Air Quality, Atmosphere & Health

, Volume 6, Issue 3, pp 563–573 | Cite as

The effect of grid resolution on estimates of the burden of ozone and fine particulate matter on premature mortality in the USA

Article

Abstract

Assessments of human health impacts associated with outdoor air pollution often use air quality models to represent exposure, but involve uncertainties due to coarse model resolution. Here, we quantify how estimates of mortality in the USA attributable to ozone (O3) and fine particulate matter (PM2.5) at coarse resolution differ from those at finer resolution. Using the finest modeled concentrations (12 km), we estimate that 66,000 (95 % CI, 39,300–84,500) all-cause and 21,400 (5,600–34,200) respiratory deaths per year are attributable to PM2.5 and O3 concentrations above low-concentration thresholds, respectively. Using model results at 36 km resolution gives mortality burdens that are 11 % higher for PM2.5 and 12 % higher for O3 than the 12-km estimates, suggesting a modest positive bias. We also scale modeled concentrations at 12 km to coarser resolutions by simple averaging and repeat the mortality assessment at multiple resolutions from 24 to 408 km, including the resolutions of global models; in doing so, we account for the effect of resolution on population exposure. Coarse grid resolutions produce mortality estimates that are substantially biased low for PM2.5 (30–40 % lower than the 12-km estimate at >250 km resolution), but less than 6 % higher for O3 at any resolution. Mortality estimates for primary PM2.5 species show greater bias at coarse resolution than secondary species. These results suggest that coarse resolution global models (>100 km) are likely biased low for PM2.5 health effects. For ozone, biases due to coarse resolution may be much smaller, and the effect on modeled chemistry likely dominates.

Keywords

Air pollution Exposure assessment Grid resolution Human health Ozone PM2.5 

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Environmental Sciences and EngineeringUniversity of North CarolinaChapel HillUSA

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