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Mortality impacts of PM

Reinhard Mechler, Markus Amann, Wolfgang Sch öpp International Institute for Applied Systems Analysis. A methodology to estimate changes in statistical life expectancy due to the control of particulate matter air pollution. Mortality impacts of PM. Time series studies

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Mortality impacts of PM

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  1. Reinhard Mechler, Markus Amann, Wolfgang SchöppInternational Institute for Applied Systems Analysis A methodology to estimate changes in statistical life expectancy due to thecontrol of particulate matter air pollution

  2. Mortality impacts of PM • Time series studies • Relate daily PM with observed daily mortality • Many studies available (APHEA, etc.) • Chronic effects captured? • Cohort studies • Follow cohorts over decades, relate cohort mortality with PM exposure. Several sites necessary. • Only few studies available, all in US • Capture acute and chronic effects • Measures of mortality: • Cases of premature deaths • Life expectancy - adopted for RAINS

  3. Available cohort studies

  4. Methodology • Life tables provide baseline mortality for each cohort • For a given PM emission scenario: modified mortality through Cox proportional hazard model • From modified mortality, calculate life expectancy for each cohort • With population age statistics: Average life expectancy for entire population • Following report of WHO Working Group on Health Impact Assessment (WHO, 2001)

  5. An example life table

  6. Example implementation • RAINS PM2.5 scenarios for 1990, CLE 2010, MFR • RAINS SO2, NOx, VOC and NH3 scenarios • Dispersion of primary PM: EMEP PPM model • Formation of secondary PM: EMEP Lagrangian model (to be substituted by Eulerian model) • Urban primary PM: assumed 25% above rural background (awaiting input from CITY-DELTA) • RR of Pope et al., 2002 • RAINS population data, UN population projections

  7. Population data in RAINS • Urban and rural population for 50*50 km EMEP grid • Compiled from a variety of sources • Geo-statistical data for 2000 • Development up to 2050 based on UN projections • Time-dependent life tables and age structures from UN • Time-dependent country-specific mortality rates derived

  8. Assumptions • Primary PM in cities 25% above rural background • RR of 1.06 [1.02-1.11] for 10 μg/m3 PM2.5 (Pope et al., 2002) • American RR applicable to Europe • No effects below 5 μg/m3 PM2.5 • Linear extrapolation beyond 35 μg/m3 PM2.5 • No effects for younger than 30 years • For each scenario constant exposure 2010-2080, cohorts followed up to end of their life time • Constant urban/rural population ratios

  9. Illustrative resultsRural background PM2.5 [μg/m3] 1990 CLE 2010 MFR 2010

  10. Illustrative resultsLosses in avg. life expectancy [months] 1990 CLE 2010 MFR 2010

  11. Illustrative resultsLosses in avg. life expectancy [days]

  12. Sensitivity analysis • Preliminary analysis limited to uncertainties of RR (95% CI 1.02-1.11) identified by Pope et al. (2002) • Loss in life expectancy (days): • Other uncertainties: Extrapolation beyond range of evidentiary studies, transferability, population projections, emission and dispersion calculations, etc. • In principle, error propagation (Suutari et al.) is possible

  13. Implementation in RAINS • Hard-wired into RAINS • Provides environmental endpoint for PM health effects • Integrated in multi-pollutant/multi-effect framework • How useful is life expectancy for target setting? • Morbidity impacts not addressed because of methodological and data problems • Quantification of ozone morbidity effects? What will drive O3 reductions?

  14. Conclusions • Methodology for impacts of PM on life expectancy developed • Example implementation in RAINS available • Losses in life expectancy are significant in Europe (~1.5 [0.5-2.5] years), should improve by 2010, and further improvements still possible • Further uncertainty and sensitivity analysis necessary • Life expectancy as additional endpoint in multi-pollutant/multi-effect strategies • Open how to handle morbidity effects in IA

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