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The spatial organization and configuration of different urban elements (i.e., urban form) shape the Urban Ventilation Corridor (UVC), facilitating air pollution dispersion and reducing health hazards. However, few UVC evaluations consider the spatiotemporal variation of hyperlocal air pollutants and environmental justice simultaneously. In this research, we collect air pollution data through mobile monitoring in Glasgow, UK, and evaluate UVC through pollution distribution, Gini coefficients, and explainable machine learning models. The results show that UVC can not only effectively improve air quality but also mitigate inequality in air pollution exposure, particularly to large particles (PM 10 ). Moreover, deprived residents residing in areas with poor ventilation suffer higher levels of air pollution and greater exposure inequality (Gini of UVC: 0.431 vs. non-UVC: 0.368) than their affluent counterparts. Particularly, the top 20% of deprived areas account for 60.02% and 54.65% of air pollutants in UVC and non-UVC regions, respectively. From a planning perspective, encouraging smaller and fragmented buildings and vegetation patches could facilitate airflow and the formation of UVC. Meanwhile, 3D urban form shapes key characteristics of urban surface roughness and impacts UVC distribution and air pollution dispersion, both individually and interactively. This study provides essential support for the improved UVC formation, pollution mitigation, and environmental justice to achieve clean and just urban transitions for global cities. • Leverage both 2D and 3D urban form to characterize the Urban Ventilation Corridor (UVC). • Evaluate the effects of UVC through mobile monitoring of air quality data and Gini coefficients. • UVC could not only effectively improve air quality but also mitigate pollution exposure inequality. • 3D urban form shapes the formation of UVC and impacts air pollution dispersion both individually and interactively.