Unequal residential exposure to air pollution and noise: A geospatial environmental justice analysis for Ghent, Belgium

Abstract

Following the growing empirical evidence on the health effects of air pollution and noise, the fair distribution of these impacts receives increasing attention. The existing environmental inequality studies often focus on a single environmental impact, apply a limited range of covariates or do not correct for spatial autocorrelation. This article presents a geospatial data analysis on Ghent (Belgium), combining residential exposure to air pollution and noise with socioeconomic variables and housing variables. The global results show that neighborhoods with lower household incomes, more unemployment, more people of foreign origin, more rental houses, and higher residential mobility, are more exposed to air pollution, but not to noise. Multiple regression models to explain exposure to air pollution show that residential mobility and percentage of rental houses are the strongest predictors, stressing the role of the housing market in explaining which people are most at risk. Applying spatial regression models leads to better models but reduces the importance of all covariates, leaving income and residential mobility as the only significant predictors for air pollution exposure. While traditional multiple regression models were not significant for explaining noise exposure, spatial regression models were, and also indicate the significant contribution of income to the model. This means income is a robust predictor for both air pollution and noise exposure across the whole urban territory. The results provide a good starting point for discussions about environmental justice and the need for policy action. The study also underlines the importance of taking spatial autocorrelation into account when analyzing environmental inequality.

Social Inequalities in Environmental Noise Exposure: A Review of Evidence in the WHO European Region

“…Participants in the group with the most area-level income deprivation were most likely to be exposed to rail noise [34]. A study from Ghent, Belgium, analysing residential exposure to noise found that only neighbourhoods with a higher percentage of people of a specific foreign origin (non-EU and non-Turkish-Maghreb) had a significantly higher exposure [35].…”

Ambient air pollution per specific land use types and activities in an urbanizing Eastern Caribbean Country, St. Kitts and Nevis

“…Previous studies showed urban areas tend to have more diminished air quality [62][63][64]. This increased risk of hazard has been framed as an environmental justice issue [65,66] especially for those socioeconomically disadvantaged [63,64,67,68]. In this investigation, most pollutant concentrations were elevated in high urban areas to varying degrees possibly owing to the selective action of the urban heat island (UHI) effect [69-71], short-term atmospheric conditions such as humidity and temperature [72] or long-term weather events such as drought [73].…”

Рынок Жилья Как Отражение Жилищной Стратификации Городов

“…Зарубежные социологи обращают внимание на нетривиальные аспекты жи лищно пространственной дифференциации городов. В работе Т. Вербеека рассматривается экологическое неравенство городской среды [Verbeek, 2019]. На фоне потока эмпирических данных о воздействии за грязнения воздуха и шума на здоровье справедливое распределение этих воздей ствий приковывает все больше внимания.…”