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Predicting gestational personal exposure to PM2.5 from satellite-driven ambient concentrations in Shanghai

Zhu, Qingyang, Xia, Bin, Zhao, Yingya, Dai, Haixia, Zhou, Yuhan, Wang, Ying, Yang, Qing, Zhao, Yan, Wang, Pengpeng, La, Xuena, Shi, Huijing, Liu, Yang, Zhang, Yunhui
Chemosphere 2019 v.233 pp. 452-461
epidemiological studies, meteorological parameters, models, particulates, prediction, pregnancy complications, pregnant women, satellites, China
It has been widely reported that gestational exposure to fine particulate matters (PM2.5) is associated with a series of adverse birth outcomes. However, the discrepancy between ambient PM2.5 concentrations and personal PM2.5 exposure would significantly affect the estimation of exposure-response relationship.Our study aimed to predict gestational personal exposure to PM2.5 from the satellite-driven ambient concentrations and analyze the influence of other potential determinants.We collected 762 72-h personal exposure samples from a panel of 329 pregnant women in Shanghai, China as well as their time-activity patterns from Feb 2017 to Jun 2018. We established an ambient PM2.5 model based on MAIAC AOD at 1 km resolution, then used its output as a major predictor to develop a personal exposure model.Our ambient PM2.5 model yielded a cross-validation R2 of 0.96. Personal PM2.5 exposure levels were almost identical to the corresponding ambient concentrations. After adjusting for time-activity patterns and meteorological factors, our personal exposure has a CV R2 of 0.76.We established a prediction model for gestational personal exposure to PM2.5 from satellite-based ambient concentrations and provided a methodological reference for further epidemiological studies.