Empirical Study on Environmental Ancillary Benefits Due to Greenhouse Gas Mitigation in Korea

nteg rated
H nvironmental
tlJtrategies

Empirical Study on Environmental Ancillary Benefits Due to
Greenhouse Gas Mitigation in Korea

Seunghun Joh, Yunmi Nam, Sanggyoo Shim, Joohon Sung and Youngchul

Shin

2001

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Empirical Study on Environmental Ancillary Benefits
Due to Greenhouse Gas Mitigation in Korea

Seunghun Joha
Yunmi Nam3
Sanggyoo Shimb

Joohon Sungc
Yeongchul Shind

a: Global Environment Research Center, Korea Environment Institute
b: Global Environment Research Center, Korea Institute of Science and Technology
c: Department of Preventive Medicine, Kangwon National University
d: Department of Economics, Daejin University

Corresponding address:

Dr. Seunghun Joh
Korea Environment Institute

613-2 Bulgwang-dong Eunpyong-gu Seoul, Korea 122-706
Phone : 82-2-380-7654
Fax : 82-2-380-7688
Email: shioh@,kei.re.kr

Abstract

This study is a part of The International Co-Control Analysis Program(ICAP) which is a new
initiative sponsored by the US EPA to assist developing countries in evaluating the
environmental and human health benefits of technologies and policies for reducing greenhouse
gas emissions . The goal of the Korea study is primarily two folds: 1) To assess and quantify
the environmental ancillary benefit resulting from greenhouse gas mitigation and 2) To help
government officials and stakeholders understand the air pollution benefits of energy
technologies that will reduce greenhouse gas emissions, thus the results of this analysis can
enhance support for appropriate policy for the United Nations Framework on Climate Change
(UNFCCC) and air quality control programs.

The results reveal that modest greenhouse gas reduction scenarios (5-15% reductions in
2020) can result in significant air pollution health benefits through reductions in PMi0
concentrations. For instance, these greenhouse gas reduction measures for Korea's energy
sector could avoid 40 to 120 premature deaths/yr. and 2,800 to 8,300 cases/yr. of asthma and
other respiratory diseases in the Seoul Metropolitan Area in 2020. The cumulative value of

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these avoided health effects is estimated to range from 17 to 21 million US$/yr (in 1999
dollars). This is equivalent to a benefit of $6.8 to $7.5 per ton of carbon emissions reduced for
the climate change scenarios.

Policy makers agreed that the ICAP approach and the results of this project were useful
in informing policy makers and the public of the co-benefit impacts of policy decisions and
assisting with the development of cost-effective integrated strategies to address both local air
quality issues and GHG mitigation concerns simultaneously.

Keywords: Climate change, ancillary benefits, energy efficiency, air quality, health effect,
valuation, Korea.

Acknowledgement

This project was funded jointly by Korea Environment Institute and United States
Environmental Protection Agency and was carried out in partnership with National Renewable
Energy Laboratory. We would like to express special appreciation to Prof. Sungwhee Shin at
University of Seoul and Dr. Alan Krupnick at Resources for the Future for advice and guidance.

TABLE OF CONTENTS

1. Introduction 1

2. Korea in UNFCCC and Air Quality Issue 1

3. Methodology 2

3.1 Key Scoping Decisions 4

3.2 Reference and GHG Reduction Scenarios 4

3.3 Air Pollution 5

3. 4 Health Effects 6

3.5. Economic Valuation 6

4. Analytic Results 7

4.1 Air Pollution Emissions and Atmospheric Concentration Levels 7

4.2 Excess Occurrences of Mortality and Morbidity 8

4.3 Economic Benefits 10

5. Policy Implications and Conclusions 12

5.1 Study limitations that affect magnitude of results 12

5.2 Relevance and usefulness of the ICAP approach and results for policy making. .. 13

6. Reference 14

LIST OF TABLES

Table 1. NAAQS in Korea vs in US and their measuring method for major air

pollutants 2

Table 2. Energy use: national compared with ICAP study covered 4

Table 3. GHG emission estimates for scenarios 5

Table 4. Reduction of PMi0 emission by sectors in case of scenario 4(tons/year) 7

Table 5. Reduction of GHG emission by scenarios 8

Table 6. Relative risks from PM10 by the organ systems, severity and chronicity of

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health effects per 50 ug/m3 8

Table 7. Decreases in occurrences of annual mortality and morbidity by GHG

reduction scenarios 9

Table 8. Values of statistical life 10

Table 9. Unit values of morbidity 10

Table 10. Estimated annual health benefits of mortality(CVM) and morbidity avoided

Table 11. Economic benefit per GHG emission avoided 11

Table 12. Cumulative results 2000 to 2020 of total excess occurrence of mortality and
morbidity avoided and the corresponding benefits 11

LIST OF FIGURES

Figure 1. Overview of ICAP Methodology

Figure 2. An average annual atmospheric PMi0 concentration by scenarios

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7

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1. Introduction

Much of the debate over global climate change involves estimates of direct costs and merits of
various policies and measures proposed to mitigate greenhouse gas(GHG) emissions. Recently,
this debate has broadened to include the issue of ancillary benefits of costs. Ancillary benefits of
GHG mitigation polices have been defined as the social welfare improvements from GHG
abatement polices other than caused by changes in GHG emissions, which incidentally arise as a
consequence of mitigation policies(Davis et al., 2000). It is widely recognized that developing
countries will make the most progress in reducing the growth of their greenhouse gas emissions
by implementing measures that are consistent with their development objectives and that
provide near term economic and environmental benefits. While many developing countries
have conducted extensive analysis of possible greenhouse gas measures, little attention has been
given to full characterization of the more immediate environmental and health benefits that
would result from these measures. This study is a part of the International Co-Control Analysis
Program(ICAP) which is a new initiative to assist developing countries in evaluating the health
and environmental benefits of technologies and policies for reducing greenhouse gas emissions1.
The goal of the Korea study is primarily two folds: 1) To assess and quantify the environmental
ancillary benefit resulting from greenhouse gas mitigation and 2) To help government officials
and stakeholders understand the air pollution benefits of energy technologies that will reduce
greenhouse gas emissions, thus the results of this analysis can enhance support for appropriate
policy for the United Nations Framework on Climate Change (UNFCCC) and air quality control
programs.

2. Korea in UNFCCC and Air Quality Issue

The Republic of Korea belongs to the group of non-Annex I countries under the UNFCCC.
Unlike Annex I countries, non Annex I countries do not have commitments under the UNFCCC
to reduce GHG emissions. It is, however, general consensus that Korea along with Mexico,
Argentina and possibly several other developing countries, are entertaining the possibility of
taking on a commitment for GHG mitigation and joining the Annex-I group as pressure on
developing countries' reduction commitment intensifies.

Korean economic structure is characterized by high energy intensity associated with primarily
with fossil-fuel energy consumption. Continued growth in energy consumption implies that
emissions of greenhouse gases vis-a-vis conventional air pollutants will increase with economic
growth unless current fossil-fuel-oriented economic structure changes. The projected C02
emissions in Korea are expected to grow from 101.1 million TC(tonne of carbon) in 1995 to
148.5 million TC in 2000, tol87.4 million TC in 2005, and to 217.0 million TC in 2010 as
energy demand for economic growth increases. The annual average growth rate of C02
emissions from 1996 to 2010 is projected at 5.2% (National Communication of the Republic of
Korea, 1998).

Air pollution and GHG emissions are closely linked with changes in energy
consumption. The population of Korea is over 46 millions in 1998 and national area accounts
for 99,373 km2. As a common situation in other countries, air pollution problem is more
prevalent in urban areas than in rural areas. Especially large cities are susceptible to air
pollution change. The high density of urbanization in Korea has a close linkage with air
pollution control issues along with economic growth and energy use. Transportation is an
important factor in air pollution perspective in the sense that it is mobile pollution so as to be
difficult to control and that the vehicle registration will keep going up for the time being in

1 For details on ICAP see http://www.nrel.gov/icap.

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Korea. National Ambient Air Quality Standards (NAAQS) in Korea and the standard measuring
methods are shown in Table 1. PM2 5 is not being measured in Korea. There are still more total
suspended particle(TSP) monitoring sites than PM10 sites in Korea, although PM10 sites are
gradually replacing TSP sites.

Table 1. NAAQS in Korea vs in US and their measuring method for major air pollutants.

Pollutants

Standard

US EPA standard

Method

so2

Annual 0.03ppm
24h average 0.14ppm
lh average 0.25ppm

Same

Pulse U.V. Fluorescence
Method

8h average 9ppm
lh average 25ppm

Same

Non-Dispersive Infrared
Method

NOx

Annual 0.05ppm
24h average 0.08ppm
lh average 0.15ppm

Same

Chemiluminescent Method

TSP

Annual 150D/D
24h average 300~/~

Annual75 /
(geometric)
24h average 260 ~/~

(3-Ray Absorption Method
Sampled by High Volume Air
Sampler

PM10

Annual 80D/D
24h average 150 /

Annual 5 0 ~ / ~ (arithmetric)
24h average 15 0 ~ / ~

(3-Ray Absorption Method
Sampled by Tape Sampler
Method

pm25

Not monitored

Annual 15 ~ / ~ (arithmetric)
24h average 50D/D

8h average 0.06ppm
lh average O.lppm

8h average 0.08ppm
lh average 0.12ppm

U.V. Photometric Method

3 months average
1.5 ~/~

Atomic Absorption
Spectrophotometry

In Korea few previous studies on environmental benefit estimates have been carried out2. The
first cost-benefit study of air quality control programs that applied the impact analysis approach
was carried out by Joh (2000) for the Kyonggi area (a part of the Seoul Metropolitan area) in
1999. In particular, no studies have dealt with ancillary benefit of GHG reduction.

3. Methodology

An important reason for controlling air pollutants such as particulate matter(PM), ozone, or
sulfur dioxide is the damaging effects(avoided cost) they have on human health(Cropper et al.
1997). In order to evaluate the impact and damage cost of pollutants in connection with
greenhouse gas emissions, two modeling approaches are generally taken(Jacobsen, 1998; Aunan
et al.,1998). Top-down approach(T-D), represented by computable general equilibrium models
is particularly suitable for analyzing the impact of indirect measures, such as taxes, on main
macroeconomic variables. From the predicted changes in economic activity the emission
reductions are deduced and the benefits from these reductions may feed back into the
macroeconomic variables. Meanwhile, bottom-up(B-U) approaches focus on specific
abatement measures considered appropriate for solving a problem. Their potentials for reducing

For review of previous international studies on the issue see a comprehensive work by Davis et al., 2000.

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adverse exposure of receptors(people, crops, forests, materials, etc.) and thereby damage, are
estimated. Assessments of the values of the costs and benefits are then made. The T-D and the
B-U approaches both have major weaknesses: While T-D analyses tend to oversimplify for
instance the biogeochemical relations, the B-U analyses tend to oversimplify, or simply leave
out, macroeconomic relations and consequences. B-U approach has advantages in explicit
valuation of environmental amenities and provides means to assess environmental values not
directly related to damage costs(Aunan et al., 1998). The principal steps of B-U approach in
case of benefit valuation of air pollution reduction can be grouped as follows:

1. Emission: Specification of the relevant technologies and the environmental burdens
they impose (e.g. kg of NOx per GWhe emitted by power plant);

2. Air dispersion: Calculation of increased pollutant concentrations in all effected regions
(e.g. incremental concentration of PM, using models of atmospheric dispersion and
chemistry for PM formation) ;

3. Impact: Calculation of the concentration from the increased exposure and calculation
of impacts(damage in physical units) from this concentration, using a concentration-
response function (e. g. cases of mortality and morbidity due to this increase in PM);

4. Valuation: The economic valuation of these impacts (e. g. multiplication by the cost
of a case of morbidity, value of statistical life by contingent valuation method) (Rabl
and Sparado 1998, 1999).

5. Extrapolation: Generalization of a site-specific result to cover other areas in policy
making, if necessary.

Figure 1 illustrates the integrated methodology applied to the study in context of B-U approach
framework described previously3. The methodology for the study starts from GHG mitigation
scenarios in the Seoul Metropolitan area, then emission inventories and concentration levels for
PMio are estimated. Reductions in occurrences of premature mortality and morbidity of asthma
and respiratory diseases are calculated based on concentration-response functions. Contingent
valuation method for premature mortality is employed along with benefit transfer method and
human capital approach. Cost of illness is applied for morbidity effects.

[ Output 1

[ Data Base 1

[ Methodology or Model 1

Mitigation

S1-S4

MOCIE

Bottom-Up

Emission

156Grids

ICAP

Area coefficients - GHG,

NIER, EPA

Concentration

156 Grids

UR-BAT

Health

C-R

Function,
Prevalence

NSO, NIH, ME,

GAM, Robust Poisson

KMA

Regression

Valuation

COI, WTP

NHIC

GIS, CVM (Mortality)
Opportunity Cost(Morbidity)

Figure 1. Overview of ICAP Methodology

Note: Sl~S4(scenarios), MOCIE(Ministry of Commerce, Industry, and Energy), ICAP(International Co-control
Analysis Program), NIER(National Institute of Environmental Research), EPA(US Environmental Protection

3 For a details on Korea-ICAP, see Joh et el.(2001).

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Agency), UR-BAT (Urban Branching Atmospheric Trajectory), C-R Function(Concentration Response),
NSO(National Statistical Office), NIH(National Institute of Health), ME(Ministry of Environment), KMA(Korean
Medical Association), GAM(Generalized Additive Model), COI(Cost of Illness), WTP(Willingness To Pay),
NHIC(National Health Insurance Corporation), GIS(Geographic Information System), CVM(Contingent Valuation
Method).

3.1 Key Scoping Decisions

The following project scoping decisions were made through an initial project scoping workshop
and further consultations with climate change, air pollution, health, and economic valuation
experts.

Area : Largely due to data availability, the Seoul Metropolitan area(Seoul, Kyounggi,
Inchon), was chosen which covers about a half of all Korean population (22 million out
of 47 million, 46.5%).

Time Period: 2000, 2010, 2020. Year 1995 plays the role of base year and 2010 and 2020
were selected to consider the potential timing of GHG mitigation under the UNFCCC.
Pollutants of Concern: PM10 was the only pollutant considered in this initial analysis and
the effects of secondary PMi0 such as sulfates and nitrates were excluded from the
analysis. Ozone was not considered in this study, as the ozone pollution
modeling/projection could not be supported4. By leaving out secondary PM we are
missing sulfate and nitrate, which are largely fine aerosols of PM2 5 which have even
greater correlation with health effects.

Economic Valuation Methods: A contingent valuation study(CVM) survey to develop
unit values for premature mortality was administrated.

3.2 Reference and GHG Reduction Scenarios

Reference Scenario: National data from the Ministry of Commerce, Industry and Energy
(MOCIE) (MOCIE, 1998) were used to develop bottom-up estimates for energy consumption
and GHG emissions through 2020. Table 2 shows the proportion of national energy
consumption that is covered by the study areas, with the three areas accounting for 24% of
national total in energy consumption.

Table 2. Energy use: national compared with ICAP study covered

ICAP Seoul

ICAP Inchon

ICAP Kyonggi

National

Total (1000 TOE)

11360.02

7642.67

17053.90

150222.28

ICAP/National (%)

7.56

5.09

11.35

GHG Reduction Scenarios: Four alternative scenarios were evaluated, including:

Reduction scenario 1 (Scenario 1) - Assumptions include a portfolio of energy efficiency
measures for all major energy sub-sectors including introduction of high-efficiency
facilities, replacement of fuels according to MOCIE, increasing efficiency of PMi0
emission controls at industrial manufacturing facilities, and the use of compressed
natural gas(CNG) fueled buses (CNG fueled buses are assumed to replace commercial
buses by 10% in 2000, 75% in 2005, and 100% to 2010).

Reduction scenario 2(Scenario 2) - Assumes 5% reduction in energy use across
economic sectors regardless of measures and the use of CNG fueled buses.

A previous study(Joh, 2000) shows that the estimate of ozone impact on health is larger than that of PM10.

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Reduction scenario 3(Scenario 3) - Assumes 10% reduction in energy use across
economic sectors regardless of measures and the use of CNG fueled buses.

Reduction scenario 4(Scenario 4) - Assumes 15% reduction in energy use across
economic sectors regardless of measures and the use of CNG fueled buses.

Scenario 1 involves assumptions regarding an enhanced program for improved air quality
control. Thus, we propose that reduction scenarios 2-4 be considered for analysis of GHG
mitigation activities in this analysis. Scenario 1 applies additional levels of air pollution control
for PM10. Also note that scenarios 2-4 do not involve any assumptions regarding additional
efficiency of pollution control and that pollution control efficiency is held constant. Table 3
provides the estimate levels of greenhouse gas emissions for each of the scenarios.

Table 3. GHG emission estimates for scenarios

1995

2000

2010

2020

1000TCE

(%)

1000TCE

(%)

1000TCE

(%)

1000TCE

(%)

Nationwide

BAU

102132

100

117540

100

160349

100

188323

100

Metro
-politan
area

BAU

28036

27.5

31499

100

45023

100

56373

100

Scenario 1

28036

27.5

30963

98.3

42976

95.5

52114

92.5

Scenario2

29924

95.0

42772

95.0

53554

95.0

Scenario3

28349

90.0

40521

90.0

50735

90.0

Scenario4

26774

85.0

38270

85.0

47917

85.0

Note: Percentages(%) of "Metropolitan area BAU" refers to the portion of "Nationwide BAU" while % of
"Scenariosl-4" refers to "Metropolitan area BAU".

3.3 Air Pollution

The target region for the analysis is the Seoul Metropolitan Area, which includes Seoul, Inchon,
and most part of Kyonggi area. Only primary total suspended particles(TSP) and PMi0 (not
secondary particulates) from fuel combustion and fugitive dusts from paved roads are
considered. Emissions are calculated with emission factors and activity data for each economic
sector relying on fuel consumption data for the sectors and data on vehicle use. The
atmospheric PMi0 concentrations are calculated with the UR-BAT (Urban Branching
Atmospheric Trajectory) model, which is a revised urban scale version of ATMOS used in
RAINS-Asia, with emission inventory and meteorological data compiled in this study.

Key assumptions include:

• The background atmospheric concentration of PMi0 is assumed as 20ug/m3,

• The number of registered vehicles in a domain is calculated based on the assumption that
there will be the growth rate of oil price of 4% and low economic growth rate of 2% every
year,

• The same meteorological input data of 1995 are used for other future years,

• Relative patterns of energy use in each region of analysis do not change from 2000 to 2020
for any reason other than the impact of energy policies in the reduction scenarios.

It is important to note that in Korea, PMi0 has been measured only since 1995 (20 sites in study
area). This relative short history and sparse networks make it difficult to precisely assess the
health effects from PMi0 pollution. There are only a few studies evaluating the health effect

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from PMio to date in Korea, although a growing body of evidence is being established about the
health effects of TSP. For this analysis, we started with the ambient concentration and
monitoring system for PMi0 and focused on PMi0 data since 1996, which is considered the most
reliable.

3. 4 Health Effects

The health effects analysis evaluates impacts of changes in PMio concentrations on the
following health effects end points:

Mortality: cardiovascular mortality and respiratory mortality. Baseline data was taken
from the death registry data for all Korean people between 1996-1998 (National
Statistical Office),

Morbidity: Asthma, Chronic Obstructive Pulmonary Diseases/Other aggravation of
respiratory function and symptoms. Baseline data was taken from the National Health
Insurance data (NHIC) between 1996-1998 for asthma and chronic obstructive
pulmonary diseases (COPD).

A Robust Poisson Regression Model was used to fit the daily count of health outcomes on air
pollution levels(PMio). Meteorological factor(average temperature and relative humidity), time
trends, days of weak, seasonal variations, and other related factors were considered.

3.5. Economic Valuation

For the economic valuation of the effects, primarily a CVM analysis was applied to estimate the
unit value of premature mortality risk reductions. The CVM was carried out for the project with
the cooperation of Dr. Alan Krupnick at Resources for the Future to obtain Willingness to
Pay(WTP) for premature mortality due to PMi0 in Korea utilizing a Korean version of a
questionnaire applied in a Canada study(Krupnick et al., 2000). The sample size for the Korean
survey amounts to 997 in Seoul with target population of 40 - 79 years of age. Of distinctive
aspects of the survey is to investigate future versus current risks. Respondents under age 60
years are asked their WTP over the next 10 years for a 5 in 1,000 risk reduction over 10 years
beginning at age 70 years. This question serves two purposes. First, it tests whether
respondents are willing to pay anything today for a future risk reduction what one would like to
measure to value reduced exposure to a pollutant with a latency period. Second, it provides a
test of internal consistency of responses because WTP today for a future risk change should be
less than WTP today for an immediate risk change. In case of the estimates of the total medical
cost of asthma and respiratory diseases, Cost of Illness(COI) approach was employed. The COI
has been estimated in the following way.

Total medical cost of outpatient treatment = personal expenses for treatment +
insurance reimbursement + traffic expenses + an estimate of the value of the waiting
time for treatment

Total medical cost of inpatient treatment = personal expenses for hospital treatment +
insurance reimbursement + expenses for travel + expenses for nursing + other
supplementary expenses + an estimate of the value of time for the treatment period

With primary approaches of CVM and COI, human capital approach and benefit transfer
method were applied for estimate of value of statistical life. The human capital approach
was estimated utilizing the expected life time of target people(between 40 and 79 years old
persons) and the population of each age in Seoul. A simple adjustment method for

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transferring the monetary values of health effects from United States to Korea is proposed,
applying the following relationship:

V SL(Korea) = VSL(US)*Radj

where VSL(Korea) and VSL(US) are the value of statistical life in Korea and the United
States, respectively, and Radj is an adjustment parameter.

The adjustment ratios associated with average incomes of the two countries are used to
extrapolate values of health endpoints from the U.S. studies(Krupnick, 2000; US EPA, 1999,
1997). All monetary figures, otherwise cited, are in 1999 present values with a conversion of
1US$=1,145.4 Korean Won (KW).

4. Analytic Results
4.1 Air Pollution Emissions and Atmospheric Concentration Levels

The results of air quality modeling revealed that PM10 emission reductions for four GHG
mitigation scenarios ranged from 20,000 to 30,000 tons/yr. in 2020 (off a forecasted baseline of
140,000 tons/yr in 2020). Figure 2 depicts changes in atmospheric concentration levels for
PMio for a typical grid cell. Most of the PMi0 reductions come from the industrial and
transportation sector along with paved-roads sectors (Table 4). Table 5 illustrates GHG abated
from the scenarios implemented.

70.0

,:ri

cj 60. 0

-i.

o 50.0
jd

S 40.0

u
sz
o

" 30.0

20.0

1990 2000 2010 2020 2030

Year

Figure 2. An average annual atmospheric PMW concentration by scenarios

Table 4. Reduction of PM10 emission by sectors in case of scenario 4(tons/year)

Year

Households

Commercial-
Public

Industry
(Manufacturing)

Transportation

Conversion

Paved
roads

Sum

1995

—e—

- BAU

B—

- Scenario 1

-—it—

- Scenario 2

Scenario 3

........

- Scenario 4

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2000

125

4128

4305

5572

14227

2010

108

4392

10606

7379

22591

2020

114

4592

13360

8877

27056

Table 5. Reduction of GHG emission by scenarios

GHG Abated (1000TCE)

2000

2010

2020

Scenariol

536

2047

4259

Scenario2

1575

2251

2819

Scenario3

3150

4502

5637

Scenario4

4725

6754

8456

4.2 Excess Occurrences of Mortality and Morbidity

In order to calculate estimates of additional numbers of premature deaths due to changes in a
pollutant, a baseline mortality rate for PMi0 was used. For this assessment, the estimates were
made in terms of annual cases, so we used the current annual average non-accidental mortality
rate as a baseline basal rate. Relative risk(RR) and prevalence or mortality rate pertinent to
changes in PMi0 were calculated separately to get epidemiologically sound values for health
benefit estimation(Table 6). As for milder health outcomes, meta-analysis was applied such as
respiratory symptoms and lung function (forced expiratory volume 1 second, FEV1). For
reference cases, employed were studies in Korea, Asian countries (China, Taiwan), and Western
countries. Mortality rate and prevalence rate (spell based, not person based) were estimated
independently to provide "basal rate" or "reference rate" of mortality and morbidity. Note that
we intentionally estimated spell-based prevalence to get more valid estimator of total medical
cost. Annual excess occurrence of mortality in area /' is obtained from following relation:

Annual Excess Occurrences = (RR-1) x Pol, x Ba x Popt

where RR is relative risks,

Poli is changes in concentration level in area i,

Ba is basal rate, and

Popt is population in area i.

Key results from the health effects analysis include(Table 7):

-The decreases in premature deaths range from 40 deaths/yr for scenario 2 to 120 deaths/yr.
in scenario 4 in 2020.

-The reductions in asthma and respiratory diseases range from 2,800 occurrences/yr. to over
8,300 occurrences/yr. in 2020.

Table 6. Relative risks from PMi0 by the organ systems, severity and chronicity of

health effects per 50 ug/m3

Respiratory system

Cardiovascular system

Etc

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Acute

Chronic

Acute

Chronic

Birth outcomes
Cancer

Functional
change

3-5% decrease of
FEV1

Symptom
and signs

RR: 1.32
(RR: 1.21-1.43)

- low birth weight
(under pilot study)

Morbidity

- aggravation of

asthma
RR: 1.011 (RR:
1.007-1.015)

- aggravation of
CHF

- congenital anomaly
-increase of lung cancer
(under pilot study)

(premature)
mortality

Respiratory
mortality
RR: 1.053
(1.022-1.085)

Cardiovascular
mortality
RR: 1.053
(1.038-1.068)

Increase of total non
accident mortality

RR: 1.024
(RR: 1.016-1.032)

Table 7. Decreases in occurrences of annual mortality and morbidity by GHG reduction

scenarios

Scenario 1

Mortality by Cardiovascular

6.22

55.46

83.37

Mortality by Respiratory

0.71

6.36

9.56

Asthma

471.54

4,207.48

6,324.48

Respiratory Diseases

9.59

85.57

128.63

Scenario 2

Mortality by Cardiovascular

22.27

29.16

36.01

Mortality by Respiratory

2.55

3.34

4.13

Asthma

1,689.71

2,212.28

2,731.60

Respiratory Diseases

34.37

44.99

55.56

Scenario 3

Mortality by Cardiovascular

44.55

58.32

72.01

Mortality by Respiratory

5.11

6.69

8.26

Asthma

3,379.43

4,424.56

5,463.21

Respiratory Diseases

68.73

89.99

111.11

Scenario 4

Mortality by Cardiovascular

66.82

87.48

108.02

Mortality by Respiratory

7.66

10.03

12.39

Asthma

5,069.14

6,636.84

8,194.81

Respiratory Diseases

103.10

134.98

166.67

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4.3 Economic Benefits

As for benefit estimation, only morbidity and mortality were calculated in connection with
PMio. Cost of illness figures were employed for economic valuation of diseases while a range of
values of statistical life was used to calculate the value of the avoided premature deaths(Table
8). As for the values of the avoided cases of asthma and other respiratory diseases COI
estimates were appplied(Table 9). All numbers are in 1999 present values with annual discount
of 7.5 percent and with converted as 1US$=1,145.4 Korean Won (KW). Key results of the
aggreagte values of mortality and morbidity include :

• The economic value(CVM) of the deaths avoided from the climate change mitigation

scenarios ranges from 3.29 million (2000, scenario 1) to 57.12 million (2020, scenario 4)
US$/yr(Table 10).

• The economic value of the cases of asthma and other respiratory diseases avoided for the

climate change mitigation scenarios range from 0.03(2000, scenario 1) million to 0.52
million(2020, scenario 4) US$/yr(Table 10).

• The economic value(CVM) of the sum of deaths and morbidities avoided from the climate
change mitigation scenarios ranges from 3.32 million (2000, scenario 1) to 57.64 million
(2020, scenario 4) US$/yr(Table 10).

• The economic benefits per GHG emission avoided range $6.2(2000, scenario 1 to
$14.4(2010, scenario 1) for the climate change scenarios(Table 11).

• The cumulative value of these avoided health effects is estimated to range from

342.16(scenario 2) to l,026.57(scenario 4) million US$(Table 12).

Table 8. Values of statistical life

VSL
(M KW)

VSL
(M US $)

Reference

Human
Capital
Approach

283.3

0.25

Average remaining expected life
time between 40 and 79: 27.5
years

Per capita GDP : 10.3 (M KW)

Transferred
Value

1,658.5

1.45

range of values :
246.1 -5,066.6 (M KW)

CVM

Current
Risk

999.6

0.87

range of values :
407.4 - 1,972.8 (M KW)

Future
Risk

543.4

0.47

range of values :
358.0- 824.7 (M KW)

Table 9. Unit values of morbidity

Cost of
Adm.
(KW)

Cost of
OPD.
(KW)

Mean Cost
(KW)

Mean Cost
(US $)

Prevalence

rate
(spell based)

Asthma

913,534

40,157

70,973

62.0

Adm: OPD

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11

= 203

5,359

Respiratory

1,040,488

33,959

63,845

55.7

Adm:

OPD

Disease

= 196

6,405

Note: Adm.: ac

mission

OPD.: outpatient

Table 10. Estimated annual health benefits of mortality(CVM) and morbidity avoided

(99 million US $)

Benefits from decreases of

2000

2010

2020

Scenario 1

Asthma and respiratory disease

0.03

0.27

0.40

Premature deaths

3.29

29.33

29.59

Total benefit

3.32

29.60

29.59

Scenario 2

Asthma and respiratory disease

0.11

0.14

0.17

Premature deaths

11.77

15.42

19.04

Total benefit

11.88

15.56

19.21

Scenario 3

Asthma and respiratory disease

0.21

0.28

0.34

Premature deaths

23.56

30.84

38.08

Total benefit

23.77

31.12

38.42

Scenario 4

Asthma and respiratory disease

0.32

0.42

0.52

Premature deaths

35.33

46.26

57.12

Total benefit

35.65

46.68

57.64

Table 11. Economic benefit per GHG emission avoided

$/ton of carbon
avoided

2000

2010

2020

Scenario 1

6.2

14.4

10.4

Scenario 2-4

7.5

6.9

6.8

Table 12. Cumulative results 2000 to 2020 of total excess occurrence of mortality and
morbidity avoided and the corresponding benefits

Scenarios

Cumulative
Decreases from
2000 to 2020
(occurrence)

Value
(M US$)

Total Value

Scenario 1

Mortality

Cardiovascular
Disease

1,102.81

523.17

588.44

Respiratory
Disease

126.45

59.99

Morbidity

Asthma

83,660

5.18

Respiratory
Disease

1,701

0.09

Scenario 2

Mortality

Cardiovascular
Disease

641.30

304.23

342.16

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12

Respiratory
Disease

73.48

34.86

Morbidity

Asthma

48,652

3.01

Respiratory
Disease

990

0.06

Scenario 3

Mortality

Cardiovascular
Disease

1,282.60

608.47

684.41

Respiratory
Disease

147.13

69.80

Morbidity

Asthma

97,305

6.03

Respiratory
Disease

1,979

0.11

Scenario 4

Mortality

Cardiovascular
Disease

1,923.90

912.70

1,026.57

Respiratory
Disease

220.61

104.66

Morbidity

Asthma

145,957

9.04

Respiratory
Disease

2,969

0.17

5. Policy Implications and Conclusions.

A review meeting for the ICAP-Korea project was held on 16 October 2000. This meeting was
attended by the Korean ICAP study team led by Korea Environment Institute, Korean policy
makers from Ministry of Environment and the Korean legislature, Korean technical experts, and
technical experts from the USA. The objectives of the meeting were to present the analytical
methodology and the outcome of the project to Korean policy makers and technical experts and
to obtain feedback on the usefulness of the project approach and results for enhancing effective
policy making in Korea in the areas of GHG mitigation and air quality management.

The ICAP-Korea assessment found that the ancillary benefits of implementing GHG
mitigation measures in Seoul Metropolitan area between 2000 and 2020 would, on average,
resulted in human health benefits of reduced air pollution of $US6.8-7.5/tonne of carbon(TC)
mitigated, a significant figure when considering the costs of potential GHG mitigation
measures. Policy makers agreed that the ICAP approach and the results of this project were
useful in informing policy makers and the public of the co-benefit impacts of policy decisions
and assisting with the development of cost-effective integrated strategies to address both local
air quality issues and GHG mitigation concerns simultaneously.

5.1 Study limitations that affect magnitude of results

The average ancillary health benefits of $US6.8-7.5/TC viewed as conservative due to several
limitations of the current study's analytical approach and methodology which tended to lead to
underestimates of the total benefits which could be realized. The reviewers recognized these
study limitations and concluded that if these limitations could be successfully addressed in
future work, the expected ancillary benefits of the GHG mitigation scenarios would likely
increase. The discussion of the key limitations identified by the policy makers and experts and
their effect on the assessment outcome is summarized below.

Mitigation scenarios:

The reviewers noted that the GHG mitigation scenarios assumed a modest level of

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implementation of effective GHG mitigation measures and that these measures were not
specifically targeted toward "integrated strategies" which would be most effective in
simultaneously reducing GHG emissions and emissions of air pollutants. A greater focus in the
mitigation scenarios on harmonized strategies that target both GHG and air pollution emissions
from specific sectors and fuel types would likely have resulted in greater emission reductions of
both types of pollutants, and hence greater health benefits.

Assessment considered a limited set of key air pollutants:

The only air pollutant considered under the assessment methodology was directly emitted PM10,
which Korean researchers estimate make up only about 50% of total air pollution health effects
in Seoul. Other pollutants which have been determined to have important impacts on human
health include fine particulate matter (PM2 5 and secondary particulate matter such as sulfates
and nitrates), S02, NOx, and 035. Atmospheric concentrations of these other pollutants would
also be expected reduced as a result of implementation of the GHG mitigation strategies, along
side PM10. Thus, the reviewers recognized that consideration of a wider range of air pollutants
would allow the project to quantify an increasingly larger set of ancillary health benefits
resulting from implementation of GHG mitigation measures.

Health effects relationships may underestimate actual impacts:

First, health effects are correlated with daily average rather than daily peak air pollutant
concentrations. Air quality modeling for this study provided estimates of future PMi0 levels as
average daily concentrations. Monitored daily average concentrations of PM10 in Seoul are often
3-5 times lower than monitored daily peak concentrations. Lower variability of the daily
average concentration levels as compared to daily peak PMi0 concentrations results in poorer
correlation with observed health effects. Thus, the resulting dose-response functions do not
capture the full impacts of increasing PMi0 concentrations. As a result, they concluded that the
assessment, by correlating health effects with daily average PMi0 concentrations,
underestimated the health impacts resulting from increased PMi0 concentrations and hence the
ancillary benefits of reducing these concentrations were also underestimated.

Second, hospital and insurance record data used to determine the magnitude of health effects
underestimates the actual number of individuals affected by an air pollution episode. It is
widely accepted that many acute respiratory cases are treated at home by individuals with over
the counter drugs available from pharmacies and are not treated by medical staff and hence do
not appear on hospital or insurance record logs. Under representing the magnitude of the effect
on public health of air pollution episodes, results in dose-response functions that under estimate
possible health impacts from increasing levels of air pollution and hence under estimate
potential ancillary benefits of GHG mitigation scenarios.

5.2 Relevance and usefulness of the ICAP approach and results for policy making

There was an overwhelming consensus that the approach and results of this project were very
useful for policy making at both local levels (on air quality management) and national levels (on
GHG mitigation). Policymakers noted that the project demonstrated the potential for real,
positive economic and social ancillary benefits from mitigation scenarios and commended the
project efforts activities to provide these estimates. An important next step in this process
would be to more widely disseminate the outcome and results of this project to achieve greater
recognition and understanding of the results in the policy-making community and the general
public. Representatives from the government noted that while in general in Korea, policy
makers place greater value on actions to improve local air quality than on actions to mitigate
GHG emissions, the approach followed in this project could be used to develop cost-effective

5 A previous study(Joh, 2000) shows that the estimate of ozone impact on health is larger than that of PM10.

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integrated strategies to address both types of concerns simultaneously. The representative from
the Legislature pointed out that the Korean government already expressed a keen interest in
climate change issues and lawmakers are very interested in the issue of ancillary benefits of
climate change mitigation actions. However, the problem of awareness extends beyond the
policymakers to the general population who view climate change as a complicated, difficult and
potentially costly problem. Thus, one benefit of this project and it's results would be to assist
with educating the general public about the potential economic and social benefits of taking
action on climate change issues in a way that allows them to better relate to these issues on a
personal level and comprehend the costs and benefits of policy decisions. The ICAP project
affords the benefit of allowing the policy issues of climate change to be viewed in the context of
sustainable development. Through linking strategies to address local air quality and improve
human health with GHG emissions reductions, the relationship between sustainable
development and climate change policy becomes more apparent. As those linkages are further
developed, it becomes clear that practical measures to address climate change are to help
achieve sustainable development goals as well.

It was also pointed out that in Korea, as in the US and many other developed countries,
pollution regulation has traditionally addressed one criteria pollutant at a time often resulting in
an overall regulatory strategy which is not optimal. The ICAP project is useful for air pollution
regulation in Korea as it aids policymakers in integrating the regulation of multiple pollutants
simultaneously, resulting in more effective, and more cost-effective strategies.

The policy makers also noted that to be useful in practical application, the ICAP
project should attempt to prioritize specific measures and strategies in terms of their benefit
potential and cost effectiveness in achieving simultaneous GHG mitigation and human health
improvement. To address this concern, ICAP would need to develop and analyze more specific
mitigation measures and technologies related to specific sectors and fuel types to determine the
overall impact and benefit ratio for these measures. In this way, the ICAP approach could more
effectively communicate to policymakers and the general public the anticipated level of
ancillary benefits of specific measures and build support for implementation of these measures.

6. Reference

Aunan, K. et al., "Health and environmental benefits from air pollution reductions in Hungry."
The Science of the Total Environment 212, Elsevier Science Ltd.. 1998.

Davis, D.L., Krupnick, A., and G. McGlynn, Ancillary Benefits and Costs of Greenhouse Gas
Mitigation, ENV/EPOC/GEEI(2000)10, OECD. 2000.

Jacobsen, H., "Integrating the bottom-up and top-down approach to energy-economy modelling:
the case of Denmark." Energy Economics, pp. 443-461. Vol. 20. 1998

Joh, S., "Studies on Health Benefit Estimation of Air Pollution in Korea," presented for
Workshop On Assessing The Ancillary Benefits And Costs Of Greenhouse Gas Mitigation
Strategies, 27-29 March 2000, Washington, DC, United States. IPCC. 2000.

Joh, S. et al., Ancillary Benefits due to Greenhouse Gas Mitigation, 2000 to 2020 - International
Co-control Analysis Program of Korea, Korea Environment Institute, 2001.

Krupnick, A. et al. "Age, Health, and the Willingness to Pay for Mortality Risk Reductions: A
Contingent Valuation Survey of Ontario Residents", Discussion Paper 00-37, RFF. September
2000.

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MOCIE, "The Second-Year Study of Planning National Actions for the UNFCCC." May 1999.

National Communication of the Republic of Korea. 1998.

Rabl, A. and J. V. Spadaro, "Damages and costs of air pollution: an analysis of uncertainties",
Environment International, Vol. 25, No. 1, Elsevier Science Ltd. .1998.

Rabl, A. and J. V. Spadaro, The cost of pollution and benefit of solar energy, Centre
D'Energetique. January 1999.

U.S. Environmental Protection Agency, The Benefits and Costs of the Clean Air Act
Amendments of1990 - 2010, Report to the U.S. Congress. November 1999.

U.S. Environmental Protection Agency, The Benefits and Costs of the Clean Air Act
Amendments of1990 - 2010, Report to the U.S. Congress. October 1997.

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