Abstract. This study examines the relationship between carbon monoxide (CO) emissions and urban mobility patterns in Casablanca, largest city and economic hub, using Google Earth Engine's (GEE) cloud-based geospatial processing capabilities (Gorelick et al., 2017). Casablanca presents a compelling case study due to its rapid urbanization, increasing vehicle ownership rates, and challenges with traffic congestion that have intensified air quality concerns in recent years. By integrating satellite remote sensing TROPOMI (Veefkind et al., 2012) satellite sensor data and Google Earth Engine (GEE) techniques, we conducted a comprehensive spatiotemporal analysis of CO concentration patterns across Casablanca's diverse urban landscape. Our GEE-based methodology enabled efficient processing of large-scale datasets to identify critical mobility-pollution relationships across the city's major transportation corridors, industrial zones, and residential areas (Kumar et al., 2020; Amegah, 2018). We provide a comprehensive assessment of air quality in Casablanca and demonstrate the value of using geospatial approaches for informing policymakers and urban planners. The results highlight seasonal variations in CO levels, the identification of pollution hotspots, and the quantification of the influence of urban features and traffic on air quality.
Kamouri et al. (Thu,) studied this question.
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