External cost as an indicator for sustainable electricity generation system
This research applies the Impact Pathway Approach [1] for identifying the external cost for the fossil-fuel electricity production in Ukraine. Using the SimPact Computer Code and Willingness to Pay survey, it calculates the external costs of the morbidity and mortality of population due to the air p...
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Matsuki, Y. Brondzia, О. Maslukivska, O. 2013-10-04T14:38:41Z 2013-10-04T14:38:41Z 2010 External cost as an indicator for sustainable electricity generation system / Y. Matsuki, О. Brondzia, O. Maslukivska // Систем. дослідж. та інформ. технології. — 2010. — №4. — С. 18-32. — Бібліогр.: 46 назв. — англ. 1681–6048 https://nasplib.isofts.kiev.ua/handle/123456789/50066 303.833.7:504.75.05 This research applies the Impact Pathway Approach [1] for identifying the external cost for the fossil-fuel electricity production in Ukraine. Using the SimPact Computer Code and Willingness to Pay survey, it calculates the external costs of the morbidity and mortality of population due to the air pollutants emitted from an electricity generation plant using as an example Triypilska Electric Power Generation Plant in Ukrainka town. Based on the research results there were made recommendations to include the external costs into the price of electricity in Ukraine generated from the fossil fuel combustion. Застосовано підхід шляху впливу (Impact Pathway Approach) для визначення зовнішніх витрат виробництва електроенергії з викопних джерел в Україні. За допомогою комп’ютерної програми SimPact та методики опитування щодо бажання платити обраховано вартість зовнішніх витрат від впливу викидів теплоелектростанції на захворюваність та смертність населення на прикладі Трипільської ТЕС у м. Українка. На основі отриманих результатів було зроблено рекомендації щодо включення вартості зовнішніх ефектів до ціни електроенергії в Україні, отриманої за допомогою спалювання викопних енергоносіїв. Использован подход пути влияния (Impact Pathway Approach) для определения внешних издержек производства электроэнергии из ископаемых энергоресурсов в Украине. При помощи компьютерной модели SimPact и методики опроса желания платить были исчислены внешние издержки от влияния выбросов теплоэлектростанции на заболеваемость и смертность населения на примере Трипильской ТЭС в г. Украинка. На основе полученных результатов были сделаны рекомендации о внесении стоимости внешних издержек в цену электроэнергии в Украине, полученную в результате сжигания ископаемых энергоносителей. en Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України Системні дослідження та інформаційні технології Теоретичні та прикладні проблеми і методи системного аналізу External cost as an indicator for sustainable electricity generation system Зовнішні витрати від забруднення при виробництві електроенергії як індикатор стійких електрогенеруючих систем Внешние издержки от загрязнения при производстве электроэнергии как индикатор устойчивых электрогенерирующих систем Article published earlier |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine |
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DSpace DC |
| title |
External cost as an indicator for sustainable electricity generation system |
| spellingShingle |
External cost as an indicator for sustainable electricity generation system Matsuki, Y. Brondzia, О. Maslukivska, O. Теоретичні та прикладні проблеми і методи системного аналізу |
| title_short |
External cost as an indicator for sustainable electricity generation system |
| title_full |
External cost as an indicator for sustainable electricity generation system |
| title_fullStr |
External cost as an indicator for sustainable electricity generation system |
| title_full_unstemmed |
External cost as an indicator for sustainable electricity generation system |
| title_sort |
external cost as an indicator for sustainable electricity generation system |
| author |
Matsuki, Y. Brondzia, О. Maslukivska, O. |
| author_facet |
Matsuki, Y. Brondzia, О. Maslukivska, O. |
| topic |
Теоретичні та прикладні проблеми і методи системного аналізу |
| topic_facet |
Теоретичні та прикладні проблеми і методи системного аналізу |
| publishDate |
2010 |
| language |
English |
| container_title |
Системні дослідження та інформаційні технології |
| publisher |
Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України |
| format |
Article |
| title_alt |
Зовнішні витрати від забруднення при виробництві електроенергії як індикатор стійких електрогенеруючих систем Внешние издержки от загрязнения при производстве электроэнергии как индикатор устойчивых электрогенерирующих систем |
| description |
This research applies the Impact Pathway Approach [1] for identifying the external cost for the fossil-fuel electricity production in Ukraine. Using the SimPact Computer Code and Willingness to Pay survey, it calculates the external costs of the morbidity and mortality of population due to the air pollutants emitted from an electricity generation plant using as an example Triypilska Electric Power Generation Plant in Ukrainka town. Based on the research results there were made recommendations to include the external costs into the price of electricity in Ukraine generated from the fossil fuel combustion.
Застосовано підхід шляху впливу (Impact Pathway Approach) для визначення зовнішніх витрат виробництва електроенергії з викопних джерел в Україні. За допомогою комп’ютерної програми SimPact та методики опитування щодо бажання платити обраховано вартість зовнішніх витрат від впливу викидів теплоелектростанції на захворюваність та смертність населення на прикладі Трипільської ТЕС у м. Українка. На основі отриманих результатів було зроблено рекомендації щодо включення вартості зовнішніх ефектів до ціни електроенергії в Україні, отриманої за допомогою спалювання викопних енергоносіїв.
Использован подход пути влияния (Impact Pathway Approach) для определения внешних издержек производства электроэнергии из ископаемых энергоресурсов в Украине. При помощи компьютерной модели SimPact и методики опроса желания платить были исчислены внешние издержки от влияния выбросов теплоэлектростанции на заболеваемость и смертность населения на примере Трипильской ТЭС в г. Украинка. На основе полученных результатов были сделаны рекомендации о внесении стоимости внешних издержек в цену электроэнергии в Украине, полученную в результате сжигания ископаемых энергоносителей.
|
| issn |
1681–6048 |
| url |
https://nasplib.isofts.kiev.ua/handle/123456789/50066 |
| citation_txt |
External cost as an indicator for sustainable electricity generation system / Y. Matsuki, О. Brondzia, O. Maslukivska // Систем. дослідж. та інформ. технології. — 2010. — №4. — С. 18-32. — Бібліогр.: 46 назв. — англ. |
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© Y. Matsuki, O. Brondzia, O. Maslukivska, 2010
18 ISSN 1681–6048 System Research & Information Technologies, 2010, № 4
UDC 303.833.7:504.75.05
EXTERNAL COST AS AN INDICATOR FOR SUSTAINABLE
ELECTRICITY GENERATION SYSTEM
Y. MATSUKI, O. BRONDZIA, O. MASLYUKIVSKA
This research applies the Impact Pathway Approach [1] for identifying the external
cost for the fossil-fuel electricity production in Ukraine. Using the SimPact Com-
puter Code and Willingness to Pay survey, it calculates the external costs of the
morbidity and mortality of population due to the air pollutants emitted from an elec-
tricity generation plant using as an example Triypilska Electric Power Generation
Plant in Ukrainka town. Based on the research results there were made recommen-
dations to include the external costs into the price of electricity in Ukraine generated
from the fossil fuel combustion.
INTRODUCTION
Ukraine is one of the countries where industries play the significant role in its
economic developments. Among various industries, the energy sector takes an
important role, to satisfy not only the demands for energy in Ukraine, but also the
demands from the other European countries. However, when talking about energy
production, nobody should ignore the fact that this activity is exactly the source of
harmful emissions into the atmosphere.
Considerable fraction of all the emissions is being generated during the
process of fossil fuel combustion, especially of coal, at fossil-fuel electricity gen-
eration stations. Today, the fossil-fuel electricity generation stations supply 45.2
percent of the total electricity in Ukraine [2], of which share is next to the nuclear
power’s 46.2 percent. However, the facilities and the equipments of power sta-
tions are in insufficient conditions. About 40 percent of the facilities/equipments
need to be replaced because they were built in the 1950s, and their working peri-
ods have already expired [3].
The National Inventory of anthropogenic emissions in Ukraine reports that
the sector of energy production emits the largest amount of greenhouse gases
among the other industrial sectors [4]. Also, at the same time, the process of en-
ergy production leads to the emissions of total suspended particles (TSP), sulfur
dioxide (SO2) and nitrogen oxides (NOx).
Total suspended particles are the air pollutants which can be divided into
two types by their aerodynamic diameters: PM10 (aerodynamic diameter is less
than 10 µm) and PM2.5 (aerodynamic diameter is less than 2.5 µm). These parti-
cles are especially harmful to the human health because particles can penetrate the
human organism, such as respiratory system, owing to their small sizes. At the
same time, they cause illnesses of cardio-vascular system, which can end with
mortality cases, among people who live in the industrial centers near the power
stations [5].
However, the same impacts are also observed in the energy production sec-
tor of the United States and the EU countries [5–7]. These countries have already
developed the methodology to assess the health impacts of air pollutions, and to
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 19
evaluate the monetary values of those health impacts (damage costs), including
the method to assess the values of the deaths after years from the exposures to the
pollutants [8–9]. The results of those studies in the US and in the EU show that
the monetary values (damage costs) of the health impacts caused by the pollutions
are significantly large [1, 8]. Considering the evaluated health impacts and the
damage costs in the US and in the EU, it is assumed that the processes of the en-
ergy production in Ukraine also cause the considerable size of the impacts and the
damage costs, hence the external costs of human health.
IDENTIFICATION OF THE PROCEDURE
In order to identify the necessary procedure to assess the size of the health im-
pacts and the external costs of human health in Ukraine, the following topics were
investigated.
1. External cost assessment. The supply and utilization of energy impose
risks and damages to a wide range of receptors, including human health, natural
ecosystems, and the built environment. Such damages are not accounted for the
costs in the decisions making on electricity generation; therefore, they are exter-
nal costs [10]. The external costs of the electricity generation systems are the
costs imposed on society and the environment that are not accounted for by the
producers and consumers of energy, i.e. that is not included in the market price
[8]. Traditional economic assessment of electricity generation systems has tended
to ignore these costs.
2. Development of the methods. Since the early 1990s, the results of sev-
eral major studies have been published on environmental impacts and resulting
external costs; and, through these studies, the consistent framework for the quanti-
fication of the energy related external costs was formulated; among them there
were the EC funded ExternE study [8, 11–17], the study on External Costs of Fuel
Cycles of the US Department of Energy [18–25], and the New York Study [26–31].
There are two approaches used for the assessment of health impacts and the
external costs of air pollutions emitted from the power plants: the top-down ap-
proach and the bottom-up approach. In the top-down approach, generic damage
costs are estimated at the national level for various types of impact and are then
ascribed to registered emissions of pollutants in order to determine an average
external cost per unit of emission. Usually, this method requires highly aggre-
gated data for emissions and damages they cause [32]. The bottom-up approach,
known as the Impact Pathway Approach, is supposed to measure impacts of the
energy generation systems through step-by-step analysis, starting from emissions
and completing with economic valuation of the damages to health and environ-
ment. The procedure starts from the identification of the pollutants from the
plants, the assessment of atmospheric dispersion of the pollutants, the estimation
of the ground concentration of the pollutants, the estimation of various health im-
pacts on the ground, and the estimation of the monetary values of those health
impacts. Together with the US EPA guideline [33], many of the studies carried
out in the US and in the EU [1, 8, 11–25] used the Impact Pathway Approach, and
reported the results with the normalized monetary value of the damages, i.e. the
damage cost in US dollars per unit electricity generation, US dollars/kWh, to fur-
ther compare the results with the price of electricity.
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 20
Later, the methodology was published by the International Atomic Energy
Agency as the guideline document [34], and also a computer code, EcoSense, was
developed by Stuttgart University and used in the ExternE project of the Euro-
pean Commission. In the guideline document [34], it was forecasted that a simpli-
fied computer code would be developed because there had been enough number
of reports published in the United States and in the European Union, to find what
parameters are more influential than others. And then, the SimPact Computer
Code [35] was developed. With this Computer Code, the possibility of calculating
the health impacts and the damage costs of air pollution increased, also in
Ukraine; however, there has not been any published report on the case study of
this topic in Ukraine.
3. Assessment of the health impacts. The method of estimating the health
impacts from the ground concentration have also been published in several major
reports, including Rabl [9] and Wilson and Spengler [36]. These publications de-
fine the factors that are to be multiplied with the ground concentration levels, to
get the number of the cases of different types of the health impacts. Among them,
Pope et al. [5] and Dockery et al. [6] reported the positive correlations between
the exposure to particles and the total mortality. And then, the methodology to
estimate the mortalities several years after the exposure to the air pollutants, the
long-term mortality, were developed [8].
Almost all of the currently available epidemiological studies of air pollution
fall into two classifications of studies, which include:
• аcute exposure studies that are typically time-series studies and use short
term changes in air pollution over time (usually 1–5 days) as the source of expo-
sure variability;
• сhronic exposure studies which use longer-term pollution data (usually
one year or even more) [36].
The primary pollutants from the fossil-fuel electricity generation stations are
PM10, SO2 and NOx [9], but there are also the secondary pollutants that are to be
chemically transformed from the primary pollutants after the emission into the air.
The SimPact Code [37] assumes that the nitrates and the sulfates are to be formu-
lated only beyond 50 km radius from the emission source, causing different types
of health impacts from those of the primary pollutants. Table 1 shows the types of
the health impacts due to the air pollutants.
4. Assessment of the damage costs. The necessity to estimate the damage
cost for the long-term mortality led to the method, including the technique to sur-
vey the people’s Willingness to Pay (WTP) for the prolongation of human life
[38] and the technique to calculate the unit cost of the long-term mortality, which
takes into account the discount-rate for a long period from the present time [39].
The unit costs to calculate the other types of health impacts are also reported
in ExternE [17]. Those unit costs such as in Rabl [9] are the values in the EU
countries, but the method to estimate the country specific unit costs in non-EU
countries was also reported by Markandya [40] that is included in the IAEA’s
SimPact Computer Code by Spadaro [35], which is called the Benefit Transfer
Model that considers the ratio of the Purchasing Power Parity Gross National
Product (PPP GNP) of the EU and the non-EU countries. About the unit cost of
Ukraine, it is reported that the methodology developed by the US EPA and ad-
justed in Russia for Eastern European transition countries was used for the as-
sessment of the air pollution costs from PM2,5 in Ukraine [41].
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 21
5. The Power Station. Under the framework of this research, the assessment
was performed for the Trypilska Power Station. This power station is located in
Kyiv region, in Ukrainka town, which is 36 kilometers from Kyiv to the south.
There are several reasons for choosing Trypilska Power Station to be a theme of
this research. First of all, it is the power station with a big size of energy produc-
tion capacity in Ukraine (1800 MWt), besides, it supplies energy to three regions
of Ukraine: Kyiv, Zhytomyr, and Cherkasy. Secondly, according to the National
report of Kyiv region in 2006, the Trypilska thermoelectric power station, which
is the biggest industrial object in Kyiv region, located about in the center of
Ukraine, is the main source of emissions in the whole region [42].
METHODOLOGY
As described in above section, there are two approaches used for the assessment:
the top-down and the bottom-up approaches. For this study, the bottom up ap-
proach is appropriate to take, because this is the common approach used in the
recent studies on the health impacts and the damage costs in the US and in the EU
([1, 8, 11–31]); and, because, by using this approach, each step of the procedure
and the input data can be examined for the case study in Ukraine.
The bottom-up approach, known as the Impact Pathway Approach, is sup-
posed to measure impacts of the electricity generation systems through step-by-
step analysis, starting from emissions and completing with economic valuation of
the damage costs. The main idea of the Impact Pathway Approach is a logical
way of quantifying the damage costs, which results in the observation of the
whole process of the electricity generation activities, emitted pollutants, their am-
bient concentrations and their incremental impacts on the environment and peo-
ple’s health, and, at last, monetary valuation of such impacts. In the case of pol-
lutants, the approach begins with determining the quantity of emissions from a
defined source, and then makes use of dispersion models and dose–response func-
tions to determine the marginal damages resulting from the emissions. The final
step consists of multiplying the marginal damages by their estimated unit mone-
tary value. The approach is site specific and the marginal external costs obtained
are in principle not transferable [32]. In order to measure impacts of fuel use on
the health, the Impact Pathway Approach is being widely used in Europe and
North America as the main approach of the external cost assessment.
The first step of the analysis is to identify the amount and the types of air
pollutants, which are specific to the concerned power station. In this study, the
primary pollutants are PM10, SO2 and NOx, which lead to different types of mor-
bidities and mortalities.
The second step is to measure atmospheric dispersion. The local and the re-
gional dispersion models are used to account for all significant damages. Local
domain is a territory up to 50 km around from the source of emissions, whereas
regional domain covers larger territory which expands up to 1000 km from the
emission source [35]. In this study, the atmospheric dispersion was calculated by
two different models for these two different dispersion ranges, as shown by for-
mulas 1 and 2. In this study, Gaussian plume model was used for estimating the
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 22
ground concentrations within the local domain (up to 50 km radius), and the Uni-
form World Model was used within the regional domain (from 50 km to 1000 km
radius) in the SimPact Computer Code [35]. The outlines of these two models are
shown by formulas 1 and 2.
Simplified Gaussian plume model for the local domain of less than 50 km [35]:
22
22
LOCAL
1 ⎟
⎟
⎠
⎞
⎜
⎜
⎝
⎛
−⎟
⎟
⎠
⎞
⎜
⎜
⎝
⎛
−
⎥
⎦
⎤
⎢
⎣
⎡
= Z
E
Y
hy
ZY
ee
uQ
C σσ
σσπ
, (1)
where, C — the concentration of pollutant in quantity per unit volume (µg/m3);
Q — the quantity emitted per unit time by a chimney stack considered to be at
the origin or coordinates; Zσ — the standard deviation of the normal distribution
densities in the vertical dispersion, depends upon the atmospheric stability (m);
Yσ — standard deviation in the horizontal dispersion, depends upon the atmos-
pheric stability (m); u — wind speed (m/s); x — distance from the source of
emission (m); y — height from the ground (m); Eh — the height of the plume,
not simply the stack height because hot gases usually make the plume rise even
after leaving the stack, although adverse meteorological conditions can cause
downwash (m).
Uniform World Model for regional domain from 50 km to about 1000 km [35]:
r
hu
k
e
rhuQ
C ⎟⎟
⎠
⎞
⎜⎜
⎝
⎛
−
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛
= MIX
UNI
1
2
1
MIXREGIONAL π
, (2)
where, MIXh — a mixing layer height, in which the atmospheric dispersion oc-
curs (m); r — radius from the emission source (m); UNIk — depletion velocity
(m/s); u — an average wind speed (m/s).
During this study, in order to estimate the health impacts from the air pollut-
ants emitted from the Trypilska Power Station, the list of Exposure-Response
Factors (ERF) was used, as shown in Table 1. These factors are to be multiplied
by the ground concentration to calculate the health impacts. PM10 Restricted Ac-
tivity Days is from ExternE 1998 [17], and the others are from Rabl 2001 [44].
The Exposure-Response Factors of these two references are based on the studies
of health impacts from the air pollutions that were started after Dockery et al.
1993 [6] found the correlation between the air pollutions and the health impacts.
The correlations are assumed as the linear functions.
The next step is to calculate the health impact caused by increased ambient
concentrations of the pollutants [34]. Impacts are estimated by the dose-response
function, also known as the concentration-response or the Exposure-Response
Factor (ERF) [43]. The ERF is concerned about the quantity of the pollutant that
affects a receptor (for example, population) to the physical impact on the receptor
(for example, the number of the hospital admissions). It was assumed that the
human body of average Ukrainian is as same as average European, and then the
ERF used for the European case studies [17, 44] was used for the case study in
Ukraine.
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 23
T a b l e 1 . Exposure-Response Factors to calculate the health impacts [17, 44]
Range Health Impact Cases/µg/m3
PM10 long-term mortality 2.600 × 10 –4
PM10 Chronic Bronchitis 5,855 × 10 –5
PM10 Restricted Activity Days 2.500 × 10 –2
NOx Chronic Bronchitis 5.055 × 10 –5
SO2 Short-term Mortality 2.300 × 10 –6
PM10 Bronchodilator Use 1.404 × 10 –3
Local Range
(<50 km radius) and
Regional Range
(from 50 to
about 1000 km)
PM10 Lower Reparatory Symptoms 3.750 × 10 –3
Nitrates Cardiovascular Hospital Admission 8.400 × 10 –4
Sulfates Long-term Mortality 4.342 × 10 –4
Nitrates Long-term Mortality 2.600 × 10 –4
Sulfates Chronic Bronchitis 9.778 × 10 –5
Nitrates Chronic Bronchitis 5.055 × 10 –5
Nitrates Respiratory Hospital Admission 2.840 × 10 –6
Regional Range
(from 50 to
about 1000 km)
Sulfates Respiratory Hospital Admission 4.743 × 10 –6
METHOD FOR MONETERY VALUATION
The damage costs are to be calculated from the health impacts that should have
been calculated in the previous step, by multiplying the unit cost of each mortality
or morbidity with the number of cases of the mortality or morbidity. In this case
study, the results are shown with the unit costs used in the other case studies car-
ried out in the EU [17, 44], and with the unit costs with Ukrainian value, which
were evaluated by the contingent valuation for the monetary values of the long-
term mortalities, and by the Benefit Transfer Model [40] for the other health im-
pacts. Contingent Valuation is the general expression of evaluating people’s will-
ingness to pay for their life, by setting a hypothetical market condition that
doesn’t exist. The estimated monetary values are to be obtained through the inter-
view process.
For monetary valuation of the long-term mortalities caused by the air pollu-
tions, such as PM10, nitrates and sulfates, the contingent valuation was used to
assess the Willingness to Pay (WTP) and to evaluate the unit cost. This method
provides the values of the environment goods, such as clean air, clean water, and
quiet environment, based on the individual preferences in terms of the willingness
to pay (WTP) for the improvement of the quality of the environment, or by the
willingness to accept the current cost of the environment [38].
In this research, the WTP Questionnaire developed during 2005–2006 by the
team of European experts headed by Rabl [38] was used. This questionnaire pre-
sents an innovative approach of the valuation because it is based directly on the
change of life expectancy (LE), in contrast to the previous valuations of air pollu-
tion mortality that were based either on accidental deaths or on small changes in
the probability of dying. The inquirer consists of four sections, which are devel-
oped in the form of questionnaire and also in the form of article about the correla-
tion of life expectancy and air pollution. Thus, there is the information about
negative influence of air pollution on human health and possible approaches that
can decrease the level of the air pollution. Interviewees are supposed to mention
the amount of money they are ready to pay for prolongation of their life on 3 and
6 months, in other words, they need to measure a value of increase in their life
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 24
expectancy if air pollution is reduced. So, as a result, a value of one year of life,
VOLY, can be measured.
VOLY obtained by the WTP Survey can be applicable for further calcula-
tions of the values of the unit costs, which are defined as the unit damage costs for
the long-term mortality.
The Benefit Transfer Model is widely used for measurement of unit damage
cost of health impacts in one country through already estimated unit damage cost
of health impacts in the other country. In this research, this model was used for
evaluating the damage costs of various health impacts, except the long-term mor-
talities. In order to estimate a damage cost, an adjustment should be made to re-
flect differences in real income, and hence the WTP to reduce damages, between
two countries [40]. Markandya recommends the following equation (3) [40] to be
used for such an adjustment:
γ
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛
×=
EU
COUNTRY
GNPPPP
GNPPPP
EUinCostUnitCOUNTRYinCostUnit , (3)
where, PPP GNPCOUNTRY is the Purchasing Power Parity Gross National Product
of the country normalized per capita, PPP GNPEU is the average European Union
Purchasing Power Parity Gross National Product normalized per capita, and γ is
the income elasticity coefficient, which shows how the WTP value will change
with the income change. As revealed by Rabl et al., if the income elasticity equals
1, the benefit transfer error is just about 36–41 % [39]. But, if income elasticity is
less then 1 (e.g. 0.35, 0.40–0.60), then the transfer error is about 67–72 % [39]. In
this research, it was assumed that the income elasticity is 1.
In the study, the above equation was applied for adjusting the EU unit costs
to the Ukrainian unit costs. The calculated values of Ukrainian unit costs are pre-
sented in Table 2. The unit costs for the long-term mortalities by PM10, nitrates
and sulfates are to be estimated by the contingent valuation (WTP survey).
T a b l e 2 . Unit damage costs for European Union countries and estimated unit
costs in Ukraine in US$1998, by the Benefit Transfer Model
EU UKRAINE
Rangle Health Impact Unit cost
(US$/case)
Unit cost
(US$/case)
PM10 long-term mortality 101 000 15 600
PM10 Chronic Bronchitis 177 800 27 462
PM10 Restricted Activity Days 116 18
SO2 Short-term Mortality 174 000 26 875
PM10 Bronchodilator Use 42 6
Local Range
(<50 km radius)
and
Regional Range
(from 50 to
about 1000 km) PM10 Lower Reparatory Symptoms 8 1
Nitrates Cardiovascular Hospital Admission 3 420 528
Sulfates Long-term Mortality 101 000 15 600
Nitrates Long-term Mortality 101 000 15 600
Sulfates Chronic Bronchitis 177 800 27 462
Nitrates Chronic Bronchitis 177 800 27 462
Nitrates Respiratory Hospital Admission 4 540 701
Regional Range
(from 50 to
about 1000 km)
Sulfates Respiratory Hospital Admission 4 540 701
PPP GNP (1998) in US$[45] 20 269 3 130
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 25
RESULTS
1. Input data
In order to carry out an impact assessment from electricity generation at the
Trypilska Power Station, the level of emissions per year in tons, meteorological
data of the region, the emission data of the power station, and number of affected
population were identified. This power station is located in Kyiv region, in
Ukrainka town, which is 36 kilometers from the capital city, Kyiv, to the south.
Table 3 shows the level of emissions in 2006 from the Trypilska Power Sta-
tion, provided by the national report about the environment in Kyiv region in
2006 [3]. The amount of the emissions of SO2 and NOx were identified; however,
because the air-pollution monitoring in Ukraine provides only the data of Total
Suspended Particles (TSP), but not the data about the level of PM10 . Therefore,
the conversion factor was used to estimate the emission level of PM10. According
to the US Environmental Protection Agency [33], the ratio between TSP and
PM10 is PM10 = 0.5TSP
Table 3 shows the technical
characteristics of the emis-
sion source of the Trypilska
Power Station.
After ground concen-
tration is calculated, the
health impact can be calcu-
lated by multiplying the
ground concentration of
pollutants by the value
of the Exposure-Response
Factor for each type of the
pollutant (See Table 2).
Table 5 shows the in-
put data for calculating the
ground concentrations of
the pollutants by atmos-
pheric dispersion models
for the local and the re-
gional domains. The at-
mospheric stability D type
was assumed, as this type represents the neutral dispersion condition.
T a b l e 5 . Input data for the assessment in the atmospheric dispersion
Parameter Value
Local Population Density 62.0 persons/ km2
Radius of Local Domain 56.0 km
Regional Population Density 76.9 persons/km2
Anemometer height 10.0 m
Air Temperature 285.5 degree K
Wind speed 2.62 m/sec
Atmospheric stability D type
T a b l e 3 . Level of emissions in 2006,
Trypilska Power Station [3]
Name of the pollutant Emissions,
tons/year
Total 74 605 000
Metals and their compounds 22 087
Total suspended particles (TSP):
PM10
21 951 116
10 975 560
Nitrogen compounds 11 108 921
Sulfur oxide and other sulfur compound 40 909 568
Carbon oxide 564 363
T a b l e 4 . Technical characteristics of the
emission source [4]
Parameters Value of
parameters
Stack height, m 180
Diameter of the stack, m 9.6
Flow rate from the stack, m/s 14
Released gas temperature, K 413
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 26
2. Willingness to Pay (WTP) survey
In order to evaluate the Willingness to Pay (WTP) for the prolongation of life for
one year, the contingent valuation was carried out among Ukrainians. This re-
search was the first time of such exploitation in Ukraine. The contingent valuation
was carried out with the questionnaire developed in European Union in
2005–2006 by a team of experts headed by Ari Rabl [38]. The WTP Survey was
conducted in between April and May 2008 upon 70 people in Kyiv City which is
the capital of Ukraine. The aim of the research was to question Ukrainian people
in order to reveal an amount of money which they are willing to pay to prolong
their life. Interviews, which were carried out on one-to-one basis, in general,
lasted on average about for 20 minutes. During an interview people were sup-
posed to answer questions developed by Rabl [38] for the purpose of defining a
Value of Life Year Lost (VOLY). This characteristic is especially important for
the impact assessment in areas with air pollution, because it shows the amount of
money in which people value one year of their life lost.
The samples were the people selected and interviewed on the streets in Kyiv,
as well as the students of the National University of Kyiv-Mohyla Academy and
the National Technical University «KPI». Table 6 shows the aspects of demogra-
phy and socio-economics among interviewees, together with the national demog-
raphy of Ukraine. This table shows that the selected samples represent the na-
tional demographic distribution of the public of Ukraine.
T a b l e 6 . Input data for the assessment in the atmospheric dispersion
Aspects Interviewees Ukraine Population[42]
Number of observations 70 48 457 000
Female, % 61.4 53.7 Gender
Male, % 38.6 46.3
Individual’s net annual income ($ PPP) 4 510
Workable age, %
(Female:16-54/ Male:16-59) 58.0
Average age 34.04 Older than workable age, %
(Femail:55/Male:60) 23.9
University education (%) 84.3 31.3
Fig. 1 shows how the interviewed people in Kyiv are aware of air pollution
and its influence on their health and the life expectancy.
Among 70 observations, 50 % of respondents replied that they are very con-
cerned with how air pollution influences their health, 42.9 % — replied that they
are somewhat concerned, 5.7 % — are not so much concerned, 0 % — is that this
problem is out of their concern (not at all), 1.4 % of samples had missing answers.
Therefore, it is obvious to conclude that about 90 % of people are concerned with
the impact of air pollution in their living area.
The next step was to identify how many people are ready to accept a higher
cost of living, therefore an increase in their daily expenses, to gain an increase in
their life expectancy. It was revealed that 9 people were negative about such in-
crease of expenses, two of them were not interested in living longer, two were
negative because they believed that someone else should pay for better environ-
ment, and other five refused such a scenario of link between air pollution and life
expectancy.
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 27
Out of 61 left observations, 17 samples were identified as defectives, be-
cause the willingness to pay for one year of life prolongation derived from 6
month gain and 3 month gain were not in the expected rational order. Therefore,
the final VOLY for one year of life prolongation was calculated with 44 samples,
from the willingness to pay for 6 month gain in life expectancy multiplied by two.
The results of this WTP survey showed that the average number of VOLY is
790 US dollars. According to the equation (4) below [39], the Value of Statistical
Life (VSL), can be calculated, on the basis of which a unit cost for long-term
mortality cases is measured,
( )Nr
V
r
V
r
VVVSL
+
++
+
+
+
+=
1
...
)1(1 2 , (4)
where, V is a value of one year of life lost, VOLY. r is a discount rate, because it
is assumed that the VOLY will become smaller every year when seeing one’s
willingness to pay in one’s own future at the present time. 3 percent was chosen
for this calculation, as practiced in the precedent studies. N is the number of the
years of a statistical human life. 37.5 years were chosen as N in this calculation,
while 37 years were assumed as the total length of human life, and it was assumed
that the a half of the total life length was the average life length left for the pur-
pose of calculating the value of life after the exposure to the pollutions.
The calculated unit cost for the long-term mortality was 18.264 US dollars,
and then 18.000 US dollars was chosen to calculate the damage costs of the
chronic mortalities to be caused by the air pollutions from the Trypilska Power
Station.
3. Damage cost
Table 8 shows the calculated numbers of the health impacts from energy produc-
tion at the Trypilska Power Station in the local domain, which has a radius of less
than 50 kilometers, and in the regional domain, which covers a territory with a
radius up to about 1000 kilometers, and which covers most of the territory of
Ukraine.
In the calculation for the local domain, the uniform wind direction, the uni-
form population density of 61.8 persons/km2 for 50 km radius, and weighted av-
0
10
20
30
40
50
60
very much somewhat not so much not at all missing
Responses
Fr
eq
ue
nc
y,
%
Fig. 1. Responses to Question: Are you concerned with the effects of air pollution on
your health?
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 28
erage wind speed of 2.62 m/sec uniformly over all directions were assumed. For
the regional domain, the population density assumed was 76.9 persons/km2. The
impact assessment in regional domain also includes the impact of secondary
chemical transformations of sulfur dioxide (SO2) and nitrogen oxides (NOx), as
shown as sulfates and nitrates respectively in Table 7.
T a b l e 7 . The distribution of health impacts in local and regional domains by
SimPact Code
cases/one year exposure Pollutant Health impact
Local domain Regional domain
Long-term mortality 14.300 954
Chronic bronchitis 3.220 215
Restricted Activity Days 1 374.000 91 690
Bronchodilator use 77.200 5 149
PM10
Lower Respiratory Symptoms 205.000 13 700
SO2 Short-term mortality 0.471 29
Long-term mortality – 2 504
Chronic bronchitis – 564 Sulfates
Respiratory hospital admission – 27
Cardiovascular hospital admission – 32
Long-term mortality – 992
Chronic bronchitis – 193
Nitrates
Respiratory hospital admission – 11
As a result, the health impact in regional domain is higher than in local do-
main, because regional population density is higher than local one, and the area of
the regional domain is larger.
In order to assess the external cost of air pollution due to the electricity gen-
eration, the total damage costs were calculated. Assessment was made with the
European Union’s unit damage costs for health impacts and Ukrainian unit
damage costs shown in Table 2.
The calculated total damage costs of the air pollution at the Trypilska Power
Station are presented in Table 8.
T a b l e 8 . Total damage cost, caused by air pollution from the Trypilska
Power Station, Ukrainka, Ukraine
Damage cost, 1000 US $
With EU unit costs With Ukrainian unit costs Pollutant
Local
domain
Regional
domain Total Local
domain
Regional
domain Total
PM10 2 179 145 456 147 635 371 24 760 25 130
SO2 82 4 983 5 065 13 770 782
Nitrates – 134 649 134 649 – 23 180 23 180
Sulfates – 353 324 353 324 – 60 570 60 570
TOTAL 640 673 109 662
If European unit costs are used for the calculations, the total damage cost
from Trypilska Power Station is about 641 million US dollars. If the Ukrainian
unit costs are used, the total damage cost is six times smaller than with European
ones, and equals to about 110 million US dollars. While comparing the results of
damage cost assessment separately for each pollutant, it is noticeable that damage
costs of PM10 in local domain and sulfates in regional domain are bigger than the
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 29
others in each domain; in the other words, PM10 and sulfates have more negative
influence on human health, and, as a result, their damage costs are higher.
The average annual electricity generation at the Trypilska Power Station is
1.80 TWh [82]. Hence, a total damage cost per kilowatt-hour of electricity gen-
eration at Trypilska Power Station was calculated. Table 9 shows the damage
costs per kilowatt-hour with the unit costs of the European Union and of Ukraine.
T a b l e 9 . Total damage cost per kilowatt-hour of electricity generation at the
Trypilska Power Station
Lokal Regional Total
EU 1.26 355 356 Damage cost per kilowatt-hour,
mUSD/kWh Ukraine 0.213 60.7 60.9
To compare with the electricity price in Ukraine, damage cost per kilowatt-
hour of electricity generation in US dollars was converted to Ukrainian national
currency, Ukrainian Hryvnya (UAH), in Table 10.
T a b l e 1 0 . Total damage cost per kilowatt-hour of electricity generation in UAH
With EU unit cost With Ukrainian unit cost Damage cost per kilowatt-hour,
mUSD/kWh 1.78 0.30
There is no doubt about this amount of money to be the external cost of elec-
tricity generation in Ukraine; because, the sum of money is not included in the
price of electricity, and at the same time, the people affected by the air pollution
from the electricity generation do not receive any compensation for the health
impacts. Nowadays, Joint Stock Company «Kyivenergo» has fixed the average
weighted tariff of electricity for consumers in the total amount of 0.2872
UAH/kWh [46]. However, it does not necessarily mean that the amount of the
external costs obtained during this research should be added to the current price of
electricity. On a contrary, policy makers in Ukraine should take into consideration
the estimated external costs. And, it is necessary to find possible ways to reduce
and/or internalize the external cost into the price mechanism of the electricity.
As shown above, the assessment of damage cost of the impact of the fossil-
fuel electricity generation station was able to be made, using the recently devel-
oped method of monetary valuation of health impacts. There is an internationally
practiced method, the Benefit Transfer Model, to transfer the values of the EU to
non-EU countries including Ukraine, using the ratio of PPP GNP between the EU
and non-EU countries. Also, the method to evaluate the people’s willingness to
pay for prolonging their life was examined in Ukraine, and compared to the calcu-
lated unit cost by the Benefit Transfer Model. While the unit cost evaluated from
the interview surveys on the people’s willingness to pay for prolonging one year
of life is 18,000 US dollars, the unit cost calculated by the PPP GNP ratio of the
EU and Ukraine is 15,600 US dollars, which are comparable to each other.
CONCLUSIONS
Upon the results of the case study in Ukraine, the followings are concluded, and
the direction of the future research is identified:
1. The externality study appeared in Europe and the United States in the
1990s as a result of existing problem of negative influence onto the human health,
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 30
natural environment, and built environment of air pollution from energy produc-
tion. Since 1996, the ExternE project of the European Commission started the
external cost assessment widely in the countries of the European Union. Unfortu-
nately, in Ukraine this type of project had not been implemented.
2. The Impact Pathway Approach is the bottom-up method, which is to as-
sess the impacts of electricity generation systems through step-by-step analysis,
starting from emissions and completing with monetary valuation of the damages.
It is a logical way of external cost assessment, which accounts the emitted pollut-
ants and their ambient concentration, the impacts on human health, and their
monetary values.
3. The Willingness to Pay Survey carried out among Kyiv citizens defined
that Ukrainians estimate the value of life loss (VOLY) in the amount of 790 US
dollars.
4. Calculation of health impacts and damage costs of air pollution from elec-
tricity generation at Trypilska Power Station in Ukrainka town were obtained,
with the SimPacts Compute Code. These impacts and the damage costs were cal-
culated in the local domain (up to 50 km radius) and in the regional domain (up to
about 1000 km).
5. The damage cost of health impacts estimated by the EU unit costs is ten
times larger than with the Ukrainian.
6. The estimated damage costs per kilowatt-hour of electricity generation is
360 mUSD/kWh and 61 mUSD/kWh by the EU unit cost and by the Ukrainian
unit cost respectively. In comparison with the current electricity price in Ukraine,
57.6 mUSD/kWh or 0.2879 UAH/kWh (assuming 1 USD (dollars) = 5 UAH), it
is concluded that the estimated external cost of the health impacts is sizable, in
comparison with the price of electricity.
7. As shown above, the assessment of damage cost of the fossil-fuel electric-
ity generation station was able to be made, using the recently developed method
of monetary valuation of health impacts. There is an internationally practiced
method, the Benefit Transfer Model, to transfer the value of the EU to non-EU
countries including Ukraine, using the PPP GNP ratio between the EU and non-
EU countries. Also, the method to evaluate the people’s willingness to pay for
prolonging their life was examined in Ukraine, and compared to the unit cost cal-
culated by the Benefit Transfer Model. While the unit cost evaluated from the
interview surveys on the people’s willingness to pay for prolonging one year of
life is 18 000 US dollars, the unit cost calculated by the PPP GNPs of the EU and
Ukraine is 15 600 US dollars.
8. The estimated damage costs of Ukraine are the external cost that are not
included in the price of electricity, and the people affected by the air pollution do
not receive any compensation for the health impacts. The policy makers in
Ukraine should take into consideration the estimated external costs and should
find possible ways to reduce and/or internalize the external costs in the price
mechanism.
REFERENCES
1. Matsuki Y. Comparison of health and environmental impact of energy systems // Interna-
tional Journal of Risk Assessment and Management. — 2002. — 3. — № 1. — Р. 1–15.
2. Ministry of Fuel and Energy of Ukraine. The amount of electricity production and
consumption (2008). — http://mpe.kmu.gov.ua/fuel/control/uk/publish/article?
art_id=126559&cat_id=35086.
External cost as indicator for sustainable electricity generation system …
Системні дослідження та інформаційні технології, 2010, № 4 31
3. Dubovyk V.S. Main tendencies of innovation development of fossil fuel energy of
Ukraine in the mid-term period. — http://incon-conference.org.ua/download/
files/Dubovuk_dok.pdf.
4. Bereznitskaya M.V., Butrim O.V., Panchenko H.H. et al. National Inventory of an-
thropogenic emissions from the sources and absorption of GHG absorbents in
Ukraine during 1990–2006, Ministry for Environmental Protection of Ukraine.
— Kyiv, 2008. — http://menr.gov.ua/documents/Nac_zvit_p_parn_gazy_90-061.pdf.
5. Pope C.A.III, Thun M.J., Namboodiri M.M., Dockery D.W. Particulate air pollution
as a predictor of mortality in a prospective study of US adults // American Jour-
nal of Respiratory and Critical Care Medicine. — 1995. — 151. — Р. 669–674.
6. Dockery Y., Pope C.A.III, Xu X., Spengler J.D. An association between air pollution
and mortality in six US cities // New England Journal of Medicine. — 1993. —
329. — Р. 1753–1759.
7. Wilson R., Colome S., Spengler J., Wilson D. Health effects of Fossil fuel burning:
Assessment and Mitigation, Ballinger, Cambridge, 1980. — 392 p.
8. Bickel P., Friedrich R. Externalities of Energy. Methodology 2005 Update, Euro-
pean Commission, 2005. — 287 p. — http://www.externe.info/.
9. Rable A. Reference of Concentration-Response Functions for Health Impacts of Air
Pollution // International Atomic Energy Agency, Vienna, 2001. — 243 p.
10. EC, DG Research. New Elements for the Assessment of External Costs from Energy
Technologies: NewExt., Technological Development and Demonstration (RTD), 2004.
11. EC, DG XII. ExternE: Externalities of Energy. — 1. — Summary, Luxembourg, 1996.
12. EC, DG XII. ExternE: Externalities of Energy. — 2. — Methodology, Luxembourg, 1996.
13. EC, DG XII. ExternE: Externalities of Energy. — 3. — Coal & Lignite, Luxem-
bourg, 1996.
14. EC, DG XII. ExternE: Externalities of Energy. — 4. — Oil & Gas, Luxembourg, 1996.
15. EC, DG XII. ExternE: Externalities of Energy — 5. — Nuclear, Luxembourg, 1996.
16. EC, DG XII. ExternE: Externalities of Energy. — 6. — Wind & Hydro, Luxem-
bourg, 1996.
17. EC, DG XII. ExternE: Externalities of Energy. — 7. — Methodology, 1998 update.
18. Oak Ridge. National Laboratory, Resources for the Future. U.S.–EC Fuel Cycle
Study: Background Document to the Approach and Issues, Rep. № 1. — Oak
Ridge Natl Lab., TN, 1992.
19. Oak Ridge. National Laboratory, Resources for the Future. Estimating Fuel Cycle
Externalities: Analytical Methods and Issues, Rep. № 2. — McGraw-Hill/Utility
Data Inst., Washington, DC, 1994.
20. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities of
Coal Fuel Cycles, Rep. № 3, McGraw-Hill/Utility Data Inst., Washington, DC, 1994.
21. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities
of Natural Gas Fuel Cycles, Rep. № 4, McGraw-Hill/Utility Data Inst., Washing-
ton, DC, 1998.
22. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities of
Oil Fuel Cycles, Rep. № 5, McGraw-Hill/Utility Data Inst., Washington, D.C., 1996.
23. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities
of Hydro Fuel Cycles, Rep. № 6, McGraw-Hill/Utility Data Inst., Washington,
DC, 1994.
24. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities
of Biomass Fuel Cycles, Rep. № 7, McGraw-Hill/Utility Data Inst., Washington,
DC, 1998.
25. Oak Ridge. National Laboratory, Resources for the Future. Estimating Externalities
of Nuclear Fuel Cycles, Rep. № 8, McGraw-Hill/Utility Data Inst., Washington,
DC, 1995.
26. RCG/Hagler Bailly. Inc, Tellus Institute. New York State Environmental External-
ities Cost Study, Report 1: Externalities Screening and Recommendations, Em-
pire State Electric Energy Research Corp., Albany, NY, 1993.
Y. Matsuki, O. Brondzia, O. Maslukivska
ISSN 1681–6048 System Research & Information Technologies, 2010, № 4 32
27. RCG/Hagler. Bailly. Inc, Tellus Institute. New York State Environmental External-
ities Cost Study, Report 2: Methodology, Empire State Electric Energy Research
Corp., Albany, NY, 1994.
28. RCG/Hagler. Bailly. Inc, Tellus Institute. New York State Environmental External-
ities Cost Study, Report 3A: EXMOD User Manual, Empire State Electric En-
ergy Research Corp., Albany, NY, 1995.
29. RCG/Hagler. Bailly. Inc, Tellus Institute. New York State Environmental External-
ities Cost Study, Report 3B: EXMOD Reference Manual, Empire State Electric
Energy Research Corp., Albany, NY, 1995.
30. RCG/Hagler. Bailly. Inc, Tellus Institute. New York State Environmental External-
ities Cost Study, Report 4: Case Studies, Empire State Electric Energy Research
Corp., Albany, NY, 1995.
31. Rowe R.D., Chestnut L.G., Lang C.M., Bernow S.S., White D.E. The New York envi-
ronmental externalities cost study: summary of approach and results, OECD
Workshop on the External Costs of Energy, Brussels,1995.
32. Kim S.H. Evaluation of negative environmental impacts of electricity generation:
Neoclassical and institutional approaches, Energy Policy. — 35, Issue 1.
2007. — Р. 413–423.
33. US Environmental Protection Agency. Guideline on Speciated Particulate Monitor-
ing, Prep. by Chow J.C., Watson J.G. — 1998. — 291 p. — http://www.epa.gov/
ttnamti1/files/ambient/pm25/spec/drispec.pdf.
34. International Atomic Energy Agency. Health and environmental impacts of electric-
ity generation systems: procedures for comparative assessment, IAEA Technical
Report Series, № 394. — 1999. — 204 p. — http://www-pub.iaea.org/MTCD/
publications/ PDF/TRS394_scr.pdf
35. Spadaro J. AIRPACTs Impact Methodology. Version 1.0. — Vienna, IAEA, Febru-
ary 2002, 1 CD-ROM.
36. Wilson R., Spengler J. Particles in Our Air: Concentrations and Health Effects. Cam-
bridge, MA: Harvard Univ. Press, 1996.
37. Spadaro J. AIRPACTs Impact Methodology. Version 1.0. — Vienna, IAEA, Febru-
ary 2002, 1 CD-ROM.
38. Rabl A., et al. Final Report on the monetary valuation of mortality and morbidity
risks from air pollution, 2006.
39. Rabl A. Comparative Health and Environmental Risks on Nuclear and Other Energy
Systems, the IAEA Research Coordination Meeting on the Coordinated Research
Program, Vienna, 1997.
40. Markandya A., Boyd R. Economic Valuation of Environmental Impacts and External
Costs, University of Bath, UK, 2000.
41. Strukova E., Golub A., Markandya A. Air Pollution Costs in Ukraine, Fondazione
Eni Enrico Mattei, Milano, 2006. — http://www.feem.it/Feem/Pub/ Publica-
tions/WPapers/default.htm.
42. State Statistics Committee of Ukraine. All Ukrainian Population Census 2001. —
http://www.ukrcensus.gov.ua/
43. Spadaro J. AIRPACTs Input Data: Exposure Response Function, Version 1.0. —
Vienna, IAEA, October 2002. — 1 CD-ROM.
44. Rabl A. Reference Database of Concentration-Response Functions for Health Im-
pacts of Air Pollution, Ecole des Mines de Paris 60 boul. St.-Michel, F-75272,
Paris 31 December, 2001.
45. Spadaro J. AIRPACTs Input Data, Monetary Unit, Version 1.0. — Vienna, IAEA,
October 2002, 1 CD-ROM.
46. Kyivenergo. Tariff structure for electricity. — http://www.mepress.kiev.ua/tariffs.
php?artid=195.
Received 23.11.2009
From the Editorial Board: the article corresponds completely to submitted manu-
script.
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