Gdansk University of Technology Faculty of Chemistry Environmental Pollution and Human Welfare Jozef M. Pacyna Center for Ecological Economics Norwegian Institute for Air Research, Kjeller, Norway
Gdansk University of TechnologyFaculty of Chemistry
Environmental Pollution and Human Welfare
Jozef M. PacynaCenter for Ecological Economics
Norwegian Institute for Air Research, Kjeller, Norway
E3ME: Energy-Environment-Economy Interactions
E3ME: Energy-Environment-Economy Interactions
ECONOMYas in national
accounts
TECHNOLOGYspecifications &
costs
ENVIRONMENTALEMISSIONS
as in environmentalstatistics
ENERGYas in energy
statistics
damage to health and buildings, productivity effects
e.g. industrial emissions of SF6
funding R&D
pricesandactivity
low-carbonprocesses &products
feedback
energy-savingequipment etc
fuel use
pollution-abatementequipment
Human Capital EconomicProductionProcess
GoodsandServices
EvolvingCulturalNorms andPolicy
Well Being(Individual andCommunity)
Consumption
Education, training,
research.
Building
Investment
GNP
Wastes
Ecologicalservices/amenities
negative impacts on all forms of capital
Restoration,
ConservationNatural Capital
ManufacturedCapital
positive impacts on human capital capacity
SolarEnergy
SocialCapital
p g y
Waste heat
Institutional
rules, norms, etc.
Expanded Model of the Ecological Economic System
Materially closed earth system
Summary of the capitalism system
Economic progress can best occur in free market systems of production and distribution where reinvested profits make labor and capital increasingly productive
Competitive advantage is gained when bigger, more efficient plants manufacture more products for sale to expanding market
Growth in total output (GDP) at least maximizes human well-being
N:\adm\arkiv\overhead\2006\CEE\Yale-2.ppt 4
Summary of the capitalism system, cont.
Any resource shortages that do occur may elicit the development of substitutes
Concerns for a healthy environment are important but must be balanced against requirements of economic growth, if high standard of well-being is to be maintained
Free enterprise and market forces will allocate people and resources to their highest and best uses
N:\adm\arkiv\overhead\2006\CEE\Yale-2.ppt 5
Summary of natural capitalism system
The environment is not a minor factor of production but a vehicle for the entire economy
The limiting factor to future economic development is the availability and functionality of natural capital, e.g. life supporting services with no market value
Misconceived or badly designed business systems, population growth, and consumption patterns are the primary causes of the loss of natural capital
N:\adm\arkiv\overhead\2006\CEE\Yale-2.ppt 6
Summary of natural capitalism systemCont.
Future economic progress can best take place in democratic market based on systems of production and distribution in which all forms of capital are fully valued
Radical increases in resource productivity are the key to the most beneficial employment of people, money, and environment
Human welfare is best served by improving the quality and flow of desired services delivered rather than merely increasing in the total dollar flow
N:\adm\arkiv\overhead\2006\CEE\Yale-2.ppt 7
Extraction
Processing
Distribution
Storage
MediaAir
Soil
Water
Food
Gases
Solids
Chemicals/ solutes
Energy
Indoor
Ambient
Occupational
Agents
Emission
Corrosion/ corasion
Discharge
Leakage
Dumping
Inhalation
Dermal contact
Ingestion
Settings
Exposures
Transport
Diffusion
Mass transfer
Health outcomes
Sub-clinical
Morbidity
Mortality
Vulnerability
Age
Gender
Pre-existing health
Lifestyle
Healthcare
POLICY
DALYs/ QALYs
Costs/ Benefits
Perception
Impacts
Equity
Goals
Aversions
Entitlements
Values
Europe:The Full Chain Approach to IA
From: INTARESE, www.intarese.org
IMPORT/EXPORT
ORE ENVIRONMENT
PROCESS-ING
FABRICA-TION
USE WASTEMGT.
IMPORT/EXPORT
ORE ENVIRONMENT
PROCESS-ING
FABRICA-TION
USE DISCARDMGT.
STAF Project© Yale University 2004
Japan Copper cycle: One Year Stocks and Flows, ca.1994
System Boundary Japan
280
New Scrap
18 Slag
Cathode
0.3
Tailings
2
Concentrate
1100
Blister1
1200
80
34
120
Ore
Semis,finished Products500Prod. Cu
950
120Old
Scrap
200
Old Scrap
LandfilledWaste,
Dissipated
180
Discards
500Prod. Alloy
240
Cathode170
NewScrap,Ingots
1805216
ProductionMill, Smelter,Refinery 7
Stock
Use
Stock
700
Lith. -2 Environment +200
Fabrication &Manufacturing
WasteManagement
Import/Export -830
© STAF Project, Yale University Units: Gg/yr
The Engineering Metals and the STAF Project
at Yale
The Engineering Metals and the STAF Project
at YaleH
Na
Li
K
Rb
Cs
(119)
Fr
Be
Mg
Y
La
Ca Sc
Sr
Ba
Ra
Hf
Zr
Ac
Ta
Rf Db
Nb
V Cr
Mo
W
Sg
BrNiFe
Al
Ga
In
Tl
C
Hg
Cd
ZnCu
Ag
Au Bi
Cl
Sb
As
P
NB
Si
Ge
Sn
Pb
Ne
Ar
F
I
At
He
Po
Te
Se
S
O
Th
PrCe
Rn
Xe
Kr
Cm
Gd
Pa Am
Eu
Pu
Sm
Np
Pm
U
Nd Tb Dy Ho
Cf Es
Er Tm
Fm Md No
Yb Lu
LrBk
(120) (121)
114 116111 112 118(115)(113) (117)Bh
Ti Mn
Tc
Re
Hs
Ru
Os
Co
Rh
Ir
Mt
Pt
Pd
110
Al
Stationary fossil fuel combustion
Vehicular traffic
Non-ferrous metal production
Iron and steel production
Cement production
Waste disposal
Other
As(5 011 tonnes)
Cd(2 983 tonnes)
Hg(2 235 tonnes)
Pb(119 259 tonnes)
Worldwide emissions of trace metals from majoranthropogenic source categories to the
Atmosphere in the mid 1990's
>100 200
330 1101500
1340
120 40
1300
1000
AF
AF
Ores and Other Nonfuel Mineral Resources
(Mercury, Gold, Zinc, Nickel, Tin, Copper, Silver, Lead, Iron,
Limestone, etc.)
VL
RetiremenTby Humans
(Warehouse, Landfill, or Deep Bedrock
Repository)
Product Use (Homes,
Businesses, Agriculture,
Medical, Dental)
Disposal ofProducts, Wastes
MV*
DA*
SV*
RS*
RXT*
OM*
DXT*
MP*
MD*
PD*
DR*
RM
SedimentBurial
(Oceans, Lakes,
River Deltas)
AXB
Geological Mercury Naturally
Available to Volatilize
XGV
Land storage 1000000
Increases 0.2% per year
LA
PV
XOO
Small-scale Gold
Mining
XCC*
PH
SH*
MH*
CV*
XO XTXG XB
OV*
OS*
SA*
DV*
OA* Recycling of MercuryXCXT*
CXT*
FH*FW
FH*FW
FH*FW
Coal + Other Fossil
Fuel Deposits
(Oil and Gas)
XC
Coal+Other Fossil Fuel Combustion
300
830
LV3500 1600
1700
Aquatic Systems
680
Ocean Storage288000
increases 0.2%per year
Land
Mercury Vapor in the
Atmosphere
Atmosphere Storage5000
Increases less than 2% per year
200
Fish
3100 2600VA AV
FH*FW
Humans Wildlife
~2200
Important Global Pathways of Mercury in Commerce and the Environment
Important Global Pathways of Mercury in Commerce and the Environment
2400 = total anthropogenic emissions
700
500
500
500
>2500
1600
1200
AF
OreRefining Manufacturing
For each source category and compound of interest:
E.g national statisticsNational reported
or estimatedHandbooks,Publications,
Other inventories
Lack of historic dataAvailability
Unknown sources
Abatement technologies,
spatial and temporal considerations
Uncertainty assessment
Fit?
Activity * Emission Factor = Emissions
Basic emission inventory methodology
WP 03 - database on emission reduction measures, potential and costs (2)
WP 03 - database on emission reduction measures, potential and costs (2)
Mercury emission projection for three scenariosaccording to contribution of particular emission sources
Other Sources
Cement Production
Chlorine Production
Energy Generation
Other Sources
Cement Production
Chlorine Production
Energy Generation
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for BAU Scenario
0
50
100
150
200
250
300
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for POT Scenario
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for DEG Scenario
0
50
100
150
200
250
300
0
50
100
150
200
250
300
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for BAU Scenario
0
50
100
150
200
250
300
0
50
100
150
200
250
300
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for POT Scenario
Hg
Emis
sion
[Mg/
a]
2005 2010 2020Year
Mercury Emission Projection for DEG Scenario
0
50
100
150
200
250
300
0
50
100
150
200
250
300
0
50
100
150
200
250
300
0
50
100
150
200
250
300
Total mercury emission according to the POT scenario in the year 2020
Global transport modellingGlobal transport modellingMonthly average elemental mercury surface concentrations (ng/m3)
GRAHM (Global/Regional Atmospheric Heavy Metals Model) simulation – Ashu Dastoor, Meteorological Service of Canada,
Environment Canada
Mercury deposition in the NH
МСЦ-В
MSC-E
Total annual mercury deposition density
Contribution of sources other than U.S. anthropogenic sources to Hg depositionContribution of sources other than U.S. anthropogenic sources to Hg deposition
AER/EPRI Modeling System for Atmospheric MercuryChristian Seigneur
Resulting concentrations for PCDD/Fs
Air Deposition Top soil concentration Ocean concentrationColor scale:0-22000 fg TEQ/m3
Color scale:0-22000 mg TEQ/km3/a
Color scale:0-1400 fg TEQ/g
Color scale:0-10 fg TEQ/l
Top soil:Upper 5 cm.
Concentrations for the base year 2000
Base year 2000
1510.34 fg TEQ/m3
BAU 2010
1035.29 fg TEQ/m3
MFTR 2010
812.78 fg TEQ/m3
Color scale always covering 0 – 10000 fg TEQ/m3
Air concentration for all DROPS scenarios (1)
Base year 2000
1510.34 fg TEQ/m3
BAU 2020
826.98 fg TEQ/m3
MFTR 2010
582.77 fg TEQ/m3
Color scale always covering 0 – 10000 fg TEQ/m3
Air concentration for all DROPS scenarios (2)
AQ Nowcast and ForecastAQ Nowcast and Forecast
Exposure AssessmentExposure Assessment
Links population datato concentration fieldsLinks population datato concentration fields Exposure hours
Number of hours a number of people is exposed to pollution over a selected value
Person doseAccumulated exposure of pollution over a selected value per person
Population LoadAccumulated exposure of pollution over a selected value for all persons within a grid square/receptor point
Extraction
Processing
Distribution
Storage
MediaAir
Soil
Water
Food
Gases
Solids
Chemicals/ solutes
Energy
Indoor
Ambient
Occupational
Agents
Emission
Corrosion/ corasion
Discharge
Leakage
Dumping
Inhalation
Dermal contact
Ingestion
Settings
Exposures
Transport
Diffusion
Mass transfer
Health outcomes
Sub-clinical
Morbidity
Mortality
Vulnerability
Age
Gender
Pre-existing health
Lifestyle
Healthcare
POLICY
DALYs/ QALYs
Costs/ Benefits
Perception
Impacts
Equity
Goals
Aversions
Entitlements
Values
Europe:The Full Chain Approach to IA
From: INTARESE, www.intarese.org
Contaminant Mas BalanceContaminant Mas Balance
agriculturalagriculturalsoilsoil
forestforestsoilsoil
forestforestcanopycanopy
fresh waterfresh water
coastalcoastalsedimentsediment
coastalcoastalwaterwater
open open waterwater
bottombottomwaterwater
bottombottomsedimentsediment
atmosphere
interphase transferdirect emissiondegradation lossadvection with air and water
Terrestrial Environment Marine Environment
fresh water sedimentfresh water sediment
Technology drivers for emission changesdue to changes in EFs
Base year 2000
BAU+Climate 2010
BAU-Climate 2010
MTFR 2010
Control MeasuresDatabase
Base year 2000Implementation
Future MeasureImplementation
harmoniseactivities and EFs
expert judgement
regulations for sourcesand/or technologies
all available relevantmeasures (EF, Costs, etc.)
OMEGA-HMOptimisation Model
emissions
activities
BAU measure
implementation
• additional emission reduction (between BAU+Climate and MTFR)
• additional costs of abatement• lists of measures implemented (i.e. increased
impl. degree or added measure in uncontrolledsources)
• resulting changes in concentrations/deposition• ...
MSC-E HM Model WATSON
SR-Matrices
depositionTrend Projection (PRIMES, etc.)Drivers for changes in emissions
due to activity changesTemp/SpatialResolution
Directives, Treatiesetc. Meta-data
(AND, XOR, ...)
ESPREMEIllustrated Model-Data-Flows
Sources Emissions into Air Emissions into Soil / Water
Fate
Mod
ellin
g
Boundary LayerAir Model
ExposureModel
Humans
Trade
FishFarm animalsCrops
WATSON: Approach
Impacts +Valuation
Soil / WaterModel
Soilsof different use
Freshwaters
Sediment
Emission
module
Environmental fate
modellingExposure modelling
including trade
Atmospheric dispersion and
inhalation module
Costs benefit
analysis module
Optimisation on
reduction options
OMEGA-HM and WATSON
WATSON
DB on activities and emission reduction options
DB on exposure response functions
Damages due to
inhalation
MSC-East data on atmospheric dispersion
Deposition into
water and soil
Damages due to
ingestion
OMEGA
Table 2.1: Accumulated exposure of selected HMs and POPs due toinhalation for all considered DROPS scenarios
Pollutant 2000 BAU 2010 BAU 2020 MFTR 2010 MFTR 2020
Inha
latio
n [u
g/m
3 ]
As 707,000 631,000 568,000 575,000 517,000
Cd 316,000 241,000 161,000 188,000 118,000
Hg 1,190,000 1,150,000 1,120,000 1,120,000 1,100,000
Ni 2,910,000 2,280,000 1,360,000 1,760,000 1,020,000
Pb 8,110,000 6,190,000 5,390,000 5,410,000 4,690,000
PCBs 50,800 23,100 15,400 16,300 3,040
PCDDs 2.27 1.69 1.43 1.29 0.97
Figure 2.1: Comparison of European emissions (a) and accumulatedexposures via the inhalation pathway (b)
Emissions for different scenarios
0
0.2
0.4
0.6
0.8
1
As Cd Hg Ni Pb PCBs PCDDFs
2000
BAU_2010
BAU_2020
MFTR_2010
MFTR_2020
Accumulated exposure for different scenarios
0
0.2
0.4
0.6
0.8
1
As Cd Hg Ni Pb PCBs PCDDFs
2000
BAU 2010
BAU 2020
MFTR 2010
MFTR 2020
Table 2.2:Sum of anthropogenic and natural direct and indirect releases into the media air, water and soil [t/year] as considered for the ingestion pathway
Pollutant 2000 BAU 2010 BAU 2020 MFTR 2010 MFTR 2020
As 108,736 108,574 108,427 108,415 108,270
Cd 1,396 1,261 1,145 1,116 1,005
Cr 18,636 18,257 17,742 15,925 15,925
Ni 11,309 10,266 9,284 8,660 7,987
Pb 24,530 20,030 18,280 18,527 16,917
PCBs 41.07 20.54 12.24 12.71 2.24
PCDDs 0.0049 0.0036 0.0030 0.0025 0.0017
Figure 2.2:Apportionment of emissions into air, water and soil as relevant for the ingestionpathway (BAU 2010 scenario); note the logarithmic scale
Emissions into different media [t/yr] as relevant for ingestion for BAU 2010
1
10
100
1,000
10,000
100,000
As Cd Cr Ni Pb
air (anthropogenic)
air (natural)
soil (arable land)
soil (pasture/grassl.)
w ater (direct)
w ater (indirect)
Table 2.3:Declining discount rate scheme suggested by Weitzmann (1999) and used withinWATSON for human health damages via ingestion
Time Horizon [years] Discount rates suggested by Weitzmann (1999)
0-25 ‘low-normal’ real annual interest rate of around 3-4%
25-75 within-period instantaneous interest rate of around 2%
75-300 within-period instantaneous interest rate of around 1%
> 300 within-period instantaneous interest rate of around 0%
Table 2.4:Approach of calculating different discount factors for different time periodsaccording to Weitzmann (1999)
Equation for calculating the discount factor Wt
Equation is valid for the time period t
1(1 0.035)t tW
for: 0 25t
25 25
1 1(1 0.035) (1 0.02)t tW
for: 25 75t
25 50 75
1 1 1(1 0.035) (1 0.02) (1 0.01)t tW
for: 75 300t
25 50 225
1 1 1 1(1 0.035) (1 0.02) (1 0.01)tW
for: 300t
Table 2.5:Accumulated exposure of selected HMs and POPs due to ingestion of different fooditems for all considered DROPS scenarios
Pollutant 2000 BAU 2010 BAU 2020 MFTR 2010 MFTR 2020
Inge
stio
n, fo
od [k
g]
As 35 33 31 31 29
Cd 24,008 22,579 21,067 21,567 20,279
Cr 2,315 2,274 2,163 2,250 2,163
Ni 202,348 185,023 159,677 170,209 150,381
Pb 207,229 189,189 181,080 181,581 174,303
PCBs 194 97 58 60 11
PCDDs 0.0009 0.0007 0.0006 0.0005 0.0003
Table 2.6:Accumulated exposure of selected HMs and POPs due to ingestion of drinking waterfor all considered DROPS scenarios
Pollutant 2000 BAU 2010 BAU 2020 MFTR 2010 MFTR 2020
Inge
stio
n, w
ater
[kg]
As 12 11 10 10 9
Cd 363 305 245 265 212
Cr 2,024 1,951 1,593 1,872 1,593
Ni 3,049 2,621 2,016 2,269 1,801
Pb 4,457 3,513 3,147 3,148 2,824
PCBs 4.49E-04 2.24E-04 1.34E-04 1.39E-04 2.45E-05
PCDDs 2.24E-10 1.66E-10 1.38E-10 1.16E-10 7.86E-11
Figure 2.3: Comparison of the accumulated exposure via the ingestion ofdifferent food items (a) and the ingestion of drinking water (b)
Accumulated exposure via food ingestion for different scenarios
0
0.2
0.4
0.6
0.8
1
As Cd Cr Ni Pb PCBs PCDDFs
2000
BAU 2010
BAU 2020
MFTR 2010
MFTR 2020
Accumulated exposure via water ingestion for different scenarios
0
0.2
0.4
0.6
0.8
1
As Cd Cr Ni Pb PCBs PCDDFs
2000
BAU 2010
BAU 2020
MFTR 2010
MFTR 2020
Figure 2.4:Fraction of different food items and drinking water to the overall accumulatedexposure due to the ingestion pathway (BAU 2010 scenario)
Fraction of food and water to the overall acccumulated exposure for BAU 2010
>99%>99%98.2%98.6%53.8%98.7%75.6%
<1%<1%1.8%1.4%46.2%1.3%24.4%
0%
20%
40%
60%
80%
100%
As Cd Cr Ni Pb PCBs PCDDs
food w ater
Figure 2.5:Comparison between different discounting schemes for the accumulated exposurevia ingestion of lead (a) and arsenic (b) in Germany (BAU 2010 scenario)
Accumulated exposure of Pb [kg] via ingestion in DE over 500 years
0
0.05
0.1
0.15
0.2
0 50 100 150 200 250 300 350 400 450 500
Accumulated exposure of As [g] via ingestion in DE over 500 years
0
0.1
0.2
0.3
0.4
0.5
0.6
0 50 100 150 200 250 300 350 400 450 500
0% constant discount rate3% constant discount rateWeitzmann discounting scheme
Table 3.1:Marginal accumulated exposure in Europe due to 1 additional ton of emission inselected countries
Pollutant Czech Rep. Germany Poland Norway
ug/m
3 *ca
pita
per
t
As 395 796 391 69
Cd 438 861 430 78
Hg 660 957 579 232
Ni 434 849 430 74
Pb 538 992 529 97
PCBs 841 2,486 5,151 3,560
PCDDs 516 347 511 213
Table 3.2:Marginal accumulated discounted exposure after 500 years [g] in Europe due to 1additional ton of emission of selected heavy metal in selected countries for threeapplied discount rates (0%, 3% constant discount rate, Weitzmann discountingscheme according to Weitzmann (1999))
PollutantCzech Republic Germany
0% 3% Weitzmann 0% 3% Weitzmann
As 4.39 2.39 2.47 19.34 10.87 11.22
Cd 2,051.63 936.43 996.30 6,281.31 2,980.04 3,149.38
Pb 196.11 20.96 30.71 615.44 65.03 93.35
PollutantPoland Norway
0% 3% Weitzmann 0% 3% Weitzmann
As 10.02 5.29 5.50 0.80 0.46 0.47
Cd 4,828.38 2,204.94 2,345.63 482.59 229.43 242.31
Pb 459.13 47.65 69.53 50.62 4.49 7.98
Extraction
Processing
Distribution
Storage
MediaAir
Soil
Water
Food
Gases
Solids
Chemicals/ solutes
Energy
Indoor
Ambient
Occupational
Agents
Emission
Corrosion/ corasion
Discharge
Leakage
Dumping
Inhalation
Dermal contact
Ingestion
Settings
Exposures
Transport
Diffusion
Mass transfer
Health outcomes
Sub-clinical
Morbidity
Mortality
Vulnerability
Age
Gender
Pre-existing health
Lifestyle
Healthcare
POLICY
DALYs/ QALYs
Costs/ Benefits
Perception
Impacts
Equity
Goals
Aversions
Entitlements
Values
Europe:The Full Chain Approach to IA
From: INTARESE, www.intarese.org
Exposure-response functions for heavy metals
Exposure time is the number of years of exposure that are needed, to cause the increase of risk for some health endpoint.Population group denotes the part of the population, the absolute risk factor refers to.
Health end-pointsHealth end-points
Ozone, PM10 (increase in concentration)
Mortality Respiratory hospital
admissions Consultations for
allergic rhinitisMinor RAD (reduced
activity days) Bronchodilator use Cough Lower respiratory
symptoms
Carcinogens: unit risk factor, percent fatal
inhalation (Benzene, Formaldehyde, Inorganic As, Cd, CrVI, Ni, PCB)
water (Inorganic As, PCB)
food (Inorganic As, PCB, dioxins)
Neurotoxicants, ingestion including water – IQ points lost due to avg. ingestion 1 microg/day (Pb, methyl-Hg)
Damage/benefit-based methods welfare measurement neoclassical economics welfare economics
Cost-based methods Avoidance costs or Restoration costs
Valuation of Health Benefits mortality (acute or chronic) morbidity (acute or chronic) dis-welfare associated with a quality of life (IQ decrement,
learning behaviour and mental dvlp., nervous system…)
Putting monetary values onnon-market goods
CBA: cost-benefit analysis: based on monetary valuation
MCA: multicriteria analysis: based on non-monetary valuation to provide information for CEA (cost efficiency of a given policy)
What is the Life worth of?Approaches for estimation of
benefits of policy interventions
Revealed-preferences techniques: e.g. Hedonic method (goods are characterized by a set of attributes and utility comes from the value of each attribute)
Cost of Illness (COI)
Stated-preferences techniques: e.g. Contingent valuation method (CVM) based on information on max WTP to compensate for variation of well-being
What is the Life worth of?Monetary valuation
QALY: Quality-Adjusted Life Years; death is scored as 0 while good health as 1; presented often in Euro/QALY
DALY: Disability-Adjusted Life Years: time spent at different ages and with different level of disability; presented in Euro/DALY
What is the Life worth of?Non-economic valuation
estimate a welfare change due to a decrease or avoided mortality risks by deriving willingness-to-pay(compensating or equivalent surplus)
supported by the economic theory
Value of a Statistical Life (VSL)
Value of Life Year (VOLY)
Years of Life Lost (YOLL)
What is the Life worth?
Type of risk being valued Unit
VSL, in mil.€
mean median
CZECH REPUBLIC- by exchange rate- (1:1000 / 5:1000)
Cardiovascular and respiratory causes of death
EURO (2004)
1.27(3.06 / 0.78)
0.58(1.92 / 0.49)
- by PPP (purchasing powerparity)
EURO (2004) 2.86 1.32
ITALY
Cardiovascular and respiratory causes of death
EURO (2004) 3.77 0.89
USA - (1:1000)- (5:1000)
All causes of death
USD (2000)
4.831.54
1.110.70
CANADA- (1:1000)- (5:1000)
All causes of death
USD (1999)
2.520.63
0.890.34
UK-FRANCE-ITALY(NewExt Project)
All causes of death
EURO (2002) 1.05 - 2.26
Recommended VSL value
- by EC- by EPA
1.0 mil. euro6.5 mil. USD
VSL results
Assessment of health benefitsAssessment of health benefits
Identification of health end-points and review of concentration-response functions
Review of benefit valuation
Cost-of-illness: treatment costs and loss of productivity
Benefit transfer and uncertainties related to monetary valuation
Uncertainties in epidemiological data and provide guidance
Monetary valuation reviewMonetary valuation review
Impairment development: IQ decrement (loss in productivity, remedial education)
Mortality: Value of life year loss (VOLY), Costs-of-illness (before death)
Morbidity valuation: Dis-comfort, Loss in productivity, Costs-of-illness
MethodologyMethodology cost-of-illness
Direct (resource) costs i.e. medical costs paid by the health service (or covered by insurance), and any other personal out-of-pocket expenses
Indirect (opportunity) costs i.e. the cost in terms of lost productivity (work time loss, performing at less than full capacity) and the opportunity cost of leisure
diswelfare Dis-utility is not captured in COI (except for costs of pain-killers
etc.) – a WTP value is needed
endpoint population at riskChronic bronchitis 27+Respiratory hospital admission allCardiac hospital admission allConsultation with primarycare physician
- asthma 0-14; 15-64; 65+- upper respiratory diseases 0-14; 15-64; 65+Restricted activity day 15-64Work loss day 15-64Medication use /bronchodilator use
5-14 (PEACE); 20+ (asthmatics)
Lower respiratory symptoms symptomatic adults; 5-14Acute respiratory symptoms all
Table 1: Health effects related to PM exposure
Table 2: Health effects related to ozone exposure
endpoint population at risk
Respiratory hospital admission 65+
Consultation with primary carephysician
0-14; 15-64
Minor restricted activity day 18-64
Medication use /bronchodilator use
5-14 asthma
Lower respiratory symptomsexcluding cough
5-14
Cough days 5-14
Table 3: Comparison of Chronic Obstructive PulmonaryDisease (COPD) costs in different countries
Source Country Type of Study
Costs Evaluated
Cost per Patient per Year, $
Cost per patient per year, EUR (2005)
Global Cost per Year, $
Morera (1992) Spain Top down Direct and indirect 961 876
Direct: 321 million Indirect: 545 million
Hilleman et al (2000) United States Bottom up Direct
Stage I: 1 681Stage II: 5 037Stage III: 10 812
Stage I: 1 532Stage II: 4 592Stage III: 9 856
Jacobson et al (2000) Swedem Top down Direct and
indirect
Direct: 111 millionIndirect: 173 million
Wilson et al (2000) United States Top down Direct
Emphysema 1 341Chronic bronchitis 816
Emphysema 1 222Chronic bronchitis 744
14 500 million
Rutten-van Mölken et al (1999) Netherlands Top down Direct 876 799
Miravitlles et al. (2003) Spain Bottom up Direct
Stage I: 1 484Stage II: 2 047Stage III: 2 911
Stage I: 1 353Stage II: 1 866Stage III: 2 654
506 million
Table 6: WTP for 1 day avoidance of various health symptoms (in EUR2005)
Health effectsVassanadun-rongdee et al.
(2004)
Previous meta-
analyses
David 1999
Dickie et al. 1997
Loehman et al.
(1979)
Navrud 1998
Ready et al.
(2001) EU
Rowe & Chestnut (85) US
Tolley et al.
(1986)
Mild cough 33 27 76 16 13 16 36
Severe cough 45 49 37 46
Mild headache 31 25 27 22 57
Severe headache 42 43 51 28
Mild shortness of breath 33 27 10 38
Severe shortness of breath 63 83 69 43
Eyes irritation 30 22 93 22 63 40
Severe asthma attack 63 83 92 65
Throat irritation 23 24 16 42
Source: adapted from Scapecchi (2007)
Table 7: WTP for avoiding mild respiratory symptoms (in EUR)
Ready et al. (2004) studyCzech Rep.NL NOR PORT SPA UK Pooled 5
WEC
CASUALTY 193 361 279 221 197 239 59
EYES 61 46 105 79 20 52 22
HOSPITALISATION 454 428 454 643 247 462 109
BED 108 180 132 170 125 147 43
COUGH 43 55 42 58 30 41 21
STOMACH 92 39 54
Table 8: Costs of general practitioner consultation
Country Cost of GP consultation (children, in EUR) Cost of GP consultation (adults, in EUR)
Poland 8.7 8.7
Czech Republic 4.2 3.5
Western Europe 44 44
Table 9: Labour productivity per effective working day (in EUR2005)
CountryLabour productivity
CountryLabour productivity
Belgium € 332 Malta € 149
Bulgaria € 34 Netherlands € 292
Czech Republic € 98 Austria € 298
Denmark € 351 Poland € 81
Germany € 285 Portugal € 135
Estonia € 86 Romania € 41
Ireland € 385 Slovenia € 138
Greece € 211 Slovakia € 81
Spain € 223 Finland € 305
France € 319 Sweden € 315
Italy € 294 United Kingdom € 298
Cyprus € 183 Norway € 495
Latvia € 59 EU 27 € 243
Lithuania € 65 EU 25 € 256
Luxembourg € 722 EU 15 € 285
Hungary € 106 NMS 10 € 89
Source: EUROSTAT, own calculations
Table 10: Costs of bronchodilator daily dose
Country Bronchodilator dose cost (children, in EUR) Bronchodilator dose cost (adults, in EUR)
Germany 1 1
Poland 0.3 0.4
Czech Republic 0.4 0.4
Table 11: Medical treatment costs for selected health endpoints (in EUR2005)
Country CzechRepublic Norway Poland Germany EU15
(ExternE)
Respiratory hospital admission 320 2 535 320 – 640 5 378 1 009
Average length of stay (days) 6.5 4.2 12 9.7 3 (assumed)
Cardiac hospital admission 670 3 575 565 5 031 1 009
Average length of stay (days) 7.2 . 13 7 3 (assumed)
GP consultation (children) 4.2 8.7 44
GP consultation (adults) 3.5 8.7 44
Bronchodilator use (per daily dose, children) 0.4 0.3 1
Bronchodilator dose (per daily dose, adults) 0.4 0.4 1
Acute respiratory symptoms in children 10.5
Figure 1: Productivity loss per working day (EUR2005)
0
100
200
300
400
500
600
EU 15EU 25EU 27
NMS 10Aus
triaBelg
iumBulg
aria
Cyprus
Czech
Rep
ublic
Denmark
Estonia
Finlan
dFranc
eGerm
any
Greece
Hunga
ryIre
land
Italy
Latvi
aLit
huan
iaMalt
aNeth
erlan
dsNorw
ayPola
ndPort
ugal
Roman
iaSlov
akiaSlov
eniaSpa
inSwed
en
United
Kingdo
m
Table 2-1: Review of COI studies on medical treatment costs associated with cancer
Exchange rate used in the study
Medical costs for lung cancer or NSLC/SCLC*
Medical costs up-scaled by 10year long
incidence
Author Countrycurrency
per 1€PPP
currency per 1€
exchange
€2005PPP
€2005exchange
rate
€2005PPP
€2005exchange
rate
Koopmanschap (1994) Netherlands 1.396 0.676 14,131 6,846
Evans et al. (1995) Canada 1.014 0.995 21,292 20,907
Berthelot et al. (2000) Canada 0.825 0.810 21,828 21,434
Wolstenholme and Whynes(1999) UK 1.834 1.996 11,190 12,179 13,165 14,328
Weissflog et al. (2001) Germany 1.041 0.577 33,744 18,703
Serup-Hansen et al. (2003) Denmark 0.106 0.140 15,231 20,173
Braud et al. (2003) France 1.065 1.089 13,332 13,637
Chouaid et al. (2004) France 0.988 0.942 24,304 23,189
Vergnenegre et al. (2004) France 1.113 1.139 27,782 28,431 38,586 39,487
Dedes et al. (2004) Switzerland 1.113 1.139 21,601 22,105 28,610 29,279
Abal Arca et al. (2006) Spain 0.999 1.041 4,637 4,835
our study (2008) Czech Rep 0.062 0.035 10,993 6,221
Table 2-2: Review of COI studies on lung cancer: medical treatment costs (direct costs)
Author country approach viewpoint discounting
Medical treatment cosi in national currenciesTime-span
€2005in purchasing power
parity
€2005in exchange rate
Currency lung cancer NSLC SCLC %NSCLC lung
cancerNSLC/SCL
Clung
cancer
NSLC/SCL
C
Koopmanschap (1994) Netherlands
incidenceprevalence not specified no NLG 1988 10,126 n.a. 14,131 6,846
Evans et al.(1995) Canada incidence GOV no CAD 1988 21,003 19,782 25,988 90%* 21,292 20,683 20,907
20,309
Berthelot etal. (2000) Canada incidence GOV no CAD 1995 24,828 41,178 90%* 21,828
21,434
WolstenholmeWhynes(1999) UK incidence Hospital
yes (6%) GBP 1993 6,150 5,668 90% 4years 11,190
12,179
Weissflog etal. (2001) Germany prevalence
Sicknessfund no DM 1996 32,415 n.a. 33,744 18,703
Serup-Hansen et al.(2003) Denmark incidence ?
yes (3%) DKK 2002 143 685 n.a. 15,231 20,173
Braud et al.(2003) France incidence Hospital no Euro 2001 12,518 13,969 7,369 90%* 13,332 14,174 13,637
14,499
Chouaid et al.(2004) France incidence
Healthcarepayment no USD 1999 24,242 26,009 79% 1.5years 24,304
23,189
Vergnenegreet al. (2004) France incidence
Healthcarepayment no Euro 1999 24,984 24,759 90%* 2years 27,782
28,431
Dedes et al.(2004) Switzerland
Healthserviceexpenses ? Euro 1999 19,212 20,992 89% 2.5years 21,601
22,105
Abal Arca etal. (2006) Spain incidence ? ? Euro 2003 4,643 5,070 3,692 74% 4,637 4,706 4,835 4,906our study(2008)
CzechRepublic incidence GOV
yes (1%) CZK 2007 176,600 n.a. 10years 10,993 6,221
Note: GOV=government spendings on public health system90% share of NSLC assumed as in Wolstenholme and Whynes (1999).
Table 2-3: Review of COI studies on lung cancer: medical costs (direct COI) and loss of productivity (indirect COI)
Author country approach discounting Currency
In national currency€2005 by purchasing power parity €2005 by exchange rate
medicaltreatment
loss ofproductivity total medical
treatmentloss ofproductivity total medical
treatmentloss of productivity total
Weissflog et al. (2001) Germany prevalence no DM 1996 32,415 262,266 294,681 33,744 273,019 306,763 18,703 151,327 170,031
Serup-Hansen et al. (2003) Denmark incidence yes (3%) DKK 2002 143,685 253,616 397,301 15,231 26,883 42,114 20,173 35,608 55,781
our study (2008) Czech R incidence yes (3%) CZK 2007 176,600 958,000 1,134,600 10,993 59,633 70,626 6,221 33,746 39,967
our study (2008) Czech R incidence yes (1%) CZK 2007 176,600 1,080,000 1,256,600 10,993 67,227 78,220 6,221 38,043 44,264
our study (2008) Czech R incidence no CZK 2007 176,600 1,152,000 1,328,600 10,993 71,709 82,702 6,221 40,580 46,800
Table 2-4: Review of cost of illness studies in lung cancer (per capita costs)
Author country approach discounting€2005 by purchasing power parity (PPP)
medicaltreatment
loss ofproductivity total
Weissflog et al. (2001) Germany prevalence no 33,744 273,019 306,763
Serup-Hansen et al. (2003) Denmark incidence yes (3%) 15,231 26,883 42,114
our study (2008) Czech R incidence yes (3%) 10,993 59,633 70,626
our study (2008) Czech R incidence yes (1%) 10,993 67,227 78,220
our study (2008) Czech R incidence no 10,993 71,709 82,702
Table 2-5: Total treatment costs for patients treated in the hospital sector
Service Year ValueCosts
DKK2002
Total costDKK2002
Total in €exch.rate Total € PPP
Primary care services
GP Consultations 1 1 105 105 15 € 11 €
1st consultation MS 1 1 502 502 70 € 53 €
Costs per person 607 85 € 64 €
Secondary care services
Inpatient hospital service (incidence=5,637) 1 1 334 19 610 4 641 652 € 491 €
Outpatient hospital service (incidence=5,637) 1 21 891 2 692 10 454 1 468 € 1 106 €
Total costs 15 095 2 119 € 1 597 €
Total costs of primary and hospital services 15 702 2 205 € 1 661 €
Table 2-6: Total direct costs for patients treated in the primary care sector
Primary care services ValueCosts
DKK2002
Total costsDKK2002
Total in €exch.rate Total € PPP
General PractitionerGP Consultations 1 3 105 315 44 € 33 €Follow-up visits 2,3,4 6 594 83 € 63 €Total costs 910 128 € 96 €Percentage treated at GP 15%Expected costs 137 19 € 14 €Medical SpecialistGP Consultations 1 1 105 105 15 € 11 €1st consultation MS 1 1 502 502 70 € 53 €2nd consultation MS 1 1 276 276 39 € 29 €
Subsequent consultations MS 1 1 135 135 19 € 14 €Follow-up visits 2,3,4 6 2 841 399 € 301 €Recurrence 2 17% 606 85 € 64 €Total 4 465 627 € 472 €Percentage treated at MS 85%Expected costs 3 795 533 € 402 €
Total costs of primary care services per person 3 932 552 € 416 €
Table 2-7:Total direct costs for patients with non-melanoma skin cancer treated in the primary care sector
Costs DKK2002
Total in €exch.rate Total € PPP
Primary care sector (70% patients) 1 179 166 € 125 €
Primary and secondary care sector (30% patients) 10 991 1 543 € 1 163 €
Costs per person 12 171 1 709 € 1 288 €
Table 2-8: Distribution of medical treatment cost over 4years (recalculated by PPP)
Treatment costs
in PPP In exchange rate
Year1 1,192 € 1,582 €
Year2 43 € 57 €
Year3 26 € 35 €
Year4 26 € 35 €
Total 1,288 € 1,709 €
Table 2-9: Costs of non-melanoma skin cancer
in purchasing power parity in exchange rate
Treatment costs
Loss ofproductivity Dis-welfare Total
costsTreatment
costsLoss of
productivity Dis-welfare Totalcosts
Year1 1 192 € 930 € 2 122 € 1 582 € 701 € 2 283 €
Year2 43 € 43 € 57 € 57 €
Year3 26 € 26 € 35 € 35 €
Year4 26 € 26 € 35 € 35 €
Total 1 288 € 930 € 45 885 € 48 103 € 1 709 € 701 € 43 780 € 46 190 €
Box: "Cessation-lag““Cancer risk reductions (in terms of annual individual risk) are, generally not expected to occur instantaneously when exposure to a carcinogen is reduced or eliminated. Rather, it is expected that the risks for those individuals having had previous higher exposures will decline over time, eventually reaching or at least approaching the risk level associated with the lower exposure levels. The rate may depend upon a combination of the carcinogen, its particular end-point and mode of action, and other factors (…).The term "cessation lag" is used to refer to this transition period between higher risks from higher exposures and lower risks from lower exposures.” (US EPA 2005: E-32)
Lung cancer relative survival (%)
0
5
10
15
20
25
30
35
1 2 3 4 5
CZECH REP.
GERMANY
NORWAY
POLAND
Skin melama relative survival (%)
50
60
70
80
90
100
1 2 3 4 5
CZECH REP. GERMANY
NORWAY POLAND
Table 3-1: Average age at cancer diagnosis, Norway.
Cancer type Carcinogen Age of cancer diagnosis
Leukemia Dioxins, PCBs, benzene 63(male) 65(female)
Liver Dioxins, PCBs, As 64(male) 68(female)
Gallbladder Dioxins, PCBs, As 62(male) 73(female)
Skin Dioxins, PCBs, As 74(male) 77(female)
Lung As, Cd, Cr, Ni, formaldehyde 70(male) 68(female)
Kidney As 66(male) 68(female)Source: Kyrre Sundseth (DROPS 2008)
Table 3-2:Derivation of dis-welfare costs following VSL approach, €2005 per incidence.
year Cumulative survival probability Dis-welfare costs due to premature death
WestE CEE WestE CEE
1 30.4% 29.9% € 1 044 300 € 1 050 975
2 16.4% 14.9% € 207 158 € 222 824
3 12.5% 10.7% € 57 924 € 61 893
4 10.7% 8.7% € 26 562 € 29 036
5 9.8% 7.6% € 12 680 € 15 994
6 8.1% 6.2% € 24 540 € 20 558
7 7.2% 5.4% € 11 623 € 10 772
8 6.6% 4.8% € 8 993 € 8 167
9 6.1% 4.4% € 7 179 € 6 404
10 5.7% 4.0% € 5 872 € 5 154
Total € 1,406,831 € 1,431,777
Table 3-3: (P)YLLs due to lung, larynx, trachea and bronchus cancer.
Total YLL Males Females Weighted average
Czech Republic 88 780 14.46 16.29 14.88
Germany 643 165 14.85 17.46 15.56
Norway 30 179 14.10 17.50 15.40
Poland 352 777 14.58 18.57 15.42
Table 3-4: Dis-welfare due to premature death per case of cancer
(P)YLL Dis-welfare due to premature death
Males Females Weighted average Males Females Weighted
average
Czech Republic 14.46 16.29 14.88619 047 € 703 916 € 638 358 €
Germany 14.85 17.46 15.56636 979 € 759 009 € 669 882 €
Norway 14.10 17.50 15.40602 495 € 760 904 € 662 451 €
Poland 14.58 18.57 15.42
624 565 € 811 862 € 663 380 €
Table 3-5: Costs per patient for three treatment periods (in CZK).
Treatment period Median Mean
Initial (6M) 72 404 97 917
Initial (3M) 41 667 58 159
Maintenance (per year) 51 011 99 506
Terminal (6M) 27 465 48 465
Table 3-6: Survival for lung cancer in men aged 60-64 years.
Years from diagnosis Survival probability for lung cancer General survival probability Number of survivors
0 839
1 0.350 0.980 288
2 0.511 0.979 144
3 0.690 0.978 97
4 0.802 0.976 76
5 0.831 0.974 62
6 0.822 0.972 49
7 0.875 0.970 42
8 0.891 0.967 36
9 0.903 0.965 31
10 0.913 0.962 28
Table 3-7:Medical treatment costs, Czech Republic, weighted average for both genders.PRTP – discount rate (pure rate of time preference
immediate effect
Years after diagnosis
median Mean
no discounting prtp=1% prtp=3% no discounting prtp=1% prtp=3%
Total costsper 1 patient
114 721 Kč 113 423 Kč 111 042 Kč 179 113 Kč 176 611 Kč 172 020 Kč
4 097 € 4 051 € 3 966 € 6 397 € 6 308 € 6 144 €
10-year latency
Years after diagnosis
median Mean
no discounting prtp=1% prtp=3% no discounting prtp=1% prtp=3%
Total costsper 1 patient
114 721 Kč 102 681 Kč 82 626 Kč 179 113 Kč 159 883 Kč 127 999 Kč
4 097 € 3 667 € 2 951 € 6 397 € 5 710 € 4 571 €
Note: There are 75% of male patients and 25% of female patient in the cohort.
Figure 3-1: Cumulative incidence of lung cancer in Norway
0%
20%
40%
60%
80%
100%
0‐ 5‐ 10‐15
‐20
‐25
‐30
‐35
‐40
‐45
‐50
‐55
‐60
‐65
‐70
‐75
‐80
‐85
+NorwayGermanyCzech RPoland
Table 3-8: Aggregated loss of productivity due to lung cancer (years per average case).
morbidity mortality total
Czech Rep. 0.103 1.82 1.92
Germany 0.106 1.51 1.61
Norway 0.086 1.45 1.53
Poland 0.100 2.08 2.18
Figure 3-2: Working loss years due to lung cancer.
0,00
0,05
0,10
0,15
0,20
0,25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
loss
of ec
onom
ic-ac
tive y
ears
years after diagnosis
Loss of productivity (WesternEurope)
average(WE) morbidityaverage(WE) mortality
0,00
0,05
0,10
0,15
0,20
0,25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
loss o
f eco
nomi
c-ac
tive y
ears
years after diagnosis
Loss of productivity (CEE countries)
average(CEE) morbidityaverage(CEE) mortality
Table 3-9: Loss of productivity – while survived and death – per one case of lung cancer, in €2005 (for the EU regions and some countries).
GDP/employ2005, €2005
No latency 10year latency
PRTR=0% PRTR=1% PRTR=3% PRTR=0% PRTR=1% PRTR=3%
EU27 51 030 € 85 128 € 80 363 € 72 339 € 85 128 € 72 893 € 54 136 €EU25 53 739 € 89 647 € 84 629 € 76 179 € 89 647 € 76 763 € 57 009 €EU15 59 656 € 93 863 € 88 555 € 79 633 € 93 863 € 80 323 € 59 594 €NMS10 19 044 € 38 990 € 36 877 € 33 297 € 38 990 € 33 449 € 24 918 €
Germany 57 782 € 93 236 € 87 892 € 78 899 € 93 236 € 79 722 € 59 045 €UK 62 727 € 98 694 € 93 113 € 83 732 € 98 694 € 84 458 € 62 661 €
Norway 109 375 € 167 697 € 158 347 € 142 655 € 167 697 € 143 628 € 106 757 €Poland 17 315 € 37 662 € 35 592 € 32 096 € 37 662 € 32 283 € 24 020 €
Czech Rep. 20 112 € 38 608 € 36 550 € 33 049 € 38 608 € 33 152 € 24 732 €
Note: We assume 2% annual growth in labour productivity and consumption per capita. Further assuming elasticity of marginal utility on consumption as one,the social discount rate is given by PRT plus consumption growth.
Table 4-2: Total costs of lung cancers.
(EU15) CEE (NMS10)
Medical costs 24,000 € 1.6% 11,000 € 0.7%
Labour productivity 80,300 € 5.3% 33,500 € 2.3%
Dis-welfare due to premature death 1,406,800 € 93.1% 1,431,800 € 97.0%
Total 1,511,100 € 1,476,300 €
Table 2-9: Costs of non-melanoma skin cancer, €2005.
in purchasing power parity in exchange rate
Treatment costs
Loss ofproductivit
y
Dis-welfare
Totalcosts
Treatment costs
Loss ofproductivit
y
Dis-welfare
Totalcosts
Year11 192 € 930 € 2 122 € 1 582 € 701 € 2 283 €
Year243 € 43 € 57 € 57 €
Year326 € 26 € 35 € 35 €
Year426 € 26 € 35 € 35 €
Total1 288 € 930 € 45 885 € 48 103 € 1 709 € 701 € 43 780 € 46 190 €
Loss in earnings and education costs
$1990
partic-weighted average (2.39%)
males (1.93%)
females (3.22%)
Salkever(assumption)
i) Loss in earnings $4 067 $3 284 $5 479 $3 352
ii) Costs of education $285 $285 $285 $219
iii) Opport costs while in school $566 $566 $566 $435
Total (i-ii-iii) $3 216 $2 433 $4 628 $2 698
€2005
partic-weighted average (2.39%)
males (1.93%)
females (3.22%)
Salkever(assumption)
i) Loss in earnings 4 962 € 4 007 € 6 685 € 4 090 €
ii) Costs of education 348 € 348 € 348 € 267 €
iii) Opport costs while in school 691 € 691 € 691 € 531 €
Total (i-ii-iii) 3 924 € 2 969 € 5 647 € 3 292 €
Casual model of lead exposure, cognitive ability and economic productivity
Source: taken from Grosse (2007)
Present value of loss in labour productivity stream per 1 IQ point
PRTR=0% PRTR=1% PRTR=3% PRTR=5%
EU27 26 897 € 18 789 € 9 711 € 5 359 €
EU25 28 353 € 19 806 € 10 236 € 5 648 €
EU15 31 857 € 22 231 € 11 470 € 6 321 €
NMS10 10 170 € 7 097 € 3 662 € 2 018 €
Table 1: Summary of estimates for value of human development disabilities
Author(s) Description ofHealth Effect
ValuationMethod
Location,Country
Year ofData
Estimated Value (2005 €)
Agee andCrocker (1994)
An increase in theinformationprovided to parentscorresponding totheir child's bodylead level
Avertingbehavior
Chelsea,Somerville(US)
1985,1978
Parents mean WTP:- overall=6.6- who chose therapy=32.9- who did not choose therapy=4.8Social mean WTP:- overall=433.5- who chose therapy=2169.9- who did not choose therapy=317.8
Agee andCrocker (1996)
A marginalreduction and a onepercent reduction inchild body leadburden
Avertingbehavior
(US) 1985,1978,1977,1976,1975
One part per million reduction- overall=2.1- who chose therapy=7.2-who did not choose therapy=1.6One percent reduction-overall=32- who chose therapy=207.7- who did not choose therapy=22.2
vonStackelbergand Hammitt(2005)
A small reduction inIQ and a probabilityof a 7-monthreduction in readingcomprehension
Contingentvaluation -dichotomouschoice
US 2005 Reduction in IQ=102.87-month reduction in readingcomprehension=120.4
Source: EVRI database
Table: Total economic costs per 1IQ point Assuming the 0.107 years of additional education by Salkever (1995)
PRTR=0% PRTR=1% PRTR=3% PRTR=5%
EU27 21 171 € 13 986 € 6 313 € 2 939 €EU25 22 355 € 14 773 € 6 676 € 3 113 €EU15 25 189 € 16 637 € 7 512 € 3 503 €NMS10 7 967 € 5 249 € 2 354 € 1 087 €
Austria 26 361 € 17 418 € 7 867 € 3 667 €Belgium 29 794 € 19 696 € 8 907 € 4 159 €Germany 24 138 € 15 957 € 7 218 € 3 372 €Denmark 31 399 € 20 757 € 9 389 € 4 386 €Spain 19 614 € 12 955 € 5 846 € 2 722 €Finland 27 401 € 18 135 € 8 226 € 3 857 €France 28 628 € 18 942 € 8 586 € 4 022 €UK 26 125 € 17 266 € 7 804 € 3 642 €Greece 20 589 € 13 626 € 6 180 € 2 897 €Ireland 34 713 € 23 002 € 10 469 € 4 934 €Italy 24 363 € 16 095 € 7 267 € 3 386 €Luxembourg 40 478 € 26 714 € 12 029 € 5 581 €Netherlands 25 850 € 17 092 € 7 736 € 3 617 €Norway 46 011 € 30 481 € 13 862 € 6 526 €Portugal 11 988 € 7 904 € 3 548 € 1 639 €Sweden 28 357 € 18 744 € 8 476 € 3 958 €Switzerland 42 782 € 28 463 € 13 092 € 6 264 €Latvia 5 033 € 3 304 € 1 464 € 662 €Estonia 7 547 € 4 978 € 2 235 € 1 031 €Lithuania 5 649 € 3 715 € 1 654 € 753 €Poland 7 105 € 4 686 € 2 106 € 974 €Hungary 9 396 € 6 196 € 2 782 € 1 285 €Czech Rep. 8 250 € 5 431 € 2 428 € 1 115 €Slovenia 12 759 € 8 442 € 3 826 € 1 792 €Slovakia 7 622 € 5 035 € 2 272 € 1 057 €Romania 3 369 € 2 192 € 950 € 415 €Bulgaria 2 334 € 1 503 € 631 € 262 €Cyprus 15 743 € 10 424 € 4 736 € 2 227 €Malta 13 084 € 8 653 € 3 919 € 1 835 €
Exposure- and dose-response relationships used in the impact assessment of DROPS
Pollutant Exposureroute
Exposure time
[years]
Population group Effect Absolute risk Exposure unit,
intake rate
Slope factor,
[risk/(kg/y)]
As Inhalation 70 all Skin cancer 4,00E-04 [risk/( ET*ug/m3]
As Inhalation 70 all Lung cancer 1,50E-03 [risk/( ET*ug/m3]
As ingestion (food) 70 all fatal cancer 1,50E+00 [risk/(ET*mg/kg(BW)/day] 8,39E-01
As ingestion (water) 70 all fatal cancer 5,00E-05 [risk/( ET*µg/liter)] 9,78E-01
Cd Inhalation 70 all Lung cancer 1,80E-03 [risk/( ET*ug/m3]
CrVI Inhalation 70 all Lung cancer 4,00E-03 [risk/( ET*ug/m3]
Ni Inhalation 70 all Lung cancer 3,80E-04 [risk/( ET*ug/m3]
Pb Inhalation 5 minors Children's IQ 1,00E-01 [risk/( ET*ug/m3]
Pb ingestion (food) 1 age (0,1) IQ points loss in children 4,20E-02 [risk/( ET*µg/day)] 1,17E+03
Pb ingestion (water) 1 age (0,1) IQ points loss in children 4,20E-02 [risk/( ET*µg/day)] 1,17E+03
MeHg ingestion (food) 1 minor IQ points loss in children 1,45E-01 [risk/(µg/day)] 2,90E-10
PCB inhalation 70 all cancer 1,00E-04 [risk/( ET*ug/m3]
PCBs ingestion (food) 70 all fatal cancer 8,00E-03 [risk/(ET*mg/kg(BW)/day] 4,47E-03
PCBs ingestion (water) 70 all fatal cancer 1,00E-05 [risk/( ET*µg/liter)] 1,96E-01
PCDDs ingestion (food) 70 all fatal cancer 2,00E+05 [risk/(ET*mg/kg(BW)/day] 1,12E+05
Note: ET – exposure time, BW – body weight, SF – slope factor, i.e. a number of risks/cases per 1kg of intake per capita and year.
Health expenditures for lung cancer and non-melanoma skin cancer, €(2005)
Years after diagnosis
Lung cancer Skin cancer
No latency 10year latency
HEXPWE HEXPSCEE HEXPWE HEXPSCEE all 1 13,661 € 6,261 € 12,367 € 5,668 € 1,1922 3,891 € 1,783 € 3,488 € 1,599 € 433 1,832 € 840 € 1,626 € 745 € 264 1,226 € 562 € 1,077 € 494 € 265 925 € 424 € 805 € 369 €6 741 € 340 € 638 € 293 €7 568 € 260 € 484 € 222 €8 459 € 211 € 388 € 178 €9 376 € 172 € 315 € 144 €10 319 € 146 € 264 € 121 €Total 24,000 € 11,000 € 21,944 € 10,058 € 1,288 €
Review of health impacts relevant for calculating medical treatment costs by this approach
Pollutant Number of impacts
Pathway of the pollutant
inhalation ingestion via food ingestion via water
Arsenic 4 Lung cancersSkin cancers Cancers Cancers
Chromium 1 Lung cancers
Cadmium 1 Lung cancers
Nickel 1 Lung cancers
PCBs 1 Cancers Impact2000* Impact2000*
Note> Health impacts due to ingestion of PCBs are calculated slightly different approach followed by the Impact2000 method (see next chapter for the details).
Intake, cumulative risks and damage for 1kg of PCBs and PCDDs
PCBs PCDDs (dioxins)
EU Oral intake - animal respiration then human consumption 2.92 E-03 5.09 E-09
EU Oral intake - excluding inhalation associated pathways 1.11 E+01 7.57 E-05
Median cumulative CR [risk per kg] 1.29 E -04 4.76 E+02
number of cancer cases [cases per year] 1.43 E-03 3.60 E-02
Cumulative damage (external costs)
- work loss years [years] 0.00238 WLYs 0.06s
- loss of productivity [€2005] 115 € 2,895 €
- cost-of-illness [€2005] 30.8 € 773 €
- dis-welfare due to premature death (mortality risks)
- based on PLYLs * VOLYs = 650,000 [€2005] 929.5 € 23,412 €
- based on VSL of 1,500,000 [€2005] 2,150 € 54,028 €
Total damage per kg of pollutant (VSL for mortality risks) 2,296 €/kg 57,695 €/kg
Note: ExternE (2005) and EcoSenseWeb Guide (2007) reports damage costs of 37,000,000 € per kg of dioxins.
Working loss years due to lung cancer
0,00
0,05
0,10
0,15
0,20
0,25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
loss
of ec
onom
ic-ac
tive y
ears
years after diagnosis
Loss of productivity (WesternEurope)
average(WE) morbidityaverage(WE) mortality
0,00
0,05
0,10
0,15
0,20
0,25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
loss o
f eco
nomi
c-acti
ve ye
ars
years after diagnosis
Loss of productivity (CEE countries)
average(CEE) morbidityaverage(CEE) mortality
Variable / Parameter
Parameter description Value Unit
E global emission rate 6,000,000 kgHg/yD global average dose rate 2.4 µgMeHg/day/pc
Tav transfer factor for ingestion f MeHg 4.00E-07
POPUL world popualtion 6.501 billionb birth rate country-specific birth/1,000 (7.6; 49.6)
dose-response function of methyl-Hg and concentration 0.18 IQ/ppm_hair
ratio hair/cord blood 0.20 ppm_hair / µg/Lcord
ratio cord blood and maternal blood concentration 1.65 µg/Lcord / µg/Lmat
relation between intake dose of Me-Hg and concentration 0.61 µg/Lmat / µg/daysDR slope factor 0.0362 µg/day
Dav(Dth=0) average dose without threshold 2.400 µgMeHg/day/pcDav(Dth=6.7) average dose those who are above threshold of 6.7 mg/day 1.052 µgMeHg/day/pclag cessation-lag 15
Variable / Parameter
Parameter description Value Unit
age to enter labour market 18 years
age to exit labour market 65 yearsPARTIP effect on participation rate (Salk by Schwartz_rev ) 0.46% % change per 1 IQpointEARN effect on earnings (Salk by Schwartz_rev) 2.18% % change per 1 IQpointEDU additional remedial education [years] 0.131 yearsg real growth in labour productivity 2% % per yeare real growth in health costs 2% % per year social rate of time preference 3% % per year
gender-weighted
PLYLs
with discounting (1% PRTP)
weighted average VOLY
region-specific VOLY
Czech Republic 14.88 638,358,€ 526,646,€Germany 15.56 669,882,€ 686,629,€Norway 15.40 662,451,€ 679,013,€Poland 15.42
663,380,€ 547,289,€EU average 663,107,€ 653,650,€
Health impact assessment in DROPS
Pollutant Exposure route Modelling of exposure/intake Impact
Cancers IQ loss
COI LP Dis-welfare LP
arsenic inhalation OMEGA Lung cancer YES (2a) YES (3a) YES (5)inhalation OMEGA Skin cancer YES (2a) YES (3a) YES (5)ingestion (food) WATSON Lung cancer YES (2a) YES (3a) YES (5)ingestion (water) WATSON Lung cancer YES (2a) YES (3a) YES (5)
Chromium VI inhalation OMEGA Lung cancer YES (2a) YES (3a) YES (5)Cadmium inhalation OMEGA Lung cancer YES (2a) YES (3a) YES (5)Nickel inhalation OMEGA Lung cancer YES (2a) YES (3a) YES (5)Lead inhalation OMEGA IQ loss in children YES (4a)
ingestion (food) WATSON IQ loss in children YES (4a)ingestion (water) WATSON IQ loss in children YES (4a)
methyl-Mercury ingestion Spadaro&Rabl 2008 IQ loss in children YES (4b)
PCBs inhalation OMEGA Cancer YES (2a) YES (3a) YES (5)ingestion (food) Impact2002 Cancer YES (2b) YES (3b) YES (5)ingestion (water) Impact2002 Cancer YES (2b) YES (3b) YES (5)
dioxins ingestion Impact2002 Cancer YES (2b) YES (3b) YES (5)
Note: Number of Chapter in this paper highlighted in the brackets. If the exposure route ‘ingestion’ is not further specified then it can be applied for both ingestion ofdifferent food items as well as ingestion of drinking water and thus represents the sum of two exposure routes.
External costs of arsenic (inhalation pathway), in EUR/t
0
5 000
10 000
15 000
20 000
25 000
30 000
35 000
40 000
NL BE UK DE IT MC FR CH LU CZ PL AT MD HU SK PT UA DK SI RO YU ES HR AL GR BA BY IE MK BG LT RU LV SE EE FI NO
PRTP = 0% no latency, PRTP = 1% no latency, PRTP = 3% 10 years latency, PRTP = 3%
Notes: PRTP – discount rate, for country codes see appendix.
External costs of arsenic emissions (ingestion pathway), in EUR/kg
0
5
10
15
20
25
PRTP = 0% PRTP = 1% PRTP = 3% PRTP = 1% PRTP = 3%
no latency 10y latency
CZ DE ES LV NO UK
Notes: PRTP – discount rate (pure rate of time preference), see appendix for country codes.
External costs of arsenic (both pathways), in EUR/tonne
0
5 00010 000
15 00020 000
25 000
30 00035 000
40 00045 000
50 000
CZ
DE ES LV NO UK CZ
DE ES LV NO UK CZ
DE ES LV NO UK CZ
DE ES LV NO UK CZ
DE ES LV NO UK
PRTP = 0% no latency, PRTP =1%
no latency, PRTP =3%
10 years latency,PRTP = 1%
10 years latency,PRTP = 3%
inhalation ingestion
Respiratory hospital admissionRespiratory hospital admission
Treatment costs: 3 days in ExternE, 7 days in CZ, 12 days in PL Disutility: ExternE – 5 country study (Ready et al.), original study in CZ Loss of productivity: 8 days in ExternE (DE, NO), 17.5 days in CZ (PL);
costs of absenteeism (ExternE) / loss of labour productivity
(in EUR 2005) treatment costs
disutility total loss of productivity
ExternE 2005 1073 487 1560 733CZ 307 106 413 1355PL 466 n.a. 466 1427DE 1073 487 1560 2424NO 3585 487 4072 4072
Cardiac hospital admissionCardiac hospital admission
Treatment costs: 3 days in ExternE (DE), 9.8 days in CZ, 13 days in PL, (?) in NO
Disutility: ExternE – 5 country study (Ready et al.; DE, NO) Loss of productivity: 8 days in ExternE (DE, NO), 72.5 days in CZ;
costs of absenteeism (ExternE) / loss of labour productivity
(in EUR 2005) treatment costs
disutility total loss of productivity
ExternE 2005 1073 487 1560 733CZ 639 106 745 5800PL 547 n.a. 547 3068DE 1073 487 1560 2424NO 5059 487 5546 4072
Consultation for asthma (children)Consultation for asthma (children)
Treatment costs: GP consultation Disutility: ExternE: 5-country study, CZ original study
(in EUR 2005) treatment costs
disutility total
ExternE 2005 47 307 353,7CZ 4 44 48PL 8DE 83 307 390,27
Review of cost-of-illness studies in lung cancer
Valuation of cancersCOI for non-fatal cancer
Author country approach per capita costs (in EUR2005)
direct costs
indirect costs
Koopmanschap (1994) Netherlands incidence and prevalence 4,597 yes no
Evans et al. (1995) Canada incidence 14,135 yes no
Berthelot et al. (2000) Canada incidence 16,709 – 27,713 yes no
Wolstenholme and Whynes (1999) UK incidence 9,280 / 8,553 yes no
Weissflog et al. (2001) Germany incidence 150,582 yes (16,564)
yes (134,018)
Serup-Hansen et al. (2003) Denmark incidence 55,770 yes (20,169)
yes (35,601)
Braud et al. (2003) France incidence 12,518 yes no
Chouaid et al. (2004) France incidence 17,153 – 23,041 yes no
Vergnenegre et al. (2004) France incidence 25,643 yes no
Abal Arca et al. (2006) Spain incidence 3,692 / 5,070 yes no
Our study (2008) Czech Republic incidence 44,700 yes (6,186)
yes (38,500€)
20,000 €2005 WE
6,000 €2005 CEE
Aggregated loss of participation due to lung cancer
(in years per average case)
Aggregated loss of participation due to lung cancer
(in years per average case)
morbidity mortality total
Czech Rep. 0.103 1.82 1.92
Germany 0.106 1.51 1.61
Norway 0.086 1.45 1.53
Poland 0.100 2.08 2.18
Valuation of Skin CancerValuation of Skin Cancer Medical treatment costs
Loss of productivity 935 € (Serup-Hansen et al. study)
Dis-welfare 32,450 € (BT from Murdoch, Thayer 1990 by Serup-Hansen et al.) Dickie and Gerking (1991, 1996) - WTP for 1%, or 5% life-time risk reduction of 1–6$, or 36.8–60.75$ Bateman and Brouwer (2005, 2006) - WTP for skin cancer risk reduction associated with UV radiation exposure in
public and private perspective> 4.5–10.1£, or 16.4–144.8 £
Total costs 35,190 € (92% comprises diswelfare)
Primary care Hospital based on … incidence prevalence Percentage of patients
30% 70%
Medical treatment costs
6 visits over 3 years in general practitioner (15%*83€) treatment at specialists (85%*399) recurrence of skin cancer in one in six patient (85€/6)
Treatment in hospital 2,106€
165€ 1,543€ Total costs (weighted) 1,708 €
Model Flows Model Flows
Industrial Activity
Heavy Metal Pollution
Loss of Productivity Years of Life Lost (reduced population)
Cost of Illness (health costs)
Macroeconomic Effects
Productivity effectsProductivity effects
Calculation of non-health benefitsCalculation of non-health benefits
CAFE scenarios for ozone dose to 2020(Baseline, MFTR),
dose-response functions,production of 5 main crops sensitive to
ozone in year 2000 in whole Europe,market prices of these crops.
Reduction of crops yielddue to ozone exposure
Reduction of crops yielddue to ozone exposure
for base year and scenarios (in million tonnes) in Europe
wheat potatoes grapes tomatoes apples
Theoretical production 2000 207.4 159.4 42.7 35.8 20.4
Base year 2000 24.0 15.7 8.0 6.2 3.0
Baseline 2020(BAU+Climate) 12.6 8.6 4.2 3.6 1.5
MFTR 2020 8.7 6.3 2.9 2.8 1.0
Reduction of wheat yield – base year 2000Reduction of wheat yield – base year 2000
Annual reduction of yieldfor 50x50 km cell
in thousand tonnes
Annual reduction of yieldfor 50x50 km cell
in thousand tonnes
Reduction of wheat yield – BAU+Climate 2020Reduction of wheat yield – BAU+Climate 2020
Annual reduction of yieldfor 50x50 km cell
in thousand tonnes
Reduction of wheat yield – MFTR 2020Reduction of wheat yield – MFTR 2020
Monetary benefitsMonetary benefits
The change in annual damages for 5 crops (in billion euro)
based on Eurostat (2002) selling prices of cropsValues are 4 times bigger than AEAT (2005) results
ScenarioDamagesin 2000
Damagesin 2020
BENEFITS
BAU+Climate11.3
6.2 5.1
MFTR 4.5 6.7