Cost-benefit Analysis of Final Policy Scenarios for the EU Clean Air …ec.europa.eu/environment/air/pdf/TSAP CBA.pdf · 2017-09-22 · Cost-benefit Analysis of Final Policy Scenarios

CBA for the Clean Air Policy Package

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Cost-benefit Analysis of Final Policy Scenarios for the EU Clean Air Package Version 2

Corresponding to IIASA TSAP Report 11, Version 2a October 2014


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Author: Mike Holland, EMRC: [email protected]

Acknowledgements: This report was produced under subcontract to IIASA (the International Institute for Applied Systems Analysis, Laxenburg, Austria) for the Service Contract on Monitoring and Assessment of Sectorial Implementation Actions (070307/2011/599257/SER/C3) of DG-Environment of the European Commission. The assistance of staff at IIASA, particularly Chris Heyes who provided input data for the modelling presented here, is gratefully acknowledged. Acknowledgement is also made of the contribution to the methods that underpin this analysis by numerous contributors in the past, particularly members of the ExternE Project team and those who collaborated on the CBA under the CAFE Project and subsequent work on revision of the Gothenburg Protocol and assessment of air pollution co-benefits of climate policies. The modelling approach that has been used for this report has been updated under the EC4MACS (European Consortium for the Modelling of Air pollution and Climate Strategies) project with financial contributions of the LIFE financial instrument of the European Community.

Changes compared to version 1: 1. NO2 effects are identified as unquantified in Table 3.14 and Table 3.15 dealing with healthcare

costs. 2. Minor clarifications to the text. 3. Hyperlinks are provided in the list of references to reviews by concawe. 4. Minor formatting changes.

Disclaimer: The orientation and content of this report cannot be taken as indicating the position of the European Commission or its services.

mailto:[email protected]


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Executive Summary

This report has been prepared as part of the process to inform the revision of the EU’s Thematic Strategy on Air Pollution. The general method used here follow those adopted for the development of the Strategy in 2005 under the Clean Air For Europe (CAFE). Methods have been kept under review since 2005 and refinements made. This includes the adoption of updated health functions, incidence data, etc. for PM2.5 and ozone, based on the REVIHAAP and HRAPIE studies led by WHO-Europe.

The analysis is linked to the work reported in IIASA’s TSAP Report11: The final policy scenarios of the EU Clean Air Policy Package. The IIASA report considers the anticipated development of emissions and their effects over the period to 2030, with detailed scenarios presented for policy analysis for both 2025 and 2030. Results are presented for scenarios describing current legislation (CLE), a Maximum Technically Feasible Reduction (MTFR) scenario, and a series of intermediate scenarios for 2025 and 2030 (see Table 1). Particular interest is given to scenarios developed around a position that approximates the point at which the marginal benefits associated with reducing mortality from PM2.5 exposure are estimated to be equal to marginal costs. Table 1. Policy scenarios considered in this report for 2025 and 2030. Gap closure

Year Scenario IA Option Label Mortality Ozone Eutrophication

2025 CLE 1 0%

2025 B1 6A 25%

2025 B2 6B 50%

2025 B6 70%

2025 B3 6C 75%

2025 B4 6C* 75% 46% 80%

2025 MTFR 6D 100%

2030 CLE 0%

2030 B7 Commission proposal 67%

2030 MTFR 100%

The CBA has focused on the health benefits of improved air quality under the scenarios. Under the CLE baseline scenario for 2025 it is estimated that there would be a shortening of life expectancy across the EU population of 2.7 million life years annually as a consequence of exposure to PM2.5, despite measures that have already been introduced to curb air pollution. This could fall to 2.0 million under the MTFR scenario. Other health impacts estimated for 2025 include 330 million days of restricted activity (RADs) attributable to PM2.5 exposure in the EU28, falling to 240 million under MTFR. In addition to these RADs it is estimated that there would be 82 million lost workdays under CLE, falling to 60 million under MTFR. Partial account has also been taken of damage to crops from ozone and to materials from acid deposition. Table 2 shows the monetised health benefits of pollution controls when moving from the CLE to the MTFR scenarios1. The figures for mortality are based on the most conservative position adopted by the Commission for valuation based on the value of a life year (VOLY). The range shown at the foot of the table includes the use of higher valuations for mortality based on the value of statistical life (VSL).

1 2005 is used as the reference year for prices in this report, for consistency with the analysis reported by IIASA.


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Table 1. Annual benefits of moving from the CLE to the MTFR scenario in 2025 and 2030 across the EU28, €million/year, 2005 prices.

Endpoint CLE – MTFR, 2025 CLE – MTFR, 2030

Particulate matter

Chronic Mortality (All ages) median VOLY 42,605 41,623

Infant Mortality (0-1yr) median VSL 198 185

Morbidity 16,187 16,388

Ozone

Acute Mortality (All ages) median VOLY 161 160

Morbidity 595 599

Total health benefits

Mortality only (median VOLY, median VSL for infant mortality)

42,424 41,968

Mortality and morbidity (median VOLY, median VSL for infant mortality)

57,996 57,759

Range 57,966 – 198,377 57,759 – 207,054

Results indicate that all EU member states would derive a net benefit (benefit – cost) for moving from CLE to the B3 scenario in 2025 and to the B7 scenario in 2030 (see Tables 2 and 3), across all of the mortality valuation positions explored. When moving further, to the MTFR scenario, costs exceed benefits for all cases except the least conservative position on mortality valuation.

Table 2. Net health benefits of the scenarios for 2025, €M/year - EU28.

Net benefits, EU28 CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 -

MTFR

Costs 222 979 2,138 1,289 51 42,327

Net benefits

Total with median VOLY 14,176 13,344 9,482 1,609 -42 -27,579

Total with mean VOLY 28,987 28,056 21,444 4,559 -35 -12,638

Total with median VSL 25,864 25,513 18,794 4,044 -58 -15,907

Total with mean VSL 48,994 49,070 37,340 8,762 -72 7,277

Table 3. Net health benefits of the scenarios for 2030, €M/year - EU28.

Net benefits, EU28 CLE - B7 B7 - MTFR

Costs 3,334 47,347

Net benefits

Total with median VOLY 35,140 -28,063

Total with mean VOLY 74,437 -8,606

Total with median VSL 70,012 -11,059

Total with mean VSL 135,371 21,002

The report provides a breakdown of results by country as well as by the totals referred to here. A limitation of this report is that the benefits analysis is incomplete, most importantly with respect to: 1. Impacts of eutrophication on ecosystems. Modelling work has demonstrated widespread

exceedance of the critical load for eutrophication, with concern focusing particularly on loss of biodiversity.

2. Impacts of NO2 exposure on health. The WHO HRAPIE study recommends the application of functions for NO2 impacts on mortality, respiratory hospital admissions and childhood bronchitis. An outline assessment has indicated that associated impacts could be substantial. However, further work is needed to characterise the link between estimated NO2 exposure and the recommended response functions.


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Contents

1 INTRODUCTION ....................................................................................................................................... 5 1.1 BACKGROUND ..................................................................................................................................................... 5 1.2 SCENARIOS CONSIDERED .................................................................................................................................. 6 1.3 SCOPE ................................................................................................................................................................... 6

2 METHODS .................................................................................................................................................. 7 2.1 OVERVIEW........................................................................................................................................................... 7 2.2 BACKGROUND TO THE METHODS FOR BENEFITS ASSESSMENT .................................................................. 8 2.3 HEALTH IMPACT ASSESSMENT ......................................................................................................................... 8 2.4 VALUATION OF HEALTH IMPACTS ................................................................................................................ 11 2.5 NON HEALTH IMPACTS ................................................................................................................................... 14

3 HEALTH BENEFITS .............................................................................................................................. 15 3.1 TRENDS, 2010 TO 2030 ............................................................................................................................... 15 3.2 AGGREGATED RESULTS FOR THE EUROPEAN AND EU28 REGIONS: 2025 SCENARIOS ...................... 16 3.3 AGGREGATED RESULTS FOR THE EUROPEAN AND EU28 REGIONS: 2030 SCENARIOS ...................... 20 3.4 SENSITIVITY ANALYSIS: CHRONIC EXPOSURE AND OZONE MORTALITY ................................................. 22 3.5 IMPACTS ON LOST WORKING DAYS AND HEALTH CARE EXPENDITURE .................................................. 23 3.6 NATIONAL RESULTS ........................................................................................................................................ 27

4 NON-HEALTH BENEFITS .................................................................................................................... 28 4.1 MONETISED NON-HEALTH BENEFITS .......................................................................................................... 28 4.2 UN-MONETISED NON-HEALTH BENEFITS ................................................................................................... 31

5 COST-BENEFIT ANALYSIS .................................................................................................................. 32 5.1 COST DATA ....................................................................................................................................................... 32 5.2 COMPARISON OF COSTS AND HEALTH BENEFITS ....................................................................................... 32

6 DISCUSSION ............................................................................................................................................ 36

7 REFERENCES .......................................................................................................................................... 37

APPENDIX 1: RESPONSE TO STAKEHOLDER COMMENTS ............................................................... 42

APPENDIX 2: COMPARISON OF RESULTS FOLLOWING CAFE AND HRAPIE RECOMMENDATIONS ................................................................................................................................... 44

APPENDIX 3: KEY INDICATORS BY COUNTRY FOR THE BASELINE SCENARIOS, 2010 TO 2030 ................................................................................................................................................................... 47

APPENDIX 4: KEY HEALTH INDICATORS BY COUNTRY FOR THE POLICY SCENARIOS, 2025 AND 2030 ......................................................................................................................................................... 53

APPENDIX 5: TOTAL NATIONAL DAMAGE (COSTED AT EU AVERAGE) UNDER THE POLICY SCENARIOS ....................................................................................................................................................... 64

APPENDIX 6: POLICY SCENARIO COST INCREMENT OVER CLE SCENARIO FROM GAINS FOR 2025 AND 2030 (AMANN, 2014) .............................................................................................................. 66


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1 Introduction

1.1 Background On December 18, 2013, the European Commission adopted a Clean Air Policy Package with the aim of further reducing the impacts of harmful emissions of air pollutants from industry, traffic, energy plants and agriculture on human health and the environment (EC, 2013a). The package includes a new Clean Air Programme for Europe with measures to ensure that existing targets are met in the short term, and new air quality objectives for the period up to 2030. The package also proposes a revised Directive on National Emission Ceilings with stricter national emission ceilings for the six main pollutants, as well as a new Directive to reduce pollution from medium-sized combustion installations. The process has been informed by analysis using the GAINS Integrated Assessment Modelling suite by the International Institute for Applied Systems Analysis (IIASA: Amann et al, 2012abc, 2013) complemented by cost-benefit analysis (Holland, 2013a). These reports have been presented to stakeholders, and comments received from stakeholders have been considered in subsequent analysis. Key results from Holland (2013a) are shown in Table 1.1, demonstrating the magnitude of economic benefits through improved health as a result of moving from the Current Legislation (CLE) scenario to the Maximum Technically Feasible Reduction (MTFR) scenario for the years 2025 and 2030.

Table 1.1. Initial estimate of benefits from moving from the CLE to the MTFR scenario, EU28, €million/year, 2005 prices (Holland, 2013a).

Endpoint CLE – MTFR, 2025 CLE – MTFR, 2030

Particulate matter

Chronic Mortality (All ages) LYL median VOLY 41,231 40,730

Infant Mortality (0-1yr) median VSL 194 180

Morbidity (core functions) 17,949 18,063

Morbidity (sensitivity functions) 2,292 2,497

Ozone

Acute Mortality (All ages) median VOLY 147 145

Morbidity (core functions) 299 290

Morbidity (sensitivity functions) 1,386 1,392

Total health benefits

Most conservative estimate: Mortality only 41,378 40,875

Most conservative estimate: Mortality and morbidity

59,800 59,400

Range 59,800 – 201,000 59,400 – 210,000

Based on the findings of TSAP Report #10 (Amann et al, 2013), comments provided by stakeholders, and extensive further analyses, the Commission Services produced a comprehensive impact assessment for the revision of the EU air quality that laid out the main policy options (EC, 2013b). This impact assessment provided the quantitative basis for discussions within the college of the European Commission, which led to the adoption of the final proposal in late 2013. This report provides the cost-benefit analysis to complement TSAP report #11 (Amann et al, 2014). It documents the key scenarios (Scenario series B) that have led to the proposal of the European Commission on new Clean Air Policy package.


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1.2 Scenarios considered Results are presented for the following scenarios:

A set of scenarios for the year 2025: Current legislation (CLE), B1, B2, B6, B3, B4, MTFR (Maximum Technically Feasible Reduction)

A set of scenarios for the year 2030: CLE, B7, MTFR

Actual/projected current legislation emissions for 2010, 2015, 2020, 2025 and 2030. The scenarios for 2025 and 2030 vary in the ambition levels set for mortality linked to PM2.5 exposure, ozone and eutrophication. The following table shows the correspondence between the scenarios presented here and those in the Commission’s Impact Assessment, together with information on the percentage ‘gap closure’ between the current legislation and MTFR scenarios defined for optimisation of the GAINS model.

Table 1.2. Scenarios assessed in this report

Gap closure

Year Scenario IA Option Label Mortality Ozone Eutrophication

2025 CLE 1 0%

2025 B1 6A 25%

2025 B2 6B 50%

2025 B6 70%

2025 B3 6C 75%

2025 B4 6C* 75% 46% 80%

2025 MTFR 6D 100%

2030 CLE 0%

2030 B7 Commission proposal 67%

2030 MTFR 100%

1.3 Scope The analysis presented here is focused primarily on the assessment of health impacts across Europe in 2025 and 2030 for the scenarios listed above. Past work (e.g. Holland et al, 2011, 2013a) has found that health impacts dominate European air pollution CBAs, though this is in part a function of the problem of quantifying ecosystem damage/benefits in monetary terms for integration to the CBA. The analysis is extended here to include effects on building materials in some applications (though excluding cultural heritage) and crops, and to provide additional detail on issues such as productivity losses and healthcare costs. It does not, however, include assessment of impacts to ecosystems.


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2 Methods

2.1 Overview

The basis for the methods used here is the impact pathway approach developed under the ExternE project (ExternE, 1995, 1999, 2005) and the CBA for the Clean Air For Europe (CAFE) Programme, and illustrated in Figure 2-1. This approach follows a logical progression from emission, through dispersion and exposure to quantification of impacts and their valuation.

Figure 2-1. Impact Pathway Approach, tracing the consequences of pollutant release from emission to impact and economic value.

Emission(NH3, NOx, PM2.5, SO2, VOCs)

Dispersion, atmospheric chemistry(primary and secondary particles, ozone, NO2)

Exposure(people, crops, buildings, etc.)

Impact(mortality, morbidity, crop loss, materials

damage, etc.)

Economic value

The general form of the equation for the calculation of impacts is:

Impact = Pollution level x Stock at risk x Response function Pollution may be expressed in terms of:

Concentration, for example in the case of impacts to human health where exposure to the pollutants of interest to this study occurs through inhalation, or

Deposition, for example in the case of damage to building materials where damage is related to the amount of pollutant deposited on the surface.

The term ‘stock at risk’ relates to the amount of sensitive material (people, ecosystems, materials, etc.) present in the modelled domain. For the health impact assessment, account is taken of the


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distribution of population and of effects on demographics within the population, such as children, the elderly, or those of working age. Incidence and prevalence rates are used to modify the stock at risk for each type of impact quantified. Improved data availability has enabled this report to use country-specific rate data to a much greater degree than before.

2.2 Background to the methods for benefits assessment

The methods used by Holland et al (1999) and Holland and King (1998) for CBA of the original Gothenburg Protocol and EU NEC Directive were developed under the European Commission-funded ExternE (Externalities of Energy) Project during the 1990s. Whilst that work had been extensively reviewed during its development it was considered appropriate for the EU’s CAFE Programme to conduct a thorough review of the methods, to consult widely with stakeholders and to subject the methodology to a formal, independent and international peer review. This is documented as follows:

Methodology Volume 1: Overview of Methodology (Holland et al, 2005a)

Methodology Volume 2: Health Impact Assessment (Hurley et al, 2005)

Methodology Volume 3: Uncertainty in the CAFE-CBA (Holland, 2005b)

Peer review: Krupnick et al (2005) The methods developed under CAFE remain broadly applicable now, though some changes were made for the Gothenburg Protocol analysis (Holland et al, 2011). The most recent full account of the benefits assessment methods was provided for the EC4MACS study (Holland et al, 2013b). That report includes conclusions from the REVIHAAP project regarding updated mortality assessment for ozone and PM (WHO, 2013a). Subsequent work on the HRAPIE project (WHO, 2013b) provides further information on morbidity impacts (hospital admissions, incidence of bronchitis, lost work days, etc.), and has been used here. Other ongoing developments on ecological impact assessment, for example under the EC funded ECLAIRE Project are not sufficiently advanced for inclusion in the methods adopted here at this time. Comments received from stakeholders were noted (see Appendix 1). Relative to the analysis performed for the CAFE Programme in 2005 there have been a number of refinements to the dispersion modelling carried out by EMEP:

Use of a finer geographic resolution

Use of updated transfer matrices

The inclusion of fine secondary organic aerosol

The inclusion of a portion (27%) of what was earlier described as ‘coarse nitrate aerosol’ in estimated concentrations of PM2.5.

2.3 Health impact assessment

For the earliest analysis performed to inform review of the Thematic Strategy the health response functions adopted were those used in the earlier CAFE CBA work (Hurley et al, 2005). These are listed in Table 2.1, with details of the population considered for each effect. For the CAFE CBA two sets of response functions were identified, those for which evidence was considered most robust were grouped as the ‘core’ set whilst those for which quantification was considered less robust formed a ‘sensitivity’ set. In practice, the sensitivity functions were seldom used; although they extended the list of effects for quantification quite significantly, their contribution to total damage was small. In any case, the question of whether or not to include the sensitivity functions becomes insignificant when compared to other uncertainties, principally those associated with mortality valuation and the relative harm linked to different types of particle, and they were therefore not applied in analysis to support review of the Thematic Strategy. In line with WHO advice, all particles, irrespective of source2 and chemical composition, were considered equally harmful. Table 2.1 notes that the effect of chronic exposure to PM2.5 on mortality can be expressed in two ways, in terms of the loss of life expectancy (expressed as the total number of years of life lost [YOLL]

2 This excludes particles from natural sources as they are not included in the modelling, as they are not controllable using the measures considered in the setting of emission ceilings.


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annually across the affected population) and the number of deaths brought forward (expressed as number of cases (deaths) per year). The loss of life expectancy is the preferred measure of impact on theoretical and practical grounds, though deaths brought forward is included for valuation purposes. The two estimates are not additive. Quantification of impacts only against exposure to ozone and PM2.5 was not intended to indicate that there are no effects of exposure to NO2 and SO2 on health. However, under CAFE it was felt that separate inclusion of functions for these pollutants would incur at least some double counting of the effects quantified when using the functions based on PM2.5 exposure, so it was not done.

Table 2.1. List of health impacts - core set from CAFE CBA.

Impact / population group Population Exposure metric

Mortality from acute exposure All ages O3, SOMO35

Respiratory Hospital Admissions Over 65 years O3, SOMO35

Minor Restricted Activity Days (MRADs) 15 to 64 years O3, SOMO35

Respiratory medication use Adults over 20 years

O3, SOMO35

Mortality from chronic exposure as life years lost or premature deaths

Over 30 years PM2.5, annual average

Infant Mortality 1 month to 1 year PM2.5, annual average

Chronic Bronchitis Over 27 years PM2.5, annual average

Respiratory Hospital Admissions All ages PM2.5, annual average

Cardiac Hospital Admissions All ages PM2.5, annual average

Restricted Activity Days (RADs) 15 to 64 years PM2.5, annual average

Including lost working days

15 to 64 years PM2.5, annual average

Respiratory medication use 5 to 14 years PM2.5, annual average

Respiratory medication use Over 20 years PM2.5, annual average

Lower Respiratory Symptom days 5 to 14 years PM2.5, annual average

Lower Respiratory Symptom days Over 15 years PM2.5, annual average

Shortly before completion of this analysis, the final recommendations of the HRAPIE study were received, generating a new set of functions for quantification (Table 2.2). HRAPIE recommends that the functions for which confidence is highest be given an ‘A’ rating and those for which confidence is less (though still sufficiently high to be quantified) be given a ‘B’ rating. This is supplemented by ‘*’ for effects that are additive. Effects that are not additive can be quantified to provide additional information, though this has not been performed here. In practice it has not been possible to apply the HRAPIE recommendations in full. The main reasons for this are as follows:

For ozone, SOMO10 exposure data are currently unavailable.

For NO2, there is a lack of agreement regarding the extent to which exposure data quantified using EMEP outputs properly reflect exposure of the population. Quantification of NO2 effects has therefore not been attempted.

For effects of chronic exposure to ozone and NO2 (leaving aside the issues of exposure modelling) on mortality, protocols for dealing with the potential for double counting against the function applied for PM2.5 have not been agreed. Neither is therefore added into total benefits. The HRAPIE report states that: ”Some of the long-term NO2 effects may overlap with effects from long-term PM2.5 (up to 33%).” This statement could of course be turned around to say that at least 67% of the NO2 impact is not accounted for within the PM2.5 function, providing a bias to underestimation.


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Table 2.2. List of health impacts – HRAPIE recommendations.

Impact / population group Rating Population Exposure metric

All cause mortality from chronic exposure B Over 30 years O3, SOMO35, summer months

All cause mortality from acute exposure A*/A All ages O3, SOMO35 (A*), SOMO10 (A)

Cardiac and respiratory mortality from acute exposure

A All ages O3, SOMO35 (A*), SOMO10 (A)

Respiratory Hospital Admissions A*/A Over 65 years O3, SOMO35 (A*), SOMO10 (A)

Cardiovascular hospital admissions A*/A Over 65 years O3, SOMO35 (A*), SOMO10 (A)

Minor Restricted Activity Days (MRADs) B*/B All ages

O3, SOMO35 (B*), SOMO10 (B)

All cause mortality from chronic exposure as life years lost or premature deaths

A* Over 30 years PM2.5, annual average

Cause-specific mortality from chronic exposure

A Over 30 years PM2.5, annual average

Infant Mortality B* 1 month to 1 year PM2.5, annual average

Chronic bronchitis in adults B* Over 27 years PM2.5, annual average

Bronchitis in children B* 6 – 12 years PM2.5, annual average

All cause mortality from acute exposure A All ages PM2.5, annual average

Respiratory Hospital Admissions A* All ages PM2.5, annual average

Cardiovascular Hospital Admissions A* All ages PM2.5, annual average

Restricted Activity Days (RADs) B* All PM2.5, annual average

Including lost working days

B* 15 to 64 years PM2.5, annual average

Asthma symptoms in asthmatic children B*

5 to 19 years PM2.5, annual average

All cause mortality from chronic exposure B* Over 30 years NO2 annual mean >20ug.m-3

All cause mortality from acute exposure A* All ages NO2 annual mean Bronchitis in children B* 5 – 14 years NO2 annual mean Respiratory hospital admissions A* All ages NO2 annual mean

Despite some obvious differences, there remains much consistency between the CAFE and HRAPIE recommendations for the purpose of the analysis performed here, with the analysis for mortality impacts little changed and the morbidity effects that generate the largest economic damage (chronic bronchitis and restricted activity days, RADs) being retained. Comparison with the effects included in the USEPA’s CBA of the US Clean Air Act also shows much common ground with the recommendations of HRAPIE (Figure 2-2, reproducing Table 5-1 of USEPA, 2011).

Figure 2-2. Effects included and omitted from the CBA of the US Clean Air Act.


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This Table suggests that the HRAPIE recommendations could be seen as cautious in some areas, for example through omission of ozone effects on school attendance and outdoor productivity. It also indicates that there is evidence for an association between air pollution and numerous unquantified health endpoints.

2.4 Valuation of health impacts

Valuation is performed by multiplying impacts (e.g. respiratory hospital admissions) by an appropriate estimate of the unit value of each impact (e.g. the cost of a respiratory hospital admission). Unit values seek to describe the full economic effect of the impacts that they are linked with. For health impacts, for example, which dominate the analysis, this will include elements associated with the costs of health care, lost productivity amongst workers and aversion to premature death or ill health. Valuation data have been updated since the CAFE work was completed to 2005 prices for consistency with the cost data generated by the current version of the GAINS model (an increase over 2000 values of 11% for the health impacts). Associated values linked to the CAFE function set are shown in Table 2.3.

Table 2.3. Values for the health impact assessment in CAFE (price year 2005)

Impact / population group Unit cost Unit

Ozone effects

Mortality from acute exposure 57,700 / 138,700 €/life year lost (VOLY)

Respiratory Hospital Admissions 2,220 €/hospital admission

Minor Restricted Activity Days (MRADs) 42 €/day

Respiratory medication use 1 €/day of medication use

PM2.5 effects

Mortality from chronic exposure as: Life years lost, or Premature deaths

57,700 / 133,000 1.09 / 2.22 million

€/life year lost (VOLY)

€/death (VSL)

Infant Mortality 1.6 to 3.3 million €/case

Chronic Bronchitis 208,000 €/new case of chronic bronchitis


Cardiac Hospital Admissions 2,220 €/hospital admission

Restricted Activity Days (RADs) 92 €/day

Respiratory medication use 1 €/day of medication use

Lower Respiratory Symptom days 42 €/day

As discussed above, mortality impacts are quantified both in terms of deaths brought forward and the loss of life expectancy. Deaths are valued using a long-established metric, the value of statistical life (VSL, also known as the value of a prevented fatality, VPF), whilst changes in life expectancy are valued using the value of a life year (VOLY). For the CAFE CBA methodology, the independent external peer reviewers and several stakeholders suggested that both the VSL and the VOLY approaches be used, to show transparently the variation in results arising from use of these two approaches. In CAFE, ozone related mortality was treated differently, with only the VOLY being applied. Unlike PM mortality effects which are related to long-term exposure in our methodology and that generate a substantial change in life expectancy, the effect of ozone on mortality was linked only to short term exposures. More recent work (e.g. Jerrett et al, 2009) provides evidence of a link between mortality and long-term exposure. Estimates are, therefore, provided here for the chronic mortality impact of ozone as a sensitivity case. The set of values described above requires adaptation for use with the HRAPIE recommendations on concentration-response functions partly because of differences in the effects covered and partly in response to the emergence of new information since the CAFE work was completed.


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Table 2.4. Updated values for the health impact assessment (price year 2005)

Impact / population group Unit cost Unit

Ozone effects


57,700 / 133,000 1.09 / 2.22 million


€/death (VSL)



Cardiovascular Hospital Admissions 2,220 €/hospital admission

Minor Restricted Activity Days (MRADs)

42 €/day

PM2.5 effects

Mortality from chronic exposure as: Life years lost, or Premature deaths (all-cause and cause-specific mortality)

57,700 / 133,000 1.09 / 2.22 million


€/death (VSL)


Infant Mortality 1.6 to 3.3 million €/case

Chronic Bronchitis in adults 53,600 €/new case of chronic bronchitis

Bronchitis in children 588 €/case


Cardiac Hospital Admissions 2,220 €/hospital admission

Restricted Activity Days (RADs) 92 €/day

Work loss days 130 €/day

Asthma symptoms, asthmatic children

42 €/day

NO2 effects (though not quantified in this report)


57,700 / 133,000 1.09 / 2.22 million


€/death (VSL)


Bronchitis in children 588 €/case

Respiratory Hospital Admissions

2,220 €/hospital admission

The differences between Table 2.3 and Table 2.4 are as follows:

1. Removal of respiratory medication use (not considered by HRAPIE as the impact has previously been shown to make an insignificant contribution to total damage). Removal of lower respiratory symptom days as there may be some overlap with restricted activity days. Inclusion of asthma symptoms for asthmatic children.

2. Addition of bronchitis in children. This effect lasts for about 2 weeks and has been valued as 14 days at €42/day3 (€588). Aggregation of WTP values in this fashion carries a bias to

overestimation, though here there are a number of mitigating factors: a. The view that effects on children should be valued more highly than those on adults

(Scapecchi, in OECD, 2006). b. The assumption that affected children are impacted only once annually. The definition

applied in the epidemiology literature is whether children had experienced bronchitis in the past year, which leaves open the question of how many episodes they may have experienced.

c. The limitation of the analysis to children aged 6 to 12 years. This reflects the age group studied in the epidemiology literature (Hoek et al, 2012), which was restricted to avoid inclusion of children who were ‘undeclared’ smokers. The HRAPIE report provides some leeway to extending the age group covered to 6 to 18 (effectively

3 This being the value associated with a symptom day in Table 2.4.


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doubling the population at risk). Discussion with the HRAPIE team indicated that sensitivity may persist to around age 22, further extending the population at risk.

d. The likelihood that parents would need to take time off work to care for children. Being linked to long-term exposure, such effects would not be included in the assessment of work days lost.

e. The value obtained is broadly consistent with the $400 WTP for children suffering bronchitis for one week, measured by Dickie and Ulery (2001).

Overall, therefore, it is considered that the approach taken for valuation of this endpoint is a reasonable compromise.

3. The value for chronic bronchitis in adults has been reduced to €53,600, linked to the central value recommended for chronic bronchitis from the literature review in the HEIMTSA study (Hunt et al, 2011: €60,000 in 2010 prices). The decision to reduce the valuation is based on discussion with the HRAPIE team concerning the interpretation of ‘chronic bronchitis’. It is noted that the valuation applied by USEPA (2011, Table 5.4) is considerably higher, in the region of $450,000 (also considerably higher than the CAFE estimate of €208,000). The figure adopted is also towards the lower end of the range of $9,000 to $340,000 described by Abt Associates (2012, Table I-3) for use in the US BenMap model.

4. The valuation of work loss days was bound up with the valuation of restricted activity days in the CAFE work, with a value of €94/day (at 2005 rates) being applied, based on assessment of the costs of absenteeism to employers by the Confederation of British Industry (CBI, 1998). This value included only direct costs to employers, covering sick pay, lost output and provision of cover through temporary staff or overtime. It did not include indirect costs related to lower customer satisfaction and poorer quality of products or services leading to a loss of future business, which were estimated to be roughly twice as high as direct costs, though subject to higher uncertainty. A revised valuation here takes account of more recent publications from CBI covering the years 2010 (CBI, 2011) and 2012 (CBI, 2013) to provide a value of €130/day for the EU in 2005 prices, though this still excludes the indirect costs.

Databases from WHO provide further information on the time spent in hospital and on the ‘hotel’ costs of hospitalisation (‘hotel’ costs, not including the costs of specific treatments). These suggest that the costing adopted in CAFE and retained here underestimates costs. In CAFE, it was assumed that the average time spent in hospital following admission for respiratory or cardiac illness would be 3 days. WHO’s Hospital Morbidity Database instead indicates 7.3 days for respiratory admissions and 8.6 days for cardiovascular admissions as an average for EU countries. WHO’s CHOICE database then indicates that that the ‘hotel’ costs of hospitalisation are on average in the region of €280/day for the EU. Put together these data suggest that total ‘hotel’ costs per hospital admission are around €2,240, slightly greater than the figure shown in Table 2.4, but lacking treatment costs and the WTP not to require hospitalisation and the pain and suffering that goes with it. The CAFE values are representative of willingness to pay in EU Member States. Being based in willingness to pay, they are income dependent. For the CBA of the Gothenburg Protocol both estimated average EU-values and average values for the wider UNECE region (adjusted using population weighted PPP4-adjusted GDP/capita) were used to demonstrate sensitivity to assumptions

made at this point. The difference between the original EU valuations and the UNECE-Europe equivalent was shown to be small; the latter being lower by 18%. Here, however, only EU-averaged valuations are applied, given that the scenarios are focused on emission reductions within the EU. The results of the benefits analysis used by Amann et al (2013) to assess the point at which marginal costs and benefits are equal considered only impacts within the EU28. Consideration is given in the discussion at the end of this report to the likely effects of applying the VOLY derived by Desaigues et al (2011) and to the major review by OECD on the use of VSL to inform environmental policy making. A comparison of results based on CAFE and HRAPIE functions is provided in Appendix 2. It is concluded that differences in monetised damage estimates are small, slightly lower (around 5%) for HRAPIE than CAFE, but lacking quantification of effects of NO2.

4 Purchasing power parity


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2.5 Non health impacts

Detailed quantification of effects of the policy scenarios on ozone damage to crops and acid damage to buildings requires additional pollutant metrics to those made available for this analysis. A simpler approach has therefore been taken, details of which were given by Holland et al (2011). It is noted that there are several limitations of this approach for quantifying non-health impacts:

It only permits quantification of crop and ‘utilitarian’ material damage.

It does not fully quantify effects on either utilitarian buildings or crops. For example, no account is taken of changes in the productivity of grassland that may impact production of livestock and associated goods, and no account is taken of the effects of particle emissions on building soiling.

It only accounts for effects within the EU.

It is based on emission scenarios for 2010, which may introduce significant error, particularly for ozone impacts due to their non-linearities and dependence on the overall pollution climate.

Damage to other non-health receptors, notably ecosystems and cultural heritage, has not been quantified.


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3 Health benefits

3.1 Trends, 2010 to 2030 The first part of the analysis shows how effects change over time, from 2010 to 2030 using reported emissions for 2010 and estimated emissions under current legislation for future years. Trends in impacts are shown with respect to mortality from exposure to ozone and PM2.5 (Figure 3-1), for which there is a 27% and 37% reduction in estimated impact respectively.

0.00

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2010 2015 2020 2025 2030

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Figure 3-1. Mortality trends for the EU28 linked to reduced exposure to PM2.5 and ozone (expressed as SOMO35) from 2010 to 2030.

Further details are presented by Member State in Appendix 3. Results are presented in aggregated monetised form in Figure 3-2, covering all quantified health impacts based on the HRAPIE function set. The range shown demonstrates sensitivity to mortality valuation based on the median-VOLY to mean-VSL interval. The fall in damage over time follows the trajectory for reduced PM2.5 impacts very closely as these dominate the health impact assessment at present. However, it is to be remembered that it has not been possible to quantify NO2 related impacts here, which would clearly add to the estimated damage shown in the Figure.


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0

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2010 2015 2020 2025 2030

€billion/year

Figure 3-2. Trends in air pollution related health damage costs for the EU28 from 2010 to 2030 (2005 prices, with range based on median-VOLY to mean-VSL valuation).

3.2 Aggregated results for the European and EU28 regions: 2025 scenarios The Tables below provide the following results for 2025: Table 3.1. Estimated annual health impacts due to air pollution, EU28. Table 3.2. Change in estimated annual health benefits between scenarios, EU28. Table 3.3. Monetised equivalent of health impacts due to air pollution, EU28. Table 3.4. Benefits from comparison between scenarios, EU28. Further results are provided by country in Appendix 4. These tables indicate substantial health benefits from moving from the CLE scenario to the MTFR scenario, with each 25% of gap closure between the two scenarios reducing health damage by between €14 and €50 billion per year (the range reflecting alternative assumptions on valuation). There are over 2.7 million life years lost per year in the EU28 under the baseline scenario and many more cases of hospital admissions, chronic bronchitis and various effects that may be thought of as minor in individual severity, but which affect a large number of people. For effects quantified against PM2.5 exposure it is estimated that moving to the MTFR scenario would reduce impacts by approximately one quarter. There is estimated to be a slightly lower reduction in ozone impacts (around one sixth of total impacts for ozone). Considering the distribution of monetary damage across impact categories it is clear that effects quantified against PM2.5 exposure greatly dominate effects quantified against ozone exposure. Overall, taking the most conservative valuation of mortality, effects of chronic exposure on mortality account for around three quarters of damage. Amongst the morbidity effects, chronic bronchitis, restricted activity days, and lost working days all make significant contributions. In contrast, infant mortality, hospital admissions and asthma symptom days make a negligible contribution to the total damage. Differences between the B3 and B4 scenario are small according to these tables. Appling the VOLY for mortality valuation generates a slight benefit in the transition between the two, applying the VSL gives a slight disbenefit. However, the added benefits of B4 are focused on protection of ecosystems and hence do not show up in these tables.


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Table 3.1. Estimated annual health impacts due to air pollution, 2025, EU28.

IMPACTS CLE B1 B2 B6 B3 B4 MTFR

2025 2025 2025 2025 2025 2025 2025

Acute Mortality (all ages) Prem. deaths O3 17,795 17,520 17,315 16,717 16,566 16,510 15,011

Respiratory hospital admissions (>64) Cases O3 19,079 18,775 18,571 17,955 17,803 17,738 16,167

Cardiovascular hospital admissions (>64) Cases O3 84,022 82,710 81,762 78,856 78,161 77,902 70,661

Minor Restricted Activity Days (all ages) Days O3 85,595,047 84,247,271 83,291,248 80,456,626 79,750,856 79,475,968 72,287,989

Chronic Mortality (30yr +) * Life years lost PM 2,709,099 2,526,849 2,345,736 2,198,934 2,162,716 2,162,693 1,980,065

Chronic Mortality (30yr +) * Prem. deaths PM 306,543 286,122 265,322 248,958 244,795 244,807 224,360

Infant Mortality (0-1yr) Prem. deaths PM 443 413 384 358 353 352 322

Chronic Bronchitis (27yr +) Cases PM 241,927 225,672 209,236 196,547 193,258 193,304 177,100

Bronchitis in children aged 6 to 12 Cases PM 774,889 722,834 671,547 630,707 620,289 620,338 567,852

Respiratory Hospital Admissions (All ages) Cases PM 104,858 97,691 91,005 85,160 83,729 83,717 76,653

Cardiac Hospital Admissions (>18 years) Cases PM 80,462 75,177 69,951 65,490 64,383 64,369 58,970

Restricted Activity Days (all ages) Days PM 330,056,263 307,877,833 285,398,338 268,138,003 263,687,287 263,748,898 241,530,373

Asthma symptom days (children 5-19yr) Days PM 8,172,500 7,623,421 7,074,662 6,660,901 6,548,851 6,550,771 6,002,655

Lost working days (15-64 years) Days PM 81,805,617 76,312,826 70,982,844 66,601,781 65,471,611 65,474,984 60,036,338

life years lost and deaths from chronic exposure to PM2.5 are alternate measures of the same effect


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Table 3.2. Reduction in estimated annual health impacts between scenarios, 2025, EU28.

IMPACTS CLE - B1 B1 - B2 B2 - B6 B6-B3 B3 - B4 B4 - MTFR

2025 2025 2025 2025 2025 2025

Acute Mortality (all ages) Prem. deaths O3 275 205 598 151 56 1,499

Respiratory hospital admissions (>64) Cases O3 305 203 616 152 65 1,571

Cardiovascular hospital admissions (>64) Cases O3 1,312 947 2,907 694 260 7,241

Minor Restricted Activity Days (all ages) Days O3 1,347,776 956,023 2,834,622 705,771 274,888 7,187,978

Chronic Mortality (30yr +) * Life years lost PM 182,250 181,113 146,803 36,218 23 182,628

Chronic Mortality (30yr +) * Prem. deaths PM 20,421 20,800 16,364 4,163 -13 20,447

Infant Mortality (0-1yr) Prem. deaths PM 30 29 26 6 0 30

Chronic Bronchitis (27yr +) Cases PM 16,255 16,436 12,689 3,288 -46 16,204

Bronchitis in children aged 6 to 12 Cases PM 52,055 51,287 40,839 10,419 -49 52,486

Respiratory Hospital Admissions (All ages) Cases PM 7,167 6,686 5,845 1,431 13 7,064

Cardiac Hospital Admissions (>18 years) Cases PM 5,285 5,227 4,461 1,107 14 5,399

Restricted Activity Days (all ages) Days PM 22,178,430 22,479,495 17,260,335 4,450,716 -61,611 22,218,524

Asthma symptom days (children 5-19yr) Days PM 549,079 548,759 413,762 112,050 -1,920 548,116

Lost working days (15-64 years) Days PM 5,492,790 5,329,982 4,381,063 1,130,170 -3,373 5,438,646

* life years lost and deaths from chronic exposure to PM2.5 are alternate measures of the same effect


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Table 3.3. Monetised equivalent of health impacts due to air pollution, 2025, EU28, €million/year, 2005 prices.

Damage, €M/year CLE B1 B2 B6 B3 B4 MTFR

2025 2025 2025 2025 2025 2025 2025

Acute Mortality (All ages) median VOLY O3 1,027 1,011 999 965 956 953 866

Acute Mortality (All ages) mean VOLY O3 2,468 2,430 2,402 2,319 2,298 2,290 2,082

Respiratory hospital admissions (>64) O3 42 42 41 40 40 39 36

Cardiovascular hospital admissions (>64) O3 187 184 182 175 174 173 157

Minor Restricted Activity Days (MRADs all ages) O3 3,595 3,538 3,498 3,379 3,350 3,338 3,036

Chronic Mortality (All ages) LYL median VOLY PM 156,315 145,799 135,349 126,878 124,789 124,787 114,250

Chronic Mortality (All ages) LYL mean VOLY PM 375,752 350,474 325,354 304,992 299,969 299,965 274,635

Chronic Mortality (30yr +) deaths median VSL PM 334,132 311,873 289,201 271,364 266,826 266,840 244,552

Chronic Mortality (30yr +) deaths mean VSL PM 680,525 635,191 589,015 552,687 543,444 543,472 498,079

Infant Mortality (0-1yr) median VSL PM 724 675 628 586 577 576 526

Infant Mortality (0-1yr) mean VSL PM 1,475 1,376 1,279 1,193 1,174 1,174 1,072

Chronic Bronchitis (27yr +) PM 12,967 12,096 11,215 10,535 10,359 10,361 9,493

Bronchitis in children aged 6 to 12 PM 456 425 395 371 365 365 334

Respiratory Hospital Admissions (All ages) PM 233 217 202 189 186 186 170

Cardiac Hospital Admissions (>18 years) PM 179 167 155 145 143 143 131

Restricted Activity Days (all ages) PM 30,365 28,325 26,257 24,669 24,259 24,265 22,221

Asthma symptom days (children 5-19yr) PM 343 320 297 280 275 275 252

Lost working days (15-64 years) PM 10,635 9,921 9,228 8,658 8,511 8,512 7,805

Total: Core median VOLY 217,818 203,420 189,097 177,477 174,579 174,570 159,822

Total: Core mean VOLY 439,082 409,873 380,838 357,256 351,408 351,392 321,703

Total: Core median VSL 394,569 368,483 341,991 321,059 315,726 315,733 289,313

Total: Core mean VSL 742,028 692,812 642,763 603,285 593,234 593,255 543,651


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Table 3.4 (EU28) shows the benefits of moving between scenarios. These results are compared with costs below.

Table 3.4. Total health benefits from comparison between scenarios, 2025, EU28, €million/year, 2005 prices.

BENEFITS: EU28 CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 - MTFR

Total, with median VOLY 14,398 14,323 11,620 2,897 9 14,748

Total, with mean VOLY 29,209 29,035 23,582 5,848 16 29,689

Total, with median VSL 26,086 26,492 20,932 5,334 -8 26,420

Total, with mean VSL 49,217 50,049 39,478 10,050 -21 49,604

The impacts and benefits described in this chapter are specific to the EU28. The actions undertaken also bring benefits to non-EU countries through the transboundary movement of pollutants. Accounting for these would add benefits of at least5 €3.5 billion/year under the median VOLY position, and €11 billion/year under the mean VSL position for moving from the CLE to the MTFR scenarios.

3.3 Aggregated results for the European and EU28 regions: 2030 scenarios The Tables below provide the following results for 2030: Table 3.5. Estimated annual health impacts due to air pollution, EU28. Table 3.6. Change in estimated annual health benefits between scenarios, EU28. Table 3.7. Monetised equivalent of health impacts due to air pollution, EU28. Table 3.8. Benefits from comparison between scenarios, EU28. Further results are provided by country in Appendix 4. Results for 2030 show very similar patterns to those discussed above for 2025. There is a slight reduction in baseline (CLE) health burden compared to 2025 and, similarly, a reduction in health effects under the MTFR scenario.

Table 3.5. Estimated annual health impacts due to air pollution, 2030, EU28.

IMPACTS CLE B7 MTFR

2030 2030 2030

Acute Mortality (all ages) Prem. deaths O3 17,239 16,160 14,461

Respiratory hospital admissions (>64) Cases O3 20,060 18,840 16,914

Cardiovascular hospital admissions (>64) Cases O3 87,705 82,138 73,337

Minor Restricted Activity Days (all ages) Days O3 83,557,315 78,394,378 70,210,896

Chronic Mortality (30yr +) * Life years lost PM 2,538,700 2,055,443 1,817,335

Chronic Mortality (30yr +) * Prem. deaths PM 303,878 246,169 217,880

Infant Mortality (0-1yr) Prem. deaths PM 394 319 281

Chronic Bronchitis (27yr +) Cases PM 233,889 189,551 167,748

Bronchitis in children aged 6 to 12 Cases PM 732,056 594,606 525,802

Respiratory Hospital Admissions (All ages) Cases PM 100,854 81,624 72,124

Cardiac Hospital Admissions (>18 years) Cases PM 77,180 62,578 55,309

Restricted Activity Days (all ages) Days PM 320,525,771 259,895,350 229,943,301

Asthma symptom days (children 5-19yr) Days PM 7,728,256 6,287,999 5,567,708

Lost working days (15-64 years) Days PM 76,102,105 61,685,767 54,585,603

5 ‘At least’, because some neighbouring countries, such as Turkey, are not included in the analysis.


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Table 3.6. Reduction in estimated annual health impacts between scenarios, 2030, EU28.

IMPACTS CLE – B7 B7 - MTFR

2030 2030

Acute Mortality (all ages) Prem. deaths O3 1,079 1,699

Respiratory hospital admissions (>64) Cases O3 1,220 1,926

Cardiovascular hospital admissions (>64) Cases O3 5,567 8,801

Minor Restricted Activity Days (all ages) Days O3 5,162,938 8,183,481

Chronic Mortality (30yr +) * Life years lost PM 483,257 238,107

Chronic Mortality (30yr +) * Prem. deaths PM 57,709 28,290

Infant Mortality (0-1yr) Prem. deaths PM 75 37

Chronic Bronchitis (27yr +) Cases PM 44,338 21,803

Bronchitis in children aged 6 to 12 Cases PM 137,450 68,804

Respiratory Hospital Admissions (All ages) Cases PM 19,229 9,500

Cardiac Hospital Admissions (>18 years) Cases PM 14,602 7,269

Restricted Activity Days (all ages) Days PM 60,630,421 29,952,049

Asthma symptom days (children 5-19yr) Days PM 1,440,257 720,291

Lost working days (15-64 years) Days PM 14,416,337 7,100,165

* life years lost and deaths from chronic exposure to PM2.5 are alternate measures of the same effect

Table 3.7. Monetised equivalent of health impacts due to air pollution, 2030, EU28, €million/year, 2005 prices.

Damage, €M/year CLE B7 MTFR

2030 2030 2030

Acute Mortality (All ages) median VOLY O3 995 932 834

Acute Mortality (All ages) mean VOLY O3 2,391 2,241 2,006

Respiratory hospital admissions (>64) O3 45 42 38

Cardiovascular hospital admissions (>64) O3 195 182 163

Minor Restricted Activity Days (MRADs all ages) O3 3,509 3,293 2,949

Chronic Mortality (All ages) LYL median VOLY PM 146,483 118,599 104,860

Chronic Mortality (All ages) LYL mean VOLY PM 352,118 285,090 252,064

Chronic Mortality (30yr +) deaths median VSL PM 331,228 268,325 237,489

Chronic Mortality (30yr +) deaths mean VSL PM 674,610 546,496 483,693

Infant Mortality (0-1yr) median VSL PM 644 521 460

Infant Mortality (0-1yr) mean VSL PM 1,312 1,061 937

Chronic Bronchitis (27yr +) PM 12,536 10,160 8,991

Bronchitis in children aged 6 to 12 PM 430 350 309

Respiratory Hospital Admissions (All ages) PM 224 181 160

Cardiac Hospital Admissions (>18 years) PM 171 139 123

Restricted Activity Days (all ages) PM 29,488 23,910 21,155

Asthma symptom days (children 5-19yr) PM 325 264 234

Lost working days (15-64 years) PM 9,893 8,019 7,096

Total: Core median VOLY 205,607 167,133 147,848

Total: Core mean VOLY 412,981 335,210 296,469

Total: Core median VSL 389,379 316,032 279,744

Total: Core mean VSL 733,734 595,030 526,681


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Table 3.8. Total health benefits from comparison between scenarios, 2030, EU28, €million/year, 2005 prices.

BENEFITS: EU28 CLE - B7 B7 - MTFR

Total, with median VOLY 38,474 19,284

Total, with mean VOLY 77,771 38,741

Total, with median VSL 73,346 36,288

Total, with mean VSL 138,705 68,349

Again, there would be some increase in benefit were the effects of emission reductions in EU Member States on non-EU countries to be included.

3.4 Sensitivity analysis: Chronic exposure and ozone mortality Under the HRAPIE study, a recommendation was made to quantify the effects of long term exposure to ozone on mortality, but not to add it into the totals presented above (see Table 2.2, where the effect is given a ‘B’ rather than a ‘B*’ rating). Miller et al (2011) provide a life-table analysis that is closely aligned with the REVIHAAP/HRAPIE conclusion. We have therefore applied their result in terms of life years lost per unit change in ozone.

Table 3.9. Comparison of results for ozone mortality, short term (acute) exposures vs. long term (chronic) exposures, EU28, 2025.

EU28 CLE B1 B2 B6 B3 B4 MTFR

Acute effects: deaths (=YOLL)

17,795 17,520 17,315 16,717 16,566 16,510 15,011

Acute effects: damage (€M/yr)

1,027 1,011 999 965 956 953 866

Chronic effects: years of life lost

157,207 154,750 152,993 147,703 146,398 145,893 132,690

Chronic effects: damage (€M/yr)

9,071 8,929 8,828 8,522 8,447 8,418 7,656

Ratio, chronic damage: acute damage

8.8 8.8 8.8 8.8 8.8 8.8 8.8

Table 3.10. Comparison of results for ozone mortality, short term (acute) exposures vs. long term (chronic) exposures, EU28, 2030.

EU28 CLE B7 MTFR

Acute effects: deaths (=YOLL)

17,239 16,160 14,461

Acute effects: damage (€M/yr)

995 932 834

Chronic effects: years of life lost

150,057 140,716 126,000

Chronic effects: damage (€M/yr)

8,658 8,119 7,270

Ratio, chronic damage: acute damage

8.7 8.7 8.7

The first data row in the table shows the number of deaths quantified using the recommended functions for ozone mortality assessment. As these are effects of acute exposure it is assumed that on average, each death equates to one lost life year (see Hurley et al, 2005). The third row


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of the table indicates the estimate of life years lost via effects of chronic exposure to ozone. The ratio in the last row of the table (chronic effect damage divided by acute effect damage) indicates that the chronic effects are 8.8 times higher than the estimated acute effects in 2025, and slightly less than this (8.7 times) in 2030 (the difference reflecting some demographic change). This is broadly in line with the conclusions of Miller et al (2011). These results indicate that the inclusion of chronic effects of ozone on mortality would roughly double estimated ozone damage under the most conservative valuation assumptions for mortality, increasing the importance of ozone, but still leaving PM2.5 effects dominant. For both 2025 and 2030 the inclusion of chronic effects of ozone on mortality rather than acute effects would add over €1.2 billion/year to the benefits of moving from CLE to MTFR. There is potential for some double counting of chronic effects on mortality between ozone and PM2.5.

3.5 Impacts on lost working days and health care expenditure Summary information on lost working days and their associated value is shown in Table 3.11 for 2025 and Table 3.12 for 2030. Each lost working day has been valued at €130 (CBI, 2011, 2013). Data by country are provided in Appendix 4.

Table 3.11. Summary information on lost working days attributed to air pollution (values in €million/year), EU28, 2025.

EU28 CLE B1 B2 B6 B3 B4 MTFR

Lost working days (million) 82 76 71 67 65 65 60

Value of lost working days 10,635 9,921 9,228 8,658 8,511 8,512 7,805

Table 3.12. Summary information on lost working days attributed to air pollution (values in €million/year), EU28, 2030.

EU28 CLE B7 MTFR

Lost working days (million) 76 62 55

Value of lost working days 9,893 8,019 7,096

It is easy to sum up the healthcare costs for those effects for which such data are available, and indeed this is done below. However, before doing that it is necessary to consider whether the total so calculated is a reliable indicator of overall healthcare costs linked to air pollution. The following table provides a brief review, from the author’s perspective, for each quantified impact.


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Table 3.13. Availability of healthcare cost data for health impacts of air pollution

Effect Commentary

Mortality

Acute Mortality For adults it is assumed that there is no additional healthcare cost for ‘acute mortality’ beyond what would have been incurred had death occurred slightly later. In essence, the primary cause of death seems likely to be unchanged at least in the vast majority of cases. This may be a slightly conservative position.

Chronic Mortality The position with respect to chronic mortality is more complicated than for acute. In part, the same issue applies, with the treatment costs immediately leading up to death possibly being identical. [It could be argued that one should calculate the difference in NPV of treatment costs now vs. treatment costs at the point in time in the future when individuals would have died]. However, if (as concluded in the WHO review studies) prolonged exposure to air pollution has an impact on mortality, it is expected to have other implications for health as well. The question then becomes one of whether morbidity costs are adequately captured. For chronic morbidity effects we estimate chronic bronchitis impacts only. Even if it is considered that this fully captures chronic effects on respiratory morbidity, it does not capture any possible impact on morbidity associated with cardiovascular morbidity.

Infant Mortality The small number of cases of infant mortality estimated here (under 500 cases annually in the EU28 in total, with a potential reduction under MTFR of around 120 cases per year for both 2025 and 2030) indicates that the aggregate of healthcare cost associated with these infant deaths will be low, even if the average treatment cost per child is high. However, like the situation with chronic mortality for adults, this is a ‘tip of the iceberg’ situation, given that we quantify no morbidity effects for this age group. It is quite illogical to consider that the only effect of air pollution on infant health is mortality, if we accept the link to mortality as robust.

Morbidity

Minor Restricted Activity Days (acute)

Given that these are defined as ‘minor’ restricted activity days it is anticipated that whilst overall number are high (48 million days per year in the 2025 baseline, with a potential reduction of 7 million days per year under the MTFR scenario), those experiencing the effect would be unlikely to seek medical intervention.

Chronic Bronchitis in adults Healthcare costs for chronic bronchitis have been assessed systematically in a number of European countries in a major study reporting in 2003. Results varied significantly between countries:

France: €530/patient/year (Piperno et al, 2003)

Italy: €1,261/patient per year (Dal Negro et al, 2003)

Netherlands: €614/patient/year (Wouters, 2003)

Spain: €3,238/patient/year (Izquiero, 2003)

UK €1,147/patient/year (Britton, 2003) The average figure across these countries is €1,358. The quantified impact for chronic bronchitis is ‘new cases per year’. Hence to calculate the total cost of these new cases to healthcare systems requires an estimate of an average time in years that those affected will suffer from chronic bronchitis. Using the incidence data adopted here (3.9 cases per 1000 people per year) and data on chronic bronchitis incidence discussed below (discussion around Figure 3-3), an estimate of 10 years average duration is adopted.


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Effect Commentary

Chronic bronchitis in children It can be anticipated that children with persistent symptoms would be taken to the doctor. Drawing on Netten and Curtis (2000, as reported by Hurley et al, 2005) the cost of a consultation would be in the order of €45.

Respiratory Hospital Admissions (acute)

Hospital admissions are valued at €2,220 per case. Of this, €1,000 is attributed to healthcare costs. However, this seems likely to be an underestimate given the average stay lengths linked to respiratory hospital admissions in WHO’s Hospital Morbidity Database and costs indicated by WHO’s CHOICE database.

Cardiac Hospital Admissions (acute) Hospital admissions are valued at €2,220 per case. Of this, €1,000 is attributed to healthcare costs. However, this seems likely to be an underestimate given the average stay lengths linked to cardiovascular hospital admissions in WHO’s Hospital Morbidity Database and costs indicated by WHO’s CHOICE database.

Asthma symptom days (children 5-19yr)

As a minimum it would be anticipated that children experiencing an asthma symptom day would receive some medication, valued previously at €1 per day (Hurley et al, 2005).

Restricted Activity Days (acute) The broad definition of a ‘restricted activity day’ prevents attribution of an average cost for healthcare. In many cases it is envisaged that there would be no healthcare cost. However, given the large numbers involved (255 million RADs in the EU under the 2025 baseline for those of working age with a potential improvement of 115 RADS under MTFR, with numbers potentially 45% higher if those over 65 years are included) a significant aggregate cost could arise if just a minority of cases involved some level of intervention.

Table 3.13 raises the question of the average period of time over which those who develop chronic bronchitis suffer symptoms. No data for Europe have been identified that provide an answer to this question. However, the following data have been identified for the USA (American Lung Association, 2013).

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Figure 3-3. Prevalence of chronic bronchitis by age group in the US population, 2011 (from Table 5, American Lung Association, 2013). Left side: total number affected. Right side: rate per 1000 people in the affected age group.


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The right hand side of the graph shows that incidence increases with age, as expected. The left hand side of the graph, however, shows that overall numbers affected in each age group follow a different pattern, with higher numbers in the lower age group than the older. Combining these data on total incidence with the prevalence of new cases per year (3.78 cases per thousand in the affected age groups, from Hurley et al 2005, citing Abbey et al, 1995a,b) indicates an average of 11.5 years per person affected. The data from Abbey et al is used here as it, like the American Lung Association data, are both from the USA. The use of the incidence data from Europe based on the SAPALDIA study (3.9 cases per thousand) would make very little difference. Recognising issues associated with combining data from different sources, for the present report this estimate of 11.5 years per case is rounded down to an average of 10 years per person. The results of applying these data are provided in summary in Table 3.14 for 2025 and Table 3.15 for 2030. Results are dominated by chronic bronchitis. Effects for which healthcare costs are assumed negligible and those for which they are not quantified but may be significant are listed.

Table 3.14. Estimated healthcare costs for the EU28, 2025 (€million/year)

IMPACTS CLE B1 B2 B6 B3 B4 MTFR

Respiratory hospital admissions (>64) O3 18 18 17 17 17 17 15

Cardiovascular hospital admissions (>64) O3 19 19 19 18 18 18 16

Chronic Bronchitis (adults) PM 2,771 2,585 2,397 2,251 2,214 2,214 2,029

Bronchitis in children aged 6 to 12 PM 35 33 30 28 28 28 26

Respiratory Hospital Admissions (All ages)

PM 105 98 91 85 84 84 77

Cardiac Hospital Admissions (>18 years) PM 80 75 70 65 64 64 59

Asthma symptom days (children 5-19yr) PM 8 8 7 7 7 7 6

Effects assumed to have negligible healthcare costs

Acute mortality (NO2, O3) Minor restricted activity days (O3)

Unquantified effects that may have

significant healthcare costs Chronic morbidity (in addition to chronic bronchitis) (NO2, O3 and PM2.5) Infant morbidity (PM2.5) Restricted activity days (PM2.5) Child bronchitis (NO2) Respiratory hospital admissions (NO2)

Total where quantified 3,037 2,834 2,631 2,472 2,431 2,431 2,227


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Table 3.15. Estimated healthcare costs for the EU28, 2030 (€million/year)

IMPACTS CLE B7 MTFR

Respiratory hospital admissions (>64) O3 17 16 14

Cardiovascular hospital admissions (>64) O3 20 19 17

Chronic Bronchitis (adults) PM 2,679 2,171 1,922

Bronchitis in children aged 6 to 12 PM 33 27 24

Respiratory Hospital Admissions (All ages)

PM 101 82 72

Cardiac Hospital Admissions (>18 years) PM 77 63 55

Asthma symptom days (children 5-19yr) PM 8 6 6

Effects assumed to have negligible healthcare costs

Acute mortality (NO2, O3) Minor restricted activity days (O3)

Unquantified effects that may have

significant healthcare costs Chronic morbidity (in addition to chronic bronchitis) (NO2, O3 and PM2.5) Infant morbidity (PM2.5) Restricted activity days (PM2.5) Child bronchitis (NO2) Respiratory hospital admissions (NO2)

Total where quantified 2,935 2,384 2,110

3.6 National results A summary of key health indicators is provided in Appendix 4, covering:

Life years lost (and deaths) to chronic exposure to PM2.5,

Deaths linked with short-term exposure to ozone,

Life years lost to chronic exposure to ozone (with associated values)

Work loss days (a subset of ‘restricted activity days’) associated with short-term PM2.5

exposure. Appendix 5 provides aggregated health damage cost data by country, taking the CAFE median VOLY approach to mortality valuation. This provides results that are about one third of those from use of the upper bound mean VSL option.


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4 Non-health benefits

4.1 Monetised non-health benefits Simplified methods have been applied to quantify the change in damage to materials from acid deposition and crops from ozone exposure in 2025 and 2030 under the policy scenarios, drawing on past €/tonne emission estimates of marginal damage to these receptors. This analysis is currently only possible for states in the EU28. Damage results for the two receptors are shown in the following tables.

Table 4.1. Benefits to crops in the EU28 compared to baseline, 2025, €M/year.

CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 -

MTFR

Austria 0.2 0.1 1.8 1.5 0.2 5.5

Belgium 0.6 0.0 2.4 0.1 0.3 6.8

Bulgaria 0.3 0.0 1.3 0.2 0.7 4.9

Croatia 0.4 0.3 3.1 1.0 0.0 5.4

Cyprus

Czech Rep. 1.1 0.5 5.4 1.8 0.1 10.0

Denmark 0.9 0.0 1.8 0.4 0.3 4.7

Estonia 0.1 0.0 0.1 0.0 0.0 1.5

Finland 0.0 0.0 0.2 0.1 0.1 3.8

France 1.6 9.6 19.4 5.8 0.2 62.0

Germany 23.5 2.7 34.4 0.9 3.1 65.5

Greece 6.1 0.7 0.1 0.2 0.8 8.5

Hungary 0.2 0.0 2.8 0.7 0.0 5.4

Ireland 0.0 0.1 1.5 0.6 0.1 3.6

Italy 7.7 8.7 10.4 6.2 0.4 28.1

Latvia 0.1 0.0 0.0 0.5 0.3 1.6

Lithuania 0.3 0.0 0.0 0.2 0.3 1.7

Luxembourg 0.0 0.0 0.2 0.0 0.0 0.5

Malta 0.0 0.0 0.0 0.0 0.0 0.2

Netherlands 0.1 0.5 -1.1 0.2 0.0 7.9

Poland 1.0 5.9 9.3 3.6 1.6 21.5

Portugal 0.6 0.6 2.7 0.3 2.0 3.1

Romania 1.4 1.0 10.9 1.9 0.0 9.6

Slovakia 0.1 0.6 1.7 1.2 0.1 4.2

Slovenia 0.0 0.1 1.9 0.1 0.0 1.0

Spain 10.5 0.4 12.6 5.9 8.2 29.5

Sweden 0.0 0.0 0.0 0.1 0.1 4.5

United Kingdom 4.0 8.0 16.6 4.9 0.4 32.2

Total 61.0 39.8 139.5 38.2 19.2 333.2


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Table 4.2. Benefits to crops in the EU28 compared to baseline, 2030, €M/year.

CLE - B7 B7 - MTFR

Austria 1.8 7.0

Belgium 3.6 7.0

Bulgaria 1.6 7.0

Croatia 3.8 6.3

Cyprus

Czech Rep. 7.2 10.8

Denmark 2.7 5.6

Estonia 0.1 1.4

Finland 0.2 3.8

France 29.5 68.3

Germany 64.3 67.1

Greece 5.9 8.6

Hungary 3.0 6.0

Ireland 1.5 5.0

Italy 25.4 34.5

Latvia 0.2 2.3

Lithuania 0.3 2.2

Luxembourg 0.2 0.6

Malta 0.0 0.2

Netherlands -0.4 8.4

Poland 16.6 27.9

Portugal 3.9 5.5

Romania 13.2 11.7

Slovakia 3.5 4.6

Slovenia 1.8 1.3

Spain 28.8 39.6

Sweden 0.1 4.9

United Kingdom 28.6 37.3

Total 247.3 384.8

The GAINS model now generates estimates of POD6

6 a flux-based metric preferred to the AOT40 concentration based metric used for the above calculations. Unfortunately, impacts to rather few crops can currently be assessed using POD6. Mills and Harmens (2011) provide results for just two, wheat and potato, revealing a combined loss of €2.6 billion annually across the EU27+Switzerland and Norway. Analysis by Holland (2013a) concluded that the results from the simple methods applied here provide a reasonable indication of the results that would be applied from application of the flux based methods, once other crops and impacts on crop quality (sugar and protein content) discussed by Mills and Harmens are factored in, certainly in terms of an order of magnitude type estimate. We note, however, that this is an area of on-going research, with a need for refinement of several parts of the impact pathway including the estimate of POD6.

Estimated reductions in damage to building materials (Table 4.3, Table 4.4) are lower than the estimates for crops, though as already noted, they fail to account for impacts to cultural heritage.

6 Phytotoxic ozone dose of 6 nmol m

-2s

-1


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Table 4.3. Benefits to materials in the EU28 compared to baseline, 2025, €M/year.

CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 -

MTFR

Austria 0.3 0.0 0.1 0.4 0.0 0.1

Belgium 2.0 0.9 1.7 0.2 0.0 0.0

Bulgaria 0.4 5.7 3.5 0.0 0.0 0.1

Croatia 0.2 1.5 0.3 0.0 0.0 0.4

Cyprus

Czech Rep. 1.6 1.3 0.6 0.0 0.0 0.8

Denmark 0.0 0.0 0.1 0.0 0.0 0.1

Estonia 0.0 0.0 0.1 0.0 0.0 0.1

Finland 0.0 0.0 0.0 0.0 0.0 0.2

France 2.4 3.1 1.7 0.1 0.0 1.1

Germany 4.7 2.5 2.6 1.1 0.0 1.3

Greece 0.1 0.1 2.4 0.2 0.0 3.1

Hungary 0.1 1.1 0.3 0.0 0.0 0.1

Ireland 0.1 0.1 0.2 0.1 0.0 0.1

Italy 5.3 3.2 2.5 0.4 0.0 4.4

Latvia 0.0 0.0 0.0 0.0 0.0 0.0

Lithuania 0.0 0.0 0.9 0.0 0.0 0.1

Luxembourg 0.0 0.0 0.1 0.0 0.0 0.1

Malta 0.0 0.0 0.0 0.0 0.0 0.0

Netherlands 0.1 0.7 0.2 0.1 0.0 0.5

Poland 18.5 7.2 6.1 0.2 0.0 2.0

Portugal 0.6 1.7 1.0 0.3 0.0 0.6

Romania 0.7 5.2 1.3 0.0 0.0 0.7

Slovakia 0.0 2.2 1.3 0.0 0.0 0.1

Slovenia 0.1 0.1 0.1 0.0 0.0 0.0

Spain 1.1 7.7 4.4 0.6 -0.6 3.4

Sweden 0.0 0.0 0.0 0.0 0.0 0.1

United Kingdom 13.5 8.6 1.2 2.2 0.0 0.6

Total 51.7 52.8 32.6 6.2 -0.6 20.1


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Table 4.4. Benefits to materials in the EU28 compared to baseline, 2030, €M/year.

CLE - B7 B7 - MTFR

Austria 0.4 0.5

Belgium 4.6 0.3

Bulgaria 9.9 0.3

Croatia 2.1 0.5

Cyprus

Czech Rep. 3.6 0.6

Denmark 0.1 0.1

Estonia 0.1 0.2

Finland 0.0 0.2

France 6.8 1.7

Germany 10.5 3.5

Greece 2.4 2.4

Hungary 1.5 0.1

Ireland 0.3 0.2

Italy 11.2 5.1

Latvia 0.0 0.0

Lithuania 0.9 0.1

Luxembourg 0.1 0.1

Malta 0.0 0.0

Netherlands 1.1 0.9

Poland 28.8 2.5

Portugal 3.2 1.2

Romania 7.4 0.9

Slovakia 3.7 0.1

Slovenia 0.2 0.0

Spain 13.9 3.7

Sweden 0.0 0.1

United Kingdom 16.0 3.0

Total 128.9 28.5

4.2 Un-monetised non-health benefits In addition to the effects of the pollutants of interest here to crops and materials, there are also of course effects on ecosystems from eutrophication, ozone and acidification. These have not been monetised. Information on the extent of these impacts is provided by Amann (2012b, 2013, 2014).


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5 Cost-benefit analysis

5.1 Cost data Cost data generated by the GAINS Model and presented by Amann (2014) have been used for the CBA of the 2025 and 2030 scenarios. Incremental cost data relative to the CLE scenario are also presented here, in Appendix 6, for reference.

5.2 Comparison of costs and health benefits The CBA shown in Table 5.1 taking aggregate costs and benefits for EU28 for 2025, demonstrates net benefits7 for the shift from CLE to the B3 scenario, but not for moving from B3 to MTFR. There is, however, a net benefit when moving from CLE to MTFR. This arises because there is sufficient excess benefit when moving from CLE to B3 to offset the net cost from B3 to MTFR. The reduction in net benefit when moving from B6 to B3 arises in part, because of the smaller level of gap closure between these two scenarios than for preceding scenario pairs. As noted previously, the difference between scenarios B3 and B4 is a misleading indication of benefit, as B4 differs with respect to targeting of ecological impacts that are not quantified.

Table 5.1. Net health benefits of the scenarios for 2025, €M/year.

Net benefits, EU28 CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 –

MTFR

Costs 222 979 2,138 1,289 51 42,327

Net benefits

Total with median VOLY 14,176 13,344 9,482 1,609 -42 -27,579

Total with mean VOLY 28,987 28,056 21,444 4,559 -35 -12,638

Total with median VSL 25,864 25,513 18,794 4,044 -58 -15,907

Total with mean VSL 48,994 49,070 37,340 8,762 -72 7,277

A similar pattern is observed for 2030 (Table 5.2). Fewer scenarios have been considered for 2030, reducing the resolution of the CBA. However, comparison of results indicates that the same outcome holds: that marginal benefits exceed costs up to (at least) the level of scenario B7.

Table 5.2. Net health benefits of the scenarios for 2030, €M/year.

Net benefits, EU28 CLE - B7 B7 - MTFR

Costs 3,334 47,347

Net benefits

Total with median VOLY 35,140 -28,063

Total with mean VOLY 74,437 -8,606

Total with median VSL 70,012 -11,059

Total with mean VSL 135,371 21,002

Table 5.3 for 2025 and Table 5.4 for 2030 provide an alternative way of comparing costs and benefits using benefit-cost ratios. A net cost is shown when this ratio falls below 1.

7 Net benefits = benefit from scenario less the costs of reaching that scenario


33

Table 5.3. Health benefit to abatement cost ratios for the scenarios for 2025, €M/year.

Net benefits, EU28 CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 -

MTFR

Total with median VOLY 65 15 5.4 2.2 0.2 0.3

Total with mean VOLY 132 30 11 4.5 0.3 0.7

Total with median VSL 118 27 10 4.1 -0.1 0.6

Total with mean VSL 222 51 18 7.8 -0.4 1.2

Table 5.4. Health benefit to abatement ratios for the scenarios for 2030, €M/year.

CLE - B7 B7 - MTFR

Total with median VOLY 12 0.41

Total with mean VOLY 23 0.82

Total with median VSL 22 0.77

Total with mean VSL 42 1.44

Results are provided at the national level for net benefits for 2025 and 2030 in Table 5.5 and Table 5.6 respectively, with mortality benefits quantified using the more conservative median VOLY position.


34

Table 5.5. Net health benefits by country for the scenarios for 2025, €M/year. Benefits calculated using the median VOLY from CAFE.

Core median VOLY CLE - B1 B1 - B2 B2 - B6 B6 - B3 B3 - B4 B4 -

MTFR

Albania 17 18 15 2 0 22

Austria 155 114 228 14 -1 -755

Bosnia and Herzegovina 30 30 27 5 1 29

Belgium 317 244 176 49 1 -346

Bulgaria 170 158 231 11 3 -435

Belarus 106 66 90 19 5 79

Switzerland 77 59 60 21 1 87

Serbia and Montenegro 107 112 112 17 6 97

Cyprus 2 2 3 1 0 -39

Czech Republic 371 238 315 49 5 -681

Germany 2,032 1,542 1,183 294 5 -2,831

Denmark 65 46 95 17 -1 -640

Estonia 8 4 12 2 1 -255

Spain 1,714 752 591 100 -50 -3,227

Finland 14 8 34 11 1 -896

France 1,303 840 899 150 6 -4,868

United Kingdom 1,708 1,724 701 223 5 -2,264

Greece 177 539 161 33 2 -725

Croatia 97 76 83 13 -2 -261

Hungary 288 267 375 36 7 -267

Ireland 28 25 16 1 -2 -385

Iceland nq nq nq nq nq nq

Italy 1,748 3,710 867 231 -41 -1,044

Liechtenstein nq nq nq nq nq nq

Lithuania 65 28 61 17 0 -483

Luxembourg 14 10 11 3 0 -23

Latvia 27 12 27 22 2 -497

Moldova 47 36 43 5 4 34

TFYR Macedonia 15 16 14 2 1 15

Malta 3 3 2 1 0 -12

Netherlands 356 290 224 72 5 -520

Norway 9 7 6 3 1 8

Poland 2,117 1,688 1,606 155 7 -3,002

Portugal 357 267 167 17 -4 -515

Romania 783 540 1,072 32 7 -1,583

Russian Federation 192 120 145 38 10 159

Sweden 42 33 44 19 1 -483

Slovenia 43 35 77 11 0 -56

Slovakia 173 149 217 23 3 -488

Turkey nq nq nq nq nq nq

Ukraine 362 264 300 51 17 241

Totals 15,141 14,072 10,291 1,772 4 -26,811


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Table 5.6. Net health benefits by country for the scenarios for 2030, €M/year. Benefits calculated using the median VOLY from CAFE.

Core mid VOLY CLE - B7 B7 - MTFR

Albania 49 24

Austria 478 -790

Bosnia and Herzegovina 83 36

Belgium 719 -355

Bulgaria 496 -440

Belarus 243 103

Switzerland 195 115

Serbia and Montenegro 318 123

Cyprus 7 -39

Czech Republic 920 -688

Germany 4,585 -2,669

Denmark 186 -652

Estonia 23 -292

Spain 3,180 -3,388

Finland 56 -902

France 2,945 -4,548

United Kingdom 3,819 -2,168

Greece 839 -700

Croatia 242 -276

Hungary 901 -254

Ireland 61 -439

Iceland nq nq

Italy 5,717 -818

Liechtenstein nq nq

Lithuania 144 -533

Luxembourg 36 -21

Latvia 62 -509

Moldova 114 43

TFYR Macedonia 44 18

Malta 8 -12

Netherlands 843 -997

Norway 20 12

Poland 5,205 -3,443

Portugal 762 -554

Romania 2,117 -1,515

Russian Federation 424 206

Sweden 117 -491

Slovenia 145 -48

Slovakia 528 -521

Turkey nq nq

Ukraine 848 307

Totals 37,478 -27,077


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6 Discussion The analysis presented above demonstrates that consideration of health effects alone is sufficient for the benefits for all scenarios up to B3 for 2025, and B7 for 2030, to exceed estimated costs. This applies at the national level as well as the EU28 level. Results also show that proceeding beyond this point to the MTFR scenario would not generate a net monetised health benefit compared to the costs under all cases except the least conservative position on mortality valuation8. The analysis has included the updated health functions for mortality recommended by WHO-Europe under the HRAPIE study. Estimates of working days lost and of costs to healthcare systems have been included. The estimate of lost working days may be reasonably complete, though does not include lost working days linked to some health impacts (e.g. chronic bronchitis). The estimated costs of lost working days do not include indirect effects on productivity, e.g. through reduced quality of outputs when using temporary staff who are not so experienced as those that they replace. Estimates are also provided of costs to healthcare services, in the order of €3 billion in the EU28 in both 2025 and 2030. The mortality valuation data, that dominate the CBA, are unchanged since 2005 when the CAFE study was undertaken. Consideration has been given as to whether newer information would change the conclusions reached here. A meta-analysis performed by the OECD (2012) suggests an increase in the value of statistical life beyond the upper limit considered under CAFE, to $US3.6 million (roughly €2.8 million). This would have no effect on the conclusions drawn from the analysis, given that the upper bound VSL used here is sufficient to generate a net benefit in all cases. Desaigues et al (2011) suggested a slightly lower VOLY than the lower bound adopted here (€40,000 vs. €57,700). A sensitivity analysis reveals that this would have no effect on the conclusions reached, being an insufficient change to generate net costs for any scenario where analysis using the lower bound VOLY adopted under CAFE indicates a net benefit. As noted, the analysis presented here is focused on health effects. Inclusion of other effects (such as the impacts to materials and crops assessed in Chapter 4) would strengthen the conclusions reached, though some trade-offs will be present (e.g. the effect of N deposition on carbon uptake by vegetation).

8 Even in this case, it is considered unlikely here that a true marginal analysis would show net benefits all the

way from the B3 and B7 scenarios to MTFR.


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Hoek G et al. (2012). PM10, and children’s respiratory symptoms and lung function in the PATY study. European Respiratory Journal, 40(3):538–547. Holland, M.R., Forster, D. and King, K. (1999) Cost-Benefit Analysis for the Protocol to Abate Acidification, Eutrophication and Ground Level Ozone in Europe. Report Number: Air and Energy 133, Ministry of Housing, Spatial Planning and Environment (MVROM), Directorate Air and Energy, ipc 640, P.O. Box 30945, 2500 GX The Hague, The Netherlands. Holland, M. and King, K. (1998) Economic Evaluation of Air Quality Targets for Tropospheric Ozone. Part C: Economic Benefit Assessment. http://ec.europa.eu/environment/enveco/air/pdf/tropozone-c.pdf Holland, M., Hunt, A., Hurley, F., Navrud, S., Watkiss, P. (2005a) Methodology for the Cost-Benefit analysis for CAFE: Volume 1: Overview of Methodology. http://www.cafe-cba.org/assets/volume_1_methodology_overview_02-05.pdf Holland, M., Hurley, F., Hunt, A. and Watkiss, P. (2005b) Methodology for the Cost-Benefit analysis for CAFE: Volume 3: Uncertainty in the CAFE CBA. Available at: http://www.cafe-cba.org/assets/volume_3_methodology_05-05.pdf Holland, M., Wagner, A., Hurley, F., Miller, B. and Hunt, A. (2011) Cost Benefit Analysis for the Revision of the National Emission Ceilings Directive: Policy Options for revisions to the Gothenburg Protocol to the UNECE Convention on Long-Range Transboundary Air Pollution. http://ec.europa.eu/environment/air/pollutants/pdf/Gothenburg%20CBA1%20final%202011.pdf Holland, M. (2012) Cost-benefit Analysis of Scenarios for Cost-Effective Emission Controls after 2020, Version 1, Corresponding to IIASA TSAP Report #7. November 2012. Holland, M. (2013a) Cost-benefit Analysis of Scenarios for Cost-Effective Emission Controls after 2020, Version 1, Corresponding to IIASA TSAP Report #10. March 2013. Holland, M. Pye, S., Jones, G., Hunt, A. and Markandya, A. (2013b) EC4MACS Modelling Methodology: The ALPHA Benefit Assessment Model. http://www.ec4macs.eu/content/report/EC4MACS_Publications/MR_Final%20in%20pdf/Alpha_Methodologies_Final.pdf. HRAPIE (see WHO, 2013b) Hunt, A., Navrud, S., Maca, V. and Scasny, M. (2011) Monetary values for health end-points used in the HEIMTSA/INTARESE Common Case Study. Thematic Priority 6.3, Deliverable 4.1.2. HEIMTSA (Health and Environment Integrated Methodology and Toolbox for Scenario Development. Sixth Framework Programme of the European Commission. http://www.heimtsa.eu/LinkClick.aspx?fileticket=Z79uJ1ZKuX8%3d&tabid=2937&mid=6403&language=en-GB. Hurley, F., Cowie, H., Hunt, A., Holland, M., Miller, B., Pye, S., Watkiss, P. (2005) Methodology for the Cost-Benefit analysis for CAFE: Volume 2: Health Impact Assessment. Available at: http://www.cafe-cba.org/assets/volume_2_methodology_overview_02-05.pdf Izquierdo, J.L. (2003) The burden of COPD in Spain: results from the Confronting COPD survey. Respir Med. Mar;97 Suppl C:S61-9. Jerrett M, Burnett R, Pope A C, Ito K, Thurston G. (2009). Long-term ozone exposure and mortality. N Engl J Med 360 (11) 1085-1095.

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Krupnick, A., Ostro, B. and Bull, K. (2005) Peer review of the methodology of cost-benefit analysis of the Clean Air For Europe Programme. http://www.cafe-cba.org/assets/cafe_peer_review.pdf Miller, B., Hurley, J.F. and Shafrir, A. (2011) Health Impact Assessment for the National Emissions Ceiling Directive (NECD) – Methodological Issues http://ec.europa.eu/environment/air/pollutants/pdf/IOM%20Report%20methodology%20NECD%20HIA.pdf Mills, G. and Harmens, H. (Eds.) (2011) Ozone Pollution: A hidden threat to food security. http://icpvegetation.ceh.ac.uk/publications/documents/ozoneandfoodsecurity-ICPVegetationreport%202011-published.pdf Netten, A. and Curtis, L. (2000) Unit costs of Health and Social Care 2000. Personal Social Services Research Unit (PSSRU). http://www.pssru.ac.uk/index.htm. OECD (2006) Economic Valuation of Environmental Health Risks to Children. OECD, Paris. OECD (2012) Mortality Risk Valuation in Environment, Health and Transport Policies. OECD, Paris. Ostro BD (1987). Air pollution and morbidity revisited: a specification test. Journal of Environmental Economics Management, 14(1):87–98. Ostro BD, Rothschild S (1989). Air pollution and acute respiratory morbidity: an observational study of multiple pollutants. Environmental Research, 50:238–247. Piperno D, Huchon G, Pribil C, Boucot I, Similowski T. (2003) The burden of COPD in France: results from the Confronting COPD survey. Respir Med. Mar;97 Suppl C:S33-42. REVIHAAP (see WHO, 2013a) Schindler C et al. (2009). Improvements in PM10 exposure and reduced rates of respiratory symptoms in a cohort of Swiss adults (SAPALDIA). American Journal of Respiratory and Critical Care Medicine, 179(7):579–587. Stieb DM et al. (2002). Air pollution and disability days in Toronto: results from the national population health survey. Environmental Research, 89(3):210–221. Ward DJ, Ayres JG (2004). Particulate air pollution and panel studies in children: a systematic review. Occupational and Environmental Medicine, 61(4):e13. USEPA (2011) The Benefits and Costs of the Clean Air Act from 1990 to 2020. Final Report – Rev. A. U.S. Environmental Protection Agency, Office of Air and Radiation. http://www.epa.gov/air/sect812/feb11/fullreport_rev_a.pdf. WHO (2013a) REVIHAAP: Review of evidence on health aspects of air pollution – REVIHAAP project: final technical report. World Health Organization, Regional Office for Europe, Bonn, Germany. http://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/2013/review-of-evidence-on-health-aspects-of-air-pollution-revihaap-project-final-technical-report. WHO (2013b) HRAPIE: Health risks of air pollution in Europe – HRAPIE project Recommendations for concentration–response functions for cost–benefit analysis of particulate matter, ozone and nitrogen dioxide. World Health Organization, Regional Office for Europe, Bonn, Germany. http://www.euro.who.int/en/health-topics/environment-and-health/air-

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quality/publications/2013/health-risks-of-air-pollution-in-europe-hrapie-project-recommendations-for-concentrationresponse-functions-for-costbenefit-analysis-of-particulate-matter,-ozone-and-nitrogen-dioxide. WHO databases. Copenhagen, WHO Regional Office for Europe.

European mortality database (MDB): http://data.euro.who.int/hfamdb/ European detailed mortality database: http://data.euro.who.int/dmdb/ European health for all database: http://data.euro.who.int/hfadb/ European hospital morbidity database: http://www.euro.who.int/en/what-we-do/data-and-evidence/databases/european-hospital-morbidity-database-hmdb2

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Appendix 1: Response to Stakeholder Comments In the course of this work, written comments were received from concawe (2013a, b) addressing the response functions used for health impact analysis and associated valuation respectively. This appendix provides a response to those comments. Concawe (2013a) raises a number of questions about the inclusion of chronic bronchitis as an endpoint in the CBA from review of the methods adopted under the Clean Air For Europe (CAFE) Programme, concerning:

Attribution of the impact to the fine particle fraction

Conversion of exposure metrics to PM2.5

Use of a single study (Abbey et al, 1995a) [though this overlooks the fact that this study considered also Abbey et al, 1995b, but took the lower risk factor from Abbey et al, 1995a]

The lack of statistical significance of Abbey et al (1995a) at the 5% level

The use of data from California during the period of 1966-1988

The lack of adjustment of the baseline disease rate from US data These criticisms are broadly rejected by the HRAPIE report. Indeed, the function recommended by HRAPIE based on Abbey et al (1995b) indicates a higher risk than was previously considered under the CAFE Programme. However, it is still more conservative than the function derived from the European SAPALDIA study reported by Schindler et al (2009). The incidence rate reported by SAPALDIA was very similar to that of Abbey et al (3.9 cases per 1000 adults at risk vs. 3.78 cases). Concawe also raised a number of similar questions about the inclusion of RADs in the CBA. These concerned:

Attribution of impacts to fine PM

The adjustment of an ERF for PM10 to one based on PM2.5

Assessment of these endpoints being based on the results of a single, study, the Health Interview Study, as reported by Ostro et al (1987) and Ostro and Rothschild (1989)

The potential for socioeconomic confounding

The RAD background rate being taken from a U.S. study As for chronic bronchitis, these issues are broadly addressed in the HRAPIE report. For example, it is acknowledged that the literature in this area of research is limited. However, it is wrong to say that the assessment is based on a single study as there is a wider literature demonstrating association between minor symptoms and air pollution (e.g. Hoek and Brunekreef, 1995; Ward and Ayres, 2004); the study used as the basis for quantification is considered representative of the wider literature. Further to this, it is illogical to consider that there is a link between mortality and the air pollutants of interest here, but not a link with lesser symptoms. On the question of incidence data, rather similar rates are reported by Stieb et al (2002) for the Canadian population and by Ali et al (2010) for the UK population. If the rate reported by Ali et al were adopted on the grounds that it is European, the effect estimate for RADs would increase by 21%. Concawe (2013b) is critical of the mortality values adopted above (€57,700 / €138,700). They instead propose an approach described by concawe (2012) referred to as ‘Maximised Societal Revenue’ (MSR): “If a single value is adopted to describe such WTP surveys, then MSR is a more robust approach as it respects individual expressions of WTP of all respondents to the survey. As such it reflects the full distribution of WTP survey results and reduces the dominance of more extreme values. Disregarding the VOLY values of the NewExt study as this WTP survey was not designed to


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derive a VOLY value in first place, the MSR approach gives an (weighted) average VOLY value of €9,250 (not corrected for inflation), based on the NEEDS and DEFRA WTP studies. This value is considerably less than the €54,000 to €57,700 used in current policy developments. When applying a sensitivity analysis the (weighted average) range from €3,400 to €13,000 (not corrected for inflation) should be tested.” Note the following:

The MSR approach is developed and referred to only in a review paper published by concawe on its website, rather than the peer reviewed literature.

It is unclear how it reflects ‘the full distribution of WTP survey results’ more than the use of standard summary estimates (mean and median) of a range of values.

The authors of the NEEDS study (subsequently published as Desaigues et al, 2011) do not support the values proposed by concawe, They state in the abstract to their paper that: As for confidence intervals, we argue that [for the EU] VOLY is at least €25,000 and at the most €100,000. In contrast, the upper bound of the concawe range is only half that of the lower bound indicated by Desaigues et al.

Further to the above, concawe (2012, 2013) states that: “…it was acknowledged by the CBA community during the Clean Air For Europe (CAFE) program that the most representative CBA results could be obtained by statistical analysis using the full distribution of WTP survey results”. This view appears to have influenced concawe’s development of the MSR approach. However, this position was not accepted by the ‘CBA community’. Analysis needs to be based on values that are representative of society: something that individual results from WTP surveys are clearly not. Those involved with the CBA agreed that the consequences of uncertainty should be investigated using Monte Carlo techniques, but these would be based on plausible ranges for societally representative values, taken as the median or mean from the studies.

Whilst the literature on VOLY is limited, there is an extensive literature on the VSL, reviewed by OECD (2012). The VSL estimates adopted here, and to which the VOLY estimates are closely linked, are low compared to the average recommended by OECD, USD3.6 million.

It is, naturally, to be expected that there would be some degree of consistency between estimates of VSL and estimates of VOLY, though with the former naturally greater on the grounds that VSL studies tend to focus on situations where the loss of life expectancy would run to some number of years. The proposed estimates from concawe are between 1,000 and 300 times smaller than the VSL recommended from OECD’s extensive review, a difference that seems too extreme.

A recent paper by Chanel and Luchini (2014) provides a further peer reviewed estimate for the VOLY based on analysis performed in France, of €140,000, higher than the VOLY adopted here. This indicates that the estimates for VOLY adopted here remain representative of the broader literature in the area, something that the concawe estimates are not.

Concawe (2012) is also critical of the values used for chronic bronchitis and restricted activity days (RADs). As noted above, following discussion with the HRAPIE team, it has been concluded that a reduction in the value for chronic bronchitis is appropriate. The new estimate is €53,600, a significant reduction in the previous estimate though still higher than the range suggested by concawe (€28,000 to €38,000 per case). It is, however, in accordance with the estimate provided in the review by Hunt et al (2011). Concawe expresses the view that the uncertainties in valuation of a RAD are so great that the effect should be removed from the analysis altogether, a position that effectively sets the value of a RAD to zero. On the basis that people clearly prefer not to be restricted in their activity, a zero value biases the analysis towards underestimation and will not provide the ‘realistic and sound reflection of morbidity effects’ that concawe demands. The value adopted here for a RAD is broadly equivalent to those discussed by Abt Associates (2012) for similar effects, and around half the value recommended by Hunt et al (2011). On this basis it is considered a reasonable reflection of the literature, and likely to give better guidance than an implicit value of zero.


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Appendix 2: Comparison of results following CAFE and HRAPIE recommendations

This Appendix considers whether recent changes made to the health response functions in the course of the analysis since 2012 have a significant impact on the results. This is assessed through quantification of impacts against the function sets from CAFE (including updated mortality functions from REVIHAAP) and HRAPIE (Table A2.1). Shading is used in the table to group similar effects to ease comparison between the two function sets.

Table A2.1. Estimated impacts in 2010 in the EU28 according to the CAFE CBA and HRAPIE function sets.

CAFE CBA* HRAPIE

OZONE EFFECTS

Acute Mortality (All ages)* Premature deaths 23,507 23,507

Respiratory Hospital Admissions (65yr +) Cases 24,331 19,117

Cardiovascular hospital admissions (>64) Cases - 86,279

Minor Restricted Activity Days (MRADs 15-64yr) Days 66,957,701 -

Minor Restricted activity days (65yr+, sensitivity) Days 22,506,558 -

Minor Restricted Activity Days (MRADs all ages) Days - 108,845,140

Respiratory medication use (adults 20yr +) Days 23,897,643 -

Respiratory symptoms (adults 15yr +, sensitivity) Days 265,819,826 -

PM2.5 EFFECTS

Chronic Mortality (30yr +)* Life years lost 4,030,653 4,030,653

Chronic Mortality (30yr +)* Premature deaths 379,420 379,420

Infant Mortality (0-1yr)* Premature deaths 777 777

Chronic Bronchitis (27yr +) Cases 184,612 316,685

Bronchitis in children aged 6 to 12 Cases - 1,068,990

Respiratory Hospital Admissions (All ages) Cases 69,022 142,243

Cardiac Hospital Admissions (All ages) Cases 42,568 108,989

Restricted Activity Days (RADs 15-64yr) Days 373,528,623 -

Restricted Activity Days (RADs >65, sensitivity) Days 122,510,005 -

Restricted Activity Days (all ages) Days - 436,351,761

Lost working days (15-64 years) Days - 121,378,612

Asthma symptom days (children 5-19yr) Days - 11,290,673

Respiratory medication use (all ages) Days 35,889,933 -

Lower respiratory symptom days (all ages) Days 502,265,520 -

Asthma Consultations (all ages, sensitivity) Consultations 688,603 -

Consultations for upper respiratory disease (all ages, sensitivity) Consultations 3,583,473 -

NO2 EFFECTS

Chronic Mortality (30yr +) Life years lost - NQ

Bronchitis in children Cases - NQ

Respiratory Hospital Admissions Cases - NQ NQ: Not quantified. ‘-‘ denotes effects that are not included in the function set in question. ‘*’ The mortality functions were updated at the start of this series of papers following recommendations from the REVIHAAP study.


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For mortality, results are the same in both cases, given that functions were updated at the outset of this work in line with the REVIHAAP recommendations. These made only a small difference to the estimated mortality impact for both ozone and PM2.5. For ozone, we see a significant increase in the estimated number of hospital admissions through the inclusion of cardiovascular hospital admissions. The total number of MRADs is higher in HRAPIE through extension of application of the function to all ages. The omission of respiratory symptoms appears a significant difference, but under CAFE it was only included for sensitivity. For PM2.5 there is an increase in estimated incidence of bronchitis in both adults and children when moving to the HRAPIE functions (though this is reversed in the valuation, see below, given changes to the unit value applied). There is a significant increase in estimates of both respiratory and cardiovascular hospital admissions under HRAPIE. There is also an increase in the number of RADs under HRAPIE, through extension of the RAD function to all ages. Respiratory medication use and lower respiratory symptom days are not included in HRAPIE, neither are the two sensitivity functions for consultations. For NO2, none of the effects recommended for quantification under HRAPIE have been assessed for reasons described above. The effect of these changes in response functions and changes in valuations are shown in Table A2.2. Overall there is a 5% fall in damage for the new function set at the lower end of the range and a 4% fall at the upper end (including CAFE sensitivity functions). This is, however, a conservative view on the HRAPIE position given the lack of quantification to date for the NO2 functions, and the omission here of effects of long-term exposure to ozone on mortality. The conclusion, therefore, is that results derived using the CAFE functions and valuations provided very similar guidance through the CBA to the updated function/valuation dataset.


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Table A2.2. Monetised estimates of impacts in 2010 in the EU28 according to the CAFE CBA and HRAPIE function/valuation sets.

Damage, €M/year CAFE CBA HRAPIE

Ozone effects

Acute Mortality (All ages) VOLY 1,356 - 3,260 1,356 - 3,260

Hospital Admissions (65yr +) 54 234

Minor Restricted Activity Days (MRADs 15-64yr) 2,812 4,571

Minor Restricted activity days (65yr+, sensitivity) 945 -

Respiratory medication use (adults 20yr +) 24 -

Respiratory symptoms (adults 15yr +, sensitivity)

11,164 -

PM2.5 effects

Chronic Mortality (All ages) VOLY 233,000 - 559,000 233,000 - 559,000

Chronic Mortality (30yr +) VSL 414,000 - 1,062,000 414,000 - 1,062,000

Infant Mortality (0-1yr) VSL 1,270 - 2, 586 1,270 - 2, 586

Chronic Bronchitis (27yr +) 38,399 16,974

Bronchitis in children - 629

Hospital Admissions (All ages) 248 558

Restricted Activity Days (RADs 15-64yr) 34,365 -

Restricted Activity Days (RADs >65) - ext. days 9,247 -

Restricted Activity Days (all ages) - 40,144

Asthma symptom days (children 5-19yr) - 474

Lost working days (15-64 years) - 15,779

Respiratory medication use (all ages) 36 -

Lower respiratory symptom days (all ages) 21,095 -

Consultations (sensitivity)

252 -

NO2 effects

Chronic mortality - NQ

Bronchitis in children - NQ

Respiratory hospital admissions (all ages)

- NQ

Totals

Core functions 332,000 - 943,000 316,000 - 926,000

Core + sensitivity functions 353,000 - 965,000


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Appendix 3: Key indicators by country for the baseline scenarios, 2010 to 2030

Table A3.1. Time series: Life years lost to chronic PM2.5 exposure 2010 2015 2020 2025 2030

Albania 23,755 20,669 15,173 14,641 14,465

Austria 54,835 47,672 41,317 37,702 35,419

Bosnia and Herzegovina 29,369 26,467 15,923 15,402 15,005

Belgium 94,890 83,122 72,535 68,097 65,171

Bulgaria 101,209 66,582 52,871 47,318 42,313

Belarus 88,500 78,892 69,089 63,020 59,381

Switzerland 45,953 40,271 34,359 31,048 29,129

Serbia and Montenegro 112,708 98,429 61,870 57,739 55,085

Cyprus 7,493 7,525 7,103 7,271 7,761

Czech Republic 97,433 84,157 73,466 67,214 62,874

Germany 594,864 507,423 442,256 398,656 367,827

Denmark 32,064 27,011 22,010 20,292 19,290

Estonia 7,981 6,859 5,938 5,457 5,115

Spain 270,769 241,634 206,670 197,172 194,610

Finland 20,368 17,764 15,899 15,241 14,865

France 432,492 376,632 324,494 296,324 277,744

United Kingdom 327,769 309,063 259,569 251,115 239,323

Greece 122,032 95,019 78,830 73,563 70,672

Croatia 35,436 31,092 23,145 20,918 19,691

Hungary 106,511 90,140 71,886 63,972 59,982

Ireland 13,666 13,433 12,415 11,411 11,015

Iceland nq nq nq nq nq

Italy 585,526 497,771 429,389 388,092 360,954

Liechtenstein nq nq nq nq nq

Lithuania 27,748 23,761 20,271 17,910 16,606

Luxembourg 3,986 3,478 3,226 3,085 3,019

Latvia 15,953 13,671 11,843 10,519 9,584

Moldova 39,249 33,238 26,747 24,356 23,191

TFYR Macedonia 19,095 15,747 9,900 9,301 8,868

Malta 2,606 2,131 1,671 1,578 1,571

Netherlands 124,664 108,433 92,309 87,310 83,618

Norway 9,983 9,705 9,279 9,697 9,781

Poland 519,716 450,770 403,032 353,632 321,540

Portugal 65,106 56,226 47,559 44,042 42,423

Romania 267,985 215,276 171,347 152,821 139,944

Russian Federation 1,443,823 1,354,496 1,240,508 1,163,048 1,114,443

Sweden 28,849 25,716 22,963 22,695 22,600

Slovenia 14,940 13,204 11,185 10,223 9,628

Slovakia 53,762 45,228 38,699 35,468 33,539

Turkey nq nq nq nq nq

Ukraine 577,462 516,004 414,734 381,246 375,953

Total 6,420,550 5,654,713 4,861,476 4,478,597 4,244,001


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Table A3.2. Time series: Deaths from chronic PM2.5 exposure (alternative metric to that shown in the preceding table)

2010 2015 2020 2025 2030

Albania 1,247 1,208 979 1,063 1,172

Austria 5,039 4,674 4,314 4,217 4,232


Belgium 9,272 8,530 7,800 7,596 7,535

Bulgaria 11,026 7,561 6,256 5,847 5,463

Belarus 7,810 7,278 6,652 6,369 6,298

Switzerland 4,019 3,746 3,389 3,327 3,372


Cyprus 480 521 529 591 683

Czech Republic 8,634 7,927 7,342 7,242 7,279

Germany 61,616 57,267 54,207 52,173 51,337

Denmark 3,002 2,624 2,217 2,182 2,208

Estonia 760 694 637 609 592

Spain 23,963 22,662 20,504 20,748 21,668

Finland 1,872 1,753 1,681 1,740 1,825

France 38,841 35,817 32,594 31,137 30,485

United Kingdom 30,018 29,291 25,442 25,576 25,293

Greece 12,072 9,997 8,796 8,547 8,544

Croatia 3,524 3,308 2,631 2,502 2,478

Hungary 10,568 9,332 7,761 7,231 7,095

Ireland 1,330 1,425 1,425 1,389 1,417


Italy 61,078 55,776 51,496 49,305 48,506


Lithuania 2,517 2,307 2,104 1,923 1,843

Luxembourg 308 274 259 257 261

Latvia 1,566 1,420 1,300 1,199 1,134

Moldova 3,042 2,733 2,329 2,278 2,331

TFYR Macedonia 1,366 1,230 841 858 886

Malta 203 185 160 169 187

Netherlands 10,402 9,806 9,003 9,322 9,709

Norway 863 847 818 910 972

Poland 43,168 40,387 38,857 36,708 35,869

Portugal 6,113 5,753 5,287 5,254 5,421

Romania 23,652 20,156 17,008 16,055 15,557

Russian Federation 115,792 115,306 111,947 111,299 113,050

Sweden 2,905 2,613 2,356 2,465 2,589

Slovenia 1,326 1,292 1,200 1,179 1,190

Slovakia 4,164 3,717 3,371 3,379 3,481


Ukraine 53,506 49,939 41,792 39,996 41,017

Total 579,455 540,898 492,907 480,175 480,564


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Table A3.3. Time series: Deaths from short term ozone exposure 2010 2015 2020 2025 2030

Albania 136 123 111 105 103

Austria 442 393 342 312 298

Bosnia and Herzegovina 220 195 165 154 150

Belgium 338 310 282 265 258

Bulgaria 761 656 582 543 526

Belarus 459 419 383 362 356

Switzerland 373 335 293 270 259

Serbia and Montenegro 713 626 533 497 480

Cyprus 49 47 43 42 43

Czech Republic 518 461 407 374 359

Germany 3,591 3,258 2,924 2,715 2,623

Denmark 163 150 136 127 124

Estonia 37 33 30 28 27

Spain 1,963 1,838 1,690 1,609 1,574

Finland 93 85 76 71 69

France 2,273 2,060 1,831 1,704 1,642

United Kingdom 1,371 1,298 1,238 1,192 1,171

Greece 833 749 680 642 632

Croatia 330 289 243 222 212

Hungary 775 678 583 533 510

Ireland 57 55 51 50 49


Italy 4,992 4,395 3,922 3,674 3,546


Lithuania 136 122 110 103 100

Luxembourg 16 14 13 12 11

Latvia 86 78 70 65 64

Moldova 244 224 203 194 192

TFYR Macedonia 134 119 104 98 95

Malta 24 22 20 19 18

Netherlands 424 392 358 338 329

Norway 93 87 80 77 75

Poland 1,596 1,429 1,267 1,172 1,130

Portugal 534 507 470 449 441

Romania 1,469 1,306 1,155 1,074 1,041


Sweden 223 204 184 172 167

Slovenia 125 110 94 85 81

Slovakia 288 255 221 203 194


Ukraine 3,675 3,401 3,139 3,018 3,004

Total 36,781 33,518 30,468 28,813 28,169


50

Table A3.4. Time series: Lost working days to acute PM2.5 exposure

2010 2015 2020 2025 2030

Albania 589,223 536,402 411,593 397,476 392,717

Austria 1,789,444 1,586,912 1,402,639 1,255,126 1,154,828


Belgium 2,550,785 2,217,344 1,920,368 1,792,268 1,704,929

Bulgaria 2,119,980 1,404,734 1,119,502 1,019,480 926,265

Belarus 1,698,645 1,564,475 1,412,390 1,316,134 1,264,244

Switzerland 1,391,661 1,221,417 1,043,905 922,755 846,344

Serbia and Montenegro 2,494,718 2,220,383 1,421,649 1,354,806 1,319,256

Cyprus 213,693 219,280 211,631 215,741 229,579

Czech Republic 4,169,303 3,544,196 3,040,272 2,812,038 2,658,963

Germany 26,697,694 22,878,298 20,012,127 17,654,559 15,889,787

Denmark 814,755 691,753 568,139 520,367 491,558

Estonia 169,153 146,815 128,129 120,598 115,698

Spain 7,766,734 7,054,726 6,144,135 5,875,073 5,812,584

Finland 542,357 467,305 412,825 392,210 379,128

France 12,011,652 10,455,957 9,009,131 8,236,049 7,731,522

United Kingdom 6,097,215 5,792,107 4,903,936 4,731,963 4,501,811

Greece 3,303,461 2,567,448 2,126,090 1,996,351 1,929,260

Croatia 1,086,095 962,391 722,505 656,093 619,489

Hungary 2,592,155 2,232,346 1,808,600 1,645,541 1,576,446

Ireland 381,868 377,946 352,387 327,905 320,667


Italy 16,640,607 14,115,375 12,147,887 10,896,377 10,048,475


Lithuania 487,641 432,170 380,806 338,834 315,654

Luxembourg 98,147 87,730 83,426 79,786 78,235

Latvia 325,131 286,309 254,160 231,110 215,239

Moldova 710,312 623,907 518,762 486,897 476,943

TFYR Macedonia 85,501 72,404 46,729 44,129 42,259

Malta 44,200 36,031 28,140 26,166 25,630

Netherlands 4,109,004 3,564,469 3,026,245 2,797,406 2,616,778

Norway 527,834 517,526 499,379 516,340 516,018

Poland 18,499,208 15,911,512 14,082,040 12,359,821 11,226,504

Portugal 1,704,116 1,504,312 1,299,931 1,195,513 1,141,985

Romania 4,531,501 3,721,705 3,024,146 2,774,317 2,611,230

Russian Federation 21,081,046 20,345,752 19,114,889 18,448,531 18,168,911

Sweden 803,499 714,911 637,556 628,898 625,578

Slovenia 511,727 448,368 376,226 340,782 317,734

Slovakia 1,317,487 1,118,897 965,548 885,243 836,548


Ukraine 3,814,271 3,552,220 2,965,550 2,817,818 2,867,295

Total 154,486,166 135,849,334 118,022,187 108,492,188 102,362,804


51

Table A3.5. Time series: Lost working days to acute PM2.5 exposure (valuation at average EU value, €million/year)

2010 2015 2020 2025 2030

Albania 77 70 54 52 51

Austria 233 206 182 163 150

Bosnia and Herzegovina 93 85 52 50 48

Belgium 332 288 250 233 222

Bulgaria 276 183 146 133 120

Belarus 221 203 184 171 164

Switzerland 181 159 136 120 110

Serbia and Montenegro 324 289 185 176 172

Cyprus 28 29 28 28 30

Czech Republic 542 461 395 366 346

Germany 3,471 2,974 2,602 2,295 2,066

Denmark 106 90 74 68 64

Estonia 22 19 17 16 15

Spain 1,010 917 799 764 756

Finland 71 61 54 51 49

France 1,562 1,359 1,171 1,071 1,005

United Kingdom 793 753 638 615 585

Greece 429 334 276 260 251

Croatia 141 125 94 85 81

Hungary 337 290 235 214 205

Ireland 50 49 46 43 42


Italy 2,163 1,835 1,579 1,417 1,306


Lithuania 63 56 50 44 41

Luxembourg 13 11 11 10 10

Latvia 42 37 33 30 28

Moldova 92 81 67 63 62

TFYR Macedonia 11 9 6 6 5

Malta 6 5 4 3 3

Netherlands 534 463 393 364 340

Norway 69 67 65 67 67

Poland 2,405 2,068 1,831 1,607 1,459

Portugal 222 196 169 155 148

Romania 589 484 393 361 339


Sweden 104 93 83 82 81

Slovenia 67 58 49 44 41

Slovakia 171 145 126 115 109


Ukraine 496 462 386 366 373

Total 20,083 17,660 15,343 14,104 13,307


52

The following table for the time series shows estimated health damage in each country (including non-EU states), with mortality valued using the median VOLY. Use of the mean VSL from CAFE would increase estimates by roughly a factor 3. Non-health impacts are not accounted for. Table A3.6. Aggregated health damage by scenario for 2025.

2010 2015 2020 2025 2030

Albania 1,891 1,656 1,230 1,190 1,180

Austria 4,390 3,855 3,374 3,102 2,937


Belgium 7,439 6,546 5,739 5,416 5,213

Bulgaria 7,541 5,022 4,024 3,623 3,262

Belarus 6,301 5,679 5,031 4,626 4,396

Switzerland 3,733 3,301 2,843 2,589 2,447


Cyprus 592 600 572 588 631

Czech Republic 7,525 6,555 5,770 5,315 5,009

Germany 47,465 40,901 35,993 32,660 30,346

Denmark 2,485 2,112 1,737 1,613 1,546

Estonia 594 515 451 417 393

Spain 21,736 19,633 17,013 16,349 16,251

Finland 1,591 1,401 1,266 1,221 1,200

France 34,499 30,291 26,313 24,211 22,872

United Kingdom 25,578 24,302 20,608 20,051 19,233

Greece 9,686 7,610 6,364 5,974 5,775

Croatia 2,726 2,412 1,817 1,653 1,568

Hungary 7,964 6,806 5,487 4,921 4,649

Ireland 1,078 1,068 997 923 897


Italy 47,512 40,677 35,339 32,162 30,124


Lithuania 2,016 1,748 1,510 1,343 1,254

Luxembourg 311 274 257 247 244

Latvia 1,168 1,013 889 796 731

Moldova 2,820 2,416 1,969 1,807 1,733

TFYR Macedonia 1,453 1,207 771 728 698

Malta 207 172 137 130 131

Netherlands 9,813 8,597 7,374 7,015 6,760

Norway 812 795 766 804 815

Poland 39,194 34,294 30,924 27,315 25,005

Portugal 5,130 4,483 3,838 3,578 3,468

Romania 20,098 16,298 13,099 11,765 10,853


Sweden 2,305 2,074 1,868 1,855 1,858

Slovenia 1,182 1,054 901 827 783

Slovakia 4,051 3,444 2,977 2,746 2,615


Ukraine 40,763 36,839 30,008 27,793 27,595

Totals 486,580 432,064 375,052 347,854 331,841


53

Appendix 4: Key health indicators by country for the Policy Scenarios, 2025 and 2030

Results are shown in this appendix by country for life years lost to chronic PM2.5 exposure, deaths linked to chronic PM2.5 exposure, deaths linked to short term ozone exposure, lost work days linked to short term PM2.5 exposure and the value of those lost work days. The first series of tables (A4.1 to A4.5) shows results for the 2025 scenarios, whilst the second set (A4.6 to A4.10) shows the results for 2030.


54

Table A4.1. 2025: Life years lost to chronic PM2.5 exposure CLE B1 B2 B6 B3 B4 MTFR

Albania 14,641 14,432 14,202 14,016 13,988 13,986 13,736

Austria 37,702 35,754 34,274 30,659 30,180 30,141 27,926

Bosnia and Herzegovina 15,402 15,012 14,625 14,283 14,217 14,200 13,855

Belgium 68,097 63,980 60,691 57,509 56,687 56,660 52,953

Bulgaria 47,318 45,035 42,696 38,937 38,739 38,640 36,077

Belarus 63,020 61,555 60,654 59,428 59,174 59,112 58,064

Switzerland 31,048 30,104 29,379 28,672 28,417 28,408 27,407

Serbia and Montenegro 57,739 56,326 54,845 53,402 53,184 53,109 51,921

Cyprus 7,271 7,252 7,223 7,183 7,160 7,156 7,073

Czech Republic 67,214 62,385 59,165 54,175 53,248 53,193 48,315

Germany 398,656 373,148 352,161 334,029 325,796 325,511 306,618

Denmark 20,292 19,458 18,874 17,391 17,119 17,057 15,784

Estonia 5,457 5,335 5,280 5,067 5,033 4,999 4,194

Spain 197,172 175,872 165,804 156,869 154,435 155,569 140,410

Finland 15,241 15,061 14,964 14,457 14,224 14,204 12,990

France 296,324 279,902 268,903 254,756 252,063 251,987 222,139

United Kingdom 251,115 228,827 205,093 194,491 189,350 189,270 178,949

Greece 73,563 71,341 64,181 61,825 61,140 61,112 56,717

Croatia 20,918 19,653 18,588 17,286 17,037 16,985 15,663

Hungary 63,972 60,152 56,381 50,788 50,027 49,941 46,199

Ireland 11,411 11,057 10,716 10,413 10,252 10,228 9,670

Iceland

Italy 388,092 366,223 317,323 304,628 299,256 300,547 274,353

Liechtenstein

Lithuania 17,910 17,032 16,658 15,648 15,294 15,222 14,024

Luxembourg 3,085 2,910 2,778 2,617 2,568 2,567 2,379

Latvia 10,519 10,163 9,985 9,613 9,091 9,052 8,044

Moldova 24,356 23,712 23,225 22,650 22,582 22,534 22,095

TFYR Macedonia 9,301 9,103 8,888 8,708 8,684 8,678 8,498

Malta 1,578 1,544 1,499 1,475 1,467 1,466 1,414

Netherlands 87,310 82,808 79,060 75,764 74,689 74,629 70,569

Norway 9,697 9,587 9,507 9,442 9,412 9,405 9,319

Poland 353,632 325,037 300,837 275,093 271,692 271,326 243,228

Portugal 44,042 39,466 35,759 33,165 32,773 32,696 29,922

Romania 152,821 142,425 134,814 118,665 118,056 117,295 103,535

Russian Federation 1,163,048 1,160,417 1,158,789 1,156,910 1,156,409 1,156,284 1,154,405

Sweden 22,695 22,166 21,757 21,165 20,814 20,774 19,526

Slovenia 10,223 9,680 9,222 7,777 7,525 7,504 7,030

Slovakia 35,468 33,185 31,052 27,488 27,000 26,962 24,363

Turkey

Ukraine 381,246 376,226 372,575 368,506 367,821 367,593 364,475

Total 4,478,597 4,283,324 4,092,425 3,934,951 3,896,605 3,896,002 3,703,840


55

Table A4.2. 2025: Deaths from chronic PM2.5 exposure (alternative metric to that shown in the preceding table)

CLE B1 B2 B6 B3 B4 MTFR

Albania 1,063 1,048 1,031 1,018 1,016 1,016 997

Austria 4,217 3,999 3,834 3,429 3,376 3,371 3,124


Belgium 7,596 7,137 6,770 6,415 6,323 6,320 5,907

Bulgaria 5,847 5,565 5,276 4,812 4,787 4,775 4,458

Belarus 6,369 6,221 6,130 6,006 5,981 5,974 5,868

Switzerland 3,327 3,225 3,148 3,072 3,045 3,044 2,936


Cyprus 591 589 587 584 582 582 575

Czech Republic 7,242 6,721 6,374 5,837 5,737 5,731 5,205

Germany 52,173 48,835 46,088 43,715 42,638 42,600 40,128

Denmark 2,182 2,092 2,030 1,870 1,841 1,834 1,697

Estonia 609 595 589 565 561 557 468

Spain 20,748 18,507 17,447 16,507 16,251 16,370 14,775

Finland 1,740 1,720 1,709 1,651 1,624 1,622 1,483

France 31,137 29,411 28,256 26,769 26,486 26,478 23,342

United Kingdom 25,576 23,306 20,889 19,809 19,285 19,277 18,226

Greece 8,547 8,288 7,457 7,183 7,103 7,100 6,589

Croatia 2,502 2,351 2,223 2,067 2,038 2,031 1,873

Hungary 7,231 6,799 6,373 5,741 5,655 5,645 5,222

Ireland 1,389 1,346 1,305 1,268 1,248 1,246 1,178

Iceland

Italy 49,305 46,527 40,314 38,702 38,019 38,183 34,855

Liechtenstein

Lithuania 1,923 1,829 1,788 1,680 1,642 1,634 1,506

Luxembourg 257 243 232 218 214 214 198

Latvia 1,199 1,158 1,138 1,096 1,036 1,032 917

Moldova 2,278 2,218 2,172 2,119 2,112 2,108 2,067

TFYR Macedonia 858 840 820 804 801 801 784

Malta 169 166 161 158 157 157 152

Netherlands 9,322 8,842 8,442 8,090 7,975 7,968 7,535

Norway 910 899 892 886 883 882 874

Poland 36,708 33,740 31,228 28,556 28,203 28,165 25,248

Portugal 5,254 4,708 4,266 3,956 3,909 3,900 3,569

Romania 16,055 14,963 14,163 12,466 12,402 12,322 10,877

Russian Federation 111,299 111,047 110,892 110,712 110,664 110,652 110,472

Sweden 2,465 2,408 2,363 2,299 2,261 2,256 2,121

Slovenia 1,179 1,116 1,064 897 868 865 811

Slovakia 3,379 3,162 2,958 2,619 2,572 2,569 2,321

Turkey

Ukraine 39,996 39,469 39,086 38,659 38,588 38,564 38,237

Total 480,175 458,436 436,647 419,203 414,824 414,778 393,369


56

Table A4.3. 2025: Deaths from short term ozone exposure CLE B1 B2 B6 B3 B4 MTFR

Albania 105 105 370 108 100 100 94

Austria 312 312 2,316 513 288 287 257

Bosnia and Herzegovina 154 154 818 129 143 143 131

Belgium 265 265 1,033 197 248 247 221

Bulgaria 543 543 1,773 279 510 508 468

Belarus 362 362 1,043 164 348 347 329

Switzerland 270 270 1,203 256 254 254 233

Serbia and Montenegro 497 497 2,063 325 466 465 432

Cyprus 42 42 94 28 41 41 39

Czech Republic 374 374 1,992 313 344 343 307

Germany 2,715 2,715 17,982 3,015 2,533 2,525 2,279

Denmark 127 127 401 152 120 120 110

Estonia 28 28 120 19 27 27 25

Spain 1,609 1,609 5,999 2,992 1,516 1,506 1,402

Finland 71 71 665 181 69 68 63

France 1,704 1,704 8,528 2,089 1,601 1,596 1,451

United Kingdom 1,192 1,192 3,070 1,569 1,123 1,121 1,040

Greece 642 642 2,200 642 605 604 564

Croatia 222 222 609 126 200 199 174

Hungary 533 533 2,175 325 488 486 435

Ireland 50 50 200 105 48 48 46

Iceland

Italy 3,674 3,674 17,109 3,428 3,377 3,369 3,007

Liechtenstein

Lithuania 103 103 550 70 98 98 91

Luxembourg 12 12 97 20 11 11 10

Latvia 65 65 206 27 62 62 57

Moldova 194 194 522 82 185 185 176

TFYR Macedonia 98 98 456 72 93 93 88

Malta 19 19 85 29 18 18 16

Netherlands 338 338 1,393 284 316 316 284

Norway 77 77 455 137 74 74 70

Poland 1,172 1,172 7,585 1,005 1,083 1,079 979

Portugal 449 449 1,318 542 428 423 399

Romania 1,074 1,074 4,170 657 986 983 903


Sweden 172 172 864 195 164 164 152

Slovenia 85 85 359 110 77 76 67

Slovakia 203 203 1,130 168 185 185 165

Turkey

Ukraine 3,018 3,018 7,735 1,218 2,926 2,923 2,818

Total 28,813 28,813 117,680 24,561 27,308 27,242 25,406


57

Table A4.4. 2025: Lost working days to acute PM2.5 exposure


Albania 397,476 391,803 385,545 380,515 379,754 379,696 372,911

Austria 1,255,126 1,190,268 1,141,009 1,020,652 1,004,725 1,003,411 929,687


Belgium 1,792,268 1,683,887 1,597,325 1,513,601 1,491,960 1,491,251 1,393,690

Bulgaria 1,019,480 970,304 919,896 838,907 834,650 832,522 777,296

Belarus 1,316,134 1,285,549 1,266,715 1,241,120 1,235,807 1,234,520 1,212,627

Switzerland 922,755 894,686 873,145 852,125 844,553 844,292 814,526

Serbia and Montenegro 1,354,806 1,321,646 1,286,898 1,253,032 1,247,917 1,246,153 1,218,285

Cyprus 215,741 215,184 214,315 213,133 212,442 212,331 209,879

Czech Republic 2,812,038 2,609,991 2,475,293 2,266,540 2,227,764 2,225,431 2,021,343

Germany 17,654,559 16,524,937 15,595,528 14,792,569 14,427,971 14,415,326 13,578,647

Denmark 520,367 498,980 484,009 445,976 439,002 437,421 404,782

Estonia 120,598 117,886 116,688 111,979 111,223 110,466 92,682

Spain 5,875,073 5,240,420 4,940,403 4,674,178 4,601,646 4,635,439 4,183,764

Finland 392,210 387,576 385,087 372,042 366,034 365,519 334,280

France 8,236,049 7,779,603 7,473,901 7,080,704 7,005,859 7,003,751 6,174,138

United Kingdom 4,731,963 4,311,966 3,864,726 3,664,944 3,568,080 3,566,566 3,372,082

Greece 1,996,351 1,936,047 1,741,734 1,677,793 1,659,223 1,658,457 1,539,189

Croatia 656,093 616,411 583,014 542,165 534,355 532,739 491,262

Hungary 1,645,541 1,547,259 1,450,258 1,306,403 1,286,820 1,284,624 1,188,355

Ireland 327,905 317,748 307,934 299,228 294,619 293,937 277,891

Iceland

Italy 10,896,377 10,282,373 8,909,431 8,552,976 8,402,168 8,438,401 7,702,966

Liechtenstein

Lithuania 338,834 322,226 315,141 296,046 289,337 287,976 265,316

Luxembourg 79,786 75,254 71,835 67,680 66,402 66,375 61,512

Latvia 231,110 223,289 219,379 211,205 199,720 198,875 176,715

Moldova 486,897 474,036 464,305 452,810 451,444 450,477 441,713

TFYR Macedonia 44,129 43,188 42,170 41,314 41,202 41,174 40,317

Malta 26,166 25,601 24,851 24,453 24,316 24,312 23,447

Netherlands 2,797,406 2,653,174 2,533,087 2,427,488 2,393,040 2,391,108 2,261,041

Norway 516,340 510,448 506,193 502,756 501,119 500,792 496,210

Poland 12,359,821 11,360,392 10,514,580 9,614,820 9,495,949 9,483,148 8,501,092

Portugal 1,195,513 1,071,297 970,666 900,260 889,603 887,506 812,208

Romania 2,774,317 2,585,586 2,447,423 2,154,241 2,143,188 2,129,371 1,879,572

Russian Federation 18,448,531 18,406,810 18,380,983 18,351,182 18,343,235 18,341,249 18,311,448

Sweden 628,898 614,235 602,919 586,504 576,782 575,666 541,081

Slovenia 340,782 322,677 307,406 259,224 250,848 250,129 234,351

Slovakia 885,243 828,255 775,008 686,071 673,886 672,927 608,071

Turkey

Ukraine 2,817,818 2,780,716 2,753,732 2,723,657 2,718,597 2,716,911 2,693,862

Total 108,492,188 102,793,733 97,304,956 92,754,243 91,587,571 91,582,141 85,981,592


58

Table A4.5. 2025: Lost working days to acute PM2.5 exposure (valuation at average EU value, €million/year)


Albania 52 51 50 49 49 49 48

Austria 163 155 148 133 131 130 121

Bosnia and Herzegovina 50 48 47 46 46 46 45

Belgium 233 219 208 197 194 194 181

Bulgaria 133 126 120 109 109 108 101

Belarus 171 167 165 161 161 160 158

Switzerland 120 116 114 111 110 110 106

Serbia and Montenegro 176 172 167 163 162 162 158

Cyprus 28 28 28 28 28 28 27

Czech Republic 366 339 322 295 290 289 263

Germany 2,295 2,148 2,027 1,923 1,876 1,874 1,765

Denmark 68 65 63 58 57 57 53

Estonia 16 15 15 15 14 14 12

Spain 764 681 642 608 598 603 544

Finland 51 50 50 48 48 48 43

France 1,071 1,011 972 920 911 910 803

United Kingdom 615 561 502 476 464 464 438

Greece 260 252 226 218 216 216 200

Croatia 85 80 76 70 69 69 64

Hungary 214 201 189 170 167 167 154

Ireland 43 41 40 39 38 38 36

Iceland

Italy 1,417 1,337 1,158 1,112 1,092 1,097 1,001

Liechtenstein

Lithuania 44 42 41 38 38 37 34

Luxembourg 10 10 9 9 9 9 8

Latvia 30 29 29 27 26 26 23

Moldova 63 62 60 59 59 59 57

TFYR Macedonia 6 6 5 5 5 5 5

Malta 3 3 3 3 3 3 3

Netherlands 364 345 329 316 311 311 294

Norway 67 66 66 65 65 65 65

Poland 1,607 1,477 1,367 1,250 1,234 1,233 1,105

Portugal 155 139 126 117 116 115 106

Romania 361 336 318 280 279 277 244


Sweden 82 80 78 76 75 75 70

Slovenia 44 42 40 34 33 33 30

Slovakia 115 108 101 89 88 87 79

Turkey

Ukraine 366 361 358 354 353 353 350

Total 14,104 13,363 12,650 12,058 11,906 11,906 11,178


59

Table A4.6. 2030: Life years lost to chronic PM2.5 exposure

CLE B7 MTFR

Albania 14,465 13,870 13,596

Austria 35,419 28,738 25,845

Bosnia and Herzegovina 15,005 13,948 13,519

Belgium 65,171 54,719 49,903

Bulgaria 42,313 34,864 31,711

Belarus 59,381 56,082 54,725

Switzerland 29,129 26,778 25,458

Serbia and Montenegro 55,085 50,948 49,429

Cyprus 7,761 7,672 7,561

Czech Republic 62,874 49,829 43,886

Germany 367,827 305,409 276,342

Denmark 19,290 16,710 14,907

Estonia 5,115 4,766 3,891

Spain 194,610 152,816 134,610

Finland 14,865 14,109 12,511

France 277,744 237,903 201,930

United Kingdom 239,323 187,307 170,360

Greece 70,672 59,557 53,536

Croatia 19,691 16,266 14,553

Hungary 59,982 47,254 42,532

Ireland 11,015 10,154 9,296

Iceland

Italy 360,954 285,788 253,574

Liechtenstein

Lithuania 16,606 14,492 12,937

Luxembourg 3,019 2,544 2,276

Latvia 9,584 8,743 7,288

Moldova 23,191 21,648 21,084

TFYR Macedonia 8,868 8,302 8,093

Malta 1,571 1,471 1,410

Netherlands 83,618 72,503 66,710

Norway 9,781 9,546 9,418

Poland 321,540 245,770 210,139

Portugal 42,423 32,002 28,291

Romania 139,944 109,910 92,877

Russian Federation 1,114,443 1,108,799 1,106,329

Sweden 22,600 21,111 19,425

Slovenia 9,628 7,385 6,605

Slovakia 33,539 25,649 22,429

Turkey

Ukraine 375,953 364,374 360,397

Total 4,244,001 3,729,738 3,479,383


60

Table A4.7. 2030: Deaths from chronic PM2.5 exposure (alternative metric to that shown in the preceding table)

CLE B7 MTFR

Albania 1,172 1,124 1,102

Austria 4,232 3,433 3,088


Belgium 7,535 6,326 5,770

Bulgaria 5,463 4,502 4,094

Belarus 6,298 5,948 5,804

Switzerland 3,372 3,099 2,947


Cyprus 683 675 665

Czech Republic 7,279 5,769 5,081

Germany 51,337 42,626 38,569

Denmark 2,208 1,912 1,706

Estonia 592 552 451

Spain 21,668 17,014 14,987

Finland 1,825 1,732 1,536

France 30,485 26,112 22,163

United Kingdom 25,293 19,796 18,005

Greece 8,544 7,200 6,472

Croatia 2,478 2,047 1,831

Hungary 7,095 5,590 5,031

Ireland 1,417 1,306 1,196

Iceland

Italy 48,506 38,405 34,076

Liechtenstein

Lithuania 1,843 1,609 1,436

Luxembourg 261 220 197

Latvia 1,134 1,034 862

Moldova 2,331 2,176 2,119

TFYR Macedonia 886 829 809

Malta 187 175 167

Netherlands 9,709 8,418 7,746

Norway 972 949 936

Poland 35,869 27,416 23,442

Portugal 5,421 4,089 3,615

Romania 15,557 12,218 10,325

Russian Federation 113,050 112,477 112,227

Sweden 2,589 2,419 2,226

Slovenia 1,190 913 817

Slovakia 3,481 2,662 2,328

Turkey

Ukraine 41,017 39,754 39,320

Total 480,564 419,552 389,957


61

Table A4.8. 2030: Deaths from short term ozone exposure CLE B7 MTFR

Albania 103 99 93

Austria 298 277 243

Bosnia and Herzegovina 150 140 126

Belgium 258 242 214

Bulgaria 526 497 448

Belarus 356 343 322

Switzerland 259 245 222

Serbia and Montenegro 480 454 415

Cyprus 43 42 40

Czech Republic 359 331 292

Germany 2,623 2,455 2,185

Denmark 124 117 106

Estonia 27 26 24

Spain 1,574 1,487 1,366

Finland 69 67 61

France 1,642 1,551 1,389

United Kingdom 1,171 1,111 1,018

Greece 632 601 553

Croatia 212 193 165

Hungary 510 470 412

Ireland 49 48 45

Iceland

Italy 3,546 3,303 2,896

Liechtenstein

Lithuania 100 96 88

Luxembourg 11 11 10

Latvia 64 61 56

Moldova 192 185 174


Malta 18 17 16

Netherlands 329 310 274

Norway 75 73 69

Poland 1,130 1,049 936

Portugal 441 421 390

Romania 1,041 964 869


Sweden 167 160 146

Slovenia 81 74 63

Slovakia 194 179 156

Turkey

Ukraine 3,004 2,923 2,803

Total 28,169 26,849 24,766


62

Table A4.9. 2030: Lost working days to acute PM2.5 exposure

CLE B7 MTFR

Albania 392,717 376,553 369,129

Austria 1,154,828 936,989 842,656


Belgium 1,704,929 1,431,476 1,305,509

Bulgaria 926,265 763,207 694,193

Belarus 1,264,244 1,194,008 1,165,114

Switzerland 846,344 778,037 739,694

Serbia and Montenegro 1,319,256 1,220,187 1,183,815

Cyprus 229,579 226,957 223,656

Czech Republic 2,658,963 2,107,283 1,855,940

Germany 15,889,787 13,193,399 11,937,737

Denmark 491,558 425,808 379,857

Estonia 115,698 107,806 88,005

Spain 5,812,584 4,564,277 4,020,501

Finland 379,128 359,846 319,083

France 7,731,522 6,622,497 5,621,103

United Kingdom 4,501,811 3,523,355 3,204,576

Greece 1,929,260 1,625,844 1,461,463

Croatia 619,489 511,729 457,850

Hungary 1,576,446 1,241,912 1,117,811

Ireland 320,667 295,600 270,621

Iceland

Italy 10,048,475 7,955,955 7,059,161

Liechtenstein

Lithuania 315,654 275,466 245,905

Luxembourg 78,235 65,908 58,980

Latvia 215,239 196,359 163,684

Moldova 476,943 445,212 433,604

TFYR Macedonia 42,259 39,561 38,562

Malta 25,630 23,995 23,003

Netherlands 2,616,778 2,268,939 2,087,662

Norway 516,018 503,626 496,851

Poland 11,226,504 8,581,021 7,336,972

Portugal 1,141,985 861,450 761,547

Romania 2,611,230 2,050,832 1,732,995

Russian Federation 18,168,911 18,076,888 18,036,628

Sweden 625,578 584,377 537,704

Slovenia 317,734 243,716 217,988

Slovakia 836,548 639,763 559,442

Turkey

Ukraine 2,867,295 2,778,984 2,748,652

Total 102,362,804 87,439,701 80,128,043


63

Table A4.10. 2030: Lost working days to acute PM2.5 exposure (valuation at average EU value, €million/year)

CLE B7 MTFR

Albania 51 49 48

Austria 150 122 110

Bosnia and Herzegovina 48 44 43

Belgium 222 186 170

Bulgaria 120 99 90

Belarus 164 155 151

Switzerland 110 101 96

Serbia and Montenegro 172 159 154

Cyprus 30 30 29

Czech Republic 346 274 241

Germany 2,066 1,715 1,552

Denmark 64 55 49

Estonia 15 14 11

Spain 756 593 523

Finland 49 47 41

France 1,005 861 731

United Kingdom 585 458 417

Greece 251 211 190

Croatia 81 67 60

Hungary 205 161 145

Ireland 42 38 35

Iceland

Italy 1,306 1,034 918

Liechtenstein

Lithuania 41 36 32

Luxembourg 10 9 8

Latvia 28 26 21

Moldova 62 58 56


Malta 3 3 3

Netherlands 340 295 271

Norway 67 65 65

Poland 1,459 1,116 954

Portugal 148 112 99

Romania 339 267 225


Sweden 81 76 70

Slovenia 41 32 28

Slovakia 109 83 73

Turkey

Ukraine 373 361 357

Total 13,307 11,367 10,417


64

Appendix 5: Total national damage (costed at EU average) under the Policy Scenarios

The following tables for 2025 and 2030 respectively show estimated health damage in each country (including non-EU states), with mortality valued using the median VOLY. Use of the mean VSL from CAFE would increase estimates by roughly a factor 3. Non-health impacts are not accounted for. Table A5.1. Aggregated health damage by scenario for 2025.

2025 CLE B1 B2 B6 B3 B4 MTFR

Albania 1,190 1,173 1,155 1,140 1,137 1,137 1,115

Austria 3,102 2,945 2,826 2,533 2,494 2,491 2,305


Belgium 5,416 5,092 4,834 4,581 4,516 4,514 4,216

Bulgaria 3,623 3,452 3,277 2,993 2,978 2,970 2,772

Belarus 4,626 4,520 4,454 4,364 4,346 4,341 4,262

Switzerland 2,589 2,511 2,452 2,393 2,371 2,371 2,283


Cyprus 588 587 584 581 579 579 572

Czech Republic 5,315 4,939 4,688 4,297 4,224 4,219 3,831

Germany 32,660 30,605 28,916 27,437 26,773 26,748 25,169

Denmark 1,613 1,548 1,502 1,386 1,365 1,360 1,258

Estonia 417 408 403 387 385 382 321

Spain 16,349 14,625 13,813 13,083 12,884 12,972 11,722

Finland 1,221 1,207 1,199 1,159 1,141 1,139 1,042

France 24,211 22,893 22,009 20,862 20,643 20,635 18,205

United Kingdom 20,051 18,299 16,433 15,591 15,185 15,178 14,344

Greece 5,974 5,796 5,229 5,040 4,984 4,981 4,624

Croatia 1,653 1,556 1,473 1,371 1,351 1,347 1,240

Hungary 4,921 4,632 4,347 3,921 3,863 3,856 3,564

Ireland 923 895 868 843 830 829 783

Iceland nq nq nq nq nq nq nq

Italy 32,162 30,384 26,443 25,393 24,951 25,052 22,850

Liechtenstein nq nq nq nq nq nq nq

Lithuania 1,343 1,278 1,250 1,175 1,149 1,143 1,054

Luxembourg 247 233 223 210 206 206 191

Latvia 796 769 756 728 689 686 610

Moldova 1,807 1,760 1,724 1,682 1,676 1,673 1,639

TFYR Macedonia 728 713 696 682 680 680 665

Malta 130 128 124 122 121 121 117

Netherlands 7,015 6,658 6,360 6,096 6,010 6,005 5,673

Norway 804 795 788 782 780 779 771

Poland 27,315 25,127 23,275 21,296 21,034 21,005 18,833

Portugal 3,578 3,216 2,924 2,718 2,686 2,679 2,455

Romania 11,765 10,978 10,402 9,172 9,123 9,065 8,010


Sweden 1,855 1,813 1,780 1,732 1,703 1,700 1,597

Slovenia 827 784 748 633 613 611 571

Slovakia 2,746 2,573 2,410 2,137 2,099 2,096 1,894

Turkey nq nq nq nq nq nq nq

Ukraine 27,793 27,431 27,167 26,868 26,817 26,800 26,559

Totals 347,854 332,492 317,443 305,011 301,950 301,896 286,377


65

Table A5.2. Aggregated health damage by scenario for 2030.

2030 CLE B7 MTFR

Albania 1,180 1,131 1,107

Austria 2,937 2,394 2,151


Belgium 5,213 4,384 3,996

Bulgaria 3,262 2,699 2,454

Belarus 4,396 4,153 4,050

Switzerland 2,447 2,252 2,138


Cyprus 631 624 614

Czech Republic 5,009 3,983 3,508

Germany 30,346 25,269 22,855

Denmark 1,546 1,342 1,197

Estonia 393 367 300

Spain 16,251 12,840 11,328

Finland 1,200 1,139 1,011

France 22,872 19,638 16,692

United Kingdom 19,233 15,111 13,746

Greece 5,775 4,885 4,394

Croatia 1,568 1,299 1,161

Hungary 4,649 3,677 3,307

Ireland 897 828 758

Iceland nq nq nq

Italy 30,124 23,989 21,275

Liechtenstein nq nq nq

Lithuania 1,254 1,096 979

Luxembourg 244 206 184

Latvia 731 667 557

Moldova 1,733 1,619 1,576


Malta 131 122 117

Netherlands 6,760 5,869 5,397

Norway 815 796 784

Poland 25,005 19,162 16,395

Portugal 3,468 2,638 2,337

Romania 10,853 8,556 7,242


Sweden 1,858 1,737 1,598

Slovenia 783 604 540

Slovakia 2,615 2,008 1,756

Turkey nq nq nq

Ukraine 27,595 26,747 26,441

Totals 331,841 291,029 270,758


66

Appendix 6: Policy scenario cost increment over CLE scenario from GAINS for 2025 and 2030 (Amann, 2014)

Note: The Commission proposals make no demands on non-EU Member States, so their costs are zero.

Table A6.1. Incremental cost data relative to CLE scenario for 2025. Country B1 B2 B6 B3 B4 MTFR

2025 2025 2025 2025 2025 2025

Austria 2 7 71 96 100 1041

Belgium 7 22 98 114 115 759

Bulgaria 1 18 71 75 80 713

Croatia 1 7 27 34 40 408

Cyprus 0 0 0 1 1 47

Czech Rep. 5 18 95 119 119 1188

Denmark 0 0 22 26 32 774

Estonia 1 1 5 6 8 324

Finland 0 0 6 13 14 1007

France 15 59 307 376 378 7676

Germany 23 169 465 835 855 5265

Greece 1 29 57 79 80 1162

Hungary 1 19 70 93 93 652

Ireland 0 2 10 22 26 456

Italy 30 261 444 655 595 3841

Latvia 0 1 2 19 20 593

Lithuania 0 0 14 23 28 601

Luxembourg 0 0 2 3 3 41

Malta 0 1 1 1 1 18

Netherlands 1 9 49 63 63 914

Poland 70 235 607 714 736 5910

Portugal 4 29 68 82 93 832

Romania 4 40 199 215 266 2905

Slovakia 1 15 71 86 86 777

Slovenia 0 1 39 48 50 146

Spain 9 69 208 307 269 4747

Sweden 0 0 4 13 15 601

United Kingdom 44 186 327 510 512 3610

EU-28 222 1201 3339 4628 4679 47006

Albania 0 0 0 0 0 0

Belarus 0 0 0 0 0 0

Bosnia-H 0 0 0 0 0 0

FYR Macedonia 0 0 0 0 0 0

R Moldova 0 0 0 0 0 0

Norway 0 0 0 0 0 0

Russia 0 0 0 0 0 0

Serbia-M 0 0 0 0 0 0

Switzerland 0 0 0 0 0 0

Turkey 0 0 0 0 0 0

Ukraine 0 0 0 0 0 0

Non-EU 0 0 0 0 0 0

Total 222 1201 3339 4628 4679 47006


67

Table A6.2. Incremental cost data relative to CLE scenario for 2030. Country B7 MTFR

2030 2030

Austria 66 1099

Belgium 109 853

Bulgaria 67 752

Croatia 26 441

Cyprus 0 49

Czech Rep. 106 1269

Denmark 18 814

Estonia 4 362

Finland 5 1036

France 290 7784

Germany 493 5576

Greece 51 1241

Hungary 71 695

Ireland 8 517

Italy 418 3949

Latvia 2 620

Lithuania 14 664

Luxembourg 3 45

Malta 0 17

Netherlands 47 1517

Poland 639 6849

Portugal 67 923

Romania 180 3010

Slovakia 78 852

Slovenia 34 147

Spain 231 5131

Sweden 4 634

United Kingdom 303 3836

EU-28 3334 50681

Albania 0 0

Belarus 0 0

Bosnia-H 0 0

FYR Macedonia 0 0

R Moldova 0 0

Norway 0 0

Russia 0 0

Serbia-M 0 0

Switzerland 0 0

Turkey 0 0

Ukraine 0 0

Non-EU 0 0

Total 3334 50681