Satellite-Based Seasonal Monitoring of PM2.5-Related Trace Gases and Aerosol Loading over the Lazio Region

Abstract

Ground-based monitoring networks often provide uneven spatial coverage, limiting the characterization of air-quality in heterogeneous regions. This study proposes a data-driven framework that identifies spatially coherent atmospheric regimes from multi-gas satellite observations. The framework is applied to investigate the seasonal distribution of PM2.5-related trace-gas indicators and aerosol loading over the Lazio region, central Italy, using TROPOMI-derived vertical column densities of NO2, HCHO, and CO products together with MODIS-MAIAC Aerosol Optical Depth, and integrating satellite observations with land-cover, topographic, and ground-based NO2 data. In this approach, TROPOMI provides spatially continuous information on atmospheric composition, unsupervised clustering identifies multi-gas patterns, and land information supports the interpretation of drivers of emission. The seasonal analysis showed winter NO2 maxima associated with combustion-related emissions, urban areas, and transport corridors, while HCHO peaked during summer, reflecting enhanced VOC-related photochemical activity. CO displayed a more diffuse spatial distribution, consistent with its longer atmospheric lifetime and broader combustion-related sources. The multivariate classification highlighted the Sacco Valley as a multi-pollutant area, the Tiber Valley as a peri-urban agricultural corridor, and the Lepini Mountains as a cleaner sector. The proposed framework provides spatially explicit information useful for interpreting regional air-quality variability, identifying under-monitored sectors, and supporting monitoring and mitigation strategies.