Results provide limited evidence for an association of early-life mobile source air pollution with childhood asthma incidence with a steeper concentration-response relationship observed at lower levels of exposure.

Investigations of ambient air pollution health effects rely on complete and accurate spatiotemporal air pollutant estimates. Three methods are developed for fusing ambient monitor measurements and 12 km resolution chemical transport model (CMAQ) simulations to estimate daily air pollutant concentrations across Georgia. Temporal variance is determined by observations in one method, with the annual mean CMAQ field providing spatial structure. A second method involves scaling daily CMAQ simulated fields using mean observations to reduce bias. Finally, a weighted average of these results based on prediction of temporal variance provides optimized daily estimates for each 12 × 12 km grid. These methods were applied to daily metrics of 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) over the state of Georgia for a seven-year period (2002-2008). Cross-validation demonstrates a wide range in optimized model performance across pollutants, with SO2 predicted most poorly due to limitations in coal combustion plume monitoring and modeling. For the other pollutants studied, 54-88% of the spatiotemporal variance (Pearson R(2) from cross-validation) was captured, with ozone and PM2.5 predicted best. The optimized fusion approach developed provides daily spatial field estimates of air pollutant concentrations and uncertainties that are consistent with observations, emissions, and meteorology.

Prenatal air pollution exposure is frequently estimated using maternal residential location at the time of delivery as a proxy for residence during pregnancy. We describe residential mobility during pregnancy among 19,951 children from the Kaiser Air Pollution and Pediatric Asthma Study, quantify measurement error in spatially-resolved estimates of prenatal exposure to mobile source fine particulate matter (PM2.5) due to ignoring this mobility, and simulate the impact of this error on estimates of epidemiologic associations. Two exposure estimates were compared, one calculated using complete residential histories during pregnancy (weighted average based on time spent at each address) and the second calculated using only residence at birth. Estimates were computed using annual averages of primary PM2.5 from traffic emissions modeled using a research line-source dispersion model (RLINE) at 250 meter resolution. In this cohort, 18.6% of children were born to mothers who moved at least once during pregnancy. Mobile source PM2.5 exposure estimates calculated using complete residential histories during pregnancy and only residence at birth were highly correlated (rS>0.9). Simulations indicated that ignoring residential mobility resulted in modest bias of epidemiologic associations toward the null, but varied by maternal characteristics and prenatal exposure windows of interest (ranging from −2% to −10% bias).

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