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Health Impact Assessment on the Benefits of Reducing PM 2.5 Using Mortality Data from 26 European Cities Introduction The proposed draft of the new European.

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Presentation on theme: "Health Impact Assessment on the Benefits of Reducing PM 2.5 Using Mortality Data from 26 European Cities Introduction The proposed draft of the new European."— Presentation transcript:

1 Health Impact Assessment on the Benefits of Reducing PM 2.5 Using Mortality Data from 26 European Cities Introduction The proposed draft of the new European Directive on ambient air quality (CAFE Directive) has generated debate regarding the establishment of appropriate PM 2.5 values. The draft proposes an annual average PM 2.5 concentration of 25 µg/m 3 by 2015, while the European Parliament proposes an annual limit value of 20 µg/m 3. In addition, the equivalent Environmental Protection Agency (EPA) standard for the U.S. is 15 µg/m 3, and the World Health Organization (WHO) guideline is 10 µg/m 3. This study estimates the potential benefits in terms of deaths that could be prevented by reducing PM 2.5 annual levels to 25, 20, 15 and 10 µg/m 3 respectively in 26 European cities in the Apheis network (www.apheis.net). F Ballester 1, S Medina 2, P Goodman 3, E Boldo 4, A Le Tertre 2, M Neuberger 5, S Larrieu 2, N Künzli 6, K Cambra 7, K Katsouyanni 8, V Puklová 9, C Lourenço 10, I Walda 11, H Neus 12, M González 13, C Iñiguez 1, J Schwartz 14, and the contributing members of the APHEIS Network (1)Valencian School of Health Studies (EVES), Valencia. (2) Institute for Public Health Surveillance, Saint Maurice. (3) Dublin Institute of Technology, Dublin. (4) Carlos III National Institute of Health, Madrid. (5) Institute of Environmental Health, Medical University of Vienna, Vienna. (6) University of Southern California, Los Angeles. (7) Department of Health, Basque Government, Vitoria-Gasteiz. (8) University of Athens Medical School, Athens. (9) National Institute of Public Health, Prague. (10) Environmental Health Department, Lisbon. (11) Municipal Health Service Rotterdam, The Netherlands (12) Department for Science and Health Hamburg Germany. (13) Public Health Agency of Barcelona. (14) Harvard School of Public Health, Cambridge, U.S.A. e-mail: ballester_fer@gva.es Acknowledgements The Apheis programme was supported by the European Commission DG SANCO [programme of Community action on pollution-related diseases] and the participating institutions in 15 European countries. Corrected PM 10 P95 Mean P5 Converted PM 2.5 P95 Mean P5  g/m3 Figure 1. Annual levels for corrected PM 10 and converted PM 2.5 for each Apheis city Figure 2. Potential reductions (%) in the total burden of premature mortality among people age 30 years and over for different decreases in annual PM 2.5 levels in the Apheis cities. % Methods This study used the WHO methodology for Health Impact Assessment (HIA) and the Apheis guidelines for data collection and analysis. The 26 cities in the Apheis network provided population data, deaths for all causes and annual mean concentrations of PM 10 (Table 1). The HIA exposure-response functions (ERFs) for total mortality in people age 30 years and over were derived from Pope et al 2002. PM 10 measurements were corrected to fit with gravimetric methods used by Pope et al, and converted to PM 2.5 using a local conversion factor; if the latter was not available, the default European factor of 0.7 was used. Results Mean annual levels of corrected PM 10 ranged from 17.0 to 61.0 µg/m 3 (Figure 1). The derived PM 2.5 values ranged from 7.2 to 42.7 µg/m 3. Only Dublin had an annual PM 2.5 level below 10 µg/m 3, and seven cities reported PM 2.5 annual concentrations above 25 µg/m 3. Figure 2 shows the potential reductions (%) in the total burden of premature long-term mortality in people age 30 years and over for different scenarios of reduction in PM 2.5 levels. If annual PM 2.5 levels were reduced to 10 µg/m 3, all the cities but Dublin would benefit from this reduction with proportional reductions in the total burden of mortality ranging from 1.1 % (Stockholm) to 17.9 % (Rome). The combined reduction for all the cities would be 6.2%. The benefits clearly diminish when the scenarios are less ambitious, and fall to 3.7, 2.0 and 1.2 % for reductions to 15, 20 and 25 µg/m 3 respectively. Figure 3 shows the combined HIA findings. Reducing the PM 2.5 levels to 10 µg/m 3 would prevent 22,266 premature deaths per year for the 26 Apheis cities combined (95% confidence interval of 6,061-37,343). Reducing PM 2.5 concentrations to 15, 20, and 25 µg/m 3 would respectively prevent 13,291, 7,316 and 4,467 premature deaths. Discussion/Conclusions Direct PM 2.5 measurements were not used in this HIA, but a previous study showed that converted PM 2.5 levels were quite similar to direct levels in 12 cities where both measurements were available (Medina et al, 2005). However conversion factors from PM 10 to PM 2.5 in our study were somewhat heterogeneous across the cities ranging from 0.3 to 0.8. The accuracy of these estimates will improve when reliable direct PM 2.5 will be available on a routine basis in most of the cities. This study illustrates the large reduction in premature deaths that could be achieved by lowering annual PM 2.5 levels in European cities. In specific, reducing annual mean levels of PM 2.5 to 15 µg/m 3 could prevent three times more premature deaths in the Apheis cities than a reduction to 25 µg/m 3 (13,291 vs. 4,467 deaths). This number could grow by up to five times if PM 2.5 levels were reduced to 10 µg/m 3 (22,266 vs. 4,467 deaths). Although several limitations in HIA methodology have been described, its use has proven helpful in estimating the potential health impact of new environmental policies. Figure 3. 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 PM 2.5 levels. Scenarios for reduction of annual PM 2.5 levels (µg/m 3 ) Attributable cases and the potential reduction (%) in mortality for each scenario were estimated for each city and for the 26 cities as a whole. Scenarios of reduction of annual PM 2.5 levels to (µg/m 3 ) References Boldo E, Medina S, Le Tertre A, et al, 2002. Apheis: Health Impact Assessment of Long-term Exposure to PM(2.5) in 23 European Cities. Eur J Epidemiol. 2006 Available: http://www.apheis.net/ Pope A, Burnett R, Thun M, et al, 2002. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287:1132-41. Medina S, Boldo E, Saklad M, et al, 2005. APHEIS Health Impact Assement of Air Pollution and Communications Strategy. Third year report, 2002-2003. Institut de Veille Sanitaire, Saint-Maurice, 232 pages. Available: http://www.apheis.net/ Table 1. Apheis cities, demographic data, methods and factors for PM measurements 1 TSP: total suspended particulates. *Correction factor by default. # Conversion factor by default. (a) French cities: as part of the national program for PM surveillance, a specific polynomial regression has been used for correction of PM10 in each city. The coefficients of these regressions, were derived from parallel PM10 measurements within each city. (b) PM10=TSP*0.58. (c) Estimated PM2.5 by local modelling. Ref: Boldo et al, 2006; and participating cities.


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