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Spatiotemporal characterization of indoor PM₂.₅ exposure across urban microenvironments using ground-based monitoring, spatial clustering, and satellite observations
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DOI：10.1007/s11869-026-02020-6.png)
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Abstract
En 中文
Indoor environments constitute primary exposure settings in urban populations, yet systematic spatial characterization across diverse microenvironments remains limited. This study develops an integrated methodological framework to characterize indoor PM₂.₅ exposure patterns across the Mumbai Metropolitan Region (MMR), a rapidly urbanizing megacity region, by combining high-resolution ground-based monitoring from 122 locations across six microenvironment categories (residences, offices, schools, shopping malls, cinema halls, and restaurants), satellite remote sensing data (MODIS AOD), and advanced spatial analytical techniques including PCA-assisted K-means clustering and Getis-Ord Gi* spatial autocorrelation analysis. AOD derived from MODIS MOD04_3K product were spatially matched with monitoring locations to indicate ambient regional aerosol loading patterns and independently support hotspot identification. Indoor PM₂.₅ concentrations demonstrated substantial spatial heterogeneity (98th percentile range: 6.2–350 µg m⁻³). Multivariate clustering identified distinct pollution profiles: low-exposure clusters (15–40 µg m⁻³) versus high-burden clusters (35–112 µg m⁻³), with Principal Component Analysis explaining 63–70% of variance through mean concentrations and temporal characteristics. Getis-Ord Gi* analysis revealed statistically significant hotspots in central-eastern urban sectors, independently validated through satellite-derived AOD correspondence. Time-weighted exposure analysis demonstrated systematic disparities: residential hotspots imposed ~ 370 min/day unhealthy exposure versus < 150 min/day in coldspots. This integrated framework provides reproducible methodology for characterizing indoor air quality in heterogeneous urban environments globally, informing targeted interventions, building design standards, and exposure reduction strategies addressing environmental health disparities in rapidly urbanizing regions worldwide.
Keywords:
Spatial clustering
IAQ
Hotspot identification
MMR
Indoor air quality policy
Exposure assessment
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