Health-Related External Cost Assessment in Europe - ACS Publications

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Health-related external cost assessment in Europe: methodological developments from ExternE to the 2013 Clean Air Policy Package Jonathan van der Kamp, and Till M. Bachmann Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es5054607 • Publication Date (Web): 09 Feb 2015 Downloaded from http://pubs.acs.org on February 18, 2015

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Environmental Science & Technology

Health-related external cost assessment in Europe: methodological developments from ExternE to the 2013 Clean Air Policy Package Jonathan van der Kamp (*) a, b, Till M. Bachmann a a

European Institute for Energy Research (EIFER)

Emmy-Noether-Str. 11 76131 Karlsruhe Germany Email: [email protected], [email protected] Telephone (van der Kamp, J.) +49 721 6105 1723 b

Karlsruhe Institute of Technology (KIT)

Kaiserstr. 12 76131 Karlsruhe Germany 1

ACS Paragon Plus Environment


Key words: air pollution, ExternE, external cost, health risk, methodology, variability

2


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1

Abstract

2

“Getting the prices right” through internalizing external costs is a guiding principle of

3

environmental policy making, one recent example being the EU Clean Air Policy Package

4

released at the end of 2013. It is supported by impact assessments, including monetary valuation

5

of environmental and health damages. For over 20 years, related methodologies have been

6

developed in Europe in the Externalities of Energy (ExternE) project series and follow-up

7

activities. In this study, we aim at analyzing the main methodological developments over time

8

from the 1990s until today with a focus on classical air pollution-induced human health damage

9

costs. An up-to-date assessment including the latest European recommendations is also applied.

10

Using a case from the energy sector, we identify major influencing parameters: differences in

11

exposure modelling and related data lead to variations in damage costs of up to 21%; concerning

12

risk assessment and monetary valuation, differences in assessing long-term exposure mortality

13

risks together with assumptions on particle toxicity explain most of the observed changes in

14

damage costs. These still debated influencing parameters deserve particular attention when

15

damage costs are used to support environmental policy making.

16

TOC/Abstract art 6.0 5.21

[€-cent(2000) per kWh]

5.0

4.0

+15% 2.78

3.0

-66%

2.0

1.77

3.21

-5%

2.64

+57%

1.0

0.0

17

ExternE1998

NewExt2004

NEEDS2009

Year2013

Year2013*

Morbidity endpoints

0.88

0.59

0.93

0.74

0.74

Mortality endpoints

4.33

1.18

1.85

2.47

1.90

3



18

1 INTRODUCTION

19

External costs constitute a market failure, implying an inefficient allocation of resources and

20

economic losses to society. In the European Union (EU), “getting the prices right”, i.e.

21

internalizing externalities, is a guiding principle of environmental policy making.1 In the air

22

quality context, related policies have been revised recently, leading to the 2013 Clean Air Policy

23

Package.2 As already before,3, 4 scientific impact assessments, including the monetary valuation

24

of environmental and health damages, supported the review process.5, 6 The underlying

25

methodology, focusing on energy-related externalities due to atmospheric emissions, has been

26

originally developed in the Externalities of Energy (ExternE) project series7 and several follow-

27

up projects.

28

Notwithstanding their common methodological basis, modelling components and assessment

29

parameters have changed over time, resulting in differences in published external costs.8-13 A few

30

studies analyzed the link between methodological assumptions and quantified external costs,

31

covering the years 1995 to 2005 at most. For instance, Krewitt14 discussed the politically

32

acceptable level of variation in external cost estimates, the limitations in terms of considered

33

impacts and general policy implications. Krewitt and Schlomann15 looked at methodological

34

developments throughout different EU projects. Besides greenhouse gas valuation (e.g.

35

quantification approaches, discounting), they analyzed the classical air pollutant damage

36

assessment at a rather aggregated level (e.g. epidemiological evidence, considered impacts,

37

relevant pollutants).

38

Given the manifold scientific developments over the past 20 years and the continued relevance of

39

air-pollution-induced health costs for policy-making both in and outside Europe, the current 4


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study aims to deepen these analyses on the impacts of methodological developments on the

41

magnitude of quantified external costs and extend these to the present. Our main contribution is

42

to disentangle the influencing factors that are otherwise hidden in aggregated external cost

43

estimates. Whilst raising decision-makers’ awareness on these factors, we also identify research

44

needs, aiming at improving the underlying methodology.

45

To illustrate developments in terms of exposure modelling, risk assessment and monetary

46

valuation, a coal-fired power plant unit located in Western Europe is used as a case. Accordingly,

47

we assess methodological influences independently of operational or geographical variations,

48

addressed elsewhere.16

49

While discussing parameter and model uncertainty in section 4.1, our analysis focuses on the

50

variability in external cost estimates arising from heterogeneous methodological choices. A

51

discussion of general limitations and latest advances in assessing human health-related external

52

costs, such as a cause-specific assessment of mortality impacts, concludes.

5



53

2 METHODOLOGY AND DATA

54

2.1 What is understood by “external costs”?

55

Following the European Commission,17

56

[…] an external cost arises, when the social or economic activities of one group of

57

persons have an impact on another group and when that impact is not fully accounted, or

58

compensated for, by the first group.

59

According to economic theory, external costs refer only to the non-internalized fraction of the

60

total environmental damage costs.18 In practice defining the degree of internalization of external

61

effects is often difficult, depending on national policies and also on the methods for their

62

quantification. Henceforth, we therefore use the term damage costs instead of external costs. The

63

damage costs quantified are marginal, i.e. resulting from the provision of an extra unit of a

64

specific product (a kWh of electricity); this will not always be explicitly stated.

65

2.2 General external cost quantification framework

66

In 1991, the joint ExternE research project between European and US partners set out to

67

establish a common external cost quantification approach for the energy sector.19, 20 While

68

ExternE continued as a project series in Europe, comparable research activities were pursued in

69

the US, equally used for policy support nowadays.21, 22

70

2.2.1

71

In the ExternE project series, effects on human health, building materials, agriculture and

72

biodiversity (plant species) caused by emissions of classical air pollutants like SO2, NOx and

73

particulate matter (PM) were identified. Primary and secondary classical air pollutants are

Impacts caused by classical air pollutants

6


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distinguished. While primary pollutants are directly emitted, secondary pollutants form in the

75

atmosphere, essentially including secondary inorganic aerosols, also termed secondary PM, as

76

well as tropospheric ozone. NOx, SO2 and NH3 are precursors for secondary (inorganic) PM;

77

NOx and non-methane volatile organic compounds (NMVOC) contribute to ozone formation.

78

We only consider human health impacts given their dominance in quantified damage costs in the

79

past.23-25

80

2.2.2

81

In ExternE, external costs of a specific activity are calculated in a site- and time-dependent way

82

following the so-called impact pathway approach (IPA), distinguishing steps corresponding to

83

the Driver-Pressure-State-Impact-Response (DPSIR) scheme without including responses

84

(Figure 1).26 For polluting activities and similar to any environmental risk assessment, the

85

assessment follows a bottom-up approach by establishing a causal link between emissions and

86

impacted receptors. Impacts are valued in monetary terms, based on resource costs (e.g.

87

healthcare expenses), opportunity costs (e.g. lost productivity) and disutility costs (e.g. loss of

88

wellbeing of concerned individuals).27, 28

Impact Pathway Approach

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89

DPSIR scheme

Driver, Pressure

Impact Pathway Approach (IPA) Emission source specifications

Air quality modelling

Emission inventory Meteorology

Concentration changes Δ c

Exposure modelling

State

Population-level exposure E

Health risk functions

sCR

Health baseline data

Impact assessment Health impacts (physical units)

Impact Monetary values m

Population counts p

Particle toxicity t Affected population f

Monetary valuation Health-related damage costs

90 91 92

Figure 1: Impact pathway approach for assessing health-related damage costs following the DPSIR scheme (oval shapes = input data; rectangles = output data; rounded rectangles = assessment steps)

93

For health-related damage costs, the following general equation conceptualizes the approach:

𝐶𝑖 = �[∆𝑐𝑟 × 𝑝𝑟 ] × �� 𝑓𝑖 × 𝑠𝐶𝐶𝑖 × 𝑡 × 𝑚𝑖 �� 𝑟 �� 𝐶𝑖,𝑢𝑢𝑢𝑢 𝐸

(1)

94

Ci represents the damage costs related to health impact i, given in €base year; E is the population

95

exposure in �𝑚3 × 𝑝𝑝𝑝𝑝𝑝𝑝�, calculated by summing the exposures in all sub-regions r of the

96

𝜇𝜇

assessed geographic domain, where Δcr is the concentration change of a given pollutant, given in 8


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𝜇𝜇

98

[𝑚³] for inhalation and pr is the number of affected individuals [𝑝𝑝𝑝𝑠𝑠𝑠]; Ci,unit represents the

99

μg/m³ per year; fi is the share of the population affected by health impact i [fraction], here

97

100 101

damage costs of health impact i per unit pollution increment, given in €base year per person per

assumed to be constant; 𝑠𝐶𝑅𝑖 is the slope of the impact function of health impact i, for inhalation 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑐𝑐𝑐𝑐𝑐

given in [𝜇𝜇 𝑚³

×𝑝𝑝𝑝𝑝𝑝𝑝×𝑦𝑦𝑦𝑦

], merging information on the risk increase (described by a so-called

102

concentration-response or exposure-response function and typically given as relative risk; here

103

assumed to be linear with respect to concentration changes) and baseline rate of a given health

104

impact i;29 t is a factor to account for different assumptions on particle toxicity; and mi is the

105

monetary value per case of health impact i, given in [

106

2.3 Approach of the analysis

107

We compare four implementations of the impact pathway approach (termed IPA

108

implementations henceforth) and a sensitivity scenario for the most recent implementation:

109

ExternE1998, New Elements for the Assessment of External Costs from Energy Technologies

110

(NewExt2004), New Energy Externalities Developments for Sustainability (NEEDS2009) and

111

Year2013/2013*, described in section 2.4. We apply these to an exemplary emission point source

112

for which damage costs had already been quantified before, i.e. a 600 MWel pulverized coal

113

combustion unit, located in Western France (cf. Supporting Information, Table S1). This choice

114

is supported by the fact that coal is a widely-used fuel in the European electricity generation

115

mix.30 To ensure comparability, we kept technical emission source specifications constant. For

116

ExternE1998 and NewExt2004, we use published damage costs.23, 24, 31 We calculated the

€base year 𝑐𝑐𝑐𝑐

].

9



117

NEEDS2009 results with the tool EcoSenseWeb that were then updated to obtain damage costs

118

for Year2013 and Year2013* (cf. section 2.4.1).

119

While the data provided in section 2.4 help explaining most of the observed changes in damage

120

costs, disentangling the influence of single parameters of equation (1) is not straightforward. To

121

quantitatively estimate their influence on damage costs, the following elements are successively

122

analyzed.

123

First and regarding population exposure (E), the question is: which damage costs result if the

124

population exposure modelling of the most recent tool is used instead of the original exposure

125

modelling? We derived aggregated population exposure figures per pollutant from the

126

NEEDS2009 assessment and then respectively combined them with damage costs per pollution

127

increment (ci, unit) from the original 1998 and 2004 IPA implementations (cf. section 2.4.6).

128

In addition to an updated exposure modelling, the next question concerns particle toxicity (t):

129

what is the impact of using the current recommendation of equal particle toxicity? To this end,

130

we adapted results from step 1 in terms of particle toxicity. We defined factors applicable to

131

secondary PM by using the toxicity coefficients as stated in section 2.4.3 and assuming a mass

132

ratio of nitrates and sulfates of 2:1, derived from dedicated EcoSenseWeb calculations.

133

Among all health endpoints, long-term mortality accounts for the largest share in total quantified

134

health-related damage costs (cf. section 3.1). The influence of updating the related impact

135

assessment parameters (f, sCR and m) according to NEEDS2009 is assessed on top of the

136

outcome of step 2 (updated exposure modelling and updated particle toxicity).

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137

2.4 Models and data used

138

2.4.1

139

We calculated part of the damage costs with the web-based software tool EcoSenseWeb 1.3,

140

developed in the NEEDS project.32 This choice allows comparison with the ExternE1998 and

141

NewExt2004 results, calculated with its predecessor, the EcoSense desktop tool.33

142

EcoSenseWeb is applicable to stationary point emission sources in Europe.16, 34 Besides the

143

models also the data needed for a site-dependent externality assessment are provided, i.e.

144

receptor data, risk slopes and monetary values. While the tool allows assessing other pressures

145

(e.g. greenhouse gas emissions) and impact categories (e.g. crop damages), we only consider

146

health impacts caused by classical air pollutants.

147

As a novel feature, we updated EcoSenseWeb results in terms of impact functions and monetary

148

values to reflect the latest expert recommendations at European level,5, 35 as further detailed in

149

sections 2.4.4 and 2.4.5, respectively. We defined two parameter sets, representing a base case

150

and a sensitivity case with differing mortality valuation, denoted by Year2013 and Year2013*,

151

respectively.

152

2.4.2

153

Two types of regional (European-wide) air quality models were used, i.e. a Lagrangian model

154

and a (parameterized version of a) Eulerian model that mainly differ in the mathematical

155

treatment of air parcels and associated chemical interactions (Table 1).36 Moreover, modelling

156

resolutions as well as emission, meteorological and population data varied. To ensure

157

comparability, we only considered regional, i.e. European-scale, air quality models. For

158

availability reasons, the Year2013 assessments do not include the updated EMEP (European

The tool EcoSenseWeb, its case study application and updates

Exposure modelling

11



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159

Monitoring and Evaluation Programme) source-receptor matrices,37 having been used to assess

160

the EU Clean Air Policy Package in 2013.

161

Beyond the changes displayed in Table 1, ozone damages were modelled by a generic factor in

162

1998 and by a site-dependent approach since 2004.24 The ozone exposure metric was changed

163

from ExternE1998/NewExt2004, relying on 6-hour average values, to NEEDS2009, being based

164

on the SOMO35 (Sum Of (maximum daily 8h) Means Over 35 parts per billion, ppb) metric,

165

disregarding ozone effects below 35 ppb.17

166

Table 1. Air quality and exposure modelling characteristics for classical air pollutants

167

other than ozone for the considered IPA implementations24, 31, 32 ExternE1998

NewExt2004

NEEDS2009 / Year2013/2013*

Air quality

Windrose Trajectory

Windrose Trajectory

EMEP/MSC-West

model

(Lagrangian) Model

(Lagrangian) Model

Eulerian dispersion model, parameterized

Emission

1990

1998

inventory Meteorology

2010 (projected in 2006)

1990

1998

Average of 1996, 1997, 1998 and 2000

12


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Modelling

Eurogrid

EMEP50

EMEP50

resolution

(100km x 100km)

(50km x 50km)

(50km x 50km)

Population data

EUROSTAT REGIO

EUROSTAT REGIO

SEDAC 2007 and NEEDS

168 169

2.4.3

Particle toxicity

170

Assumptions about the toxicity of different PM compounds relative to primary particles also

171

varied over time: In ExternE1998, sulfates were estimated to be 1.67 times more toxic than

172

nitrates and primary PM10 particles because of their typically smaller size and hence larger

173

damage potential.17, 31 In NewExt2004, due to lacking evidence for its effects, nitrates were

174

assumed to be half as toxic as sulfates and primary particles.24 In NEEDS2009 and

175

Year2013/Year2013*, all types of particles are assumed to be equally toxic,38, 39 although the

176

topic remains debated (cf. section 4.3).

177

2.4.4

178

The four IPA implementations use health-related impact functions that are pollutant (i.e., PM10,

179

PM2.5 and ozone), risk group and age group-specific (Table 2). Driven by new or re-evaluated

180

scientific evidence, changes concerned the risk slope itself, the affected population fraction or

181

the particle size to which impacts are associated. For comparability reasons, we disregarded

182

effects that could not be quantified with EcoSenseWeb, i.e. SO2-related endpoints in

183

ExternE1998 and NewExt2004, and NO2-related endpoints in Year2013/Year2013*. While the

184

latter risks underestimating damage costs, potential double counting with PM impacts and

185

causality issues are debated.35

Impact functions

13



186

Drawing on recommendations by the WHO35, we considered only impact functions with a

187

sufficiently high level of confidence in the 2013 implementations (categories A* and B*

188

according to the HRAPIE (Health Risks of Air Pollution In Europe) project).

189

Since NEEDS2009 and even more so in the Year2013 implementation, endpoints are more

190

frequently related to PM2.5 than to PM10. Some endpoints were dropped for Year2013, e.g.

191

bronchodilator usage, and others have been newly introduced, e.g. asthma symptom days among

192

children due to PM10.

193

For mortality assessment and following HRAPIE, we only considered natural causes, i.e. no

194

deaths due to accidents or other external causes. Two assessment approaches co-exist: While the

195

YOLL (Years Of Life Lost) approach, based on life table calculations,40 was generally advocated

196

in the ExternE project series,17 the U.S. EPA estimates cases of deaths.22 To account for differing

197

expert opinions, both approaches were used in parallel in the CAFE (Clean Air For Europe)

198

Programme41 and the impact assessment underlying the EU Clean Air Policy Package.5 For the

199

IPA implementations we study, mortality risks in adults are expressed in YOLL, while for

200

infants cases of death are estimated.

201

The risk coefficient for cases of premature death due to long-term PM2.5 exposure as provided by

202

the HRAPIE project needs to be converted into EU average YOLL, consistent with earlier

203

projects. For Year2013 and Year2013*, following an expert recommendation,41 the YOLL-based

204

impact function from NEEDS2009 is scaled linearly using the quotient of the relative risk

205

provided by the HRAPIE (0.062 / 10 (µg PM2.5/m³) and the NEEDS project (0.06 / 10 (µg

206

PM2.5/m³)).

14


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207

Table 2. Health-related impact function slopes (sCR) and corresponding risk/age group,

208

expressed in 10 𝜇𝜇

𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖

𝑚³

×𝑝𝑝𝑝𝑝𝑝𝑝×𝑦𝑦𝑦𝑦

and grouped by pollutant24, 35, 42

Endpoint Risk group, age group Ozonea All-cause mortality (acute)b All, all ages Asthma attack Asthmatics, all ages Bronchodilator usage (summertime) Asthmatics, 20+ Cardiovascular hospital admission (excl. stroke) All, 65+ Cough day All, children 5-14 Lower respiratory symptoms (excl. cough) All, children 5-14 Minor restricted activity day (MRAD)c All, 18-64 All, all ages All, adults 18+ Respiratory hospital admission All, 65+ All, all ages Symptom day All, all ages PM10 (primary and secondary) All-cause infant mortality All, infants 0-1 All-cause mortality (chronic) All, 30+ All-cause mortality (acute)b All, all ages Asthma symptom day Asthmatic children, children 5-19 Bronchitis prevalence

Unit

ExternE 1998

NewExt NEEDS Year2013/ 2004 2009 2013*

0.00004

0.00004 0.00002 0.00003

0.4930

0.4930

YOLL days cases 0.7300 cases 0.0005 days 0.9300 days 0.1600 days 0.1154 0.1201 0.0976

0.0976

cases 0.00004

0.00004

0.3307

0.3307

0.0001

0.0001

0.0001

0.0001

days

cases YOLL 0.0072

0.0039

0.00003

0.00003

YOLL days

15


1.7374


Endpoint Risk group, age group All, children 6-12 Bronchodilator usage Asthmatics, 20+ Asthmatics, adults 18+ Asthmatics, children 0-18 PEACE criteria, children 5-14 Cardiac hospital admission All, all ages Cerebrovascular hospital admission All, all ages Chronic bronchitis case All, 18+ All, 27+ All, adults 18+ Chronic bronchitis episode All, children 0-18 Chronic cough All, children 0-18 Congestive heart failure All, 65+ Cough day Asthmatics, adults 18+ Asthmatics, children 0-18 Lower respiratory symptoms (wheeze) Asthmatics, adults 18+ Asthmatics, children 0-18 Lower respiratory symptoms (incl. cough) All, children 5-14 Respiratory symptoms, adults 15+ Respiratory hospital admission All, all ages Restricted activity day (RAD); (RAD – net)d All, adults 18+ PM2.5 (primary and secondary) All-cause mortality (chronic) All, 30+

Unit

ExternE 1998

cases cases

Page 16 of 36

NewExt NEEDS Year2013/ 2004 2009 2013* 0.0149 0.9125

1.6290 0.7790

1.6290 0.7790 0.1825

cases 0.00004 cases 0.0001

0.0001

cases 0.0005 0.0003 0.0005

0.0005

cases 0.0161 cases 0.0207

0.0207

0.0002

0.0002

1.6760 1.3350

3.3520 2.6700

0.6060 1.0290

0.6060 1.0290

cases days

days

days 1.8600 1.3000 cases 0.00002

0.00002 0.00007

0.2499; (0.2472)

0.2499; (0.2472)

days

YOLL

16


0.0107

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Endpoint Risk group, age group All, all ages Cardiovascular hospital admission All, all ages Minor restricted activity day (MRAD) All, 18-64 Respiratory hospital admission All, all ages Restricted activity day (RAD); (RAD – net)d All, all ages

Unit

ExternE 1998

NewExt NEEDS Year2013/ 2004 2009 2013* 0.0065

cases 0.0002 days 0.5772 cases 0.0003 days 0.6061; 0.8930; (0.0957) (0.5853)

days Work loss day (WLD) All, 15-64 0.2070 All, 20-65 0.6385 a Seasonal 6 hour-averages for 1998 and 2004; SOMO35 for 2009 and 2013

209 210 211

b

Assuming 0.75 YOLL per case for ExternE1998/NewExt2004/NEEDS200932 and 1 YOLL per case for Year2013/2013*43

212

c

213 214 215

d

MRAD should be calculated net of asthma attacks due to ozone24

To avoid double counting, net effects are obtained by correcting for work loss days, hospital admission days, minor restricted activity days and symptom days caused by either ozone or PM24, 32, 35

216 217

2.4.5

Monetary valuation

218

Monetary values of specific health endpoints varied over the years (Table 3). Depending on the

219

mortality risk metric, different monetary values are used: YOLL are valued by a so-called Value

220

Of a Life Year (VOLY; previously also abbreviated by VLYL, Value of a Life Year Lost), while

221

cases of death are valued by a Value of a Statistical Life (VSL).44

222

For the Year2013 implementation, we adopt the monetary parameters from the cost-benefit

223

analysis of the EU Clean Air Policy Package.5 This implies that newer evidence for the adult 17



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224

mortality-related VOLY from the NEEDS2009 project is disregarded. Instead, the parameters

225

recommended in the CAFE Programme in 2005, based on NewExt2004, are used.3 To account

226

for differing expert judgments on this crucial parameter, we use alternative values for the

227

Year20135 and Year2013*45 implementation, the latter equaling the NEEDS2009 valuation.

228

Further changes of the Year2013/2013* implementations towards the NEEDS2009

229

implementation concern mortality risks in infants (using the median VSL based on CAFE

230

implies a decrease of 52% compared to NEEDS), restricted activity days (the CAFE valuation is

231

used, being 36% smaller than in NEEDS), chronic bronchitis cases (an updated value from the

232

Health and Environment Integrated Methodology and Toolbox for Scenario Assessment

233

(HEIMTSA) project46 is considered, amounting only to about 25% of the NEEDS valuation), and

234

work loss days (these are valued according to data from the Confederation of British Industry,

235

reducing the NEEDS value by 60%).

236

For ExternE1998, we converted monetary parameters from ECU1995 into €2000 using a factor

237

of 1:1 and an inflation rate of 1.5% for the concerned period. For Year2013/2013* and where

238

necessary, we converted monetary parameters from €2005 to €2000 using an average EU

239

inflation rate of 2.1%.47 Table 3. Monetary values (m) expressed in €2000 for health endpoints5, 24, 31, 32

240

Health endpoint

ExternE1998

NewExt2004 NEEDS2009 Year2013/2013*

Acute mortality (VOLY)

166 979

75 000

60 000a

52 005b/60 000a

Asthma attack

81

75

-

-

18


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241 242


Health endpoint

ExternE1998

NewExt2004 NEEDS2009 Year2013/2013*

Asthma symptom day

-

-

-

38

Bronchitis children (prevalence)

242

-

-

530

Bronchodilator usage

40

40

1

-

Cardiac hospital admission

-

-

2 000

-

Cardiovascular hospital admission

-

-

-

2001

Cerebrovascular hospital admission

8 478

16 730

-

-

Chronic bronchitis case

113 115

169 330

200 000

48 310

Chronic cough

240

-

-

Congestive heart failure

242 8 478

3 260

-

-

Cough (asthmatics)

8

45

-

-

Infant mortality (VSL)

-

-

3 000 000

1 442 086b

Lower respiratory symptoms (wheeze)

9

8

38

-

Lower respiratory symptoms

-

-

38

a

Mortality due to long term exposure (VOLY)

90 847

50 000

40 000

52 005b/40 000a

Minor restricted activity day (MRAD)

48

45

38

38

Respiratory hospital admission

8 478

4 320

2 000

2 001

(Net) Restricted activity day

81

110

130

83

Symptom day

48

45

-

-

Work loss day 295 117 a 48 45, 49 Expressed in €2000; by contrast, the original study presumably uses €2005 as monetary unit, which would reduce the indicated values b

243

median parameter estimate

244

19



245

2.4.6

Damage costs per unit pollution increment

246

Because of the manifold changes in impact functions, population fractions and monetary values

247

over time, different health endpoints are hardly comparable across the IPA implementations.

248

Therefore, we defined marginal damage costs per pollution increment (Cunit in equation (1)). The

249

resulting damage factors for primary particles and ozone are applicable to the general European

250

population, independently of actual exposure levels (cf. Supporting Information, Table S2).

251

20


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Page 21 of 36


252

3 RESULTS

253

3.1 Development of damage costs over time

254

The coal-fired power plant’s health-related damage costs vary between 1.77 (NewExt2004) and

255

5.21 (ExternE1998) €-cent2000 per kWh of electricity produced (Figure 2). Damage costs

256

decreased by 66% from 1998 to 2004, mainly due to reduced mortality impacts, and increased by

257

57% from 2004 to 2009. Depending on assumptions about mortality risk valuation, estimated

258

damage costs either increase by 15% (Year2013) or decrease by 5% (Year2013*) from 2009 to

259

2013. 6.0 5.21


5.0

4.0

+15% 2.78

3.0

-66%

2.0

1.77

3.21

-5%

2.64

+57%

1.0

0.0

260

ExternE1998

NewExt2004

NEEDS2009

Year2013

Year2013*

Morbidity endpoints

0.88

0.59

0.93

0.74

0.74

Mortality endpoints

4.33

1.18

1.85

2.47

1.90

261

Figure 2. Marginal damage costs of a coal-fired power plant unit, estimated with different IPA

262

implementations

21



263

For data availability reasons, only the self-calculated results can be further decomposed (cf.

264

Supporting Information, Figure S1). With 66%/77%/70% (NEEDS2009/Year2013/Year2013*)

265

of all quantified damage costs, mortality due to long-term PM2.5 exposure is by far the most

266

important single health endpoint, consistent with previous observations.14, 50, 51 This is followed

267

by work days lost (10%/7%/10%), net restricted activity days (7%/11%/14%) and chronic

268

bronchitis cases (10%/4%/5%).

269 270

3.2 Quantitative analysis on the influence of single elements in the assessment chain

271

In the following, we study the influence of individual elements of the assessment chain

272

according to equation (1) (Figure 3).

273

Using NEEDS2009 exposure modelling instead of the original exposure modelling reduces the

274

quantified health-related damage costs by 21% and 9.4% for ExternE1998 and NewExt2004,

275

respectively. This implies that human exposure to classical air pollutants was estimated to be

276

higher in 1998 than in 2004 and 2009 for the studied case.

277

Additionally assuming equal instead of differential particle toxicity reduces damage costs by

278

another 17% for ExternE1998 and increases them by 43% for NewExt2004, underlining the

279

importance of particle toxicity in equation (1).

280

When finally using the NEEDS2009 impact function and monetary valuation for long-term

281

exposure mortality, damage costs are reduced by 29% for ExternE1998 and increased by 15%

282

for NewExt2004, bringing both values considerably close to the NEEDS2009 result.

22


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283

Our comparison is limited in that the NEEDS2009-based exposure modelling includes neither

284

ozone-related impacts below the 35 ppb threshold nor direct impacts from SO2. Both types of

285

impacts are included in the original damage costs from ExternE1998 and NewExt2004,

286

explaining partly the residual differences in Figure 3.

287

Given its importance, the development of long-term exposure mortality risk assessment deserves

288

more scrutiny: the original impact function used in 1998 was directly derived from a US study.24

289

Accounting for differences between Europe and the US slightly decreased the impact function in

290

2004. Simultaneously, the associated monetary value was substantially reduced due to a more

291

refined valuation method. From 2004 to 2009, the monetary value decreased further, reflecting

292

updated evidence.45 This change, however, did not reduce damage costs because of the increased

293

toxicity coefficient for secondary particles. From NEEDS2009 to Year2013, the monetary

294

valuation of long-term exposure mortality impacts increased, while the risk slope remained

295

almost constant. Effectively, an increase of damage costs per concentration increment resulted.

296

In the sensitivity case (from NEEDS2009 to Year2013*), the monetary value remained constant

297

while the risk slope slightly increased, thereby rising mortality-related external costs (cf.

298

Supporting Information, Table S2).

23



Page 24 of 36

6.0


5.0 4.0 3.0

5.21 4.14

2.0

3.44 2.45

1.0

1.77 1.60

2.30 2.65

2.78

0.0 ExternE1998

NewExt2004

NEEDS2009

Original Original + NEEDS2009 exposure modelling Original + NEEDS2009 exposure modelling + equal particle toxicity Original + NEEDS2009 exposure modelling + equal particle toxicity + NEEDS2009 long-term mortality assessment

299 300

Figure 3. Influence of exposure modelling, particle toxicity and long-term mortality assessment

301

on health-related damage costs of a coal-fired power plant unit

302

24


Page 25 of 36


303

4 DISCUSSION

304

We compared energy-related health damage cost estimates of four IPA implementations,

305

corresponding to different stages of the ExternE project series and follow-up activities. Referring

306

to recent European recommendations, we proposed and applied two variants of an up to date

307

assessment, differing only in mortality risk valuation.

308

Disentangling influencing factors that are otherwise hidden in estimates of human health-related

309

damage costs is a central achievement of this work, realized through literature research and

310

quantitative analyses. Case study results reveal that exposure modelling accounted for

311

differences between damage costs of up to 21%. Among health endpoints, mortality risks due to

312

long-term PM2.5 exposure are by far the most influential single endpoint (e.g. 76% of the health-

313

related Year2013 damage costs). Particle toxicity assumptions remarkably influence damage

314

costs as well, affecting all PM-related endpoints simultaneously.

315

The presented quantitative findings cannot be generalized because exposure modelling results

316

and corresponding damage costs depend on the emission profile and location of the source. For

317

this reason, we determined source-independent damage costs per concentration increment that

318

confirmed the importance of long term mortality risks relative to other endpoints (cf. Supporting

319

Information, Table S2). Due to data and model accessibility constraints, we could not further

320

analyze the influence of individual exposure modelling components.

321

4.1 Uncertainty and policy implications

322

We focused on variability in health-related damage costs from exposure to classical air pollutants

323

stemming from differences in methodological choices. Further uncertainty sources exist, notably 25



324

data uncertainty underlying risk and monetization-related parameter estimates, and atmospheric

325

modelling-related uncertainty. Specific uncertainty information are lacking for EcoSenseWeb.

326

Some general indications from dedicated uncertainty assessments are nevertheless available.

327

Topics addressed by Holland50 include methodological biases and statistical Monte-Carlo

328

analysis, yielding probability distributions around central estimates of specific health-related

329

endpoints. Spadaro and Rabl56 analytically addressed data uncertainty in inhalation-induced

330

damage costs of classical air pollutants:51 Assuming lognormal parameter distributions, they

331

found the 68% confidence interval of associated damage costs to fall within a range of 1/3 and 3

332

times the geometric mean.

333

The consequences induced by uncertainties in damage costs depend on the application context.

334

While uncertainties in the damage costs are considerable, Rabl et al.52 showed that the associated

335

potential error in political decisions is small when defining efficiency-based emission limit

336

values. This finding relies on the analysis by Spadaro and Rabl56 that however uses different

337

(notably atmospheric) models than those used here. The transferability to our study is thus not

338

straightforward.

339

Speaking of environmental policy making, further information beyond human health damage

340

costs is relevant: for instance, air-pollution induced impacts on other endpoints such as crops,

341

materials and biodiversity/ecosystems should be considered. Following micro economic

342

principles, there is also broad consensus to consider information on spatial and temporal

343

variability in addition to uncertainty when using damage costs in decision making.53

26


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Page 27 of 36


344

4.2 Latest advances in assessing mortality-related damage costs

345

Mortality risk assessment assumptions are not only influential but also debated. In the

346

assessment of the EU’s Clean Air Policy Package, a VSL-based approach for mortality risks in

347

adults with a VSL as large as 2.22 million €2005 per fatality is adopted as upper bound, increasing

348

damage costs 3.4-fold compared to the currently recommended lower-bound VOLY.5 This VSL

349

is relatively close to the value of 3.6 million US$2005 recommended for the EU in a review by the

350

OECD.44 When following US E.P.A.’s recommendation for a VSL of 7.9 million US$2008,

351

however, the difference would substantially increase.54 This shows an important discrepancy

352

between what is currently recommended at both sides of the Atlantic with potentially important

353

policy implications. Even when only varying the VOLY, we found that damage costs for

354

Year2013 and Year2013* differed from NEEDS2009 by +15% and -5% respectively.

355

We excluded long term all-cause mortality impacts in adults from NO2 from our analysis, while

356

noting that the risk of double counting with PM2.5 is at most 33%.35. This disregard is primarily

357

motivated by consistency and causality questions (cf. section 2.4.4).

358

Another subject is the regionalization of impact assessments, e.g. by considering national

359

mortality baseline rates.29, 35 Higher baseline rates, for instance, imply elevated mortality risks

360

due to PM2.5 for Eastern European compared to Central or Western European residents.40

361

Currently limited by data availability, country-specific life expectancy loss assessments would be

362

a next step. Such an approach may suggest region-specific emission reduction strategies. Less

363

developed countries, often suffering from higher pollution levels, therefore risk to be confronted

364

with substantially increased emission reduction requirements and ultimately higher costs.

27



365

Although being economically efficient, a more regionalized health risk evaluation may not be

366

pursued for associated equity concerns.

367

In the same context, the shape of the mortality risk curve as a function of the underlying cause

368

and of background concentration levels is studied.55 We will discuss cause-dependency here.

369

According to latest WHO recommendations,35 specific causes of death are to be assessed in a

370

sensitivity analysis only, while all-cause mortality assessment remains the default approach. This

371

is due to data availability and reliability reasons. Yet, related sources state that using cause-

372

specific risk functions and baseline rates would yield more accurate results.39, 40, 55 In an

373

exploratory study, Amann and Schöpp56 found damage costs to generally increase when

374

assessing cause-specific mortality risks. However, own exemplary estimates for France, carried

375

out independently of the analysis in section 3, yield opposite results: combining risk slopes from

376

the Global Burden of Disease study,57 based on WHO,35 with country-specific background

377

rates58 yields lower mortality risks per pollution increment than an all-cause mortality risk

378

approach. This is mainly due to the substantially lower baseline rates of the four specific cause

379

categories compared to the all-cause mortality baseline rate. Strongly depending on the context

380

and in particular on the choice of baseline rates and risk slopes, the implications of a cause-

381

specific mortality valuation approach thus deserve more research.

382

4.3 Equal or unequal particle toxicity

383

Evidence about the relative toxicity of different particles is ambiguous.39, 59-62 The WHO35, 38

384

recommends equal toxicity for all particle components, as reflected in the two more recent IPA

385

implementations (i.e. NEEDS2009 and Year2013). At the same time, different particle

28


Page 28 of 36

Page 29 of 36


386

components are acknowledged to trigger different health effects, showing ambiguity even within

387

the WHO 35 and a need for further research.

388

4.4 Outlook

389

We identified several points for improvement, e.g. disentangling the influence of different air

390

quality modelling approaches and delving further into parameter uncertainty.

391

As a conclusion and as argued elsewhere,16, 63, 64 if welfare economic instruments such as social

392

cost-benefit analysis to verify the societal efficiency of policies are increasingly integrated into

393

legislation, a harmonized and robust framework for estimating damage costs is needed, allowing

394

competent authorities to base their decisions on comparable grounds. Regarding health-related

395

damage costs in Europe, we currently consider the impact functions proposed by the WHO’s

396

HRAPIE project first choice. A similar harmonized effort for monetary valuation, especially with

397

regard to valuing mortality risks, is currently lacking.

398

Acknowledgement

399

The support of Sonna Pelz (University of Hohenheim) in collecting and compiling data at an

400

early stage of the work is gratefully acknowledged. Helpful comments by the anonymous

401

referees are also acknowledged.

402

Supporting Information

403

Complementary information on the specifications of the emission source used as a case,

404

exposure level-independent damage costs per unit concentration increment and the detailed

405

composition of quantified health-related damage costs is available in the Supporting Information.

406

This material is available free of charge via the internet at http://pubs.acs.org/ . 29



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