Integration of Satellite, Models and Ground Sensors for City-scale Air Quality Monitoring through the Open Data Cube

Abstract. Effective air quality monitoring is crucial for assessing pollution levels and mitigating associated health risks, particularly in densely populated urban environments. Traditional ground-based monitoring stations provide accurate data but lack the spatial coverage necessary for comprehensive city-wide analysis. This study presents an integrated approach that combines satellite observations, atmospheric composition models, and ground sensor data within the Open Data Cube framework. The Open Data Cube system facilitates data access, processing, and analysis by structuring multi-source air quality information into a unified data endpoint. The Metropolitan City of Milan serves as a case study to evaluate this framework’s potential. The results highlight the feasibility of this approach with the potential of enhancing operational air quality assessments to empower future monitoring services, including real-time applications and improved data accessibility for decision-making and public communication.