Abstract

Background: Characterizing the spatial distribution of PM2.5 species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled the estimation of PM2.5 species concentrations using satellite remote sensing data. In this study, we linked these satellite-based estimates with California birth records to estimate associations between pollutant concentrations and birth weight.Methods: Daily 24-hour average ground-level PM2.5 species concentrations of organic carbon, black carbon, nitrate, and sulfate were estimated during 2005 - 2014 in California at approximately 1 km resolution using ground observations, fractional aerosol optical depth data from the multi-angle imaging spectroradiometer on the Terra satellite and community multiscale air quality modeling simulations. Birth records were provided by the California Department of Public Health - Vital Records. Pollutant exposures averaged across pregnancy were calculated for each birth by linking on maternal residential zip code. Continuous infant birth weight was modeled using multiple linear regression, adjusting for covariates contained on the birth records.Preliminary Results: There were 4.7 million live singleton births included with a median of 28 days of exposure measurements per pregnancy. We observed decreases in mean birth weight per 1 µg/m3 increase in pregnancy-averaged pollutant exposure for organic carbon (β = -3.08, 95% CI: -3.64, -2.51), black carbon (β = -10.27, 95% CI: -11.86, -8.68), nitrate (β = -7.00, 95% CI: -7.55, -6.45), and sulfate (β = -16.21, 95% CI: -17.53, -14.88).Discussion: The use of satellite remote sensing data to estimate PM2.5 components is novel and may help overcome limitations related to the sparse monitoring network. Limitations of this study include uncertainty in the daily exposure estimates, as well as the potential for confounding by factors not ascertained on birth records.

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