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Predicting air pollution exposure based on household characteristics, indoor and outdoor air quality sensors, and a land use regression model

  • Author(s): Romano, Celeste
  • Advisor(s): Ritz, Beate R
  • et al.
Abstract

Air quality sensors enable the direct ascertainment of household air pollution measures but can usually only be utilized for short periods of time. With indoor and outdoor monitoring of PM2.5 over an extended period, we investigated trends in hourly indoor and outdoor PM2.5 concentrations among pregnant women in Los Angeles County, CA as part of the PARENTs study. Linear mixed effects models were employed to predict hourly indoor PM2.5 concentrations using outdoor PM2.5 concentrations, household characteristics, and resident activities. From 6:00 a.m. to 10:00 p.m., no air conditioning use and a gas oven were associated with higher indoor PM2.5 concentrations (9.71, 95% CI: 1.75, 17.67; 8.21, 95% CI: 0.70, 15.73). From 10:00 p.m. to 6:00 a.m., only outdoor PM2.5 concentrations were associated with indoor measures (0.29, 95% CI: 0.08, 0.50). Results strengthen our understanding of the relationship between hourly indoor and outdoor air pollution.

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