Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019 v1

The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 �m (PM2.5) increases mortality and morbidity.

PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019.