Education and environmental inequality

Multi-hazard, non-linear, and spatially varying

Bibliographic Data

ID24218258
AuthorsBardia Mashhoodi (0000-0002-7037-3932), Gamze Dane (0000-0001-6107-2727), Yang Hu (0000-0003-2027-8491), Jian Zhong (0000-0002-5998-250X), Yue Che (0000-0002-9318-8123), Ying-En Ge (0000-0002-8435-0483), Ayyoob Sharifi
Year2026
Volume151
Pages107956
Publication date2026-11-01
Open AccessYes
TypeARTICLE
VenueSustainable Cities and Society (JOURNAL)
Journal identifiersISSN: 2210-6707 • E-ISSN: 2210-6715
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.scs.2026.107956
OpenAlexW7214800898
LanguageEN
References cited72

Existing analyses on educational attainment and environmental inequalities are often single-hazard, linear and spatially stationary. To bridge these gaps, we study associations between the share of residents in neighbourhoods with low educational attainment and Noise pollution, PM2.5, NO2, O3, Physiological Equivalent Temperature (PET) simulated for a tropical day, and green surfaces in 1,467 urbanised neighbourhoods of the Netherlands, controlling for socioeconomic factors. To the country-scale associations, an aspatial XGBoost model (Global-XGBoost) produces robust goodness-of-fit but high overfitting, indicating location-specific variations in the associations. Accordingly, a complementary geographically weighted XGBoost (GW-XGBoost) model is developed on local associations. The results show that the importance of environmental variables is higher (22% compared to 11%) in the GW-XGBoost models than in Global-XGBoost, and two clusters of neighbourhoods with low and high environmental sensitivities, mainly concentrated inside or outside of highly urbanised areas, could be distinguished. The predictions are both non-linear and spatially varying. At the country scale, neighbourhoods’ lower educational attainment is associated with higher PM2.5, NO2, and PET, lower Noise exposure, lower Non-tree and Tree coverages, and the association with O3 is U-shaped. The associations differ for NO2 (declining), as well as O 3 and Non-tree vegetated surfaces (increasing) at the local scale.

Air pollution · Educational attainment · environmental inequality · environmental sensitivity · Netherlands · Nitrogen dioxide · Noise pollution · nonlinear relationship · Ozone · physiological equivalent temperature · PM2.5 · Socioeconomic Factors · tree cover · urban neighborhoods · Air Quality and Health Impacts · Environmental Justice and Health Disparities · Urban Green Space and Health

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