Environmental Pollution and Human Welfare · 2014-03-21 · CV* X G X B X O X T OV* OS* SA* DV* OA*...

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


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


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


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



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


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


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


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



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


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



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


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


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


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


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)


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


Loss of productivity (WesternEurope)

average(WE) morbidityaverage(WE) mortality

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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


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


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


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


in thousand tonnes

Reduction of wheat yield – BAU+Climate 2020Reduction of wheat yield – BAU+Climate 2020


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

Environmental Pollution and Human Welfare · 2014-03-21 · CV* X G X B X O X T OV* OS* SA* DV* OA*...

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Transcript of Environmental Pollution and Human Welfare · 2014-03-21 · CV* X G X B X O X T OV* OS* SA* DV* OA*...