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Environ Health Perspect. 2010 Sep;118(9):1189-95. doi: 10.1289/ehp.0901220. Epub 2010 Apr 8.

An estimate of the global burden of anthropogenic ozone and fine particulate matter on premature human mortality using atmospheric modeling.

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1
University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Abstract

BACKGROUND:

Ground-level concentrations of ozone (O3) and fine particulate matter [< or = 2.5 microm in aerodynamic diameter (PM2.5)] have increased since preindustrial times in urban and rural regions and are associated with cardiovascular and respiratory mortality.

OBJECTIVES:

We estimated the global burden of mortality due to O3 and PM2.5 from anthropogenic emissions using global atmospheric chemical transport model simulations of preindustrial and present-day (2000) concentrations to derive exposure estimates.

METHODS:

Attributable mortalities were estimated using health impact functions based on long-term relative risk estimates for O3 and PM2.5 from the epidemiology literature. Using simulated concentrations rather than previous methods based on measurements allows the inclusion of rural areas where measurements are often unavailable and avoids making assumptions for background air pollution.

RESULTS:

Anthropogenic O3 was associated with an estimated 0.7 +/- 0.3 million respiratory mortalities (6.3 +/- 3.0 million years of life lost) annually. Anthropogenic PM2.5 was associated with 3.5 +/- 0.9 million cardiopulmonary and 220,000 +/- 80,000 lung cancer mortalities (30 +/- 7.6 million years of life lost) annually. Mortality estimates were reduced approximately 30% when we assumed low-concentration thresholds of 33.3 ppb for O3 and 5.8 microg/m3 for PM2.5. These estimates were sensitive to concentration thresholds and concentration-mortality relationships, often by > 50%.

CONCLUSIONS:

Anthropogenic O3 and PM2.5 contribute substantially to global premature mortality. PM2.5 mortality estimates are about 50% higher than previous measurement-based estimates based on common assumptions, mainly because of methodologic differences. Specifically, we included rural populations, suggesting higher estimates; however, the coarse resolution of the global atmospheric model may underestimate urban PM(2.5) exposures.

PMID:
20382579
PMCID:
PMC2944076
DOI:
10.1289/ehp.0901220
[Indexed for MEDLINE]
Free PMC Article
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