Air pollution has long been a growing concern, shaped by disparities in economic development, industrialization, and urbanization. In this context, this study quantifies the spatial and temporal interactions between socio-economic indicators and key air pollutants using European region as case study. To this end, socio-economic datasets, alongside air pollution levels derived from numerical modeling, are used to perform a versatile statistical analysis that can be applied to regions beyond Europe. The obtained results identify four distinct country groups, including a prosperous north-central cluster with the cleanest air, a southern block characterized by high ozone and particulate burdens alongside economic vulnerability, a populous central-western triad showing elevated nitrogen oxide levels, and an eastern cluster that remains largely neutral. The findings confirm a close coupling between social inequality and environ-mental exposure, demonstrate both the power and limitations of freely available data, and suggest that such clustering can guide future, targeted investigations. Moreover, cross-national averages may mask within-country inequalities, underscoring the need for finer-scale, multi-year analyses in future work. These insights provide a foundation for more equitable and effective environmental policies across Europe and beyond.
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Cardoso et al. (2026) studied this question.
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