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External cost of electricity generation
               systems


               Y. Matsuki, D.Sc.
           Professor, Department of
        Mathematical Method for System
         Analysis, IASA, NTUU “KPI”
               August 10, 2010
How can you calculate the externalities?
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)
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
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
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?
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?
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.
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
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
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.
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
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
Mortality by respiratory disease and
      cardiovascular disease
• Large effect on respiratory disease
  mortality
• Also cardiovascular disease causing death
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?
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.
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.
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.
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.
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
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
Exacerbation of asthma
       Respiratory symptoms
• Asthma, Bronchodilator
• Cough
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
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.
Key words
• Pneumonia
• COPD: chronic obstructive pulmonary
  (lung) disease
• Coronary Artery Disease
• Disrythmias (such as slow heart rate)
• Congestive Heart Failure
Lung function

• FEV: forced expiratory volume (a measure
  of lung function)
• FVC: forced vital capacity
• PEF: Peak expiratory flow
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
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
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
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.
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.
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
Prospective Cohort Mortality
              Studies
• 3 cohort mortality studies
• With improved study design
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
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.
Shape of the figure

• Mortality risk and fine particulate
• Nearly linear
• No threshold
Implications of prospective cohort
           mortality results
• The increased risk from air pollution bigger
  or smaller than cigarette smoking?
• Small
• But, there is a correlation.
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)
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
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
Plant
Trypilska Power Station
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
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
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
Concentration of the pollution(μg/m3)
  C(x,Q): Gaussian Plume Model
          Q               - h2
C = ---------------- exp [--------]
   21/2 π3/2 uxσz            2σz2
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
σz
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
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
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
Exposure-Response
• PM10 long-term mortality
• 2,60 × 10 -4 μg/m3



• (Leksell & Rabl, 2001)
Examples of externality studies
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
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
Germany 1997
Damages of fossil fuel cycles
Damages of nuclear fuel cycle
External costs of PV cycle
External costs of wind fuel cycle
Damages of biomass fuel cycle
Biomass 2
Biomass 3
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
Monetary values used for
  economic valuation
Results of the coal fuel cycle
before NewExt [€-Cent/kWh]
Results of the oil fuel cycle
before NewExt [€-Cent/kWh]
Results of the gas fuel cycle
before NewExt [€-Cent/kWh]
• DENOX NOx removal system
• FGD Flue Gas Desulfurization
• SCR Selective catalytic reduction

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External Cost of Electricity Generation Systems (2)

  • 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
  • 11.
  • 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.
  • 13.
  • 14.
  • 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.
  • 23.
  • 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
  • 27.
  • 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
  • 32.
  • 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
  • 35.
  • 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
  • 37.
  • 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.
  • 44.
  • 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.
  • 47.
  • 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
  • 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
  • 60.
  • 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)
  • 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
  • 67.
  • 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
  • 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
  • 76.
  • 77.
  • 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