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Reducing ambient levels of fine particulates could substantially improve health: a mortality impact assessment for 26 European cities
  1. Ferran Ballester1,2,
  2. Sylvia Medina3,
  3. Elena Boldo2,4,
  4. Pat Goodman5,
  5. Manfred Neuberger6,
  6. Carmen Iñiguez1,2,
  7. Nino Künzli2,7
  1. 1
    Valencian School of Health Studies (EVES), Valencia, Spain
  2. 2
    CIBER Epidemiology and Public Health (CIBERESP), Spain
  3. 3
    Institute for Public Health Surveillance, Saint Maurice, France
  4. 4
    Carlos III National Institute of Health, Madrid, Spain
  5. 5
    Dublin Institute of Technology, Dublin, Ireland
  6. 6
    Medical University of Vienna, Austria
  7. 7
    Centre of Research in Environmental Epidemiology CREAL and ICREA, Barcelona, Spain
  1. Ferran Ballester, Epidemiology and Statistics Unit, Escola Valenciana d’Estudis en Salut-EVES (Valencian School of Health Studies), c/Joan de Garay 21, 46017 Valencia, Spain; ballester_fer{at}


Recently new European policies on ambient air quality—namely, the adoption of new standards for fine particulate matter (PM2.5), have generated a broad debate about choosing the air quality standards that can best protect public health. The Apheis network estimated the number of potential premature deaths from all causes that could be prevented by reducing PM2.5 annual levels to 25 μg/m3, 20 μg/m3, 15 μg/m3 and 10 μg/m3 in 26 European cities. The various PM2.5 concentrations were chosen as different reductions based on the limit values proposed by the new European Directive, the European Parliament, the US Environmental Protection Agency and the World Health Organization, respectively. The Apheis network provided the health and exposure data used in this study. The concentration-response function (CRF) was derived from the paper by Pope et al (2002). If no direct PM2.5 measurements were available, then the PM10 measurements were converted to PM2.5 using a local or an assumed European conversion factor. We performed a sensitivity analysis using assumptions for two key factors—namely, CRF and the conversion factor for PM2.5. Specifically, using the “at least” approach, in the 26 Apheis cities with more than 40 million inhabitants, reducing annual mean levels of PM2.5 to 15 μg/m3 could lead to a reduction in the total burden of mortality among people aged 30 years and over that would be four times greater than the reduction in mortality that could be achieved by reducing PM2.5 levels to 25 μg/m3 (1.6% vs 0.4% reduction) and two times greater than a reduction to 20 μg/m3. The percentage reduction could grow by more than seven times if PM2.5 levels were reduced to 10 μg/m3 (3.0% vs 0.4%). This study shows that more stringent standards need to be adopted in Europe to protect public health, as proposed by the scientific community and the World Health Organization.

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The European Union (EU) air quality legislation is currently based on several directives, and air quality limits have been settled on for the major air pollutants. Despite effective abatement policies in the past, substantial investments have to be put into further emission reductions to decrease the remaining health risks. Regarding health impact, particulate matter (PM) air pollution is a major environmental factor affecting human health and there is no safe level of exposure—that is, a threshold has not been identified.1 Particles of special health concern are those known as fine particles, less than 2.5 μm in diameter (PM2.5). Both short-term and long-term effects of PM2.5 have been described, including substantial effects on life expectancy as a result of long-tem exposure. Recently Pope and Dockery2 have emphasised the importance of PM2.5 from a health perspective; they indicate that this smaller fraction is of immense importance and appears to be more significant that PM10. In practice, an annual average is considered to be sufficient to represent long-term average concentrations of ambient PM.1

The PM pollution must be reduced to better protect public health. Limit values for PM10 (particulates with a diameter smaller than 10 μm) were established in a daughter directive in 1999.3 A limit value of 40 μg/m3 for PM10 annual mean was settled on to be attained in 2005; and 20 μg/m3 in 2010; this last limit has not been implemented yet as it was not ratified in 2005. Recently new PM abatement strategies and European air quality directives have generated wide debate regarding appropriate targets and exposure levels. The commission’s Clean Air for Europe programme (CAFE) released a proposal for a new ambient air quality directive in September 2005.4 One of the major features in the CAFE programme has been to recognise, based on scientific evidence, the importance of measuring particles with a diameter smaller than 2.5 μm as a better marker for health effects. The proposed draft directive includes a mandatory 25 μg/m3 annual average “concentration cap” for PM2.5 to be met in 2010, that has generated debate regarding the establishment of appropriate PM2.5 values to protect the population from the risk of exposure to particles. On the other hand, more ambitious PM2.5 reduction targets have been proposed by different institutions. The European Parliament favours the introduction of a PM2.5 target value of 20 μg/m3 in 2010.5 In parallel, the US Environmental Protection Agency (US EPA) equivalent standard for the United States is 15 μg/m3,6 and the current World Health Organization guideline is 10 μg/m3.7 This discrepancy reflects the differences in the ambitions of different institutions to protect public health.

Health impact assessment (HIA) has been defined by WHO as “a combination of procedures or methods by which a policy, programme or project may be judged as to the effects it may have on the health of a population.”8 HIA studies have been shown to be informative and effective tools of communication with the general public and policy-makers In the domain of air pollution, health impacts have been assessed, providing estimates of both burden of disease attributable to air pollution9 10 and of potential benefits from policies driven to improve air quality.11

In this context, the Apheis network ( has estimated the potential benefits in terms of premature deaths from all causes that could be prevented by reducing annual levels of PM2.5 to 25 μg/m3, 20 μg/m3, 15 μg/m3 and 10 μg/m3 in 26 European cities. These various PM2.5 concentrations have been chosen as different scenarios of reduction, based on the figures described above.


This study uses the WHO methodology for HIA12 13 and the Apheis guidelines for data collection and analysis.14 15 The 26 cities in the Apheis network provided population data, deaths from all causes, annual mean concentrations of PM10 and information on measurement methods. Health and exposure data were available for 2001 or 2002 (table 1).

Table 1 Apheis cities, demographic and environmental data

Provided adequate data on population, outcome and exposure are available, uncertainties involved in estimating the health effects of air pollution are the first concern.7 12 16 Assuming that the relation between particles and mortality is causal, the major uncertainties in this work could arise from the selection of the risk estimate and of the methods for obtaining PM2.5 levels. Taking into account the influence of these decisions on the estimates of the attributable impact of PM2.5, we decided to adopt an “at least” approach—that is, choosing the alternative providing the lowest impact.9

The HIA concentration-response functions (CRF) for total mortality in people aged 30 years and over were derived from the American Cancer Society study performed by Pope and colleagues.17 This is the largest cohort study assessing long-term effects of air pollution on health. Data on risk factors for approximately half a million adults followed from 1982 to 1998 were linked to air pollution data for metropolitan areas in the United States and combined with vital status and cause of death. Concentrations of PM2.5 were measured in 1979–83 and 1999–2000. Models were estimated separately for each of the two PM2.5 measurement periods and also for the average of them. The relative risk of dying from all causes per 10 μg/m3 of chronic exposure to PM2.5 was 1.06 (95% confidence interval (CI) 1.02 to 1.11) for both the PM2.5 average and the 1999–2000 period, and 1.04 (95% CI 1.01 to 1.08) for the 1979–83 period. We used the last one as the “at least” option and the former for the sensitivity analysis. The published estimates of Pope et al17 used linear functions for mortality of the population aged 30 years and over and for exposures in a range between 10 μg/m3 and 30 μg/m3. This corresponds to the range covered in our study (table 1), for which we also used a linear model for the population aged 30 years and over.

PM10 measurements obtained by automatic methods (β-attenuation and TEOM, tapered element oscillating microbalance) were corrected to fit with gravimetric methods used by Pope et al, and converted to PM2.5 using a local conversion factor (ranging between 0.3 and 0.8). When no local factor was available, the lower limit of the range (0.5–0.8) of the PM2.5/PM10 ratio for European cities was selected.7 16 In order to test the sensitivity in estimates of the selection of this ratio in cities with no available local factor, and according to some European publications,4 18 0.7 was also used as the default conversion factor.

Attributable cases and the potential reduction (percentage) in mortality for each scenario were estimated for each city and for the 26 cities as a whole. Relative risks (RR) for each city (i) and scenario (j) were calculated as RRij  =  exp[β × Cij], β being the regression coefficient from Pope et al17 for an increase in 1 μg/m3, and Cij the difference between the actual concentration in a city (i) and the PM2.5. in each scenario (j). Assuming all the population is exposed to the mean concentration in a city, the attributable fraction (AF) to estimate the impact of changing the exposure can be calculated by: AFij  =  (RRij –1)/RRij. To calculate the expected number (EN) of deaths attributable to air pollution, the AFij is applied to the total number of deaths among people aged 30 years and over in each city. So, the expected number of attributable deaths in each city and scenario will be:

ENij  =  number of deaths in city i and for scenario j × AFij

We call these deaths among the population being studied “premature deaths” because we assume exposure to air pollution causes these deaths earlier than would normally occur. To calculate the expected proportional reductions in mortality we divided this number by the total number of deaths among people aged 30 years and over in each city. For the combined estimates we obtained the number of attributable deaths for the 26 cities and applied it to the total number of deaths among people aged 30 years and over in the 26 cities.

To be comparable with previous impact assessments we used the central estimates and the 95% confidence interval of the C-R functions. Finally, in order, to describe quantitatively the range of uncertainties we performed a sensitivity analysis of the more important assumptions.


Mean annual levels of corrected PM10 ranged from 17–61 μg/m3 (fig 1). The derived PM2.5 values using 0.5 as the default conversion factor ranged from 7.2–33.8 μg/m3. London and Dublin presented an annual PM2.5 level below 10 μg/m3, and Athens, Cracow and Rome concentrations above 25 μg/m3.

Figure 1 Annual levels for corrected PM10 and converted PM2.5 for each Apheis city (conversion factor by default: 0.5).

Table 2 shows the estimates of reductions in annual mortality rates among people aged 30 years and over for different scenarios of reduction in PM2.5 levels for each of the 26 cities using the “at least” approach—that is, RR: 1.04 (95% CI 1.01 to 1.08) for a 10 μg/m3 increase in chronic (annual) exposure to PM2.5, and 0.5 as the default ratio for PM2.5 conversion. Table 2 illustrates the magnitude of the potential benefits among the different scenarios and cities, depending on their annual level of particles and the baseline mortality rate. All other things being equal, if annual PM2.5 levels were reduced to 10 μg/m3, all the cities but Dublin and London would benefit with percentage reductions in premature mortality ranging from 0.3% (Stockholm) to 9.0% (Cracow). The average reduction in the total burden of mortality among people aged 30 and over in all the cities would be 3.0% (95% confidence interval: 0.8% to 5.8%). It would be 1.6% (0.4% to 3.1%), for PM2.5 reductions to 15 μg/m3. The benefits clearly decrease when the reduction scenarios are less ambitious, and fall to 0.8% (0.2% to 1.6%) and 0.4% (0.1% to 0.8%) for PM2.5 reductions to 20 μg/m3 and 25 μg/m3, respectively.

Table 2 Potential reductions in premature deaths rates per 100 000 (and their 95% confidence intervals) and percentage reductions in the total burden of premature mortality (and their 95% confidence intervals) among people age 30 years and over for different decreases in annual PM2.5 using a conservative estimate (“at least” approach)*

Figure 2 shows the results of the sensitivity analysis of the estimates for potential reductions in premature mortality in people age 30 years, and over for the 26 Apheis cities combined, using alternative options for the CRF (1.06, 1.02 to 1.11) and the conversion factor (0.7). When these last two options are applied in the same model, the estimates for reductions in premature deaths double. A reduction in PM2.5 annual levels to 10 μg/m3 would prevent 6.2% of the total burden of mortality (95% CI 1.7% to 10.4%). Reducing PM2.5 concentrations to 15 μg/m3, 20 μg/m3 and 25 μg/m3 would reduce the burden of mortality by 3.7% (1.0% to 6.2%), 2.0% (0.6% to 3.4%) and 1.2% (0.3% to 2.1%), respectively.

Figure 2 Sensitivity analysis of potential reductions in total annual deaths (central estimate and 95% CI) among people age 30 years and over in the 26 Apheis cities for different decreases in annual PM2.5 levels.


This study illustrates the reduction in premature deaths that could be achieved by lowering annual PM2.5 levels in European cities. Specifically, and using the “at least” approach in the 26 Apheis cities with more than 40 million inhabitants, reducing annual mean levels of PM2.5 to 15 μg/m3 could lead to a reduction in the total burden of mortality among people aged 30 years and over which is four times greater than the reduction in mortality that could be achieved by reducing to 25 μg/m3 (1.6% vs 0.4% reduction) and two times greater than a reduction to 20 μg/m3. The percentage reduction could grow by up to more than seven times if PM2.5 levels were reduced to 10 μg/m3 (3.0% vs 0.4%).

Methodological issues

Several limitations could affect HIA estimates as sources of uncertainty and variability. One shared problem is that of exposure assessment and, related to that, comparability between cities. In our study direct PM2.5 measurements were not available in more than half of the cities, but a previous study showed that converted PM2.5 from PM10 levels were similar to measured levels of PM2.5 in 12 cities where both measures were available.15 In the present work conversion factors from PM10 to PM2.5 were somewhat heterogeneous across the cities ranging from 0.3 to 0.8, and, among other reasons, this fact led us to perform the sensitivity analysis using two default conversion factors. The accuracy of these estimates will improve when reliable direct PM2.5 levels are available on a routine basis in more cities.

The choice of the concentration-response functions (CRFs) is very influential in the HIA process. In line with guidelines and previous HIA we used estimates from cohort studies to capture the long-term effects.7 911 15 While we used the estimates from the US ACS study it is of note that various European longitudinal studies have recently shown results consistent with a causal link between long-term air pollution exposure and mortality in Europe as well (in France,19 in The Netherlands,20 in Norway21 and in Germany).22 Moreover, the re-analyses of the ACS data among participants from southern California, using more detailed assignment of exposure,23 and an update of the 6-Cities study in the United States,24 provided larger estimates than the original ACS study. The percentage increase in total mortality estimated in the ACS for a 10 μg/m3 increase in PM2.5 was about 6%, while in the more recent and powerful studies, this percentage is between 15% and 18%. This newer evidence is also reflected in an expert solicitation conducted by the US EPA.25 They used a new approach with standardised one-by-one interviews and structured protocols to investigate the judgment of 12 selected experts regarding causality as well as the probability distribution of the CRFs. A causal role in the air pollution–mortality association was considered the most likely interpretation of the literature, and “best estimates” for the CRFs ranged higher than those used in this HIA. In that way, a meta-analysis combining results from American and European studies of the effect of particulate air pollution on adult mortality26 provided a relative risk of 1.059 (95% CI 1.031 to 1.088) per 10 μg/m3 in PM10 concentration, which depending on the PM2.5/PM10 ratio assumed (0.7 or 0.5), is 1.4 or two times higher than the bigger CRF (1.06; 95% CI: CI 1.02 to 1.11) we used for PM2.5. Thus, we conclude that health benefits of improved air quality would most likely be larger than those expressed in our study.

The use of “attributable death” may be a source of debate. We emphasise that reductions of air pollution—similar to smoking cessation—cannot prevent but only postpone death. As in the case of smoking, those not (or less) exposed gain life expectancy. However, expression of “attributable death” remains of use to communicate the burden of air quality. This is also supported by intervention-like studies such as the coal ban in Dublin, which was immediately followed by a decline in air pollution and reduced number of deaths in the years after the ban.27 Attributable death and loss in life expectancy are interrelated measures of health as the derivation of life expectancy depends on the observed death rates in the population. A previous paper by the Apheis network estimated that a sustained reduction of the annual mean values to 15 μg/m3 PM2.5 would translate into non-negligible gains in life expectancy.11 Depending on the city, the increase in life expectancy would be between 1 month and more than 2 years. Thereby, the greater the reduction in PM2.5 concentration, the greater the benefit.

The health impact and benefit assessment in this study has been made considering PM2.5 as an indicator of the complex air pollution mixture. Although there have been suggestions that specific PM fractions—for example, the primary combustion-derived particles (soot) combined with nitrogen dioxide from motor vehicles, are more important for toxicity and adverse health effects,28 it was not possible, however, to precisely quantify the contribution of different sources and different PM components. Research is ongoing to better understand the specific toxicity of certain PM fractions but the evidence on the effects of PM on health, one of the most documented issues in environmental epidemiology, is more than robust today. To the extent that PM2.5 values are or will be subject to clean air regulations, and given that numerous epidemiological studies are based on this measure, it is of policy relevance to express the health impact using PM2.5 as well.

A sensitivity analysis taking into account the main assumptions in the model was performed to deal with uncertainty in our estimates. The estimates for each scenario vary by twofold as a maximum compared with our “at least” approach, but the comparison between scenarios ranged up to more than seven times in potential reduction in mortality for reductions of the PM2.5 annual mean values to 25 μg/m3 compared to reductions to 10 μg/m3. The sensitivity analysis indicates that base estimates were sensitive to the choice of both the coefficient from the ACS study and the default PM2.5/PM10 ratio, but the most important changes in the estimates came from the target concentration to be potentially achieved.

Policy relevant issues

Although several limitations in HIA methodology have been described, its use has proved helpful in estimating the potential health impact of different environmental scenarios and consequently in helping the decision-making process in public health and environmental policies.29 Lowering PM2.5 levels in urban locations in Europe could result in a substantial decrease in the number of premature deaths and in a considerable gain in life expectancy. Some of these deaths will occur within hours after reaching high concentrations of air pollution.30 We emphasise, however, that the full benefit as expressed in our calculations, including subacute and chronic effects and effects with long latency, are unlikely to happen in the very first year. A model based on air pollution studies concluded that under the most plausible assumptions more than 80% of the total annual benefit in reduced death might be reached within 5 years,26 but in a scope of multinational regulatory effort the process could be more complex and changes in air quality would probably play out over more extended periods.

Our study is limited to the quantification of the health effects of PM2.5; it does not consider the specific abatement strategies to reach lower levels, their technical feasibility or their associated costs. Other studies have already analysed the economic implications, as a key consideration in most environmental policies. Based on recent updated benefit estimates, the US EPA has estimated that meeting the annual standard of 15 μg/m3 for PM2.5 will result in benefits ranging from $20 billion (£9.7 billion; €13.6 billion) to $160 billion a year.6 In Europe, the cost-benefit analysis of CAFE has shown that large benefits are predicted if current legislation on emissions was implemented in all countries of the EU. If all member states reach their climate policy obligations under the Kyoto Protocol, and carry on implementing greenhouse gas reduction policies from 2000 to 2020, the reduction in air pollution could reduce annual costs by €89 billion (£63.5; $130 billion) to €183 billion per year from current policies by 2020.31 It is clear that reducing air pollution levels is not an easy task but the health and economic benefits have been proved.

What is already known about this subject

  • A huge body of evidence indicates that particulate air pollution has a detrimental effect on human health. Fine particles (those less than 2.5 μm in diameter, PM2.5) have a strong impact on public health, and both their acute and chronic effects have been described. Studies also show that improvements in air quality lead to reductions in mortality and morbidity.

  • Standard health impact assessment methods (HIA) can be used to estimate the health burden attributable to air pollution and the expected reduction in the burden for various scenarios of improvements in air quality. In Europe the Clean Air for Europe (CAFE) programme has evaluated the potential benefits of current and future control strategies, and the Apheis Programme has evaluated the impact of air pollution in 26 European cities in 12 countries.

What this paper adds

  • This paper aims to provide information useful in choosing the best future target value for PM2.5 in the European Union.

  • Specifically, EU institutions are currently negotiating a new air-quality directive. For fine particulate matter (PM2.5) the European Commission and the European Parliament have respectively proposed mean annual levels of 25 μg/m3 and 20 μg/m3 as limit values; 15 μg/m3 is the standard value for the annual level of PM2.5 recently approved by the US EPA, and 10 μg/m3 is the WHO guideline.

  • Meeting US EPA or WHO air-quality standards would substantially reduce mortality in European cities. The Apheis network has estimated the number of premature deaths from all causes that might be prevented by reducing PM2.5 levels in 26 European cities: reducing annual mean levels of PM2.5 to 10 μg/m3 could prevent seven times more premature deaths than a reduction to 25 μg/m3; the decrease would be fourfold with a reduction to 15 μg/m3, and only twofold with a reduction to 20 μg/m3.

Policy implications

  • Air pollution has decreased substantially over the last few decades in Europe. However, lowering pollution levels further, PM2.5 in particular, in urban areas in Europe could result in a substantial decrease in the number of premature deaths and, thus, in a considerable increase in life expectancy.

  • To tackle air pollution and adequately protect public health in Europe, the political willpower is needed to adopt the air-quality standards proposed by the scientific community and WHO.

In the context of the debate of the future European legislation on PM, epidemiological findings are important because (1) they do not indicate a threshold for PM health effects in the population, and (2) the elderly, children and people with existing chronic respiratory and cardiovascular diseases appear to be at greater risk from exposure to particles. European air quality standards should be set at levels to protect the most sensitive groups within the population. The precise choice of a future limit or target value for PM2.5 is therefore a political decision based on the willingness to accept certain health risks and the efforts needed to prevent them.

Air pollution has substantially decreased over the past few decades in Europe. However, lowering PM2.5 levels in urban locations in Europe could result in a substantial decrease in the number of premature deaths and, subsequently, in a considerable gain in life expectancy. Political willpower is needed to tackle air pollution and adequately protect public health in Europe. Indeed, our assessment puts the current discussions of European decision-makers into ambiguous light. Most of the research projects that provided the strongest evidence for a causal role of air pollution in morbidity and mortality in Europe were publicly funded, often by the European Commission and by national agencies. The net scientific evidence has led WHO to propose lowering PM2.5 annual mean values to 10 μg/m3. In some developed parts of the world such as California, where an annual mean PM2.5 value of 12 μg/m3 has been legally binding since 2002, actions to improve air quality became main policy targets. If the basic objective of the new EU directive is to safeguard health, more stringent standards need to be adopted, as proposed by the scientific community and WHO.7

Meeting WHO standards on air quality, or at least those in effect in California or the United States in general, would produce considerable health benefits in European cities; as such these standards should be adopted as soon as possible.


The Apheis programme was supported by the European Commission DG SANCO programme of European Community action on pollution-related diseases (contract Nos SI2.131174 [99CVF2-604]; SI2.297300 [2000CVG2-607]; SI2.326507 [2001CVG2-602] and the participating institutions in 15 European countries.

Results of this work have been presented at the International Conference on Environmental Epidemiology and Exposure Analysis, Paris September 2006.

The opinions, findings, and conclusions expressed are those of the authors and are not necessarily those of their institutions.


Participants in the Apheis network

Coordinator: Sylvia Medina (Saint Maurice, France). Working team: Koldo Cambra, Eva Alonso, Francisco Cirarda, Teresa Martinez, Luis González De Galdeano: Department of Health, Basque Government, Vitoria-Gasteiz, Spain. Florian Franck, Laurence Pascal: Regional Centre of Epidemiology, National Institute of Public Health Surveillance, Saint Maurice, France. Sylvia Medina, Alain Le Tertre: Department of Environmental Health, National Institute of Public Health Surveillance, Saint Maurice, France. Manuel Gonzalez Cabré, Estela Diaz De Quijano Sanchez, Natalia Valero: Environmental Health Service, Public Health Agency of Barcelona, Spain

Apheis city centres

Athens: Antonis Analitis, Giota Touloumi, Klea Katsouyanni, Department of Hygiene and Epidemiology, University of Athens, Athens, Greece; Austria (Vienna/Innsbruck): Manfred Neuberger and Hanns Moshammer, Institute for Environmental Health, Center for Public Health Medical University of Vienna, Vienna, Austria; Barcelona: Manuel Gonzalez Cabré, Estela Diaz De Quijano, Natalia Valero, Environmental Health Service, Public Health Agency of Barcelona, Spain; Bilbao: Koldo Cambra, Eva Alonso, Francisco Cirarda, Teresa Martínez, Department of Health, Basque Government, Vitoria-Gasteiz, Spain; Bucharest: Emilia Maria Niciu, Institute of Public Health, Bucharest, Romania; Budapest: Anna Paldy and Janos Bobvos, Jozsef Fodor National Center for Public Health, National Institute of Environmental Health, Budapest, Hungary; Brussels: Catherine Bouland, Institute for the Management of The Environment (BIME), Brussels, Belgium; Copenhagen: Lisbeth Knudsen, Department of Environmental and Occupational Health, Institute of Public Health and Lis Keiding, National Board of Health, Copenhagen, Denmark; Cracow: Krystyna Szafraniec, Epidemiology and Preventive Medicine, Jagellonian University, Cracow, Poland; Dublin: Pat Goodman and Luke Clancy, Saint James Hospital, Dublin, Ireland; France: PSAS-9 project: Sylvie Cassadou (Toulouse), Pascal Fabre, Hélène Prouvost, Christophe Declerq (Lille), Sophie Larrieu (Bordeaux), Laurence Pascal (Marseilles), Jean François Jusot (Lyon), Myriam Blanchard (Rouen, Le Havre), Agnès Lefranc, Benoìt Chardon (Paris) Institut de Veille Sanitaire, Saint-Maurice, France; Hamburg: Michael Schümann, Institute of Medicine, Biometry and Epidemiology (IMBE) and Hermann Neus, Department for Science and Health (BWG) Hamburg, Germany; Lisbon: Cristina Fraga Amaral Filomena Araujo, Catarina Lourenço Environmental Health Department, General Health Directorate, Lisboa, Portugal; Ljubljana: Tina Gale, Peter Otorepec Institute of Public Health, Ljubljana, Republic of Slovenia; London: Richard Atkinson and Ross Anderson, Saint George’s Hospital Medical School, London, UK; Madrid: José Frutos García García, Laura Lopez Carrasco, Department of Environmental Health. Belén Zorrilla Torras, Ana Gandarillas Grande, Ana Robustillo Rodela, Department of Epidemiology, Institute of Public Health, Regional Ministry of Health, Madrid Regional Government, Madrid, Spain; Prague: Ruzena Kubinova, Vladimíra Puklová,, Helena Kazmarová, Environmental Health Centre, National Institute of Public Health, Prague, Czech Republic; Rome: Ursula Kirchmayer and Paola Michelozzi, ASL RM/E Azienda Sanitaria Locale Roma E (Local Health Authority Roma E), Rome, Italy; Rotterdam: Ingrid Walda Municipal Health Service Rotterdam and Reind Van Doorn, Health Protection Agency, Rotterdam, The Netherlands; Seville: Antonio Daponte, Silvia Toro, Andalusian School of Public Health, Granada, Spain; Sweden (Stockholm/Gothenburg): Bertil Forsberg, Lars Modig, Umeå University, Department of Public Health and Clinical Medicine, Umeå, Sweden; Valencia: Ferrán Ballester, Francisco Garcia, Carmen Iñíguez, and José Luis Bosch (City Council), Valencian School of Health Studies, Valencia, Spain.

Experts on outdoor air pollution

Ferran Ballester: Valencian School of Health Studies, Valencia, Spain; Sylvie Cassadou: National Institute of Public Health Surveillance, InVS, Toulouse, France; Fintan Hurley: Institute of Occupational Medicine, Edinburgh, UK; Nino Künzli: Centre of Research in Environmental Epidemiology CREAL and ICREA, Barcelona, Spain; Odile Mekel: Institute of Public Health North Rhine-Westphalia NRW (lögd), Bielefeld, Germany; Hans-Guido Mücke: WHO Collaborating Center (Air)-Federal Environmental Agency, Berlin, Germany; Nikolaos Stilianakis: Institute for Environment and Sustainability, European Commission, JRC, Ispra, Italy.



  • * See list of Apheis participants at the end of the paper.

  • Competing interests: None.

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