.

Flight measurements - This analysis is used to observe the behavior of pollutants over
long distances. Flights can be made off a place to follow the air pollution dispersion
on trajectories. (Flinterman et al., 1986)

Computer Modeling - Computer modeling is a useful approach to address speciﬁc
regional-scale air pollution problems. In the European and North American acid rain
debate, computer modeling has been extensively used in establishing the relationship
between the amount of pollutants emitted, e. g. C02, NO,, and 802, and the
concentration and deposition of those pollutants. (US. National Research Council,

1983, and OECD, 1979)

5. Principles of the Stockholm Declaration

The issue of acid rain and transboundary air pollution in an international forum

was raised for the ﬁrst time at the 1972 Stockholm World Conference on Human

 

‘5 If lead is measured in the air, it is likely to be from emissions of motor oil. Likewise, the detection of
vanadium in the air may indicate that it comes from fuel oil.

37

Environment. (Caldwell, 1990) The Principles of Declaration of the 1972 Stockholm

Conference on the Human Environment“ include:

o the maxim of sic utere tuo ut alienum non laedas, or “so use your own that you do not
cause injuries to others” (Flinterman et. al., 1986: 244) — the responsibility of
individual states to ensure that activities in their territories do not cause
environmental injuries beyond the limits of their national jurisdiction

0 liability for environmental injuries - states’ obligation to accept the liability for
damage actually caused by transboundary pollution (Koskenniemi, 1990)

0 cooperation in the prevention of transboundary air pollution by multilateral or
bilateral measures — an urge or pleas for international peaceful cooperation on
environmental issues and for multilateral and bilateral measures.

Seven years later, in 1979, when the Convention on Long-range Transboundary

Air Pollution created within the framework of the UN/ECE was signed, an international

strategy for combating acid rain was organized by the countries both affected by acid rain

and by the countries causing it.47 These Principles can also provide a ﬁrm legal ground
for regional environmental cooperation in Northeast Asia, more speciﬁcally bilateral

cooperation between China and Korea for the prevention of transboundary air pollution.

 

‘6 Brunnee, 1988

‘7 A good example is the Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in
Europe (EMEP, or European Monitoring and Evaluation Program) under the UN-ECE Convention on
Long-range Transboundary Air Pollution.

38

Chapter 3

CASE STUDY: DETECTION OF TRAN SBOUNDARY AIR POLLUTION IN
NORTHEAST ASIA

Air pollutants including Yellow Sands have been known to travel from the west to
the east in the Westerly region of Northeast Asia. However, there has not been enough
scientiﬁc research that analyzes the transportation of air pollutants across the region, i.e.
transboundary movement. The transboundary air pollution problems to be identiﬁed
scientiﬁcally include: the sources of air pollutants; the amount of air pollutants that are
transported and deposited; the trend of transboundary air pollution in terms of
concentration and volume; and economic and non-economic consequences of the
transboundary air pollution in the region.

Among many areas and problems related to the transboundary air pollution in
Northeast Asia, this dissertation research will concentrate largely on:

O the inﬂuence of transboundary air pollution at a few industrial sites in Korea to infer
any possible economic loss by examining the production loss at a few manufacturing
sites in Korea

0 the amount of air pollutants, such as sulfur dioxides (S02) and nitrogen oxides (N 0,)
that are transported, and its trend from the past to the future

The ﬁrst issue of the two mentioned above is the subject of Chapter 3, and the
other is the subject of Chapter 4.

A case study was performed to detect and analyze the impacts of transboundary

air pollution in Northeast Asia. As an example of transboundary air pollution in the

39

region, Yellow Sands that ﬂew from China to Korea over the political boundary was
selected. The case study was carried out at an industrial site in Korea. This case study is
focused on the identiﬁcation of possible negative effects of Yellow Sand Phenomenon in
the panel forming process at plant sites of a TV bulb maker in Korea. (APPENDIX A)

As higher resolution and sophisticated technologies become more and more
popular nowadays, the quality of the panel of TV bulbs48 has become a critical factor in
quality control in TV and monitor manufacturing industry. A small-sized surface defect49
of a TV bulb panel that would not have been considered to be signiﬁcant before has

become a factor that a producer cannot neglect any more.

A. Methodology

First of all, the case study deals with the shrinkage rates50 in the panel forming
process with and without Yellow Sand Phenomenon, in order to identify the difference, if
any. Second, a chemical analysis was carried out to identify the characteristics, in terms
of ingredients and content, of the particles taken from the surface of sample panels with
defects that were produced when Yellow Sand Phenomenon was present. An electronic
microscope was used for the chemical analysis. Finally, the result of the ingredient

analysis of the sample panels was compared with the chemical characteristics of Yellow

 

‘8 Here, the panel of TV bulbs indicates the glass part of computer monitors and TV sets.

‘9 “Surface defect” means a defect made when particles in the air fall on the inside surface of TV bulb
panels in their forming process. It is considered to be a critical defect in the picture quality of TV bulbs or
monitors. (to be extended)

5° The shrinkage rate indicates the percentage rate of the TV panels produced with defects over the total TV
panels produced at a particular production site.

40

Sands. This is to determine whether Yellow Sands that ﬂew from China to Korea by the

transboundary movement caused the defects.

B. Presentation of Data

Data collected are shrinkage rates in six different panel forming process lines at
the plant site of the TV bulb maker. The shrinkage rates data available were those in
1995, from the ﬁrst of January to the end of May,’1 and collected by an ofﬁcial at the
plant.52 Since most Yellow Sand Phenomenon tend to take place during spring, the
shrinkage rates data are considered to be useful in identifying possible differences of the
shrinkage rates with and without the Phenomenon.

Seasonal Data on Yellow Sand Phenomenon during the ﬁve months, from January
to May, in 1995 were collected from Annual Report 1995 by Meteorological
Administration of the Government of Korea. The Annual Report contains the daily
records of the weather condition and shows the dates when the Yellow Sand Phenomenon
were present in Korea. According to the Annual Report 1995, the Phenomenon spread all
over the Korean Peninsula four times during the ﬁve months in 1995 mentioned above,

and they are listed in Table 3-1.

 

5‘ Since 1996, a project for a better air ﬂow and quality control system installation has been carried out as
well as, at the same time, a full maintenance checkup of the plant facilities. This project is designed to
reduce the shrinkage rates in the TV bulb forming process. Therefore, the 1995 shrinkage rates data are
considered to be the most recently recorded ones available.

52 Upon the author’s request, the data were released under the condition that the company and the ofﬁcial
are not to be identiﬁed.

41

Table 3-1. Dates with Yellow Sand Phenomenon in the Spring of the Year 199553

 

Phase I April 7 through April 9
Phase II April 18 through April 19
Phase 111 April 23 through April 26

Phase IV April 28 through May 2

 

 

 

 

 

 

 

Although the Weather Report shows the dates when Yellow Sand Phenomenon
were present, it doesn’t show the degree or signiﬁcance of the Phenomenon. However,
some of the pictures may help readers to get a better idea how the air quality gets
degraded when Yellow Sand Phenomenon is present. (APPENDIX B and APPENDIX C).
APPENDD( B shows a dusty road due to the Yellow Sands that ﬂew from China.
Pictures in APPENDIX C are a northern city view of Seoul and a western city View of

Seoul, with the dusty air covering the whole city due to the Yellow Sand Phenomenon.

C. Analysis of Data

One of the major TV-bulb panel makers was chosen as the object of the case
study. Two plants of the chosen company that reside in the mid-west and southeast of the
Korean Peninsula were selected. The plant in the mid-west region consists of four lines
of the panel forming process, while the one in the southeast has two lines. For the sake of
classiﬁcation in this research, those in the mid-west region were named Line (A), Line

(B), Line (C), and Line (D), and those two in the southeast were named Line (E) and Line

(F).

 

’3 Source: Annual Report 1995, Meteorological Administration of the Government of Korea

42

The six lines produce different sizes of panels: Line (A) for small sized panels,S4
Line (B) for large sized ones, and Line (C), (D), (E), and (F) for mid sized ones. The
smaller sized panels in the forming process that are designed for smaller monitors with
high resolution tend to require the air to be cleaner with less dust. This is because a piece
of dust which falls on a panel surface in the forming process would make the panel
critically defected for a small sized one with high resolution. Larger sized panels in the
forming process also tend to be exposed relatively greatly to the dusts in the air because

of its size, thus having greater chance to become defected.

l. Shrinkage Rates With and Without Yellow Sand Phenomenon (January-May, 1995)

When there is Yellow Sand Phenomena present, panels in the forming process are
more likely to be exposed to the risk of being produced with face defects, because of the
increased concentration level of suspended particulates in the air. Although the plant is
equipped with an air quality control system, it is not likely to be completely free from the
increased concentration of the suspended particulates in the air during while the Yellow
Sand Phenomenon is present. Therefore, some important ﬁndings can be withdrawn by
studying the behavior change of shrinkage rates with and without Yellow Sand

Phenomenon.

 

’1 Fourteen and ﬁfteen inch panels were considered to be small. However, numerical sizes were not to be
provided for the mid- and large-sized panels by the ofﬁcials at the plant for business secrecy.

43

Figure 3-1. Shrinkage Rates, January-May, 1995 (%)

 

Shrinkage Rates (96)

 

QN eb\ .53 Q) \ 95.9 to “L ’\ 'L 'L in G: 9: Q:
\- x \‘N -\ \ (pxq'xtb'to‘l, m\%(L'LrL%Q%°%\% (504(5vaqu h‘bmhm‘otsx <0:Q 6"; <0 @95anme

Dates (Month. Day)

 

+SmaII-Size Line (A) +Large-Size Line (B) -—Mid—Size 1 Line (C)
+Mid-Size 2 Line (D) +Mid—Size 3 Line (E) +Mid—Size 4 Line (F)

 

 

Figure 3-1 is a graph that shows how the shrinkage rates changed during the panel
forming process for the six lines from January 1995 until the end of May in the same year.
In Figure 3-1, shrinkage rates ﬂuctuate between 1 percent and 4 percent most of the
period. However, during the periods when Yellow Sand Phenomenon was present the
shrinkage rates rose to a great extent. The graphs that display the shrinkage rates of each
panel forming process line are presented in the six Figures 3-2 through 3-7 below
respectively. In order to be distinguished from the rates without Yellow Sand
Phenomenon, the shrinkage rates during the periods with Yellow Sand Phenomenon are
circled and identiﬁed as Phase 1, Phase II, Phase III, and Phase IV on the graphs,

according to the time order.

Figure 3-2. Shrinkage Rates of Line (A), Small-Sized Products

 

Shrinkage Rate

 

\ x 6 Qt ’\ (L t 6
\Q'xéox \\\¢\¢\g\¢d” ‘1, OT, b’l/Q’o’l/(L‘bo ‘59 ‘5 'bK‘bm’bq’hQ 56095 5.3, (turbo? ”609* bxﬁfcb‘f‘i’s

Date (MonthDay) in 1995

 

Figure 3-3. Shrinkage Rates of Line (B), Large-Sized Products

 

Shrinkage Rate (96)

 

\6KQ: QHQbQ Q‘LA‘LA‘LA Q; Ce 0% \b\
\QNCIONKNKNQINQ’NQ? "60% ’1’ tattle-Q "5° '5' ’5 (509,5va 6°59 »- $999956 ‘3 obK‘OKbﬁw‘om‘o‘b

Date (MonthDay) in 1995

 

 

 

45

 

Figure 3-4. Shrinkage Rates of Line (C), Mid-Sized Products I

 

 

 

9
8
7
A 6
93L
8
a 5
a:
0
S 4
x
.E
E
‘0 3
2
1
0
\‘b'xb’xbxbb Q‘O’LA’LN'L Next: ‘23 Q>KK\%
\ 300 'LCNN/Qt?timmmYeQeQeNeKeq’eﬁvQ39 \ 39 3A} $60606 ‘3 41,637,635
Date (Month.Day) in 1995

 

 

Figure 3-5. Shrinkage Rates of Line (D), Mid-Sized Products II

 

Shrinkage Rate (%)
J}

 

o
e e x 6 tr, « rt ’\ (r, e \ gt:
\QNQBN \\\- \q’xgm- Vita q, Q’L' (tor-PeQQIbNtbmeq’fsgst s36 rat’s-(Les 0° ‘5 <0 634(49an
Date (Month.Day) in 1995

 

 

 

46

Figure 3-6. Shrinkage Rates of Line (E), Mid-Sized Products III

 

Shrinkage Rate (%)
§

 

04
\b’x‘bxbx “1,1031% bx
KSKSK.‘ KT‘ KfLKQ‘Kn-HLP ¢\¢\¢¢¢®5°g°g\g\qmqms° 3°C 96 “(1,0969 $068.5 ‘3 isabmbfﬁﬁg
Date (Month.Day) in 1995

 

 

 

Figure 3-7. Shrinkage Rates of Line (F), Mid-Size Products IV

 

 

ES
0
a 4
[I
a:
8’
x 3
E
.E
(I)
2
1
x x Q3 (3 ~61, A “L ’L E) x t) “~69 6,5
\°\°b\~\\ \rl’KrLNfb'l/So "l,“"1;:0'13rb'13q’ﬁrB %Q%\%\’b¢‘3®h°b°b\ b-Kb >096th ‘3 ‘3 ‘3 Kro‘.3q"3q"3

 

Date (Month.Day) in 1995

47

Figures 3-2 through 3-7 show the ﬂuctuations of the shrinkage rates at all the six
lines from (A) to (F) during the period, from the beginning of January until the end of
May in 1995. According to those Figures above, the shrinkage rates with Yellow Sand
Phenomenon were more than two to four times as high as those without Yellow Sand
Phenomenon. Therefore, it can be concluded that regardless of the plant location, the
shrinkage rates in the panel forming process of the TV bulb manufacturing plants
increased considerably when there was Yellow Sand Phenomenon present. It is believed
that the shrinkage rates went up greatly because Yellow Sand Phenomenon brought about

the increased concentration of suspended particulates in the air.

2. Average Shrinkage Rates With and Without Yellow Sand Phenomenon”

The average shrinkage rates of each line can make it easier for the comparison
between the shrinkage rates with and without Yellow Sand Phenomenon. Table 3-2
shows three different average shrinkage rates calculated for each of the six panel forming
process lines. The information in Table 3-2 is also graphically displayed in Figure 3-8.
The three different average shrinkage rates are:

0 overall average of shrinkage rates for each line for the whole period from January to
May, 1995;
0 average shrinkage rates when Yellow Sand Phenomenon was not present; and

0 average shrinkage rates when Yellow Sand Phenomenon was prevailing.

48

Table 3-2. Comparison of Average Shrinkage Rates of Panel Forming Process Lines

Overall Average 3.48 3.50 2.78 3.13 2.44 2.34
Average Without YSP 3.13 3.24 2.47 2.91 2.18 2.02
Ave_r_age With YSP 6.86 6.09 5.87 5.25 5.04 5.48

 

 

 

 

 

 

 

 

 

 

 

Figure 3-8. Comparison of Average Shrinkage Rates

 

Small—Size Line (A)

   
  

Md—Size 4 Line (F) ~"

Md—Size3 Line(E) '1 WMd—Sizel Line (C)

,, Mid-Size 2£nei(D)

1 + Total Average + Average Without YSP —0— Average With YSP i

 

 

 

 

According to Table 3-2 and Figure 3-8, the shrinkage rates with Yellow Sand

Phenomenon were much higher than those without Yellow Sand Phenomenon and than

 

’5 J anuary-May, 1995

49

the overall averages. At most lines, the shrinkage rates with Yellow Sand Phenomenon
got approximately twice as high as those without Yellow Sand Phenomenon. The panels
in the lines (A) and (B), each for the smaller and larger sized panels respectively, became
defective, resulting in higher shrinkage rates with Yellow Sand Phenomenon. It can be
easily understood that average shrinkage rates when Yellow Sand Phenomenon was
prevailing were higher to a great extent than those during normal conditions, when there
was not Yellow Sand Phenomenon present.

Therefore, it can be concluded again that, no matter where the plant or a process
line was located, the shrinkage rates in the panel forming process of the TV bulb
manufacturing plants increased greatly when there was Yellow Sand Phenomenon present.

However, it is also worth while to re-examine the conclusion that those panels
were defected because of Yellow Sand Phenomenon. For this purpose, a chemical
analysis was carried out on the sample particles from the defect selection during when
Yellow Sand Phenomenon was present, so as to test the ingredients of the particles on the

surface that deposited during the forming process.

D. Ingredient Analysis of the Sample Particles from the Defect Selection

The Yellow Sands are not indigenous to Korea. Because of that fact, there can be
some unique characteristics of the Yellow Sands, compared with domestic dusts or sands
in the air. Table 3-3 shows Ryu et al.’s ingredient analysis result of the dusts in the air
with and without Yellow Sand Phenomenon for a comparison. (Ryu et al., 1994) With

Yellow Sand Phenomenon present, the levels of the total suspended particulates (TSP’s)

50

increased to a great extent (from 157ug/m3 to 538.4ug/m3) compared to those during the

period without it.

Table 3-3. Ingredients: Suspended Particles with and without Yellow Sand Phenomenon"5

I i r _. 3

ii! 3

 

 

 

 

 

 

 

 

 

 

 

 

or 6.648 (10.5%) 4.790 (9.6%) 1.388
No, 8.798 (13.9%) 10.055 (20.2%) 0.875
so: 25.191 (39.7%) 22.763 (45.8%) 1.107
NH; 2.381 (3.8%) 2.490 (5.0%) 0.956

Na 0.722 (1.1%) 0.745 (1.5%) 0.969

l‘ Ca 8.711 (13.7%) 3.724 (7.5%) 2.339

Mg" 2.316 (3.7%) 0.933 (1.9%) 2.482

Fe 7.826 (12.3%) 3.716 (7.5%) 2.106

Pb 0.483 (0.8%) 0.266 (0.5%) 1.816

Mn 0.312 (0.5%) 0.115 (0.2%) 2.713

Ni 0.059 (0.01%) 0.059 (0.1%) 1.000
Total 63.447 (100%) 49.656 (100%) 1.161
TSP 538.4 157.7 3.414

 

 

 

 

 

 

As listed in Table 3-3, Ryu et al. concluded that the absolute amount of metals,
including magnesium, iron, lead, and manganese, increase in the atmosphere with Yellow
Sand Phenomenon. The shaded rows represent those increased with Yellow Sand
Phenomenon in terms of absolute concentration in the air. Those metals including
magnesium, iron, lead, and manganese increased with Yellow Sand Phenomenon in terms
of both absolute and relative concentration levels in the air. Cl' and SO,+ also increased

in the absolute concentration, but decreased in the relative concentration that was

 

5" Samples were taken in the city of Seoul. Percentage in each cell was calculated by the author based on
the data in Table 3-3. Those percentage numbers were added in the parentheses and they indicate the
relative weights among those ingredients. (Unit: ug/m’) (Ryu er al., 1994) The items in the first-left
column respectively represent chlorine ion, nitrogen trioxide ion, sulfate ion, ammonium ion, magnesium,
iron (ferrum), plumbum (lead), manganese and nickel.

51

represented by percentage. Ryu et al. argue that increased absolute amount of metals and
decreased concentration of ions in relative terms is a characteristic of air quality with

Yellow Sand Phenomenon. (Ryu et al., 1994)

Figure 3-9. Pictures of Sample Particles of the Sample Defect Panels.’7

 

In order to analyze the ingredients of the sample particles from the defect

selection, an electronic microscope was used. The microscope analysis was carried out

 

‘7 These pictures were taken by an electronic microscope with the 2,500-times zoom.

52

by a microscope specialist in the research department at the plant upon the author’s
request. The pictures of the particles taken from the defected samples were taken by the
microscope. The chemical information of the particles was also collected and provided to
the author by the same specialist, again upon the author’s request.

Figure 3-9 displays the collection of the pictures taken by the electronic
microscope. The sample particles were obtained from the defect samples that were
produced during two days when Yellow Sand Phenomenon was prevailing in April, 1998.
The two dates were the 19m and the 28‘h of April. The pictures (a)-(d) in Figure 3-9 show
the particles taken from the defected panels produced on the 19th of April in 1995 at the
panel forming process line (A). The pictures (e)-(i) show those on the 28‘h of April in the

same year at the panel forming process line (C).

Table 3-4. Ingredients of the Sample Particles”

2.8
2.7
0.9
3.1

97
13.4 0.6
4 5.8
9.7 15.8

 

 

’8 These sample particles were collected Ran the sample defected panels produced on April 19 and 28,
1995. The items to the right of diameter in the ﬁrst row respectively represent silicon, aluminum, iron
(ferrum), kalium (potassium), calcium, natrium (sodium), plumbum (lead), barium, strontium, magnesium,
Zinc, manganese.

53

The chemical analysis revealed the ingredients of the sample particles. The
ingredient information of each particle in the pictures above was reported to the author.
Table 34 displays the chemical characteristics of those particles taken from the sample
particles with Yellow Sand Phenomenon.

Each cell represents the ingredient in the relative term with Yellow Sand
Phenomenon. As shown in the Table 3-4, all the samples had high concentrations of
metals except the samples (e) and (1). Silicon is the major raw material that is used in
panel forming process, and it is considered to have come off the defect samples with the
particles when collected. Aluminums are intrinsic pollutants inside the processing lines
during the process. Sample (e) represents the normal particle with calcium as the major
ingredient. Sample (1) has iron as the major ingredient. The chemical specialist at the
plant argued that the two samples were like the typical particles at the normal condition
when Yellow Sand Phenomenon was not present. Sample (e) was considered to be
regular dust, and Sample (1) was considered to be from the sample particle with the rusted
iron from the building structure over the production facilities. Several metal ingredients
such as aluminum, iron, plumbum, magnesium, Zinc, and manganese in shaded rows that
were characteristic ingredients of Yellow Sands were found from the other sample

particles, represented by the non-shaded rows.

54

Chapter 4

MODELING AND SIMULATION: FORECASTING TRANSBOUNDARY AIR
POLLUTION IN NORHEAST ASIA

Due to the increasing industrialization and urbanization in Northeast Asian
countries in recent years, a large volume of air pollutants is being emitted increasingly in
this region. The countries in Northeast Asia have suffered from the increasing emission
amount of air pollutants. China and Korea are good examples of those countries.
Particularly, a large portion of the pollutants have been emitted by China, which has been
among the highest air pollutant emitting countries in the world.59 These are contributed
by coal and heavy oil-ﬁred sources60 concentrated on the Yellow Sea coastal area" such
as Shantung peninsula including Liaoning region, Shanghai region, and Kangsao
province centered on Peking. (N IER, 1991)

The energy consumption of China is projected to increase, and it may be doubling
or even tripling by 2025. (WRI, September 1998) The growth of energy use is expected
to result in doubling or tripling of coal consumption and the emissions of air pollutants
such as green house gases and carbon dioxides (C02) over the next thirty years. Unless

environmentally cleaner alternative fuels become China’s major energy, global

 

’9 According to Environmental Education Project of World Resources Institute, China is ranked at the third
in the world in terms of energy consumption, and at the fourth in terms of electricity use, although China’s
energy use per capita is still relatively low. Less than 0.03 percent (%) of the average American household
energy consumption is consumed by a typical Chinese household, which eventually means China has great
potential in energy consumption growth. (WRI, September -l998)

6° In terms of the energy sources in China, more than 80 percent comes from coal and the increasing
reliance on coal is making the air pollution problems including acid rain more and more serious both at
regional and global levels. 19 percent of China’s energy comes from oil. (WRI, September -l998)

6' The Yellow Sea is between China and Korean peninsula. Therefore, Yellow-sea coastal region of China
means its eastern coast.

55

environmental problems such as global warming, acid rain damage, and ozone layer
depletion, will become more and more serious, as well as local and regional problems.

As a result, the westerly wind in Northeast Asia that blows from the Chinese
mainland over its east coast towards the Far East is projected to transport more and more
air pollutants to those countries. Those countries are very concerned about potential
problems with long-range transport of air pollutants originating abroad, and each country
tries to deal with these problems effectively. The country that has suffered and will
suffer most from the transboundary air pollution whose origin is China is likely to be
Korea, which lies closest to China’s east coast. Therefore, Korea is concerned about the
increasing pollution emission levels in China, part of which will be transported to Korea
by westerly winds.

Under these circumstances, it is worth building a simulation model that is based
on the amounts of air pollution emitted in Northeast Asia, particularly China and Korea.
The model should also deal with policy options that will actively reduce adverse effects
by long-range transport of those air pollutants from China to Korea. This Chapter
describes a relevant simulation model, which forecasts the emission of air pollutants that
causes the problems in this region. It deals with the potential benefits which would result
from a combined control of emissions by major environmental policy tools that can be

created by policy cooperation or agreement between China and Korea.

56

A. Methodology

In order to foresee the trend of transboundary movement of air pollutants from
China to Korea in Northeast Asia, computer-aided graphical modeling and simulation
techniques in the environment of STELLA Research 5.1.1 were adopted. (HPS, 1996)
The STELLA software is a model-building and simulation tool. It helps to create the
capacity for understanding systems of dynamic interrelationships. Building models with
STELLA Research 5.1.1 compresses time and space, so that it makes it easier by systems
thinking to forecast the impacts that can be caused by the current actions taken by
humans. The STELLA Research 5.1.1 also shows relevant interactions between variables
and between models, and even the impacts on future generations.

It is a useful tool not only for the analysis of social and environmental systems,
but also offers methods for decision support. The modeling process of the transboundary
air pollution problem between China and Korea shed light on the unintended
consequences of Chinese emission of air pollutants. Finally, the simulation model will

display the consequences of possible policy options.

B. Presentation of Data

In general, the air pollution generation of a nation is greatly dependent on its

economic activities and energy consumption. Gross domestic product (GDP) is a widely

used measure of a nation’s economic output.62 The more economic activities there are in

 

‘2 GDP is the sum of the total money value of the goods and services that were produced by the residents of
a nation during a certain period (usually a year). (Stiglitz, 1997) All the GDP numbers described and

57

a nation during a certain period, the larger the GDP of the nation is likely to be for the
period. The data of GDP, primary energy consumption, and emission of sulfur dioxides
and nitrogen oxides are presented as follows, for both China and Korea.

The data in Table 4-1 and 4-2 were obtained from different sources and combined
into one table. The population, the GDP and the primary energy consumption data were
obtained from the web site of the US. Energy Information Administration, while the SO,
and NO, emission data were obtained from the estimation by Park et al.’s research
project supported by Ministry of Environment, the Government of Korea.63 The growth
rates of GDP, primary energy consumption, and SO, and NO, emissions were calculated
and added by the author. However, some units of the data were changed for the sake of
convenience. First, the primary energy consumption data were converted into trillion
British Thermal Unit (BTU)"4 from quadrillion BTU. Second, the GDP data were
converted from millions to billions of 1987 US. dollars. Third, the conversion of SO,
and NO, emission data was made from 10,000 to 1,000 tons per year.

According to Table 4-1, during the years 1980’s and 1990’s, China’s GDP has
grown ﬁom the minimum of 3.0 percent to the maximum of 14.4 percent, with the
average of 9.90 percent increase. Particularly, China’s GDP has grown by the average of

12.26 percent since the year 1991. Likewise, since the year 1980, China’s primary

 

presented in Chapter 4 are per year.

‘3 Data Source: Population, Energy lnforrnation Administration (EIA), “World Primary Energy
Consumption, 1980-1996,” Country Analysis Briefs. September, 1998; GDP, Energy lnforrnation
Administration (EIA), “World Primary Energy Consumption, 1980-1996,” Country Analysis Briefs.
September, 1998; Primary energy consumption, ElA, “Gross Domestic Product at Market Exchange Rates,
1980-1996,” Country Analysis Briefs. September, 1998; and SO, and NO, emission, Park et al., 1997.

6‘ British Thermal Unit (Btu or BTU) is a science and engineering term. It is a unit to measure heat or
energy. The original definition of one Btu was “the quantity of heat required to raise the temperature of 1
lb (0.45 kg) of water from 59.5°F (153°C) to 60.5°F (158°C) at constant pressure of 1 atmosphere.” For
the improvement of its precision, the Btu is redefined in terms of the joule as equal to 1055 joules; in
engineering, a Btu is equivalent to approximately 0.293 watt-hour. Joule is l watt-second, or 10 million

58

energy consumption has grown by an average of 4.95 percent, and by 5.4 in the years

1990’s. Regarding the emissions of SO, and NO,, China’s SO, and NO, emissions have

grown steadily with the average growth rates of 5.6 and 6.8 percent respectively.

Table 4-1. Chinese Historical Data Used in Modeling and Simulation

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Population GDP and Primary SO, Emission NO,Emission

& Growth Growth Energy & Growth & Growth

Rate (%) Rate (%) Consumption Rate (%) Rate (%)
Year Millions Billions of1987 Trillion BTU 1000 ton / year 1000 Ion /
\Unit US. $ year
1980 987.1 - 131.344 - 17,215.32 - 10,448 - 39,075 -
1981 1000.7 1.4 136.741 4.1 16,920.43 -l.7 10,243 -2.0 37,837 -3.2
1982 1016.5 1.6 147.790 8.1 18,033.81 6.6 10,756 5.0 39,728 5.0
1983 1030.1 1.3 162.830 10.2 19,506.31 8.2 11,482 6.7 42,462 6.9
1984 1043.6 1.3 186.293 14.4 21,184.94 8.6 12,475 8.6 46,398 9.3
1985 1058.5 1.4 210.400 12.9 22,148.52 4.5 13,525 8.4 50,418 8.7
1986 1081.3 2.2 228.177 8.4 23,240.79 4.9 14,120 4.4 54,390 7.9
1987 1104.2 2.1 253.523 11.1 24,742.17 6.5 15,645 10.8 59,534 9.5
1988 1121.9 1.6 282.197 11.3 26,454.69 6.9 16,679 6.6 64,212 7.9
1989 1139.2 1.5 294.004 4.2 26,936.01 1.8 17,510 5.0 68,443 6.6
1990 1155.3 1.4 305.614 3.9 26,993.61 0.2 17,951 2.5 71,513 4.5
1991 1170.1 1.3 331.405 8.4 28,236.23 4.6 18,860 5.1 78,295 9.5
1992 1183.6 1.2 378.921 14.3 29,304.61 3.8 19,614 4.0 84,165 7.5
1993 1196.4 1.1 432.158 14.0 31,340.96 6.9 20,912 6.6 90,960 8.1
1994 1208.8 1.0 487.042 12.7 33,971.57 8.4 22,208 6.2 97,754 7.5
1995 1221.5 1.1 538.181 10.5 36,345.85 7.0 N/A N/A
1996 1232.1 0.9 590.385 9.7 37,040.32 1.91 N/A N/A

 

 

 

 

 

 

 

 

Table 4-2 shows the information on Korea’s GDP, primary energy consumption,

and SO, and NOx emissions. The Korea’s GDP has grown by the average of 8.45 percent

since 1980. However, the GDP growth has been slowed down from 9.0 percent in the

1980’s to 7.7 percent in the 1990’s. The primary energy consumption of Korea has

 

ergs, and is 0.000948 Btu or so. (Microsoft, 1998: Encyclopedia Articles)

59

 

increased by the average of 9.32 percent. Unlike GDP growth, however, the growth rates
of Korea’s primary energy consrunption have been higher in the 1990’s than in the
1980’s, with 11.4 percent versus 7.4 percent respectively. Regarding the emissions of
SO, and NO,, Korea’s SO, and NO, emissions have grown steadily with the average

growth rates of 4.3 and 12.1 percent respectively.

Table 4-2. Korean Historical Data Used in Modeling and Simulation

 

Population GDP and Primary SO, Emission NO, Emission
And Growth Growth Energy & Growth & Growth
Rate (%) Rate (%) Consumption Rate (%) Rate (%)

 

Year Millions Billions of1987 Trillion BTU 1000 ton/year 1000 ton/year
\Unit U.S.$

 

 

 

 

 

 

 

 

 

1980 38.1 - 74.47 - 1,736.80 - N/A N/A
1981 38.7 1.6 79.28 6.5 1,819.19 4.7 N/A N/A
1982 39.3 1.6 83.76 5.6 1,817.90 -O.1 N/A N/A
1983 39.9 1.5 93.65 11.8 1,964.18 8.0 N/A N/A
1984 40.4 1.3 101.88 8.8 2,154.44 9.7 N/A N/A
1985 40.8 1.0 109.23 7.2 2,257.99 4.8 N/A N/A
1986 41.2 1.0 121.98 11.7 2,497.28 10.6 N/A N/A
1987 41.6 1.0 136.32 11.8 2,740.43 9.7 N/A N/A
1988 42.0 1.0 151.73 11.3 3,054.64 11.5 1117.0 - 416.5 -

 

1989 42.5 1.0 161.50 6.4 3,292.71 78 1182.9 5.9 449.5 79

 

1990 42.9 1.0 177.12 9.7 3,679.41 11.7 1308.8 10.6 507.2 12.8

 

1991 43.3 1.0 193.42 9.2 4,189.20 13.9 1377.8 5.3 583.1 15.0

 

1992 43.7 1.0 203.42 5.2 4,652.42 11.1 1405.4 2.0' 666.0 14.2

 

 

1993 44.2 1.0 214.46 5.4 5,385.29 15.8 1432.6 1.9 753.8 13.2
1994 44.6 1.0 232.85 8.6 5,900.62 9.6 1473.5 2.9 842.9 11.8
1995 45.1 1.0 253.66 8.9 6,531.94 10.7 1494.9 1.5 924.9 9.7
1996 45.5 1.0 271.74 7.1 7,158.20 9.6 N/A N/A

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The population of China and Korea has grown at steady low rate, with the average
growth rates of 1.4 percent and 1.1 percent respectively. Since the year 1990, both

nations slowed down their population growth further to 1.13 percent and 1.01 percent.

60

 

The population growth is also an important factor that generally tends to be on a positive
relationship with the air pollution generation. Table 4-1 and 4-2 show that Population,
GDP, Primary Energy Consumption, and SO, and NO, Emissions have a positive

relationship with each other.

C. Analysis of Data

Using the data in Table 4-1 and Table 4-2, some important information can be
drawn by calculation. First, the emission data were divided by the GDP data, results of
which are presented in the columns of SO,/GDP and NOJGDP for China in Table 4-3
and for Korea in Table 4—4. This calculation provides the information about how much
air pollution is emitted per certain money value produced for a certain period. Second,
the emission data were divided by the primary energy consumption data, and the values
are in the columns of SO,/Energy and NOJEnergy for China in Table 4-3 and for Korea
in Table 4-4. These values show the volume of air pollutants emitted per certain amount
of energy used, and they indicate the energy efficiency in terms of air pollution
generation. Third, the primary energy consumption data were divided by the GDP data,
and the results were categorized into Energy/GDP for China in Table 4-3 and for Korea
in Table 4-4. The values in this category mean how much energy is consumed to produce
a certain amount of goods and services for a certain period, and these values are likely to
depend on how clean or environmentally friendly the production processes, including
technologie, are. Finally, the primary energy consumption data were divided by the

population data. The results are presented in the Energy/Population columns for China in

61

Table 4-3 and for Korea in Table 4-4. The Energy/Population columns provide the

information on the energy consumption per capita for both nations.

1. Analysis of Chinese Data

Table 4-3. Calculated Ratios (China)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SO, / NO,/ SO, /Energy NOx / Energy / Energy
GDP GDP Energy GDP /Population

Year 1000 ton 1000 ton 1000 ton 1000 Ion Trillion BTU Million

\ Unit per 198 7 per 1987 per Trillion per Trillion per 1 98 7 US. BTU per
US. Billion US. Billion BTU BTU Billion $ capita

$ $
1980 79.55 264.395 0.607 2.270 131.070 17.44
1981 74.91 232.371 0.605 2.236 123.741 16.91
1982 72.78 213.255 0.596 2.203 122.023 17.74
1983 70.52 201.816 0.589 2.177 119.796 18.94
1984 66.96 203.342 0.589 2.190 113.718 20.30
1985 64.28 198.870 0.61 1 2.276 105.269 20.92
1986 61.88 192.738 0.608 2.340 101.854 21.49
1987 61.71 202.494 0.632 2.406 97.593 22.41
1988 59.10 210.108 0.630 2.427 93.745 23.58
1989 59.56 206.524 0.650 2.541 91.618 23.64
1990 58.74 188.728 0.665 2.649 88.326 23.37
1991 56.91 181.172 0.668 2.773 85.202 24.13
1992 51.76 172.809 0.669 2.872 77.337 24.76
1993 48.39 169.014 0.667 2.902 72.522 26.20
1994 45.60 165.577 0.654 2.878 69.751 28.10
1995 N/A N/A N/A N/A 67.535 29.76
1996 N/A N/A N/A N/A 62.739 30.06
Avg.65 51.49 200.214 0.629 2.476 82.466 -
6’ Average

62

 

China has emitted less and less SO, and NO, into the atmosphere per certain
amount of goods and services produced. In 1980, China emitted 79.55 and 264.395 kilo
tons of SO, and NO, per 1987 US. billion dollars of products, but, in 1994, Chinese
emission per the same amount of GDP decreased to 45.60 kilo tons for SO, and 200.214

kilo tons for NO,. Figure 4-1 displays the trends of the information in Table 4-3.

Figure 4-1. Display of the Ratios of Chinese Data

 

3 0 0
2 5 0 »
2 0 0
15 0 >
1 O O
5 0 >
0
(3‘90 @PXQQ’KQQ’KQQNQQ’OD $388 9333939 \qgiquaqaqgﬂagh

Ratio

 

 

 

 

)\
Year

+602 /GDP"_+ 602 /Energy + NOﬂxm/GDP —x—vNOx /Energyl

 

140
120 *
100
80
6O
40 *
20

Ratio

 

 

 

 

 

.+~ *Energy /GDP_~+_ EnergyT/Poptllatioh

63

However, unlike the amount of SO, and NO, emission per GDP, the Chinese
emission of air pollutants such as S0, and NO, per trillion British Thermal Unit (BTU)
has had a tendency to increase. For example, SO, /Energy (unit: kilo ton per trillion
BTU) has increased from 0.607 in the year 1980 to 0.654 in the year 1994. Likewise,
NO/Energy had been in an increasing trend, from 2.270 to 2.878 kilo tons per trillion
BTU. This means China has emitted less and less air pollutants emission per certain
amount of the GDP, but more and more per the energy consumption, while the GDP and
the energy consumption have continued to grow as in Table 4-1.

The Energy/GDP has also continued to become smaller and smaller since 1980.
For example, the energy consumption per 1987 US. billion dollars of products was
decreased, from 131.070 tons of 1987 US. billion dollar in the year 1980 and to 62.739
in the year 1994. Therefore, it can be stated that China’s economic growth has been more
and more efficient in terms of energy consumption.

Although the China’s economic growth has become more and more energy
efﬁcient, at the same time, it has been generating more and more air pollution in terms of
both the total amount and the emissions per GDP growth. The growth rate of China’s air
pollution generation has been higher than that of energy use. Chinese population grth
has stayed at consistently low rates. However, Chinese energy use per capita has grown
from 17.44 to 30.06 million BTU per capita because of its continued GDP growth at high
rates, with the average of 9.90 percent during the years, 1980 through 1996.

With all the information in Table 4-3, it can be concluded that as China’s

economy grew the air pollution generating industry grew at higher rates. This conclusion

64

is supported by the Chinese data that show that the more energy is used for economic

growth, the more air pollution was generated at higher rates.

2. Analysis of Korean Data

Table 4-4 and Figure 4-2 present the ratios derived from the Korean data in Table

4-2. In the case of Korea, the energy consumption per GDP has remained almost

constant since 1980, while China has experienced an about 37 percent decrease.

However, the Korean energy consumption per capita has continued to grow rapidly, from

45.56 million BTU in the year 1980 and 85.83 in the year 1990, reaching 157.18 in the

year 1995, which is approximately a 83 percent increase.

Table 4-4. Calculated Ratios (Korea)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SO, / NO,/ SO, / NO,/ Energy / Energy /
GDP GDP Energy Energy GDP Population
Year 1000 (on per 1000 ton 1000 Ion 1000 ton Trillion BTU Million BTU
\ Unit 1987 US. per 1987 per Trillion per Trillion per 1987 US. per capita
Billion $ US. Billion BTU BTU Billion $
3
1980 N/A N/ N/A N/A 23.321 45.56
1981 N/A N/A N/A N/A 22.946 46.98
1982 N/A N/A N/A N/A 21.705 46.22
1983 N/A N/A N/A N/A 20.974 49.22
1984 N/A N/A N/A N/A 21.146 53.31
1985 N/A N/A N/A N/A 20.672 55.33
1986 N/A N/A N/A N/A 20.473 60.60
1987 N/A N/A N/A N/A 20.103 65.84
1988 7.363 2.745 0.366 0.136 20.133 72.68
1989 7.324 2.783 0.359 0.137 20.388 77.57
1990 7.390 2.864 0.356 0.138 20.774 85.83
1991 7.123 3.015 0.329 0.139 21.659 96.75
1992 6.909 3.274 0.302 0.143 22.871 106.37

 

65

 

 

 

 

 

 

 

1993 6.680 3.515 0.266 0.140 25.112 121.87
1994 6.328 3.620 0.250 0.143 25.340 132.18
1995 5.893 3.646 0.229 0.142 25.750 144.86
1996 N/A N/A N/A N/A 26.342 157.18
Avg.‘56 6.876 3.183 0.307 0.140 22.336 83.43

 

 

 

 

 

 

 

Figure 4-2. Display of the Ratios of Korean Data

 

 

 

 

 

 

 

 

 

 

 

 

Ratio
O—‘NOO-hcnmﬂm

 

 

1988

b: _sd.2/GDP_ +;__ _, 6627:

160.000
140.000

120.000 L

1 100.000
' 80.000
1 60.000
40.000
20.000
0.000

Ratio

1989

1990

 

1991

1992

Year

989v +_ NOVGDP +9 NoxlEneraxf 3

1993

1994

 

 

 

1995

 

__.._1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I-r-TTTEn—ergv/GQE’ +z Egéiévﬁ/POLEEB‘E

 

6" Average

 

66

1H: ;tA :3 3 3 :W
l
OFNmeonmOf—Nmﬂ'm
mmmmmmmwwwmmmmmm
030300303030300303030303030303
a-w—v—w—Y-V—a—a—v—s—v-Pv-a—a—v-
Year

 

3. Comparative Analysis of Chinese and Korean Data

With some of the data in Table 4-1 through 4-4, the comparison between China
and Korea was carried out and its results are presented in Table 4—5. The Chinese data
were divided by the same Korean data in order to get the ratios. The data used in these
calculations include population, GDP, primary energy consumption, SO, and NO,

emission, emission-GDP ratios, and emission-energy consumption ratios.

Table 4-5. Comparison between China and Korea (Ratio: China/Korea)

 

Popula— GDP PEC (PEC SO, NO, SO,/ NO] SO,/ NOJ
Year tion per capita)67 GDP GDP Energy Energy

 

 

1980 25.89 1.98 9.91 (0.38) - - - - - -

 

1981 25.85 2.05 9.30(0.36) - - - - - -

 

1982 25.85 2.22 9.92 (0.38) - - - - - -

 

1983 25.81 2.25 9.93 (0.38) - - - - - -

 

1984 25.82 2.24 9.83 (0.38) - - - - - -

 

1985 25.94 2.32 9.81 (0.38) - - - - - -

 

1986 26.24 2.31 9.31(0.35) - - - - - -

 

1987 26.53 2.16 9.03 (0.34) - - - - - -

 

1988 26.69 2.01 8.66(0.32) 14.93 154.17 8.03 82.89 1.72 17.80

 

1989 26.84 2.05 8.18(0.30) 14.80 152.26 8.13 83.64 1.81 18.61

 

1990 26.95 2.14 7.34(0.27) 13.72 141.00 7.95 81.71 1.87 19.22

 

1991 27.02 2.23 6.74 (0.25) 13.69 134.27 7.99 78.37 2.03 19.92

 

1992 27.06 2.39 6.30 (0.23) 13.96 126.37 7.49 67.84 2.22 20.06

 

1993 27.07 2.51 5.82 (0.21) 14.60 120.67 7.24 59.88 2.51 20.73

 

1994 27.08 2.54 5.76 (0.21) 15.07 115.97 7.21 55.45 2.62 20.14

 

1995 27.09 2.12 5.56(0.21) - - - - - -

 

1996 27.05 2.17 5.l7(0.19) - - - - - -

 

 

 

 

 

 

 

 

 

 

Avg 26.52 2.22 8.03 (0.30) 14.40 134.96 7.72 72.83 2.11 19.50

 

 

 

’7 Chinese Primary Energy Consumption (PEC) divided by Korean PEC (Chinese PEC per capita divided
by Korean PEC per capita)

67

While the rapid economic growth of Korea started in the nineteen sixties, that of
China started in the late nineteen eighties. Although, China is a newly developing nation,
it is one of the largest countries in the world in terms of both the geographical size and
the population. Therefore, China has a great potential for economic growth and the
pollution generation which may accompany it.

Above all, the population of China is about 27 times as large as that of Korea for
the year 1996. The Korean population growth rate has been lower than the Chinese
population growth rate, as shown in Table 4-1 and Table 4-2, thus leading the population
ratio between the two nations to grow as presented in Table 455. However, the GDP
ratios between the two nations have not greatly changed, ranging from 1.98 to 2.54 with
the average of 2.22. This is because both nations’ economic growths have continued at
similarly high rates.

According to the energy consumption data in Table 4-5, China has consumed
much more energy than Korea in their economic growth, considering the GDP ratio and
the energy consumption ratio. The primary energy consumption ratio between the two
nations, however, has shown a tendency to become smaller and smaller since 1980, in
terms of both total amount consumed and the consumption per capita. This shows the
growth rate of Korea’s primary energy consumption has been much higher than that of
Chinese primary energy consumption. Considering the fact that the two nations have had
similar GDP growth rates, it can also be stated that Korea’s economy has been in
transition of the relatively highly increasing energy consumption compared with the
China’s economy. Figure 4-3 shows the comparison of the energy intensity between

China and Korea, where the energy intensity means the amount of energy consumption

68

per unit of economic output. According to Figure 4-3, Korea’s energy intensity has been
relatively much lower than China’s, but has been in a slightly increasing trend since the
year 1987. China’s energy intensity has declined at a rapid rate since the year 1980 by
adopting more efﬁcient factories and power plants. The Energy Information
Administration’s analysis on China’s energy situation reports that, at present, China has

still one of the highest energy intensities in the world. (EIA, 1998)

Figure 4-3. Comparative Display of Energy Intensity of China and Korea

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We

§ 140.000

m 1
. 120.000 1

U).

3 100.000 1

§ 80.000 1

Pee 60.000 1
8 40.000 . 1

2 20.000

m i

c 0.000 ' L ’ * ' 1 l L .

.9 Ov-NOOVLDCDNGDCDOw—NOOVLDCDI

= cococooooooooocooooommmcnmcnoai

E eeaeeeeeeeeeeeeee'
. L L. _ ___.z__ z#____m_m. 1
.__+_‘____C_hina +K re Year

 

 

Regarding the SO, and NOx emission ratios, they turned out to be much higher
than the GDP and the energy consumption ratios in Table 4-5. The ratios of SO, and NO,
emissions per GDP and per the energy consumption between the two nations, are much
higher than the primary energy consumption ratio as well as the GDP ratios with an
exception of the SO, emission per energy consumption. Therefore, it can be concluded

that China has been generating much more pollution than Korea during the years from

69

1980 through 1996, in terms of the SO, and NO, emission per GDP and per energy
consumption as well as in terms of the total amount of SO, and NO, emitted.

In particular, China emitted NO, to a much greater extent than Korea. While the
average of the SO, ratio between the two nations was 14.40, that of the NO, ratio has
been 134.96. The NOx emission ratios are almost ten times larger than the SO, emission
ratios as presented in the six columns from the right of Table 4-5. This means that,
unlike Korea, China has had much more NO, generating economic growth than 80,.

Finally, Korea can be said to have had an environmentally cleaner economic
growth since 1980 than China, possibly due to its stricter environmental standards and
regulation, environmentally cleaner technologies, more investment into the environment,

and more public awareness about environmental issues.

D. Modeling and Simulation Analysis

As real world problems are complex, multifaceted, and interrelated, it is not easy
to understand them. Therefore, it is useful to abstract from details and simplify problems
in order to understand the problems on a larger picture. Such abstractions of the real
problems are models, and they are often useful."8

With the help of a personal computer and graphical programming, a Northeast
Asian transboundary air pollution model was created. The model mimics the phenomena
in the real world and makes possible the explanation of the dynamic process of the

transboundary air pollution problems in Northeast Asia. This computer model is

70

dynamic and attempts to sense and represent changes in simulated time in a system’s
behavior. It can also predict the futures of those problems.
In this section of the Chapter, the details of the Northeast Asian transboundary air

pollution model are presented, including its modeling process and the simulation results.

1. Introduction of Model Components. (HPS, 1994 and 1996)

There are some basic components that are used in modeling within the
environment of STELLA Research 5.1.1. They are stocks, ﬂows, converters, and
connectors.

Stocks are states of being, and show how things are. They represent anything that
accumulates by ﬂowing in and out. Stocks represent accumulations, both physical and
non-physical. An accumulation exists at a point in time. These stocks are state variables
that indicate and record the states or condition of the system in the model. The state
variables or stocks are used to make all the calculations when the model is run.

Flows represent activities that will change the magnitudes of stocks in a system
by ﬁlling and draining. They exist over time, but they disappear when the action is
frozen. The ﬂows are control variables that control the states of state variables or stocks.

Converters are translation variables that are used to store constants, deﬁne
external inputs and perform algebra. They make explicit the details of ﬂow logic and

house graphical function. They also contain various built-in functions.

 

6‘ A basic principle in modeling is a model should be simple. Einstein said “The best models are as simple
as possible, but no simpler!” St. Exupéry also argued “The way to determine when a model is “good
enough” is not when there’s nothing left to add, but when there’s nothing left to take out.”

71

Connectors are information arrows that carry the information which generate or
regulate ﬂows, and they are inputs, not inﬂows. Connectors transmit rather than transport,

and therefore cannot connect into stock.

Figure 4-4. Model Components

 

 

 

 

 

 

 

:9 Sector A a
Stock Converter Connector

 

 

 

 

 

 

2. Assumptions

It is important to make some assumptions when building a simulation model, for
the sake of the model simpliﬁcation and making the model runnable. Running the
simulation model produces the results of the structural and dynamic assumptions made in
the abstractions of the transboundary air pollution problems in Northeast Asia.

Several assumptions were made prior to building of the transboundary air
pollution model. Firstly, only the ‘factories’ emit the air pollutants, the SO, and NO,.69
This is for the sirnpliﬁcation’s sake. Secondly, the emission of the air pollutants is in a

positive relationship with the number of factories. Thirdly, the difference of the GDP

 

6" The only air pollutants that the Northeast Asian transboundary air pollution model deve10ped in this

72

between the two nations, China and Korea, makes that of the number of factories between
the two nations in the initial year of the simulation run, the year 1988. Fourthly, the total
amount of air pollutants that reside in China is the total Chinese emission of them
subtracted by the amount that ﬂies over to Korea by the transboundary movement.
Fiﬂhly, the total amount of air pollutants that affect Korea is the sum of the air pollutants
from China and the amount of Korean emissions subtracted by the amount of air
pollutants that ﬂie or disperse out of Korea. Sixthly, as GDP increases, more factories
are built, thus creating more emission of air pollutants. Seventhly, as an assumption of
the Korean air pollution regulation policy, the top one percent of the air pollution
generating factories in Korea get their emission control system upgraded, or else, closed
down every year by the government, while China doesn’t have the same regulation for
their factories yet. Finally, with the adoption of cleaner technology, newly built factories
emit 10 percent less than the average SO, and NOx emission levels of all the factories in

the previous year in China and Korea.
3. Process of Simulation Model Construction

The steps taken in constructing the Northeast Asian transboundary air pollution
model are presented in Figure 4-4.

Firstly, the deﬁnition of the problem and the goals of the model were set as
described previously.

Secondly, the decision was made on what the state variables should be. The

examples of the state variable in the Northeast Asian transboundary air pollution model

 

research deals with are SO, and NO,.

73

include: air pollutants in China and in Korea (both SO, and NO,); and the number of
Chinese and Korean factories that produce those air pollutants. (APPENDIX E and
APPENDIX F) Some conditions were given based on actual measurements such as the
SO, and NO, emissions in China and Korea for the initial year, 1998. The numbers are:
16679 kilo tons of SO, and 64212 kilo tons NO, for China, and 1117 kilo tons of SO, and
417 kilo tons of NOx for Korea. Some arbitrary numbers were given as conditions for
both Chinese and Korean number of factories for the initial year 1988 by the author’s
guess. The number for Chinese factories was given 500,000. Using the number 500,000,
the number for Korean factories (268,817 was given) was calculated in proportion to the
ratio (1.86:1) between the Chinese GDP (282.197 billions of 1987 US. dollars) and the
Korean GDP (151.726) in the year 1988.

Thirdly, the control variables were selected. The examples of control variables in
the model are as follows with the numbers or the way the values were given in the
parentheses following each variable (APPENDIX E):

O factories built and to be built (arbitrary graphical function);

0 factories to close and to be shut down (arbitrary graphical function);

0 average emission fraction (amount of emission divided by the number of factories”);

0 emission fraction for new factories (average emission fraction multiplied by 0.90 for
both SO, and NO, emissions in China, and average emission fraction multiplied by
0.90 for both SO, and NO, emissions in Korea);

0 air pollution regulation (zero for China, and 0.1 for Korea);

0 tax-induced decrease of air pollution (zero for both China and Korea);

 

7° The amount of a pollutant emission equals the number of factories multiplied by the average emission per
factory calculated.

74

O factory utilization fraction (1 for the default value); and

O transboundary movement fractions (0.01, which means 1 percent of Chinese

emissions are transported to Korea by the transboundary movement).

Fourthly, the time length of the model to be run was set to 23 years from the year

1988 to the year 2010, with the size of the simulation time step (‘Delta Time: DT’) one

year, over which stocks (state variables) are updated. The parameters were selected and

set as follows with the minimum and maximum numbers, or the way the values can be

changed in the parentheses following each variable (APPENDIX E):

factories to be built (sets of graphical function);

emission fraction for new factories (minimum of zero to the maximum of one);

air pollution regulation (minimum of zero to the maximum of 0. 1);

tax-induced decrease of air pollution (minimum of zero to the maximum of 0.3);
factory utilization fraction (minimum of zero to the maximum of 1.25);
international agreement (minimum of 0.5 to the maximum of 1.0); and
transboundary movement fractions (on or off, where the value will return 1 for ‘on,’
and zero for ‘off‘)

Fiﬂhly, the selected components were combined into the model and its layout was

examined to check any possible violations or requirements. The directions of ﬂows and

the connection were examined. The unit for all the emissions or the ﬂows to and from the

emission stocks was ‘1,000 tons per year’ except those converters containing constant

numbers.

75

Figure 4-5. Simulation Model Construction Procedure

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Deﬁne Designate Select
Problems D1 State Control
and Goals Variables Variables
Revise & Validate Run, Check Build
Finalize Model
Model - Model Behavior - Model

 

 

 

 

 

 

 

Sixthly, the model was run, and, then, the behavior of the model and its
consistency were examined by varying the parameters. The checking points include:
what controlled the addition and subtraction of the statae variables (the amount of air
pollutants and the number factories); how the addition and subtraction of the state
variables was controlled; and how the stocks were added and subtracted.

Seventhly, aﬂer the model was run, the results were compared with empirical data,
matching the time period and the unit to get validated.

Finally, the model was revised and ﬁnalized.

4. Model Validation

The model validation “to determine if a model is indeed a valid representation of
the system of interest.” (Grant, 1986: 128) A valid model generates good testable

hypotheses that are relevant to certain problems in interest. The design of a validated

76

model will achieve what is expected of it in appropriate conditions. A validated model
will not also get into a confused or illegal state. If a model runs without any
contradictory outcomes or error, then that model is consistent and sound. A consistent

and sound model does not generate or entail mutually contradictory outcomes.

a. Validation By Graphical Display and Tabulation

The type of validation technique depends on what kind of model is to be validated.
It is, therefore, important that the Northeast Asian transboundary air pollution model
adequately simulates present day levels of emission if future projections are to be believed.
Validation of an empirical model like the Northeast Asian air pollution model in this
Chapter should emphasize the correspondence between the behavior of the model and that
of the real system.

To validate the Northeast Asian transboundary air pollution model, the total of
four simulation runs was done. The results of those four runs were compared with the
empirical data collected by the author. The four were the simulation runs of the Chinese
SO, emission, the Chinese NOx emission, the Korean SO, emission, and the Korean NOx
emission, during the years 1988 through and 1994 for China and 1988 through and 1995

for Korea.

77

Figure 4-6. Validation of the Model: SO2 in China

 

Kilo Tons

 

23,000

21,000

19,000

17,000

15,000

+ Simulated $02 + Historical $02

1988 1989 1990 1991 1992 1993 1994
Year

 

 

Figure 4-7. Validation of the Model: NO, in China

 

Kilo Tons

 

100,000

87,500

75,000

62,500

50,000

+Simulated NOx + Hstorical NOx

 

1988 1989 1990 1991 1992 1993 1994
Year

 

78

 

 

Figure 4-8. Validation of the Model: SO2 in Korea

 

 

1,600
1,450
U)
C
.9
2 1,300
.2
1,150
-o-— Simulated 802 + Hstorical 802
1,000
1988 1989 1990 1991 1992 1993 1994 1995
Year

 

 

 

Figure 4-9. Validation of the Model: NO, in Korea

 

 

1,000

800
E’
,2
2 600
.2

400

+ Simulated NOx + Hston‘cal NOx
200
1988 1989 1990 1991 1992 1993 1994 1995
Year

 

 

 

79

Table 4-6. Validation of the Model (Unit: 1,000 tons)71

 

China Korea

Year S SO, E SO, SNO,L ENO, S SOL E SO, SNO, ENOx
1988 16,679.00 16,679.00 64,212.00 64,212.00 1,117.00 1,117.10 417.00 416.50
1989 17,210.73 17,510.00 68,257.86 68,443.00 1,200.681,182.90 465.69 449.50
1990 18,260.49 17,951.00 73,660.50 71,513.00 1,284.051,308.80 529.10 507.20
1991 19,111.11 18,860.00 79,177.73 78,295.00 1,352.481,377.80 604.09 583.10
1992 20,128.72 19,614.00 84,602.27 84,165.00 1,406.841,405.40 669.80 666.00
1993 20,990.75 20,912.00 89,839.11 90,960.00 1,446.09 1,432.60 734.18 753.80
1994 21,990.51 22,208.00 95,145.51 97,754.00 1,483.541,473.50 807.68 842.90
1995 - - - - 1,515.701,494.90 882.65 924.90
Mean 19195.90 19104.86 79270.71 79334.57 135080134913 638.77 642.99

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

As shown in Figures 4-6, 4-7, 4-8, and 4-9 and Table 4-6, the outputs of the
simulation runs are considerably similar to the empirical emission data for both air
pollutants in the two nations. Some simulation outputs for certain years are not as similar
to the historical records of the emission data as others, but the trend of the emission
increase is very close to the empirical data. Considering that no model can mimic a real

world problem identically, it can be stated that this simulation model is sound.

b. Validation by Statistical Analysis: t test and P-value’2

The projected amounts of emissions are only conjectures about the actual

emission amount. However, these conjectures may or may not be true. They could be less

 

7‘ “S” stands for the simulated results, while “E” stands for the empirical data.

72 The t test is a statistical test for the mean of a population and is used when the population is normally
distributed, the standard deviation of the population is unknown, and the sample size is less than 31. The
P-value is the actual probability of getting the sample mean value if the null hypothesis is true. If P is small,
it means a large difference between the quantities of interest in the sample. In this case, the null hypothesis
is rejected. For the decision of how small is small, the maximum probability is speciﬁed, denoted as or, the
level of signiﬁcance selected. If P-value is greater than or, it is for a result that is not statistically signiﬁcant
and the null hypothesis is not rejected (Moore and McCabe, 1993)

80

or more than the actual amounts of emissions. Therefore, it is important how close the
simulated results are to the empirical data to get the simulation model validated.

The sample mean, for example, for the simulated Chinese SO, emissions
(19,195.90 kilo tons) is slightly larger than that for the empirical Chinese SO, emissions
(19,104.86 kilo tons). The difference is 91.04 kilo tons. To ﬁnd out whether this
difference is statistically signiﬁcant, or whether the data lead on to believe that the
simulated and empirical amounts of emissions have different values, statistical analysis
(the t test) was carried out with all the values in Table 4-6. Since the values of the
simulated data may be less or more than those of the empirical data, the t test was two-
tailed. The output summary of the t test is listed in Table 4-7. (APPENDIX G) The
selected level of signiﬁcance (or) for the test is 0.05, which statisticians generally agree on

using.73

Table 4-7. Summary: Results of Statistical Analysis for Model Validation

 

 

 

 

 

 

 

 

 

 

 

China Korea
Test SO2 NO, SO, NO,
I test value -.827 0.1 12 -0.263 0.472
P-value (Sig.two-tailed) 0.440 0.914 0.800 0.651
a 0.05 0.05 0.05 0.05
degrees of freedom 12 12 14 14

 

The critical values of the t distribution with nc - 1 = 6 degrees of freedom are

i2.447 for the Chinese data at the 5% signiﬁcance level (0.05)." For the Korean data, the

 

’3 It is chosen considering the seriousness of the type I error. The type 1 error is a statistical terms. A type
I error occurs if the null hypothesis is rejected, when it is true.

746

the sample size of the simulated and the empirical values for the Korean data, which is 8.

81

nc’ is the sample size of the simulated and the empirical values for the Chinese data, which is 7. ‘n,’ is

 

critical values of the 1 distribution with r1k - 1 = 7 degrees of freedom are i2.365 at the 5%
signiﬁcance level (0.05). The t test values computed for the Chinese data are —0.827 (for
the Chinese SO, emission) and 0.112 (for the Chinese NO, emission), and these two
values fall between the critical values of —2.447 and +2447." For the Korean data, the
computed values of the t test are —0.263 (for the Korean SO, emission) and 0.472 (for the
Korean NO, emission), and these two values also fall between the critical values of —2.365
and +2.3 65. Therefore, the null hypothesis of no emission amount difference is not
rejected. It can be concluded that the differences observed in the samples are not
statistically signiﬁcant (P > 0.05). The observed differences are well within the bounds of
natural sampling variability, and the data provide no support for the alternative hypothesis
that the simulated values are different from the empirical values as to the amounts of

emissions.

5. Results of Simulation: Prediction of the Future Emission Trend

With all the conditions and the relations in the model components, the Northeast
Asian transboundary air pollution model was run with a personal computer to predict the
future trends of air pollution generation within the two nations, China and Korea. Figures
4-10 and 4-11 and Table 4-8 present the results of those simulation runs. By the year
2010, the emissions of Chinese SO, and NO, are projected to increase by 111.1 and 159.6
percent from those in the initial year 1988, and by 37.4 and 45.0 percent from the year
1998. The emissions of Korean SO, and NO, are projected to greatly increase by 86.0

and 296.6 percent from the year 1988, and 29.4 and 53.8 percent from the year 1998. As

 

7’ SPSS 7.5 for Windows was used for these statistical analyses.

82

analyzed in the earlier part of this Chapter, the Korean NO, emission is projected to
increase at such a rapid rate.

The average increase rates of Chinese SO, and NO,( and Korean SO, and NO,l
were 5.6, 6.8, 4.3, and 12.1 percent respectively according to the analysis of the historical
data in the former section of the Chapter. The projection of the simulation runs also
show that the grth rates of the Korean SO, and NO, are similar to those trends. For
example, the Korean NO, emission generation in the year 1988 gets doubled in the

yearl995, tripled in the year 2001, and quadrupled in the year2010.

Figure 4-10. Prediction of the Future SO, Emission Generation Trend

 

40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0

Kilo Tons

 

1988 1991 1994 1997 2000 2003 2006 2009
Year

 

 

 

83

Figure 4-1 1. Prediction of the Future NO, Emission Generation Trend

 

175,000
150,000
125,000
100,000
75,000
50.000
25,000
0

Kilo Tons

 

1988 1991 1994 1997 2000 2003 2006 2009
Year

 

 

 

Table 4-8. Prediction of the Future Emission Generation Trend (Unit: 1,000 ton)

417.00

.10

.11
45.51
1
1 422.56
11
11 1

l 1.67
.05
711.78

137

14 17
l .26
1

 

6. Sensitivity Analyses

One of the most useful types of analysis that can be performed on a model is to
tabulate or graph what happens to one or more output variables as an input variable is
changed. On the main screen of the model’s map level, a set of nodes was created in the
forms of sliders, knobs, and buttons, and it represents different scenarios for model input
values. (APPENDIX D)

In the following subsections a through d, the sensitivity analyses are carried out to
determine how the model responds to input assumptions or changes and what outputs are
made. By recalling each of the scenarios, it is possible to see how the model behaves
under different conditions. The results of the sensitivity analyses are presented in
graphical or tabular forms in those four subsections. Finally, with the outputs from the
four subsections, the sensitivity indices are calculated and presented in the following
subsection, e. With the calculated sensitivity indices for those scenarios, it is possible to

determine which policy option is most sensitive to the input change.

a. Magnitudes of Transboundary Air Pollution in Korea at Different Transboundary

Movement Fractions

The transboundary movement of air pollutants from one nation to another causes

various international environmental problems and conﬂicts between the two nations. The

Northeast Asian transboundary pollution model is designed to deal with the

85

transboundary air pollution issue in the region, particularly between China and Korea.
The model has a node for this purpose, and it was named ‘transboundary movement
fraction (‘C Trans Move Frac’)’ in its modeling layer.

The sensitivity analysis was carried out to see how much SO, and NO, would ﬂy
over to Korea from China as the transboundary movement fraction in the model is
changed. Six different transboundary movement fractions were selected for this analysis.
One of them is, for example, that 1 percent of Chinese air pollutants are ﬂown into Korea
by the transboundary movement and 0.01 was given as an input value. The other ﬁve
different values are: 0.03, 0.05, 0.1, 0.2, and 0.3. The default value in the model is set to
0.01. The results of this sensitivity analysis are presented in Figures 4-12 and 4-13 and

Table 4-9 and 4—10.

Figure 4-12. Sensitivity Analysis: Amount of SO, to Flow Into Korea

 

12,000
10,000
8,000
6,000
4,000
2,000
O

Kilo Tons

 

1988 1991 1994 1997 2000 2003 2006 2009
Year

 

 

1+1%+3%f—5%+10%+20%+30%i

 

 

 

86

Figure 4-13. Sensitivity Analysis: Amount of NOx to Flow Into Korea

 

50,000
40,000

30,000

Kilo Tons

20,000

10,000

 

0
1988 1991 1994 1997 2000 2003 2006 2009

Year
+1%f3%+5_%+10%+20%+30%l

 

 

 

 

Figures 4-12 and 4-13 show the six different lines for the six different values of
the transboundary movement fraction. The line that carries the highest values is the
result of the simulation nm with the transboundary movement fraction of 0.3. It shows
how much Chinese air pollutants are projected to ﬂy over to Korea if the transboundary
movement carries 30 percent of total Chinese emissions of SO2 and NO, to Korea. On
the contrary, the line with lowest values represents the outcome of the simulation run

with the transboundary movement fraction of 0.01.

87

Table 4-9. Sensitivity Analysis: Different Transboundary Movement Fractions (SO,)’°

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Transboundary Movement Fraction

Year 1% 3% 5% 10% 20% 30%

1988 166.79 500.37 833.95 1,667.90 3,335.80 5,003.70
1989 172.11 516.32 860.53 1,721.07 3,442.14 5,163.21
1990 182.60 547.81 913.02 1,826.04 3,652.09 5,478.13
1991 191.11 573.33 955.55 1,911.10 3,822.20 5,733.30
1992 201.29 603.86 1,006.43 2,012.86 4,025 .72 6,038.57
1993 209.91 629.72 1,049.53 2,099.06 4,198.1 1 6,297.17
1994 219.90 659.71 1,099.51 2,199.03 4,398.06 6,597.09
1995 229.66 688.99 1,148.31 2,296.63 4,593.25 6,889.88
1996 239.07 717.20 1,195.33 2,390.66 4,781.33 7,171.99
1997 247.87 743 .62 1,239.37 2,478.75 4,957.50 7,436.25
1998 256.24 768.72 1,281.20 2,562.39 5,124.79 7,687.18
1999 264.93 794.79 1,324.66 2,649.31 5,298.63 7,947.94
2000 272.56 817.69 1,362.81 2,725.63 5,451.25 8,176.88
2001 281.29 843 .86 1,406.43 2,812.85 5,625.71 8,438.56
2002 289.82 869.46 1,449.09 2,898.19 5,796.38 8,694.56
2003 297.80 893 .40 1,489.01 2,978.01 5,956.03 8,934.04
2004 305.86 917.59 1,529.32 3,058.64 6,117.28 9,175.92
2005 314.61 943 .82 1,573.04 3,146.08 6,292.15 9,438.23
2006 322.20 966.59 1,610.98 3,221.95 6,443.90 9,665.85
2007 329.75 989.25 1,648.75 3,297.51 6,595.01 9,892.52
2008 337.63 1,012.90 1,688.16 3,376.32 6,752.63 10,128.95
2009 344.64 1,033.91 1,723.19 3,446.38 6,892.75 10,339.13
2010 352.10 1,056.30 1,760.50 3,521.00 7,042.00 10,563.00

 

 

The values in the Figures 4-12 and 4-13 are presented with numbers in Table 4-9
and 4-10. For easier comparison between the absolute amount of emissions in Korea and
the amount of emissions to be transported from China at 1 percent of the transboundary
movement fraction, ﬁrst, the projected amounts of SO, and NO, emissions in Korea in
the years 1998 and 2010 are as follows:

0 S0,: 1,605.53 kilo tons for the year 1998, 2,077.89 kilo tons for the year 2010

0 N0,: 1075.50 kilo tons for the year 1998, 1653.80 kilo tons for the year 2010

 

76 Amount of SO, to ﬂow into Korea at six different transboundary movement fractions (Unit: 1,000 ton)

88

Table 4-10. Sensitivity Analysis: Different Transboundary Movement Fractions (N 0,)77

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Transboundary Movement Fraction

Year 1% 3% 5% 10% 20% 30%

1988 642.12 1,926.36 3,210.60 6,421.20 12,842.40 19,263.60
1989 682.58 2,047.74 3,412.89 6,825.79 13,651.57 20,477.36
1990 736.60 2,209.81 3,683.02 7,366.05 14,732.10 22,098.15
1991 791.78 2,375.33 3,958.89 7,917.77 15,835.55 23,753.32
1992 846.02 2,538.07 4,230.1 1 8,460.23 16,920.45 25,380.68
1993 898.39 2,695.17 4,491.96 8,983 .91 17,967.82 26,951.73
1994 951.46 2,854.37 4,757.28 9,514.55 19,029.10 28,543.65
1995 1,002.72 3,008.17 5,013.61 10,027.22 20,054.45 30,081.67
1996 1,054.23 3,162.68 5,271.13 10,542.26 21,084.51 31,626.77
1997 1,100.63 3,301.88 5,503.13 11,006.26 22,012.52 33,018.77
1998 1,149.83 3,449.50 5,749.17 1 1,498.33 22,996.66 34,494.99
1999 1,195.52 3,586.55 5,977.58 11,955.17 23,910.33 35,865.50
2000 1,243.51 3,730.53 6,217.55 12,435.11 24,870.21 37,305.32
2001 1,287.12 3,861.35 6,435.59 12,871.18 25,742.36 38,613.53
2002 1,332.13 3,996.39 6,660.65 13,321.30 26,642.60 39,963.90
2003 1,377.55 4,132.66 6,887.77 13,775.54 27,551.08 41,326.62
2004 1,418.74 4,256.23 7,093.71 14,187.42 28,374.83 42,562.25
2005 1,463.21 4,389.64 7,316.06 14,632.13 29,264.25 43,896.38
2006 1,506.72 4,520.15 7,533.58 15,067.17 30,134.33 45,201.50
2007 1,547.01 4,641.03 7,735.05 15,470.] 1 30,940.22 46,410.32
2008 1,586.93 4,760.78 7,934.63 15,869.25 31,738.51 47,607.76
2009 1,627.37 4,882.11 8,136.84 16,273.69 32,547.38 48,821.07
2010 1,666.97 5,000.92 8,334.86 16,669.72 33,339.44 50,009.16

 

 

With the value 0.01 given as the transboundary movement fraction, Tables 4-8
and 4-9 show the amounts of the Chinese SO, and NO, emissions to be ﬂown into Korea
from China. They are the amounts to be added to the domestic SO, and N0, emissions in
Korea, and they are projected to be as follows:

0 80,: 256.24 kilo tons for the year 1998, 352.10 kilo tons for the year 2010

O NO,: 1,149.83 tons for the year 1998, 1,666.97 kilo tons for the year 2010

 

77 Amount of NO, to ﬂow into Korea at six different transboundary movement fractions (Unit: 1,000 ton)

89

They represent 16.0 percent and 16.9 percent of the projected domestic S0,
emissions, and 106.9 percent and 100.8 percent of the projected domestic NO, emissions
in Korea for the two years respectively.

If 3 percent is taken as the value for the transboundary movement, the amounts of
the Chinese SO, and N0, emissions to be added to the Korean domestic emissions gets
tripled. The amounts to be transported are projected to be about 47.9 percent and 50.8
percent of the domestic SO, emissions and 320.7 percent and 302.3 percent of the
domestic NOx emissions in Korea. When the transboundary movement fraction value
was changed to higher values as 0.03, 0.05, 0.1, 0.2, and 0.3, Tables 4-9 and 4-10 show
that the magnitude of the emissions to be transported to Korea increases greatly.

In the case of transboundary movement of the Chinese nitrogen oxides into Korea,
it seems far more serious. This is because nitrogen oxides are emitted much more than
sulfur dioxides in China, while nitrogen oxides are emitted much less compared with
sulfur dioxides in Korea. For example, according to the historical data, the Chinese
emissions of SO, and N0x in the year 1994 were 22,208 and 97,754 kilo tons, while the
Chinese emissions of SO, and N0, in the year 1994 were 1,473.5 and 842.9 tons in the
year 1995. The absolute amount of the Chinese NOx emissions in 1994 is far more than
one hundred times of the Korean NOx emissions in the same year. Therefore, a small
portion of the Chinese S0, and NO, emissions, if ﬂown into Korea, are likely to bring
about enormous impact on the air quality in Korea, and it will be much more in the case
of the nitrogen oxides. For example, with the transboundary movement fraction set to 30

percent, 50,009.16 kilo tons of the Chinese NOx emissions were projected to ﬂy to Korea

90

in the year 2010. It is about thirty times as much as the amount of the Korean domestic
NO, emissions projected in the same year, 1,653.80 kilo tons.

In the following sections of the sensitivity analysis for the transboundary
movement impact, the transboundary movement fraction was assumed to be 0.01, the
smallest number of those six tested. For the subsections b, c, and d, the scenarios and
policy options to be tested are assumed to be put into practice in the year 1998, and, the
consequences of those scenarios and options are set to be occur from the following year
1999. Therefore all the numbers for the years 1998 or earlier, they are exactly same as
those in Table 4-11 which represent the emissions without any scenarios or policy

options taken, except the transboundary movement fraction of 1 percent.

b. Economic Performance

A nation’s economic growth can be boosted or collapsed by unforeseen events in
the economic and non-economic environment. A sudden drop of oil prices and its
maintenance of lower prices for a certain period in international raw materials markets
may lead the economic performance of a nation to increase, if the nation is heavily
dependent on the imported oil as an energy source. In this case, low oil prices are likely
to lead to more consumption of oil, thus leading to more emissions of air pollutants. A
recent ﬁnancial crisis in Asian countries caused their economic performance to become
lower than expected. Many facilities of the factories became idle and many automobiles
reduced their hours of running, which results in less energy consumption and less air

pollution generation.

91

In general, if the economic activities in a nation increase, more pollution is likely
to be generated. In the Northeast Asian transboundary air pollution model, increased
economic activities can be represented in two ways: ﬁrst, as the increase of emissions per
factory or average emissions per factory; and, second, as the increased number of
factories in operation. In the sensitivity analysis to see how much more air pollution will
be generated in China and ﬂown into Korea if China’s economic performance increases
by 10 percent, the latter method was adopted. It means the utilization rates of factories
increase by 10 percent both in China and Korea. The model has nodes for this purpose,
and they were named ‘utilization fraction (‘C Utilization frac’ in China section of the
model).’

Figures 4-14 and 4-15 and Table 4-11 show the total amount of SO, and NO, in
Korea with 1 percent of transboundary movement fraction. These two ﬁgures will be the
ones with which the results of scenarios will be compared in the rest of the Chapter.
Figures 4-14 and 4-15 show the total amount of air pollutants (SO, and NO,) in Korea as
the sum of the amount of those Korean emissions that stay in Korea and the amount of
the Chinese emissions to be ﬂown into Korea. It can easily be understood that quite large
amount of the Chinese emissions is projected to be transported and added to the domestic

air pollutants in Korea.

92

Figure 4-14. Total SO, in Korea at 1% Transboundary Movement Fraction

 

1500
1250
1000

Kilo Tons
‘1
0'!
0

01
O
O

  

N
0'1
0

   

0 , _, 7 , _ , I
1988 1991 1994 1997 2000 2003 2006 2009

Year
lElDomestic 802 .802 from China—l

 

 

 

Figure 4-15. Total NO, in Korea at 1% Transboundary Movement Fraction

 

3,000
2,500
2,000
1,500
1,000

500 .1
1988 1991 1994 1997 2000 2003 2006 2009
Year
F Domestic NOx INOx from China ‘

Kilo Tons

  

 

 

 

93

Table 4-11. Total SO, and NO, in Korea at 1% Transboundary Movement Fraction"

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

so, NOx

Year Domestic from China Total Domestic from China Total

1988 558.50 166.79 725.29 208.50 642.12 850.62
1989 600.34 172.11 772.45 232.85 682.58 915.42
1990 642.02 182.60 824.63 264.55 736.60 1,001.16
1991 676.24 191 .11 867.35 302.04 791.78 1,093.82
1992 703.42 201.29 904.70 334.90 846.02 1,180.92
1993 723.05 209.91 932.95 367.09 898.39 1,265.48
1994 741.77 219.90 961.67 403.84 951.46 1,355.30
1995 757.85 229.66 987.51 441.33 1,002.72 1,444.05
1996 770.53 239.07 1009.60 476.97 1,054.23 1,531.20
1997 787.87 247.87 1035.75 507.46 1,100.63 1,608.09
1998 802.66 256.24 1058.90 537.75 1,149.83 1,687.58
1999 816.75 264.93 1081.69 569.67 1,195.52 1,765.19
2000 835.36 272.56 1107.92 599.50 1,243.51 1,843.01
2001 859.11 281.29 1140.39 623.73 1,287.12 1,910.84
2002 877.50 289.82 1167.32 648.03 1,332.13 1,980.16
2003 891.63 297.80 1189.43 673.59 1,377.55 2,051.14
2004 909.31 305.86 1215.17 698.84 1,418.74 2,117.59
2005 928.67 314.61 1243 .28 721.48 1,463.21 2,184.70
2006 949.63 322.20 1271.82 743.66 1,506.72 2,250.38
2007 964.64 329.75 1294.39 766.25 1,547 .01 2,313.26
2008 983.87 337.63 1321.50 786.95 1,586.93 2,373.87
2009 1011.22 344.64 1355.86 807.54 1,627.37 2,434.91
2010 1038.94 352.10 1391.04 826.90 1,666.97 2,493.87

 

In this section of the sensitivity analysis, two different scenarios are recalled in

combination, such as the combination of 1 percent as the transboundary movement

fraction and 10 percent as the utilization fraction for China. Table 4-12 and Figures 4-16

and 4-17 present the amount of the air pollution that is projected to be ﬂown into Korea

by the transboundary movement with 1 percent of transboundary movement fraction.

 

’3 Unit: 1,000 ton

94

 

Figure 4-16. Sensitivity Analysis (80,: 10% Utilization )79

 

1,600
1,400
1,200
1,000
800
600
400
200
O
1988 1991 1994 1997 2000 2003 2006 2009
_ Year
L1:1 Domestic 802 l902_frorn China

Kilo Tons

 

 

 

 

 

 

As anticipated, the simulated results show that, with the 10 percent increase of
Chinese economic performance from the year 1999, more SO, and NO, emissions are
projected to be transported to Korea. Figures 4-16 and 4-17 show sudden increases of the
emission amounts in the year 1999. This stems from the increased production activities
of the Chinese factories and the increased air pollution generation pertaining to them.

With 10 percent increase of the utilization of both Chinese and Korean factories,
the Chinese SO, to ﬂow into Korea (in Figure 4-16) amounts up to 387.31 kilo tons from
352.10 in the year 2010, which is the amount projected without the 10 percent utilization
increase. The increase of the Chinese NO, to ﬂow into Korea is 166.7 kilo tons from
1,666.97 kilo tons to 1,833.67 kilo tons (in Figure 4-17) in the year 2010. Both of the

increases of the Chinese SO, and NO, emissions to be ﬂown into Korea are about 10

 

7’ Total simulated amount of S0, in Korea, with 10% increase of factory utilization in China and Korea

95

percent. The amounts of Chinese SO, and NO, emissions to ﬂow into Korea in the year
2010 are 33.9 percent and 201.6 percent of the domestic SO, and NO, emissions that stay
in Korea. (The default fraction for the dispersion of Korean domestic emissions is set to
50 percent, which means 50 percent of Korean domestic emissions disperse or ﬂy away
out of the Korean Peninsula, and the remaining 50 percent of the emissions stay inside

Korea.)

Figure 4-17. Sensitivity Analysis (NO,: 10% Utilization) 8°

 

3,000
2,500
2,000
1,500
1,000

500 ' _ ‘
1988 1991 1994 1997 2000 2003 2006 2009
ﬂ , LL,
{DDomestic NOx INOx from China

Kilo Tons

      

     

     

 

 

(ﬁe-1 1

 

 

 

 

 

Therefore, the 10 percent increase of the Chinese economic performance is
projected to result in the addition of a considerable amount of NO, to the Korean
domestic NO, emission problem, but the SO, amount projected to be added doesn’t seem

to be as much as the NO, emissions although it is still a considerable amount.

 

‘° Total Simulated Amount of NO, in Korea, With 10% Increase of Factory Utilization in China and Korea

96

Table 4-12. Sensitivity Analysis: Utilization (Unit: 1,000 ton)81

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SO, N0,

Year Domestic From China Total Domestic From China Total
1988 558.50 166.79 725.29 208.50 642.12 850.62
1989 600.34 172.11 772.45 232.85 682.58 915.42
1990 642.02 182.60 824.63 264.55 736.60 1,001.16
1991 676.24 191.11 867.35 302.04 791.78 1,093.82
1992 703.42 201.29 904.70 334.90 846.02 1,180.92
1993 723.05 209.91 932.95 367.09 898.39 1,265.48
1994 741.77 219.90 961.67 403.84 951 .46 1,355.30
1995 757.85 229.66 987.51 441.33 1,002.72 1,444.05
1996 7 70.53 239.07 1,009.60 476.97 1,054.23 1,531.20
1997 787.87 247.87 1,035.75 507.46 1,100.63 1,608.09
1998 802.66 256.24 1,058.90 537.75 1,149.83 1,687.58
1999 898.43 291.42 1,189.86 626.64 1,315.07 1,941.71
2000 918.90 299.82 1,218.71 659.45 1,367.86 2,027.31
2001 945.02 309.41 1,254.43 686.10 1,415.83 2,101.93
2002 965.25 318.80 1,284.05 712.84 1,465.34 2,178.18
2003 980.80 327.58 1,308.38 740.95 1,515.31 2,256.25
2004 1,000.24 336.45 1,336.69 768.73 1,560.62 2,329.34
2005 1,021.54 346.07 1,367.61 793.63 1,609.53 2,403.17
2006 1,044.59 354.41 1,399.01 818.03 1,657.39 2,475.41
2007 1,061.10 362.73 1,423.82 842.88 1,701.71 2,544.59
2008 1,082.26 371.39 1,453.65 865.64 1,745.62 2,611.26
2009 1,112.34 379.10 1,491.45 888.29 1,790.11 2,678.40
2010 1,142.84 387.31 1,530.15 909.59 1,833.67 2,743.26

 

 

c. Governmental Environmental Policies

A nation’s air pollution is regulated by the governmental environmental policies
that are designed to reduce the emissions. Sometimes, governments provide subsidies to

lead the factories to reduce their emission levels, or levy pollution tax to make them pay

 

8‘ Total simulated amount of SO, and NO, in Korea with 10% increase of factory utilization rates in China
and Korea, at 1% transboundary movement ﬁaction.

97

for the cleanups. If there are certain effective enforcements of air pollution regulations

by the government in a nation, the amount of air pollutant emission is likely to be

reduced.

The reduction can be made by in many ways. Some of them include: building
more efﬁcient coal-powered generating plants, replacing outdated industrial boilers,
producing more efﬁcient coal briquettes, expanding the energy supply by building
hydropower plants, developing nuclear power, using natural gas for heating and cooking,
and investing in renewable energy sources. (EPA, 1998) Sometimes, governments set a
standard that factories should abide by, and if they don’t observe the standard, they are
forced to stop operation or even to close down their facilities.

In this section of the sensitivity analysis, two policy options are tested:

0 ﬁrstly, the Chinese government forces 1 percent of air-pollution-generating factories
to stop operating every year (those factories are removed from the market)”; and,

O secondly, the Chinese government levies an air pollution tax on highly polluting
factories, forcing the them to get their emission control system upgraded, which
should result in 15 percent reduction of the total Chinese emissions.

The results of the sensitivity analysis are displayed in Figures 4-18, 4-19, 4-20
and 4-21, and Tables 4-13 and 4-14. With the 1 percent reduction of the number of
Chinese factories from the year 1999, the Chinese SO, to ﬂow into Korea gets reduced
from 352.10 kilo tons down to 323.37 kilo tons (in Figure 4-18) in the year 2010. It
means 8.2 percent reduction from the amount projected in the year 2010 without the

environmental regulation option.

 

’2 In real policy arena, it is more reasonable to choose some of most highly polluting factories of all.
However, in this model, for the simpliﬁcation of the analysis, 1 percent of the factories are forced to stop

98

Figure 4-18. Sensitivity Analysis: SO, Regulation”

 

1600
1400
1200
1000

800

Kilo Tons

     

1988 1991 1994 1997 2000 2003 2006 2009
Year
ETD—omestic $02 ISOZ from China

 

 

 

 

 

The decrease of the Chinese NO, to ﬂow into Korea is by 135.11 kilo tons from
1,667.97 kilo tons to 1,531.86 kilo tons (in Figure 4-19) in the year 2010, which is about
8.1 percent reduction compared to the projected amount of the Chinese NO,( to ﬂow into
Korea without the Chinese governmental regulation option tested.

Therefore, the 1 percent reduction of the number of the Chinese factories by the
Chinese environmental regulation turns out to be effective in reducing the amount of air
pollutants ﬂying from China to Korea as well as reducing the amount of emissions in
China. However, regardless of the reduction, due to the transboundary movement of air
pollutants from China, Korea is still projected to suffer from the addition as much as

about 31.1 percent and 185.3 percent of its own domestic SO, and NO, emissions.

 

operation and to be removed from the market.
3’ : Impact of 1% Reduction of the Number of Chinese Factories that are environmentally unclean.

99

Figure 4-19. Sensitivity Analysis: NO, Regulation84

 

3000
2500
2000
1500
1000

500

o ir 'V i .1 W1 :1, V l
1988 1991 1994 1997 2000 2003 2006 2009
Year

IDDomestic N0x INOx from China 1

Kilo Tons

 

 

 

 

 

 

Table 4-13. Sensitivity Analysis: Regulation (Unit: 1,000 ton)85

From From
1 2

1 .58
19

 

 

" Impact of 1 % Reduction of the Number of Chinese Factories that are environmentally unclean). Unit:
1,000 ton.

'5 Total simulated amount of air pollutants in Korea, with the reduction of the number of Chinese factories
that are environmentally unclean by 1% by the regulation of the Chinese government, at 1 % transboundary
movement fraction.

100

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2000 835.36 269.91 1105.27 599.50 1231.56 1831.05
2001 859.11 276.00 1135.11 623.73 1263.11 1886.83
2002 877.50 281.91 1 159.40 648.03 1296.01 1944.04
2003 891.63 287.26 1 178.89 673.59 1329.25 2002.84
2004 909.31 292.71 1202.01 698.84 1358.18 2057.02
2005 928.67 298.84 1227.51 721.48 1390.35 2111.84
2006 949.63 303.82 1253.44 743.66 1421.49 2165.15
2007 964.64 308.77 1273 .41 766.25 1449.35 2215.61
2008 983.87 314.06 1297.93 786.95 1476.81 2263.76
2009 1011.22 318.48 1329.70 807.54 1504.77 2312.31
2010 1038.94 323.37 1362.31 826.90 1531.86 2358.76

 

The second policy option was tested to see how much the amount of pollution

from China would be reduced, by upgrading the emission control systems of the factories

in China and Korea, which were designed to result in 15 percent reduction of the total

emission generation in both nations from the year 1999. The results of this particular

sensitivity analysis are displayed in Figures 4-20 and 4-21, and Tables 4-14, and they

 

 

were the outcomes with 1 percent of transboundary movement fraction.

With the 15 percent emission reduction by upgrading the emission control
systems of both Chinese and Korean factories from the year 1999, the Chinese 80, to
ﬂow into Korea gets reduced from 352.10 kilo tons down to 335.86 kilo tons (in Figure
4-20) in the year 2010. This is a 4.6 percent reduction from the amount projected in the
year 2010 without this policy option.

The amount of the decreased Chinese NO, to ﬂow into Korea is 260.98 kilo tons,
from 1,666.97 kilo tons to 1,406.99 kilo tons (in Figure 4-21), in the year 2010. This is

about 15.6 percent reduction.

101

Figure 4-20. Sensitivity Analysis: SO, Air Pollution Tax Policy“

 

1600
1400
1200
1000
800
600
400
200
1988 1991 1994 1997 2000 2003 2006 2009
Year
kDﬁDgnestic $02 .802 from China 1

Kilo Tons

 

 

 

 

 

 

It is worth noting that the growth rate of the projected amount of the Chinese SO,
and NO, to ﬂy over to Korea decreased, although the absolute projected amount of air
pollutants to be transported continued to grow. Particularly, the amount of the Chinese
NO, to ﬂy over to Korea begins to increase at lower rates immediately from the year
1999 (in Figure 4-21), thus those graph lines becoming to be in smoother increasing
trends from the year 1999. This combined reduction is projected to be greatly effective in
reducing the total amount of N0, in Korea. The amount of N0, generated and residing in
Korea without any foreign addition NO, in the year 2010 was 825.19 kilo tons. However
the total amount of NO, combined with the Chinese NO, ﬂown into Korea in the year
2010 is projected to be 2232.18 kilo tons, which is 10.5 percent reduction compared with

the amount without this policy option.

 

'6 An air pollution tax policy to bring about 15% reduction of air pollutants by forcing the factories to get
their emission control system upgraded.

102

Figure 4-21. Sensitivity Analysis: NO, Air Pollution Tax Policy"7

 

3000
2500
2000
1500
1000

500

Kilo Tons

  

' It“. J VL . A. 1 5‘"? J 1 . ﬂ.“
1988 1991 1994 1997 2000 2003 2006 2009
Year

in Domestic N0x INOx from China 1

 

 

 

 

 

 

Both the total amounts of SO, and NO, including the Chinese additions were projected to
be reduced greatly in the year 2010 with the air pollution tax policy that led to the
upgrade of the emission control systems of the factories in China and Korea, designed to

reduce the total amount of emissions by 15 percent.

 

'7 An air pollution tax policy to bring about 15% reduction of air pollutants by forcing the factories to get
their emission control system upgraded.

103

Table 4-14. Sensitivity Analysis: Air Pollution Tax (Unit: 1,000 ton)88

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SO, NO,

Year Domestic From China Total Domestic From China Total

1988 558.50 166.79 725.29 208.50 642.12 850.62
1989 600.34 172.11 772.45 232.85 682.58 915.42
1990 642.02 182.60 824.63 264.55 736.60 1001.16
1991 676.24 191.11 867.35 302.04 791.78 1093.82
1992 703.42 201.29 904.70 334.90 846.02 1 180.92
1993 723.05 209.91 932.95 367.09 898.39 1265.48
1994 741.77 219.90 961.67 403.84 951.46 1355.30
1995 757.85 229.66 987.51 441.33 1002.72 1444.05
1996 770.53 239.07 1009.60 476.97 1054.23 1531.20
1997 787.87 247.87 1035.75 507.46 1100.63 1608.09
1998 802.66 256.24 1058.90 537.75 1149.83 1687.58
1999 816.75 264.93 1081.69 569.67 1195.52 1765.19
2000 834.89 271.34 1106.23 599.38 1222.51 1821.89
2001 858.15 278.78 1136.93 623.49 1244.41 1867.90
2002 876.03 285.98 1162.00 647.66 1267.07 1914.73
2003 889.64 292.57 1182.22 673.07 1289.50 1962.57
2004 906.78 299.19 1205.98 698.18 1307.38 2005.55
2005 925.58 306.43 1232.02 720.66 1327.83 2048.49
2006 945.96 312.49 1258.45 742.67 1346.90 2089.57
2007 960.39 318.47 1278.86 765.09 1362.64 2127.73
2008 979.01 324.73 1303.74 785.61 1377.69 2163.30
2009 1005.70 330.09 1335.79 806.02 1392.86 2198.88
2010 1032.72 335.86 1368.58 825.19 1406.99 2232.18

 

(1. International Agreement between China and Korea

 

An international pollution problem cannot be solved effectively by a single
nation’s effort. It is especially the case with the transboundary air pollution problems.
The last scenario that was tested with the model was the option of the

international environmental policy cooperation between China and Korea. According to

 

8' Total Simulated Amount of Air Pollutants in Korea at 1% Transboundary Movement Fraction, With 5%
Upgrade of the Emission Control Systems by an Air Pollution Tax in China and Korea

104

this policy cooperation, from 1999 China and Korea should force the newly built
factories to be equipped with the emission control system that allows 20 percent less than
the average emission per factory in their nations.

The sensitivity analysis results of this scenario are presented in the Figures 4-22
and 4-23, and Table 4-15. This policy option was tested to see how sensitively the
amount of pollution generation in China and Korea and the transportation from China
would be reduced by the international agreement between the two nations and its
enforcement stated above.

With the option of the newly built factories being equipped with 20 percent
cleaner emission control systems in both Chinese and Korean factories, the simulation
was run. As results, according to Figures 4-22 and 4-23 and Table 4-15, the Chinese SO2
to ﬂow into Korea gets reduced from 352.10 kilo tons down to 315.33 kilo tons (in Figure
4-22) in the year 2010. This is calculated to be a 10.4 percent reduction from the amount
projected in the year 2010 without the agreement between China and Korea. As shown in
Figure 4-22, the increasing rates of the total SO2 in Korea greatly reduced and became
stable with an average of 1.3 percent.

The amount of the decreased Chinese NO, that would have ﬂown into Korea was
reduced by 218.84 kilo tons from 1,666.97 kilo tons to 1,488.13 kilo tons (in Figure 4-23)
in the year 1998, explaining about 10.7 percent decrease. The increasing rates calculated
is 4.4 percent in the year 1999, and continues to get lower, reaching down to 1.4 percent
in the year 2010. However, the projected absolute amount of the Chinese SO2 and NO, to

ﬂy over to Korea is still increasing.

105

Figure 4-22. Sensitivity Analysis: SO2 An International Agreement”

 

1600
1400
1200
1000 l,,-.r.1"
800 ->- »“ 7r73

Kilo Tons

  
  

 

0 i - ~;. .
1988 1991 1994 1997 2000 2003 2006 2009
Year

jDDomestic 802 IS02 from China 1

 

 

 

 

Figure 4-23. Sensitivity Analysis: NOx - An International Agreement90

 

3000
2600
2200
1800
1400
1000

600

200

‘i888

Kilo Tons

 

1991 1994 1997 2000 2003 2006 2009
Year

[E1 Domestic NOx INOx from China 1

 

 

 

 

 

'9 An international agreement to enforce newly built factories to be equipped with 20% cleaner emission

control system in China and Korea.
9° Enforcing newly built factories to be equipped with 20% cleaner emission control system in China and

Korea.

106

Table 4-15. Sensitivity Analysis: International Agreement (Unit: 1,000 ton)”

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SO2 NO,

Year Domestic From China Total Domestic From China Total

1988 558.50 166.79 725.29 208.50 642. 12 850.62
1989 600.34 172.11 772.45 232.85 682.58 915.42
1990 642.02 182.60 824.63 264.55 736.60 1001.16
1991 676.24 191.11 867.35 302.04 791.78 1093.82
1992 703.42 201.29 904.70 334.90 846.02 1 180.92
1993 723.05 209.91 932.95 367.09 898.39 1265.48
1994 741.77 219.90 961.67 403.84 951 .46 1355.30
1995 757.85 229.66 987.51 441.33 1002.72 1444.05
1996 770.53 239.07 1009.60 476.97 1054.23 1531.20
1997 787.87 247.87 1035.75 507.46 1100.63 1608.09
1998 802.66 256.24 1058.90 537.75 1149.83 1687.58
1999 816.75 264.93 1081 .69 569.67 1195.52 1765.19
2000 826.37 269.71 1096.09 589.86 1228.60 1818.46
2001 839.84 275.27 1115.11 605.13 1257.61 1862.74
2002 848.81 280.57 1129.39 620.10 1287.20 1907.30
2003 854.28 285.35 1139.63 635.66 1316.59 1952.26
2004 862.32 290.1 1 1 152.43 650.64 1342.23 1992.87
2005 871.46 295.29 1 166.75 663.30 1369.93 2033.23
2006 881.57 299.51 1181.08 675.34 1396.42 2071.76
2007 887.04 303.63 1 190.67 687.40 1420.09 2107.49
2008 895.47 307.92 1203.39 697.83 1443.09 2140.92
2009 909.62 31 1.49 1221.1 1 707.94 1466.10 2174.04
2010 923.70 315.33 1239.03 716.95 1488.13 2205.08

 

e. Sensitivity Indices

As the ﬁnal step of the sensitivity analysis, the sensitivity index was calculated for

each scenario or policy option tested and discussed in the preceding sections. The

sensitivity indices calculated are meant to indicate how sensitively the amount of the

107

 

Chinese emissions to ﬂow into Korea increase or decrease, responding to the change of
the scenarios or the policy options. The calculation of sensitivity indices was based on

the following formula in Figure 4-24.

Figure 4-24. Sensitivity Analysis Index

 

sx=(Axolxo)l(APoIPo)={(x1'xo)lxo}’{(P1'Po)IPo}

 

 

 

Table 4-16 and 4-17 show the comparison between policy options tested in terms
of their effectiveness in the reduction or the increase of the amount of the Chinese
emissions projected to be transported into Korea, with those policy options enforced in
the years starting from 1999. The sensitivity indices are indicators of the effectiveness of
the unit of each policy option in the emission reduction. Finally, the sensitivity ranking is
presented in Table 4-18.

According to Table 4-16, 4-17, and 4-18 the transportation of the Chinese SO2 and
NOx emissions to Korea increased most sensitively to the Chinese governmental
regulation. The Chinese governmental regulation was designed to result in the equivalent
of forcing 1 percent of the total number of the SO2 and NO, emitting factories to stop
operation or close themselves by regulating the factories that didn’t meet the Chinese
emission standards. It implies that with all the conditions built in the model, it is the

most effective policy option to control the amount of emissions.

 

9' Total Simulated Amount of Air Pollutants in Korea at 1% Transboundary Movement Fraction, With An
lntemational Agreement (Enforcing Newly Built Factories to be Equipped with 20% Cleaner Emission

108

 

The option of factory utilization, economic performance, also turned out to be a

very effective policy option. Its sensitivity indices for the 802, and NO, emissions are

0.935 and 0.938 respectively. In the analysis earlier, the value for the utilization tested

was 10 percent increase, and it resulted in the sudden increase of emissions from the year

1999. In a contrary situation that the economic performance is lowered under certain

economic environment, the Chinese emissions to be transported will also be reduced or

the increase rate of the emissions growth will be lowered.

Table 4-16. Sensitivity Indices: SO2 (Unit Except Indices: 1,000 ton)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

No Policy Utilization Regulation Tax Agreement

Year - 10% 1% 15% 20%
1998 256.24 256.24 256.24 256.24 256.24
1999 264.93 291.42 264.93 264.93 264.93
2000 272.56 299.82 269.91 271.34 269.71
2001 281 .29 309.41 276.00 278.78 275.27
2002 289.82 318.80 281.91 285.98 280.57
2003 297.80 327.58 287.26 292.57 285.35
2004 305.86 336.45 292.71 299.19 290.11
2005 314.61 346.07 298.84 306.43 295.29
2006 322.20 354.41 303.82 312.49 299.51
2007 329.75 362.73 308.77 318.47 303.63
2008 337.63 371.39 314.06 324.73 307.92
2009 344.64 379.10 318.48 330.09 31 1.49
2010 352.10 387.31 323.37 335.86 315.33
Average 305.34 333.90 292.02 298.24 288.87
Sensitivity Index - 0.935 4.362 0.555 0.270

 

 

 

Control System in China and Korea) (Unit: 1,000 ton)

109

 

Table 4-17. Sensitivity Indices: NO, (Unit Except Indices: 1,000 ton)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

No Policy Utilization Regulation Tax AJgreement
Year \ Rates - 10% 1% 15% 20%

1998 1,149.83 1,149.83 1149.83 1149.83 1149.83
1999 1,195.52 1,315.07 1195.52 1195.52 1195.52
2000 1,243.51 1,367.86 1231.56 1222.51 1228.60
2001 1,287.12 1,415.83 1263.11 1244.41 1257.61
2002 1,332.13 1,465.34 1296.01 1267.07 1287.20
2003 1,377.55 1,515.31 1329.25 1289.50 1316.59
2004 1,418.74 1,560.62 1358.18 1307.38 1342.23
2005 1,463.21 1,609.53 1390.35 1327.83 1369.93
2006 1,506.72 1,657.39 1421.49 1346.90 1396.42
2007 1,547.01 1,701 .71 1449.35 1362.64 1420.09
2008 1,586.93 1,745.62 1476.81 1377.69 1443.09
2009 1,627.37 1,790.11 1504.77 1392.86 1466.10
2010 1,666.97 1,833.67 1531.86 1406.99 1488.13

Average 1,415.59 1,548.30 1,353.70 1,299.32 1,335.49

Sensitivity Index - 0.938 4.372 0.548 0.283
Table 4-18. Sensitivity Ranking
SO2 NO,
Ranking Scenario Option Ranking Scenario Option
1 Regulation (Reduction of the 1 Regulation (Reduction of the
number of Factories) number of Factories)
2 Utilization (Economic 2 Utilization (Economic
Performance) Performance)
3 Tax (Emission Control 3 Tax (Emission Control
System Upgrade) System Upgrade)
4 Int’l Agreement (Emission 4 Int’l Agreement (Emission
Reduction) Reduction)

 

 

 

 

110

 

 

Chapter 5

CONCLUSION

Until recently, the air pollution problems that used to be given attention by
societies or nations were local problems arising from their sources. However, around the
end of the nineteen sixties, the seriousness of the acidiﬁcation of rain was noticed in
Europe, including areas and regions that were far away from the industrial sites. Since
then, the long-range movement of air pollutants and its impact on the natural and human
environments have been researched by scholars.

Air pollution is a kind of pollution that does not show any respect for national
boundaries and sovereignty. The efﬂuents of air pollutants from inside the Chinese
mainland do not show respect for the political boundaries around its land. Therefore,
Northeast Asia, like other parts of the world, is subject to environmental conﬂicts among
nations in the region.

Recently, rapidly increased economic activities in China are worsening the
problem of acid rain. Their growing population and production activities have needed
more power stations to produce electricity, which causes more pollution to be emitted
into the air. The problem of acid rain has been exacerbated because developing countries
like China cannot usually afford the cost of reducing emissions that cause acid rain.
Some of their governments refuse to recognize that acid rain and air pollution are serious

problems, and, therefore, do not want to pay the cost of emission reduction.

111

The main source of sulfur dioxides and nitrogen oxides, so called “acid rain
gases,” is known to be the combustion of fossil fuels. China, a rapidly developing nation
with a very large population, is one of the most highly fossil fuels consuming and air
pollution generating nations in the world. China and Korea, located right next to each
other in Northeast Asia, are in a situation that they need to deal with the long-range
transport of the pollutants between them. Korea has suffered from the transboundary
movement of Chinese air pollutants from China into its territory. However, there has not
been any effective effort made by the two nations to solve the problem. This is partly due
to the political regimes of the two nations, with ideological differences, which did not get
along with each other for some years. However, it is also due to the lack of scientiﬁc
evidence to prove the existence of the serious transboundary air pollution problems
between the two nations, and, to the magnitude of the environmental impacts from which
Korea have had to suffer.

Since the end of the Cold War, economic cooperation has been rapidly increasing
between China and Korea. The relationship between the two nations can be said to have
entered into a new era. Therefore, it is time that China and Korea began to think about
establishing a regime through a series of environmental negotiations, a strategy to protect
the environment in Northeast Asia. Considering all the negative effects of air pollution
and the possible beneﬁts from air pollution control, it is necessary to combat the
environmental problems arising from Long-range transport of air pollutants in Northeast
Asia. By doing so, both nations can beneﬁt in terms of environmental protection and

public health that cannot be measured by monetary terms.

112

A. Findings

In this research, the author tried to search for evidence that a large amount of air
pollutants are transported ﬁom China to Korea, bringing about various problems to the
natural environment and human health.

First, a case study was carried out at an industrial site to ﬁnd out whether there is
any transboundary movement of air pollutants from China to Korea, and, if any, the
possible negative impact of the transboundary air pollution in Korea.

In the case study to detect the Chinese air pollutants that ﬂew into Korea, one of
the major TV/monitor bulb making plants in Korea was selected. This study showed a
considerable increase of the shrinkage or defect rates in the TV/monitor panel forming
process at the plant when the dusts, i.e. Yellow Sands, were transported by the prevailing
winds from China to Korea.

It also showed that the Chinese air pollutants were the major cause of the
increased shrinkage or defect rates by analyzing the ingredients of the particles, taken
from the samples defected. Chinese air pollutants such as dusts were transported into
Korea by the winds, and increased the TSP concentration in the atmosphere in Korea.
Because of the degradation of the air quality in Korea, including the industrial sites
studies, more products in the panel forming process became defective and fell below the
company’s quality standards.

Second, the author focused on the prediction of the future trend of transboundary
movement of the Chinese air pollutants into Korea in terms of the volumes of the sulfur

dioxides and nitrogen oxides transported. A computer-based simulation model was built

113

to predict the emissions in China and Korea and their possible transboundary movement
impact.

According to the results of the simulation runs, the emissions of sulfur dioxides
and nitrogen oxides are projected to continue to increase at high rates both in China and
Korea, assuming that their economies continue to grow rapidly as they have grown. The
simulation results for the future emission prediction indicate that Northeast Asia is a
region where the air pollution problems will become more and more serious if the
nations’ economic grth continues at high rates without any additional effort to remedy
the problems.

Emission reduction in China is designed to result in reducing the amount of air
pollutants to be transported from China to Korea. More realistically, lowering the growth
rates of the Chinese emissions is expected to result in the lowering of the amount of
Chinese air pollutants to be transported into Korea. Some policy options and scenarios
were created and tested to explore the possible ways to reduce the emissions in China and
Korea. For the comparison of the simulation results of those policy options and scenarios,
a sensitivity analysis was also carried out.

This study shows that policy tools are useﬁil in lowering the growth rates of the
emissions in China and Korea, thus, lowering the growth rates of the amount of the
emissions to be transported from China to Korea, with varying effectiveness. Among the
scenarios tested, governmental regulation turned out to be the most effective policy tool
in reducing the emissions in China and in reducing the amount of emissions to be
transported. Governmental regulation is designed to force the factories to stop their

operation or to close if they do not meet the emission standards set by the government.

114

However, none of the scenarios tested were effective enough to actually reduce the total
amount of emissions in China and Korea and the total amount of the Chinese emission to
ﬂy into Korea. This is considered to come from the assumption in building the
simulation model that the Chinese and Korean economies continue to grow as rapidly as

they have grown recently.

B. Limitations of This Study

Although the ﬁndings of this study are useful, there are some limitations to this
study. The transboundary air pollution problems in Northeast Asia have not been given
much interest by the national governments. A limited number of scholars and institutes
have paid attention to the problems. Therefore, there is not much literature available that
deals with the transboundary air pollution problems in Northeast Asia. Besides, there are
not large amounts of data available, which were obtained by scientiﬁc research. In
particular, the emission data on most of air pollutants, and the emission-related data, were
not available or difﬁcult to collect. This is partly because the Chinese government has
had a tradition of not having the ofﬁcial emissions data available to the public, although
Chinese cities, including Beijing, began to issue air quality reports to the public in the
year 1998. (Rosenthal, 1998) The new ofﬁcial candor of the Chinese government on
pollutants is expected to increase the availability of the emissions data in the future.
Some of the limitations of this study are stated below.

Firstly, the data availability was the major challenge in this study, and, therefore,

some assumptions were introduced and some alternative data were used to replace some

115

emission related data that were not available. For example, the emission data by the
different sectors, such as manufacturing, agriculture, housing and buildings, power plants,
automobiles and so on, were not available or could not be obtained within the limited
time of this study. This led the author to categorize all the air pollution generating
sectors as factories.

Secondly, although difference between the Chinese and Korean factories exists in
their energy intensity, it was not incorporated into the simulation model. Instead, the
initial number of the Korean factories was calculated according to the GDP ratio of the
two nations. This is still considered relevant because the objective of the simulation
model was focused on the total amount of emissions and the amount to be transported
from China to Korea

Thirdly, the main interest of this study was placed on the transboundary
movement of the Chinese air pollutants into Korea and its amount to be transported.
Although China and Korea are located right next to each other, the Chinese emissions
from different provinces cannot bring about the same impact on Korea because of the
difference in the distance to Korea. This is related to the large physical size of the
Chinese land. The emissions from the Chinese eastern coastal area, where most of the
Chinese industrial facilities are located, are likely to be far more inﬂuential on the Korean
air quality than those from the other parts of China. Therefore, it is more reasonable to
give more weight to the emissions from the eastern coastal area of China when
considering the transboundary movement impact in Korea. However, the emissions data
used in the simulation model were the total amount of the Chinese SO2 and NO" gases

that were emitted in the entire Chinese mainland. This limitation comes from the fact

116

 

that the emissions data by the Chinese provinces and cities were not available. It also
comes from the fact that it would require such an extensive, systematic and

multidisciplinary approach to calculate the proper weights of the emissions from each
province or region in China when considering their impact on the air quality in Korea.

Fourthly, the Northeast Asian transboundary air pollution model is a simulation
model based on the macro-approach that does not incorporate atmospheric, climatic, and
chemical reaction factors. Although the climatic and chemical factors are important
while air pollutants stay in the atmosphere, the model was designed to pay most attention
to the total amount of the Chinese emissions and its portion to be ﬂown into Korea by the
transboundary movement.

Fiﬁhly, the scenarios tested by the simulation model were not withdrawn from the
policy candidates considered or discussed either by the Chinese or the Korean
government. They were arbitrarily created by the author. Also, the model does not
contain any parameters to represent environmental damage in Korea that stem from the
transboundary air pollution problems, such as acidiﬁcation of lakes, due to the limited
data availability

Finally, throughout this study it was assumed that the air pollutants from non-
domestic sources in Korea are from China. Although the statistical analysis carried out in
Chapter 4 shows the strong correlation between the growth of Chinese emissions and that
of Korean emissions, it doesn’t necessarily show the causality that those air pollutants
from foreign sources in Korea came from China. There is a possibility that the air
pollutants ﬁom other sources such as Mongolia and Siberia, Russia, contributed partly to

the total air pollutants from foreign sources in Korea. However, the author took into

117

account that Mongolia and Siberian Russia are not very industrialized, while China has
been rapidly industrialized with the rapid growth of emissions as a result, and that,
therefore, the emissions from those regions are likely to be minimal. The investigation of
the relative amount of the air pollutants from those other sources was beyond the scope of

this study.

C. Opportunities for Future Research

As stated earlier, China is one of the largest producers of the air pollutants in the

 

world, and, at the same time, one of the most rapidly growing economies. The major :—
cities of China have the highest concentrations of air pollutants in the world, which far
exceed international safety guidelines such as World Health Organization’s guideline.
(Rosenthal, 1998) Therefore, the transboundary air pollution problems are expected to
worsen in the future. To be able to respond to those problems effectively, it is important
to have the correct estimations of the related parameters. They include: the amounts of
air pollutants emitted; their transboundary movement behavior; the impact caused by the
deposition of the air pollutants at a distance from the source; the prediction of economic
performance, and the energy consumption; and so on.

For future research by other scholars or the author, the following research
opportunities might be explored.

Firstly, it could be worth while to investigate the possible costs caused by the
increasing transboundary air pollution problems at various dimensions, both at micro and

macro levels. For example, the loss stemming from the increased shrinkage rates at the

118

TV/monitor bulb processing plants, due to the air pollutants from China to Korea, can be
calculated with the information on the unit cost of the defected products and the cost of
air quality control systems. If the loss, or the cost increase, at every manufacturing plant
is summed, the total loss, or the total cost increase, at all the manufacturing plants in the
nation can be calculated. It will be part of the total costs caused by the transboundary air
pollution problems in Korea.

Secondly, the TSP is one of the most damaging air pollutants that are transported
over the national boundaries. The TSP is known as one of the air pollutants that cause
and exacerbate the acid rain problems most. If the data on the TSP levels in China can be
obtained, TSP can be another important air pollutant to consider when the transboundary
air pollution problem is investigated. With the Chinese TSP information, the simulation
model created in this study might produce more precise predictions of the total amount of
air pollutants that is to be transported by transboundary movement and cause acid
deposition in northeast Asia.

Thirdly, the impact of the transboundary air pollution problems on the ecosystem
in Korea is another issue to be researched. The acid rain has been believed to have
brought about various negative consequences on the ecosystem in Korea. A
multidisciplinary and comprehensive research to measure the acidity levels of ecosystem
should be carried out in order to estimate the impact of transboundary air pollution on the
natural environment.

Fourthly, transboundary air pollution causes negative impacts on human health.
For example, the increased TSP level can directly cause health problems when embedded

in people’s lungs. It will also be a great enhancement if the factors of the health cost and

119

the acid deposition should be incorporated into the simulation model of Northeast Asian
transboundary air pollution.

F ifthly, the amount of air pollutants to be transported over national boundaries
will heavily depend on the transboundary movement fraction. For example, the
simulation model in Chapter 4 shows the variances with different transboundary
movement fractions. Although the estimates made in the simulation results were derived
with one percent of the transboundary movement fraction, which was the minimum
option tested, the values of the estimates will greatly increase if the actual transboundary

movement fraction is larger than 1 percent. Therefore, it is important to have more 1

 

precise information on the average transboundary movement fraction, monthly or yearly,
to estimate the actual consequences of transboundary air pollution problems, and it
should be the focus of future research.

Sixthly, the policy options and international agreement options to combat the
transboundary air pollution problem in Northeast Asia could also be the focus of future
research. When dealing with the transboundary air pollution problem in Northeast Asia,
it is not merely a problem between China and Korea, although this study narrowed it
down to the transboundary movement of air pollutants from China to Korea. For
example, Japan, located just east of the Korean Peninsula, should not be omitted when
dealing with the Northeast Asia transboundary air pollution problem. When dealing with
international environmental problems, the more that the technology and ﬁnancial
resources, as well as political and diplomatic measures, are utilized, the better problem-
solving efforts can be carried out. In this regard, future research might also deal with

cooperation opportunities among the nations in Northeast Asia.

120

 

APPENDICES

121

APPENDIX A

THE PANEL FORMING PLANT SITE OF THE TV BULB MAKER IN KOREA”2

 

 

’2 This picture was provided by an ofﬁcial at the plant of the TV bulb maker in Korea. Due to the request
of the ofﬁcial, the names and logos of the company on the walls of the buildings in the picture were grayed
to be removed by the author’s graphical treatment after seaming.

122

APPENDIX B

YELLOW SANDS ON THE ROAD93

 

 

 

 

’3 This picture was taken by Choi, Jang-Soo, 1996, and cut smaller by the author.

123

APPENDIX C

CITY VIEWS OF SEOUL WITH YELLOW SAND PHENOMENON"

 

 

 

9’ The picture on top is a northern view of Seoul. (Shin, 1997) The picture at the bottom is a western view
of Seoul. (Lee, 1997) The pictures were found in Shin’s and Lee’s articles in Hankyoreh 21 No. 177 and
179, but the copyright of those pictures belong to Hankyoreh 21. These pictures were copied from the web
site of Internet Hankyoreh 21 (Top: http://www.hani.co.kr/hanla'2 l/K__97AN0179/97AN0179_020.html,
Bottom, http://www.hani.co.kr/hankr21/K_97A90177/97A90177_059.html).

124

 

APPENDIX D

MAP LEVEL OF THE SIMULATION MODEL

 

 

Northeast Asian Transboundary Air Pollution Model 1|

ll - China & Korea -

 

 

Air Pollution in China v

Push Buttons To Start

 

 

 

TO RESTORE - click on the "U" nutton

 

 

TO CHANGE A VALUE — type a numerical value of a variable In the box on the epproprle
component, or click and drag the ellder knob (SUDER) or move the dial (KNOI

 

 

 

 

 

 

TRANSBOUNDARY
MOVEMENT OPTIONS

SWITCH TransMove C Trans Move Free

(ﬂﬂNA

POLICY OPTIONS
C elr poll tax M502]

 

‘55:

I a . ' __.._.....__.r '1 r V
ECONOMIC PERFORMANCE
C Utilization Frec

 

 

KOREA

POLICY OPTIONS
K air poll tax nelson

 

125

 

APPENDIX E

DIAGRAM LEVEL OF THE MODEL

 

Northeast Asian Transboundary Air Pollution Model 11

I1 - China and Korea -

 

:9 Air Pollution in China
C build hlml C build projected C kicked out

 

    

    

   

   

‘
-. .3 Cepollutlonlegulation

A8

‘—

Historical Data

 

 

 

  

@ . K 3 induced reduction .

 

 

Kairpolltaxlrac @

K tax induced reduction

  

a: - . .
Q 1 Q
Cbuild Cavgemlssionfrac
Q CUtilizationFrac
Cavgemissionl'rac
Cavgemiesionfrac .Creginducedreductlon
. CNoofFactoriee
" A C emissioantil
c to ' I’d-Man" Air Pollutants in China M
a: - - - at “am-1 . CTransMoveFrac
’ S Chinese Air PollutantswUﬁl‘a
Cairpoll frac
Cemiseionnewfrac Cdeaea.sez 0 .
.Cainducodroduch‘on CPolltoilowinio KwUtil
:9- Air Pollution inKoree A;
CAirPollFlownintoK
. . SWITCHTransMove
SWITCH TransMove C Air Poll Flown into K 1 ,
Kklckedout . l!)
1 Q a . UtilzTotaIAirP - --K
‘._ a: TotalAlr' flectingK
69 Crew rac
pollutionregulation.
KAirPollAlreotingK
- n'lzKAirP- AnectK
KNoofFactories
Kavg emissionfec
’ae . ‘ 1
Air Pollutants in Korea .
,3 Kavgemisioantil
Kdecreesez @ KUtllizationFrac

- r Pollutants in Korea

 

 

126

 

APPENDIX F

EQUATION OF THE MODEL

 

 

Air_PoIlutants_in_China[SOZ](t) = Air_Pollutants_in_China[SOZ](t -

(C _generate[SOZ] - C_decrease[SOZ] - C_decrease_2[SOZ]) * dt

[NIT Air_Pollutants_in_China[SOZ] = 16679

Air_Pollutants_in_China[NOx](t) = Air_Pollutants_in_China[NOx](t -

(C _generate[NOx] - C_decrease[NOx] - C_decrease_2[NOx]) * dt

INIT Air_Pollutants__in_China[NOx] = 64212

C _generate[SOZ]
C_build[SOZ]*C_emission_new_frac[SOZ]*C_a_induced_reduction[SOZ]

C _generate[N Ox]
C_build[NOx]*C_emission_new_frac[NOx]*C_a_induced_reduction [NOx]

C_decrease[SOZ]
(C_die[SOZ]*C_avg_emission_frac[SOZ])+C_reg_induced_reduction[SOZ]

C_decrease[NOx]
(C_die[NOx] *C_avg_emission_frac [NOx])+(C_reg_induced_reduction [NOx])

dt)

dt)

 

 

 

127

 

 

C_decrease_2[SOZ] = C_tax_induced_reduction[SOZ]*C_avg_emission_frac[SOZ]

C_decrease_2[NOx] = C_tax_induced_reduction[NOx]*C_avg_emission_frac[NOx]

C_No_of_Factories[SOZ](t) = C_No_of_Factories[SOZ](t - dt) + (C_build[SOZ] -

C_die[SOZ] - C_kicked_out[SOZ]) * dt

INIT C_No_of_Factories[SOZ] = 500000

C_No_of_Factories[NOx](t) = C_No_of_Factories[NOx](t - dt) + (C_build[NOx] -

C_die[NOx] - C_kicked_out[NOx]) * dt

INIT C_No_of_Factories[NOx] = 500000

C_build[SOZ] = IF TIME<=1994 THEN C_build_historical[SOZ] ELSE
C_build_projected[SOZ]

C_build[NOx] = IF TIME<=1994 THEN C_build_historical[NOx] ELSE
C_build_projected[NOx]

C_die[SOZ] = C_No_of_Factories[SOZ]/40

C_die[NOx] = C_No_of_Factories[NOx]/45

C_kicked_out[SOZ] = IF TIME<=1998 THEN 0 ELSE
C_air_pollution_regulation*C_No_of_Factories[SOZ]

 

128

 

 

 

OUTFLOW FROM: C_No_of_Factories[SOZ] (IN SECTOR: Air Pollution in
China)

C_kicked_out[NOx] = IF TIME<=1998 THEN 0 ELSE
C_air_pollution_regulation*C_No_of_Factories[NOx]

OUTFLOW FROM: C_No_of_Factories[NOx] (IN SECTOR: Air Pollution in
China)

Agreement_w__K = l

Chinese_Air_PolIutants_w_Util[SOZ] = IF TIME<=1998 THEN
C_No_of_Factories [SOZ] *C_avg_emission_frac[SOZ] ELSE
C_No_of_Factories [SOZ] *C_avg_emission_w_Util[SOZ]

Chinese_Air_PolIutants_w_Util[NOx] = IF TIME<=1998 THEN
C_No_of_Factories[NOx]*C_avg_emission_frac[NOx] ELSE
C_No_of_Factories[NOx]*C_avg_emission_w_Util[NOx]

C_air_pollution_regulation = 0

C_air_poll_tax_frac[SOZ] = 0

C_air_poll_tax_frac[NOx] = 0

C_avg_emission_frac[SOZ] =
Air_Pollutants_in_China[SOZ]/C_No_of_Factories[SOZ]

C_avg_emission_frac[NOx] =

 

129

 

 

 

Air_Pollutants_in_China [NOx]/C_No_of_Factories [NOX]

C_avg_emission_w_UtiI[SOZ] = C_Utilization_Frac*C_avg_emission_frac[802]

C_avg_emission_w_Util[NOx] = C_Utilization_Frac*C_avg_emission_frac[N01]

IF TIME<=1998 THEN I ELSE

C_a_induced_reduction[Air_Pollutants]
Agreement_w_K

C_build_historical[Air_Pollutants] = time

C_build_projected[Air_Pollutants] = time

C_emission_new_frac[SOZ] = C_avg_emission_frac[SOZ]*.90

C_emission_new_frac[NOx] = C_avg_emission_frac[NOx]*.90

C_Poll_to_flow_into_K_w_Util[802] =
Chinese_Air_Pollutants_w_Util[SOZ]*C_Trans_Move_Frac*SWITCH_TransMove

C_Poll_to_ﬂow_into_K_w_UtiI[NOx] =
Chinese_Air_Pollutants_w_Util[NOx] *C_Trans_Move_Frac*SWITCH_TransMove

C_reg_induced_reduction[SOZ] = IF (T IME<=1998) THEN 0 ELSE
C_kicked_out[SOZ]*C_avg_emission_frac[802]

C_reg_induced_reduction[NOx] = IF (TIME<=1998) THEN 0 ELSE
C_kicked_out[NOx]*C_avg_emission_frac[NOx]

 

130

 

 

 

C_tax_induced_reduction[SOZ] = IF TIME<=1998 THEN I ELSE
Air_Pollutants_in_China[SOZ]*C_air_poll_tax_frac[SOZ]

C_tax_induced_reduction[NOx] = IF TIME<=1998 THEN 0 ELSE
Air_PoIlutants_in_China[NOx]*C_air_poll_tax_frac[NOx]

C_Utilization_Frac = l

C_build_historical[Air__PolIutants] = time

C_build_projected[Air_Pollutants] = time

Historical Data

C_Energy_Historical = GRAPH(time)

(1980, 17215), (1981, 16920), (1982, 18034), (1983, 19506), (1984, 21185), (1985,
22149), (1986, 23241), (1987, 24742), (1988, 26455), (1989, 26936), (1990, 26994),
(1991, 28236), (1992, 29305), (1993, 31341), (1994, 33972), (1995, 36346), (1996,
37040)

C_GDP = GRAPH(time)

(1980, 13134), (1981, 13674), (1982, 14779), (1983, 16283), (1984, 18629), (1985,
21040), (1986, 22818), (1987, 25352), (1988, 28220), (1989, 29400), (1990, 30561),
(1991, 33141), (1992, 37892), (1993, 43216), (1994, 48704), (1995, 53818), (1996,
59039)

 

131

 

 

 

C_NOx_Historical = GRAPH(time)

(1980, 39075), (1981, 37837), (1982, 39728), (1983, 42462), (1984, 46398), (1985,
50418), (1986, 54390), (1987, 59534), (1988, 64212), (1989, 68443), (1990, 71513),
(1991, 78295), (1992, 84165), (1993, 90960), (1994, 97754)

C_SOZ_Historical = GRAPH(time)

(1980, 10448), (1981, 10243), (1982, 10756), (1983, 11482), (1984, 12475), (1985,
13525), (1986, 14120), (1987, 15645), (1988, 16679), (1989, 17510), (1990, 17951),
(1991, 18860), (1992, 19614), (1993, 20912), (1994, 22208)

K_Energy_Historical = GRAPH(time)

(1980, 1737), (1981, 1819), (1982, 1818), (1983, 1964), (1984, 2154), (1985, 2258),
(1986, 2497), (1987, 2740), (1988, 3055), (1989, 3293), (1990, 3679), (1991, 4189),
(1992, 4652), (1993, 5385), (1994, 5901), (1995, 6532), (1996, 7158)

K_GDP = GRAPH(time)

(1980, 7447), (1981, 7928), (1982, 8376), (1983, 9365), (1984, 10188), (1985, 10923),
(1986, 12198), (1987, 13632), (1988, 15173), (1989, 16150), (1990, 17712), (1991,
19342), (1992, 20342), (1993, 21446), (1994, 23285), (1995, 25366), (1996, 27174)

K_NOx_Historical = GRAPH(time)

(1988, 417), (1989, 450), (1990, 507), (1991, 583), (1992, 666), (1993, 754), (1994, 843),
(1995, 925)

 

132

 

 

 

 

K_SOZ_Historical = GRAPH(time)

(1988, 1117), (1989, 1183), (1990, 1309), (1991, 1378), (1992, 1405), (1993, 1433),
(1994, 1474), (1995, 1495)

Air_Pollutants_in_Korea[SOZ](t) = Air_Pollutants_in_Korea[S02](t - dt) +
(K _generate[SOZ] - K_decrease[SOZ] - K_decrease_2[SOZ]) * dt

IN IT Air_Pollutants_in_Korea[SOZ] = 1117

Air_Pollutants_in_Korea[NOx] (t) = Air_PoIIutants_in_Korea[NOx](t - dt) +
(K _generate[NOx] - K_decrease[NOx] - K_decrease_2[NOx]) * dt

INIT Air_Pollutants_in_Korea[NOx] = 417

K _generate[S02] =
K_buildlSOZ]*K_emission_new_fac[S02]*K_a_induced_reduction[802]

K _generate [NOx] -
K_build [NOx] *K_emission_new_fac[NOx] *K_a_induced_reduction [N Ox]

K_decreaselSOZ] . =
(K_die[SOZ]*K_avg_emission_fac[SOZ])+(K_kicked_out[SOZ]*K_avg_emission_fa
c[SOZ])

K_decreaselNOx] =
(K_die[NOx]*K_avg_emission_fac[NOx])+(K_kicked_out[NOx]*K_avg_emission_f

 

133

 

 

 

 

ac[NOx])

K_decrease_2 [S02] = K_avg_emission_fac[SOZ]*K_tax_induced_reduction[SOZ]

K_decrease_2 [NOx] = K_avg_emission_fac[NOx]*K_tax_induced_reduction [NOx]

K_No_of_Factories[SOZ](t) = K_No_of_Factories[SOZ](t - dt) + (K_build[SOZ] -
K_die[SOZ] - K_kicked_out[SOZ]) * dt

INIT K_No_of_Faetories[SOZ] = 268817

K_No_of_Factories[NOx](t) = K_No_of_Factories[NOx](t - dt) + (K_build[NOx] -

K_die[NOx] - K_kicked_out[NOx]) * dt

INIT K_No_of_Factories[NOx] = 268817

K_buiid[s02] = IF TIME <=1995 THEN K_build_historical[SOZ] ELSE
K_build_projected[SOZ]

K_build[NOx] = IF TIME <=1995 THEN K_build_historical[NOx] ELSE
K_build_projected[NOx]

K_die[SOZ] = K_No_of_Factories[SOZ]/45

K_die[NOx] = K_No_of_Factories[NOx]/45

 

134

 

 

 

K_kicked_out[SOZ] = K_No_of_Factories[SO2]*K_air_pollution_regulation

K_kicked_out[NOx] = K_No_of_Factories[NOx]*K_air_pollution_regulation

Agreement_w_C = 1

C_Air_Poll__Flown_into_K[SOZ] =

Air_PoIlutants_in_China[S02]*C__Trans_Move_Frac*SWITCH_TransMove

C_Air_Poll_Flown_into_K [N Ox] =
Air_Pollutants_in_China[NOx]*C_Trans_Move_Frac*SWITCH_TransMove

C_Trans_Move_Frac = .01

K_air_pollution_regulation = 0.01

K_Air_Poll_Affecting_K[SOZ]
K_Disperse_Frac)

Air_Pollutants_in_Korea[SOZ]*(1-

K_Air_Poll_Affecting_K[NOx]
K_Disperse_Frac)

Air_Pollutants_in_Korea [NOx] *(1 -

K_air_poll_tax_frac[SOZ] = 0

K_air_poll_tax_frac[NOx] = 0

K_avg_emision_w_Util[SOZ] = K_avg_emission_fac[S02]*K_Utilization_Frac

 

 

135

 

Em.

 

 

K_avg_emision_w_Util[NOx] = K_avg_emission_fac[NOx]*K_Utilization_Frac

K_avg_emission_fac[802]
Air_Pollutants_in_Korea[SOZ]/K_No_of_Factories[S02]

K_avg_emission_fac[NOx]
Air_Pollutants_in_Korea[NOx]/K_No_of_Factories [N Ox]

K_a_induced_reduction[Air_Pollutants] = IF TIME<=1998 THEN 1 ELSE
Agreement_w_C

K_build_historical[Air_Pollutants] = time

K_build_projected[Air_PoIlutants] = time

K_Disperse_Frac = .5

K_emission_new_fac[SOZ] = K_avg_emission_fac[SOZ]*.90

K_emissi0n_new_fac[NOx] = K_avg_emission_fac[NOx]*.90

K_tax_induced_reduction[802] = IF TIME<=1998 THEN 0 ELSE
Air_PoIlutants_in_Korea[SOZ]*K_air_poll_tax_frac[S02]

K_tax_induced_reduction[NOx] = IF TIME<=1998 THEN 0 ELSE
Air_Pollutants_in_Korea[NOx]*K_air_poll_tax_frac[NOx]

K_Utilization_Frac = 1

 

136

 

 

 

 

SWITCH_TransMove = 1

Total_Air_Poll_Affecting_K[SOZ] =
C_Air_PoIl_Flown_into_K[SOZ]+K_Air_Poll_Affecting_K[SOZ]

Total_Air_Poll_Affecting_K[NOx] =
C_Air_PoIl_Flown_into_K[NOx]+K_Air_Poll__Aﬁ'ecting_K[NOx]

Util:_K_Air_Poll_Affect_K[SOZ] = IF TIME<=1998 THEN
(K_No_of_Factories[SOZ]*K_avg_emission_fac[SOZ])*(1-K_Disperse_Frac) ELSE

(K_No_of_Factories[SOZ]*K_avg_emision_w_Util[SOZ])*(1-K_Disperse_Frac)

Util:_K_Air_PolI_Affect_K[NOx] = IF TIME<=1998 THEN
(K_No_of_Factories [NOx]*K_avg_emission_fac[NOx])*(1-K_Disperse_Frac) ELSE

(K_No_of_Factories[NOx]*K_avg_emision_w_Util[NOx])*(1-K_Disperse_Frac)

Util:_Total_Air_Poll_Affect_K[SOZ] =
C_Poll_to_ﬂow_into_K_w_Util[SOZ]+Util:_K_Air_Poll_Affect_K[SOZ]

Util:_Total_Air_Poll_Affect_K[NOx] =
C_Poll_to_flow_into_K_w_Util[NOx]+Util:_K_Air_PoII_Affect_K[NOx]

K_build_historical[Air_Pollutants] = time

K_build_projected[Air_Pollutants] = time

 

137

 

 

THE OUTPUT OF THE STATISTICAL ANALYSIS USING SPSS

APPENDIX G

Paired Samples Statistics

 

1

Pair

Pair

Pair

 

Pair

Mean

Std.
Deviation

Std. Error
Mean

 

China
Historical
802

China
Simulated
802

China
Historical
NOx

China
Simulated
NOx

Korea
Historical
802

Korea
Simulated
802

Korea
Historical
NOx

Korean
Simulated
NOx

19104.86

19195.90

79334.57

79270.71

1349.1250

1 350.7975

642.9875

638.7737

 

 

 

1 956.7908

1960.4146

12297.26

11340.61

136.6796

140.7579

186.3205

164.9428

 

739.5974

740.9671

4647.9262

4286.3476

48.3235

49.7654

65.8743

58.3161

 

(continued on the next page)

138

 

 

Paired Samples Correlations

 

 

Pair

1

Pair

Pair

Pair

N

Correlation

Sig.

 

China
Historical
$02 &
China
Simulated
802

China
Historical
NOx&
China
Simulated
NOx

Korea
Historical
802 8r
Korea
Simulated
302

Korea
Historical
NOx&
Korean
Simulated
NOx

 

 

.989

.995

.992

.997

 

.000

.000

.000

.000

 

 

(continued on the next page)

139

 

 

Paired Samples Test

 

 

Paired Differences

95% Conﬁdence
Std. Std. Error Nal of the Differen Sig.

Mean Deviation Mean Lower Upper t df (2-tailed

 

 

 

Pair China

1 Historica
802-
China
Simulat
302 r

Pair China

2 Historica
NOx-
China
Simulat
NOx

Pair Korea L
3 Historica

:3; -1.672517.9878 6.3596 46.7107 13.3657 -.263 7 .800

Simulate
$02

Pair Korea

4 Historica
NOx -
Korean
Simulat
NOx

 

91.0443 [91.2100 10.0670 160.3686 78.2800 -.827 6 .440

63.8600 508.2284 170.0568 4331.02 158.7387 .112 6 .914

 

4.2138 25.2570 8.9297 116.9016 25.3291 .472 7 .651

 

 

 

 

 

 

 

 

 

140

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141

 

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