The majority of studies on environmental justice show that groups with lower socio-economic status are more likely to face higher levels of air pollution. Most of these studies have assumed simple, linear associations between pollution and deprived groups. However, empirical evidence suggests that health impacts are greater at high-pollution concentrations. In this paper, we investigate the associations of extreme levels of particulate matter up to 10 micrometres in size (PM₁₀) and ozone with deprived conditions, children and elderly people at sub-municipal level in Mexico City, using Áreas Geoestadisticas Básicas (AGEBs) as the unit of analysis. We used spatial quantile regression to analyse the association for each quantile of the range of pollution values, while also addressing spatial autocorrelation issues. Across AGEBs, higher levels of PM₁₀ are significantly positively associated with deprived economic conditions and elderly people. These results demonstrate clear variations in the associations between PM₁₀ and vulnerable groups across the ranges of these pollutants. Ozone levels are positively associated with higher numbers of children. The findings reflect differences in the source and degradation of these pollutants and provide important evidence for decision-makers addressing air pollution inequalities and injustice in Mexico City and other cities.

中文翻译：

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墨西哥城的环境不公：一种空间分位数方法

大多数关于环境正义的研究表明，社会经济地位较低的群体更有可能面临更高水平的空气污染。这些研究大多数都假设污染与贫困群体之间存在简单的线性关联。但是，经验证据表明，高污染浓度对健康的影响更大。在本文中，我们研究了尺寸最大为10微米（PM _10）的颗粒物的极端水平的关联。），以及墨西哥城郊区的儿童和老年人的贫困状况，并使用ÁreasGeoestadisticasBásicas（AGEBs）作为分析单位。我们使用空间分位数回归来分析污染值范围内每个分位数的关联，同时还解决了空间自相关问题。在AGEB中，较高的PM ₁₀与贫困的经济状况和老年人显着正相关。这些结果证明了PM ₁₀之间的关联存在明显差异以及这些污染物范围内的弱势群体。臭氧水平与儿童数量增加呈正相关。调查结果反映了这些污染物的来源和降解差异，并为决策者解决墨西哥城和其他城市的空气污染不平等和不公正现象提供了重要证据。