Reinhard Mechler, Markus Amann, Wolfgang Schöpp International Institute for Applied Systems Analysis

A methodology to estimate

changes in statistical life expectancy due to the

control of particulate matter air pollution

A study sponsored by the Netherlands Ministry for Housing, Spatial Planning and the Environment (VROM)

and the Swiss Agency for the Environment, Forests and Landscape (BUWAL)

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

Available cohort studies

Seventh-day Adventists study

Abbey et al. 1991, 1999

PM10,6338 individuals1977-1992

RR=1.12 (1.01-1.24) for 10 μg/m3 PM10

Harvard six cities study

Dockery et al., 1993 Krewski et al., 2000

PM2.5,8000 individuals1974-1991

RR=1.13 (1.04-1.24)

HEI-reanalysis:RR=1.14

American Cancer Society (ACS) study

Pope et al. 1995, 2000, 2002

PM2.5, 552138 individuals1979-2000

RR=1.07 (1.04-1.11)

2002 reanalysis:RR=1.06 (1.02-1.11)

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)

Cox proportional hazards model

y number fatalities y0 baseline fatalities

PM PM concentrationsβ functional parameter, determined by

epidemiological studies

PMeyy *0 *

PMePMRR *)(

1).()( PMPMRR

Relative risk (RR):

Approximation for small β:

An example life table

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)

• RAINS population data, UN population projections

• RR of Pope et al., 2002

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

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

Illustrative resultsRural background PM2.5 [μg/m3]

1990 CLE 2010 MFR 2010

Illustrative resultsLosses in avg. life expectancy [months]

1990 CLE 2010 MFR 2010

Illustrative resultsLosses in avg. life expectancy [days]

0

100

200

300

400

500

600

700

800

900

Cze

ch R

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Net

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and

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gium

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Aus

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Bul

garia

Rep

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Yug

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Cro

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Fra

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Sw

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Bel

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Ital

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Latv

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Sw

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Fin

land

Nor

way

Ave

rage

MFR CLE 1990

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

Mean 95% CI

1990 496 168-888

CLE 278 94-497

MFR 192 65-344

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?

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