Air pollution management has become a very big issue these days due to the rapid increase in industrialization and urbanizationUrbanization. Combining Artificial Intelligence (AIArtificial Intelligence (AI)) and Machine Learning (ML) with the pollution management system points to a different perspective of air quality and contributes to the efficient and accurate monitoring of air. This paper investigates the use of AI and ML in pollution management by tracking and con-trolling air pollutionAir pollution levels, mainly using Google Earth EngineGoogle Earth Engine (GEE) (GEE) for the monitoring of air pollutantsPollutants such as nitrogen dioxide (NO2) and carbon dioxide (CO2). Enriching the data obtained from GEE, machine learningMachine learning algorithms use satellite data in almost real-time, conducting predictive modeling and pattern recognition for pollutant dispersion. The use of AI-based techniques, linting through supervised classification and regression modelsRegression models, presents the origin of pollution, the prediction of high-risk areas, and the formulation of successful mitigation strategies. This research unveils the capabilities of AI and ML in producing innovative data-driven measures that can be used to fight the air pollution problem, hence ensuring sustainable environmental management.