Dust storms have emerged as a major environmental and public health challenge in arid and semi-arid urban regions, where heterogeneous urban structures and population distributions intensify spatial variability in vulnerability. This study aimed to spatially model urban particulate-related vulnerability associated with dust-prone conditions using an integrated framework based on exposure, sensitivity, and adaptive capacity, in which green infrastructure was represented as a key adaptive-capacity dimension. The study area included four major Iranian metropolises (Tehran, Mashhad, Isfahan, and Ahvaz), representing diverse climatic and socio-environmental conditions. Multi-source datasets, including remote sensing indicators, ground-based air quality and infrastructure data, and census-based socio-demographic variables, were integrated within a Geographic Information System (GIS) environment. A five-step spatial multi-criteria decision-making approach was applied, in which criteria were weighted using the Analytic Hierarchy Process (AHP), normalized via the Min–Max method, and aggregated using the Weighted Linear Combination (WLC) technique to produce vulnerability maps. The results revealed strong intra-urban heterogeneity and inter-city differences in vulnerability patterns. Isfahan exhibited the highest vulnerability, with 40.3% of its area and 64.4% of its population classified as high-risk, followed by Tehran (32.1% of area; 60.6% of population). Ahvaz showed moderate spatial vulnerability (20.8% of area) but high population exposure (50.6%), indicating population concentration in risk-prone zones. Mashhad demonstrated relatively lower vulnerability, with only 19.5% of its area in high-risk classes and 53.7% in low-risk zones, coinciding with more distributed green space provision. These findings demonstrate that integrating environmental, socio-demographic, and infrastructural factors, including urban green infrastructure, is essential for capturing urban vulnerability to dust hazards. The proposed geospatial framework provides a decision-support tool for identifying priority areas and informing green infrastructure planning and climate-adaptive resilience strategies in arid-region cities.
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Farhadi et al. (2026) studied this question.
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