Air pollution mapping and monitoring using Sentinel-5P data and Google Earth Engine

Urbanization and industrialization have significantly altered land surface temperature (LST) and air quality (AQ), particularly in rapidly developing regions such as Sharkia Governorate, Egypt. This research presents a comprehensive spatio-temporal distribution of LST and air pollutants (APTs) interactions in Sharkia Governorate, Egypt, for 2024. LST data were derived from the MOD11A1 product, while PM2.5 and PM10 concentrations were obtained as AOD-derived estimates using empirical models calibrated in other regions, which are considered invalidated approximations pending local calibration. Sentinel-5P (S5P) data were used for APTs, and all datasets were processed through the Google Earth Engine (GEE). The southern industrial zones, particularly 10th of Ramadan and Belbies, exhibit significantly higher LST values, whereas northern rural areas maintain lower temperatures due to vegetation cover and agricultural activity. Correlation analysis reveals strong positive relationships between LST and key pollutants such as Methane (CH 4 , r = 0.8589) and UVAI (r = 0.8874), indicating that higher temperatures enhance pollutant concentration and dispersion. A moderately positive correlation was found with Formaldehyde (HCHO, r = 0.4282). Conversely, Ozone (O 3 ) exhibited a moderately negative correlation (r = -0.7854) with LST. Particulate matter (PM2.5, PM10; r = 0.286, 0.413) showed weak correlations, suggesting that their emissions are primarily driven by anthropogenic sources rather than temperature fluctuations. Principal Component Analysis (PCA) was incorporated to explore multivariate relationships among pollutants and identify dominant underlying factors influencing air quality patterns. Geographically weighted regression (GWR) identified pollution hotspots in the southwest, particularly high-density urban and industrial areas, where CH 4 and UVAI showed stronger impacts on LST (local R 2 > 0.8). All PM results are presented as invalidated estimates, and their interpretation is approached cautiously. The findings underscore the implications of urbanization and industrial activities on local climate, air quality, and public health, emphasizing the need for ground-based validation and mitigation policies.