Terry, B., Kremer, P., Goldsmith, S. T., & Shakya, K. M. (2024). Land Use Regression Model to Predict Nitrogen Dioxide in the Greater Philadelphia Area. Atmospheric Pollution Research.
https://doi.org/10.1016/j.apr.2024.102339

has been cited by the following article:

• TITLE: Remote Sensing and Geospatial Approach for Assessing the Impact of Automobiles on Air Quality, Case Study: Casablanca

  AUTHORS: Habiba El Alami El Kamouri, Rachid Essamoud, Mustapha Hakdaoui

  KEYWORDS: Urban Air Pollution, Air Quality, Vehicle Emissions, NO2, Satellite Imagery, Google Earth Engine

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.12 No.11, November 29, 2024

  ABSTRACT: Urban air pollution is a major challenge facing rapidly growing cities in the Middle East and North Africa (MENA) region, with vehicle emissions being a significant contributor. This study aims to analyze the spatial and temporal patterns of air pollutants, particularly nitrogen dioxide (NO2), in Casablanca, Morocco, and investigate the relationship with urban development and transportation characteristics. By integrating satellite remote sensing data and Google Earth Engine (GEE) techniques, 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 NO2 levels, the identification of pollution hotspots, and the quantification of the influence of urban features and traffic on air quality. We discuss the implications of these findings for targeted interventions to improve air quality and the potential for expanding the methodology to other pollutants and cities in the region.