Assessing Environmental Sustainability in the Eastern Mediterranean Under Anthropogenic Air Pollution Risks Through Remote Sensing and Google Earth Engine Integration

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019&ndash:2024, analyzing NO2 and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman&rsquo:s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values &ge: 0.75, and statistical significance was assessed at a p &lt: 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region&rsquo:s complex political-economic landscape. NO2 concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 &times: 10&minus:8 mol/m2) and weak correlations with climatic variables (&lt:0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: &minus:2.6 &times: 10&minus:7 mol/m2) with stronger climate&ndash:pollutant correlations (0.30&ndash:0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate&ndash:pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development.