Publicly available low-cost sensor measurements for PM_2.5 exposure modeling: Guidance for monitor deployment and data selection.

ABSTRACT: High-resolution, high-quality exposure modeling is critical for assessing the health effects of ambient PM_2.5 in epidemiological studies. Using sparse regulatory PM_2.5 measurements as principal model inputs may result in two issues in exposure prediction: (1) they may affect the models' accuracy in predicting PM_2.5 spatial distribution; (2) the internal validation based on these measurements may not reliably reflect the model performance at locations of interest (e.g., a cohort's residential locations). In this study, we used the PM_2.5 measurements from a publicly available commercial low-cost PM_2.5 network, PurpleAir, with an external validation dataset at the residential locations of a representative sample of participants from the A

SUBMITTER: Bi J 

PROVIDER: S-EPMC8688284 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature