The document outlines the external costs associated with electricity generation systems, particularly focusing on the health impacts from air pollution. It discusses the methodology for calculating the monetary value of these impacts, epidemiological studies linking air pollution to mortality and morbidity, and provides data from various studies indicating the correlation between pollution levels and health outcomes. Additionally, it examines case studies and implications for public health policy and future research regarding air quality and health effects.

1. External cost of electricity generation
systems
Y. Matsuki, D.Sc.
Professor, Department of
Mathematical Method for System
Analysis, IASA, NTUU “KPI”
August 10, 2010

2. How can you calculate the externalities?

3. How to calculate the monetary
value of the health impacts
D= ∫ ρ(x)·f(x,C(x,Q))·Uv(x) dx
impact of Area
D: damage cost (Euro, US dollars, UAH)
ρ(x): population density (person/m2)
f(x,C(x,Q)): Exposure-Response Function
cases/(year.person.μg/m3)
Uv(x): unit cost (Euro/cases)
C(x,Q): Concentration of the pollution (μg/m3)
Q: Emission of the pollution (μg/year)
x: Distance from the emission source (m)

4. What’s new on the public health
issue?
• Loss of life expectancy for chronic
mortality from air pollution
• [Dockery et al 1993, Pope et al 1995] have
found positive correlations between
exposure to particles and total mortality

5. Epidemiology of Acute Health
Effects
• Table of contents
- Introduction
- Studies of air pollution episodes
- Health effects at low levels of air pollution
- Acute Morbidity
- Daily time-series mortality studies
- Slope of the mortality exposure-response relationship and lead-lag
relationships
- Acute Morbidity
- Hospital usage
- Exacerbation of asthma
- Respiratory symptoms
- Lung function
- Restricted activity

6. Introduction
• It’s about human health and pollution.
• Where in the world is this story about?
• When did this story start?
• What changed for the last 10-15 years?

7. Air pollution episodes
• Where the most dramatic episode occurred and
when?
• What happened?
• Mortality and morbidity
• How?
• Respiratory and cardiovascular
• Cardiopulmonary disease
• What was the level of particle and SO2?
• 500 μg/m3 – 2 mg/m3
• If not old days, where do these levels exist?

8. Health effects at low level of air
pollution
• What was the primary interest to air
pollution policy among the most developed
nations for the last 20 years?
• To determine the lowest level
• The length of exposure to cause health
impacts
• Threshold was often assumed.

9. Health effects at low level of air
pollution
• With improved air monitoring, is threshold
proven?
• No threshold, or bellow ambient level in
the US in 1996.
• Many of the studies suggest linear model.
• What is necessary to prove it?
• Number of time-series studies

10. What are the health effects?
• Mortality
• Hospitalization for respiratory and heart
disease
• Aggravation of asthma
• Incidence and duration of respiratory
symptoms
• Lung function
• Restricted activity

12. Acute Mortality
Daily time-series mortality studies
• US EPA reviewed Ostro 1993, Schwartz
1994c, Dockery & Pope 1994, Pope et al.
1995b.
• What these studies observed?
• Changes in daily death counts
associated with short-term changes in
particulate air pollution.
a near linear function.

15. What do you see from those table
and figures?
• Consistency in estimated effects
• Statistically significant effect
• Estimated Range?
• 0.5 percent – 1.6 percent in daily mortality
for each 10 μg/m3 increase in PM10
concentration.
• Weighted mean?
• About 0.8 percent

16. Percent increase in Mortality
per 10 μg/m3 increase in PM10
• Mortality Cases/ μg/m3 ?
• 0.5 percent – 1.6 percent in daily mortality
for each 10 μg/m3 increase in PM10
concentration.
• 5 x 10-4 – 1.5 x 10-3 Cases/ μg/m3
• Weighted mean about 0.8 percent
• 8 x 10-4

17. Mortality by respiratory disease and
cardiovascular disease
• Large effect on respiratory disease
mortality
• Also cardiovascular disease causing death

18. Shape of the mortality exposure-response
relationship and lead-lag relationships
• PM10 concentration in typical US cities
• 10 to 120 μg/m3
• Max 365 μg/m3 in the Utah Valley
• How is in Ukraine?

19. Shape of the mortality exposure-response
relationship and lead-lag relationships
• What does it say?
• Typically near linear or log-linear
• Three possibilities:
(1) no threshold
(2) threshold is bellow existing pollution
levels
(3) looking more linear than it really is.

20. Shape of the mortality exposure-response
relationship and lead-lag relationships
• Increased mortality occurred concurrently
or within 1-5 days following an increase in
air pollution.

21. Acute Morbidity
Hospital usage
• What happened in the Utah Valley during the
winter of 1986-1987?
• A labor dispute resulted in the closure of the
local steel mill, the largest single source of
particulate emission.
• This winter PM10 ave. 51 μg/m3 , max. 113
μg/m3
• Previous year ave. 90 μg/m3 , max 365 μg/m3
• Children hospital admission for respiratory
disease dropped 50 percent.

22. Acute Morbidity
Hospital usage
• What was the argument by Lamm et al.
(1994)?
• Not closure of the steel mill, but
Respiratory Syncytial Virus (RSV)
• What was the argument by Pope (1991)?
• Not by the virus.

24. Acute Morbidity
Hospital usage
• What is the exposure-response of the
hospital admission of all respiratory
diseases?
• 0.8 – 3.4 % increase per 10 μg/m3 by
PM10
• 8 x 10-4 – 3.4 x 10-3 Cases/ μg/m3 by
PM10

25. Acute Morbidity
Hospital usage
• Emergency department visit % increase by
10 μg/m3 increase of PM10
• 0.5 – 3.4 (ave. 1.0) % increase/ 10 μg/m3

26. Exacerbation of asthma
Respiratory symptoms
• Asthma, Bronchodilator
• Cough

28. Exacerbation of asthma
• What is the exposure-response relation of
asthmatic attack?
• 3 % increase in asthmatic attacks with 10 μg/m3
increase of PM10
• 3 x 10-3 cases/ μg/m3
• What is the exposure-response relation of
bronchodilator use?
• 1.1 – 12 % (ave. 3.0) increase with 10 μg/m3
increase of PM10
• 3.0 x 10-3 cases/ μg/m3

29. Respiratory symptoms
• Lower Respiratory symptoms
– Wheezing, dry cough, phlegm, shortness of breath, chest
discomfort/pain
• What is the exposure-response relation of lower
respiratory symptoms?
• Ave. 3.0 % increase in lower respiratory symptoms with
10 μg/m3 increase of PM10
• 3.0 x 10-3 cases/ μg/m3
• Upper Respiratory symptoms
– Runny nose, stuffy nose, sinusitis, sore throat, wet cough,
head cold, hay fever, red eyes
• Statistically insignificant association observed.

30. Key words
• Pneumonia
• COPD: chronic obstructive pulmonary
(lung) disease
• Coronary Artery Disease
• Disrythmias (such as slow heart rate)
• Congestive Heart Failure

31. Lung function
• FEV: forced expiratory volume (a measure
of lung function)
• FVC: forced vital capacity
• PEF: Peak expiratory flow

33. Epidemiology of Chronic Health
Effects
• Table of contents
- Introduction
- Mortality Studies
- Population-based (ecologic) mortality studies
- Research needs for improved study designs
- Prospective Cohort Mortality Studies
- Harvard six-cities study
- Implication of prospective cohort mortality results
- Chronic Health Effects; Morbidity
- Chronic differences in lung function
- Chronic respiratory symptoms and disease

34. Introduction
• What is the difference between the acute effects
and the chronic effects?
• Acute: associated with short term (day to day
change)
• Chronic = long-term: a long time + cumulative
effects of repeated exposure
• If acute effect exists, is there also chronic effect
by the same pollutant?
• Not automatically

36. Mortality Studies
Population-based mortality studies
• What is the summary of the population-based cross-
sectional study?
• Average mortality is higher in cities with higher fine
particulate and sulfate particulates.
• How the other risks were controlled?
• Smoking rate, education levels, income levels, poverty
rates, housing density, etc were included in the
regression models.
• What is the coefficients of air pollution related mortality?
• About 3 % per 10 μg/m3
• 4 x 10-3 per μg/m3

38. What are limitations of Population-
based Studies?
• Systematic and/or analytical bias
– Study designs
– Data sets
– Analytic techniques
– Regression analysis
– Hypothesis testing
– Controlling some other factors
• Size of the estimated association
– Comparison with the current pollution level to the chronic
mortality is not appropriate,
– Because now the pollution level is lower than years ago.
• Cannot control for individual differences in cigarette
smoking, and other risk factors.

39. What are limitations of Population-
based Studies?
• Age, poverty, health care, occupations,
cigarette smoking, housing quality,
cooking fuels vary among cities and
potentially could be confounding the
apparent air pollution associations.

40. Improved study designs
• What are 2 important issues 1970s –
1980s
• Threshold
• Study design – what evidence needed?
• If threshold, what will become easier?
• To establish the acceptable goal for
pollution control

41. Prospective Cohort Mortality
Studies
• 3 cohort mortality studies
• With improved study design

42. Prospective Cohort Mortality
Studies
• Not on the data available for the
population as a whole,
• But, it analyzes the incidence of health
effects in a sample of individuals.
• Negative aspect:
• It relies on community-based air pollution
monitoring.
• Costly and time-consuming

43. Harvard six-cities study
• 14-16 follow up of 8,111 adults living in 6 cities of the US
• TSP, PM10, PM2.5, SO4, H+, SO2, NO2 and O3 levels were
monitored.
• What is most strongly associated with mortality risk?
• Smoking
• But, after controlling for individual differences (age, sex,
smoking, body mass, education, occupational exposure),
• Differences in relative mortality risks across 6 cities were
strongly associated with difference in pollution levels in
those cities.
• PM10, PM2.5, SO4 than TSP and SO2, H+, or ozone.

45. Shape of the figure
• Mortality risk and fine particulate
• Nearly linear
• No threshold

46. Implications of prospective cohort
mortality results
• The increased risk from air pollution bigger
or smaller than cigarette smoking?
• Small
• But, there is a correlation.

48. Summary
• Mortality
• Acute exposure Total 0.5-1.5 %/10μg/m3
• 5 x 10-4 – 1.5 x 10-3 (cases/μg/m3)
• Chronic exposure 3 – 9 %/10μg/m3
• 3 x 10-3 – 9 x 10-3 (cases/μg/m3)

49. Exposure-Response Function f(r,C(r,Q)) PM10 and Nitrates
Health impact cases/(year.person.μg/m3)
Long-term Mortality 2.60E-4
Chronic Bronchitis 7.65E-5
Restricted Activity Days 5.0E-2
Work Days Lost 1.0E-2
Hospital Admissions
Cardiovascular, Respiratory 6.00E-5, 2.56E-6
Asthmatic adults
Bronchodilator 6.00E-2
Lower respiratory symptoms 1.63E-1
Infant Mortality 2.78E-5
Asthmatic children
Cardiovascular, Respiratory
7.8E-2, 1.0E-1

50. f(r,C(r,Q)) SO2
Health impact cases/(year.person.μg/m3)
Short-term Mortality 2.30E-6
Hospital Admissions
Admissions 2.84E-6
Source: Rabl 2001

51. Plant
Trypilska Power Station

52. Trypilska Power Station, Emissions
in 2006
Name of the pollutant Emissions, tons/year
Total 74 605.000
Metals and their compounds 22.087
Total suspended particles 21 951.116
(TSP): PM10 10 975.560
Nitrogen compounds 11 108.921
Sulfur oxide and other sulfur 40 909.568
compound
Carbon oxide 564.363

53. Technical characteristics of the
Trypilska Power Station
Parameters Value of the parameters
Stack height, m 180
Effective release height, 700
m (because of hot air and gas
flow)
Diameter of the stack, m 9.6
Flow rate from the stack,
14
m/s
Released gas
413
temperature, K

54. Cities around the Trypilska power
plant
Name of the Population, persons Down wind distance, Prevailed down
city km wind direction
Uzyn 26,434 42,500 SSW, SW
Obukhiv 32,776 9,500 WSW
Vasylkiv 39,722 30,750 W
Boyarka 35,968 37,500 WNW
Vyshneve 34,465 37,500 NW
Kyiv 2,611,327 36,250 NNW
Brovary 86,839 29,500 N
Boryspil 107,950 28,250 NE,ENE
Rzhyschiv 8,447 29,250 SE
Kagarlyk 13,757 32,250 SE
Note: The down wind distances were measured from the Power Station to the centers of the cities

55. Concentration of the pollution(μg/m3)
C(x,Q): Gaussian Plume Model
Q - h2
C = ---------------- exp [--------]
21/2 π3/2 uxσz 2σz2

56. Some hints for Excel
•=SQRT(3.14, 3)
•=EXP(-h**2/2*Sigmaz**2)
•=POWER(A1;2)
•Q in micro gram/sec
Q - h2
C = ---------------- exp [--------]
21/2 π3/2 uxσz 2σz2

57. σz

58. Atmospheric Stability
Day Night
Surface Wind Incoming Solar Radiation Thinly Heavy
Speed Overcast Cloud
(meter/second Strong Moderate Slight or clear
) sky
<2 A A-B B
2-3 A-B B C E F
3-5 B B-C C D E
5-6 C C-D D D D
>6 C D D D D

59. Weather observation
Day Wind Speed Wind Direction Atmospheric Stability(A,
(meter/second) E, ESE, SSE, S….. B… .F)
Aug 7 1800
1900
2000
2100
2200
2300
2400
Aug 8 0600
0700
0800
0900
2100
0900

61. Unit cost Uv for
Long-term Mortality
Value of 1 YOLL = v = constant
v v v
Uv = v + ---- + ----- + ……+ -----
1+r (1+r)2 (1+r)N
r = discount rate of one year
N = years of human life

62. Exposure-Response
• PM10 long-term mortality
• 2,60 × 10 -4 μg/m3
• (Leksell & Rabl, 2001)

63. Examples of externality studies

64. Summary of Cost Estimates in mECU/kWh
Canada France Germany
Pub. Occ. En G Pu Occ Env. Gw Pub Oc Env. G
v. w. b. . . . c. w.
Coal 2.3 nq 53 nq 0.5 29 8.4
Lignite 10.5
Oil 69 nq 0.7 16 16.5
Natural 12 nq 0.1 8 3.0
Gas
Nuclea 0.01- 2.5 0.07 0 0 3.8
r 0.05
Wind 0.2
Hydro
Photo 2.7
Voltaic
Pub. public impacts
Occ. occupational impacts
Env. Environmental (buildings, crops, ecosystems,…), excluding global warming
Gw. Global warming
nr not reported
nq not quantified

65. Summary of Cost Estimates in mECU/kWh (continued)
Greece US Russia
Pub. Occ. Env. Gw Pub Occ En G Pu Occ Env Gw.
. . . v. w. b. . .
Coal 0.52 nr
1.1
Lignite 20 0.30 0.66 38
Oil 10 0.17 0.95 21 0.15 nr
0.21
Natural 2.4 0.17 0.66 5.8 0.01 nr
Gas 1
Nuclea 0.17 0.4
r 0.26 -4
Wind 0.84 0.09 1.2 0.2
Hydro 1.2 3.8 0 0.14
Photo
Voltaic
Pub. public impacts
Occ. occupational impacts
Env. Environmental (buildings, crops, ecosystems,…), excluding global warming
Gw. Global warming
nr not reported
nq not quantified

66. Germany 1997
Damages of fossil fuel cycles

68. Damages of nuclear fuel cycle

69. External costs of PV cycle

70. External costs of wind fuel cycle

71. Damages of biomass fuel cycle

72. Biomass 2

73. Biomass 3

74. External costs for electricity production in
the EU (in EUR-cent per kWh) 2002
AUT: Austria, BE: Belgium, DE: Germany, DK: Denmark, ES: Spain ,
FI: Finland, FR: France, GR: Greece, IE: Ireland, IT: Italy, NL: Norway,
NO: Netherlands, PT: Portugal, SE: Sweden, UK: United Kingdom

75. Monetary values used for
economic valuation

78. Results of the coal fuel cycle
before NewExt [€-Cent/kWh]

79. Results of the oil fuel cycle
before NewExt [€-Cent/kWh]

80. Results of the gas fuel cycle
before NewExt [€-Cent/kWh]

81. • DENOX NOx removal system
• FGD Flue Gas Desulfurization
• SCR Selective catalytic reduction