ArticleFrontiers in public health2026
Spatiotemporal assessment of urban PM₁₀ and population exposure using integrated satellite, meteorological, and socio-spatial data.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: The pollution with particulate matter is a major risk factor for population health, especially in urban environments, where the interaction between anthropogenic sources, meteorological conditions and built environment characteristics generates complex spatial patterns of exposure. In this context, the present study aims to estimate the spatial distribution of PM₁₀ concentrations and assess population exposure in a medium-sized city in Romania by integrating satellite data, Methods: The methodology is based on MODIS-MAIAC satellite products to retrieve Aerosol Optical Depth (AOD) values, which are correlated with PM₁₀ data and meteorological variables from four ground-based air quality monitoring stations. Based on these data, a multiple regression model was developed to estimate PM₁₀ concentrations, and subsequently, a composite exposure index was constructed by integrating relevant socio-spatial indicators, such as population density, built environment characteristics, the Normalized Difference Vegetation Index (NDVI), and terrain elevation. Results and discussion: The results highlight pronounced seasonal variability in PM₁₀ concentrations, with maximum values in the cold season (up to 41.8 μg/m
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