Dust storms and industrial air pollutants pose significant environmental and public health challenges in Kuwait, where frequent dust events coincide with intensive industrial and urban activities. This study develops a spatially explicit vulnerability assessment framework for dust-related particulate matter and selected industrial air pollutants (NO₂, SO₂, CO) by integrating satellite remote sensing, census-based socioeconomic data, and GIS-based multi-criteria decision analysis (GIS–MCDA). Following the IPCC AR4 framework, vulnerability is modeled as a function of exposure, sensitivity, and adaptive capacity. Fifteen quantitative indicators derived from MODIS-AOD, Sentinel-5P TROPOMI, and district-level census data were weighted using the Best–Worst Method (BWM) and combined to generate overall vulnerability maps. Results reveal strong spatial heterogeneity: high and very high vulnerability levels are concentrated in residential and coastal areas, where dust events, industrial pollutants, and sensitive populations coincide. Approximately 96% of the population resides in moderate to very high vulnerability zones. In contrast, southern and northern regions with oil and gas fields and farms exhibit lower vulnerability due to lower population density and higher adaptive capacity. This integrated framework identifies vulnerability hotspots and provides a robust tool for evidence-based mitigation, urban planning, and resilience strategies in dust-prone regions.
Al-Hemoud et al. (Tue,) studied this question.