Mapping urban air pollution in data-scarce areas using GIS and satellite data

Abstract

Assessing air quality in urban areas is often challenging, especially in areas where ground-based monitoring networks are scarce or even absent. Due to local policies or limited resources, many areas in Italy lack continuous environmental monitoring over time and space.
To overcome this problem, in this study, we offer a practical GIS-based workflow to help make initial air pollution assessments when data is limited. Using the Sorrento Peninsula in Italy as case study, we implement the workflow, using a mix of satellite data and site-specific geolocalized data, to map out where key pollutants like nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) are found across the area.
The method brings together data on NO₂ in the lower atmosphere from the Sentinel-5P TROPOMI sensor and PM_2.5 estimates that come from measuring aerosol optical depth (AOD). We process all this information using QGIS and overlay it with other useful maps, like roads and ferry routes from OpenStreetMap, port locations, land use, and urbanization. By layering these details, we can spot pollution hotspots and better understand how city life and seasonal tourism (strong in the study area), like heavy road traffic or busy ports, influence air quality.
The results show that GIS satellite mapping provides a continuous spatial approximation of air quality, effectively identifying key areas in locations with limited or no in-situ monitoring. This workflow is replicable and can sustain environmental agencies and urban planners with a cost-effective tool for early hotspot detection and urban exposure assessment to inhance policy support and monitoring strategies in Data-sparse environments.