Data and code from: A comparative analysis of wildland fire smoke PM2.5 exposure estimates across California from 2008-2018

This Dryad repository contains four daily wildfire smoke PM2.5 datasets for California (2008–2018), aggregated to the census tract level using a population-weighted approach. The datasets include: (1) a chemical transport model (CTM), the U.S. Environmental Protection Agency's CMAQ model (Wilkins and Connolly, 2024), originally at 12-km resolution; (2) a machine learning (ML) model for the contiguous U.S. (Childs, 2022); (3) a California-specific ML ensemble model (Aguilera, 2023); and (4) a hybrid CTM–ML fusion product, originally at 1-km resolution (Zhang, 2023). All datasets provide isolated daily smoke PM2.5 (µg/m³). The Aguilera and Childs datasets were publicly available at the tract level and were not modified prior to analysis. The Wilkins (CMAQ) and Zhang (fusion) datasets were aggregated from their native gridded resolutions to population-weighted census tract centroids. The repository also contains R scripts used for the publication.