When space and time matter in environmental injustice: A Bayesian analysis of the association between socio-economic disadvantage and air pollution in Greater Mexico City

TY - JOUR

T1 - When space and time matter in environmental injustice

T2 - A Bayesian analysis of the association between socio-economic disadvantage and air pollution in Greater Mexico City

AU - Lome Hurtado, Alejandro

AU - Touza, Julia M.

AU - White, Piran Crawfurd Limond

AU - McClean, Colin John

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

PY - 2023/11/6

Y1 - 2023/11/6

N2 - Environmental injustice refers to the unequal burden of pollutants on groups with lower socioeconomic status. An increasing number of studies have identified associations between high levels of pollution and socioeconomic disadvantage. However, few studies have controlled adequately for spatio-temporal variations in pollution. This study uses a Bayesian approach to explore the association between socioeconomic disadvantage and pollution in Mexico City Metropolitan Area. We quantify the association of socioeconomic disadvantage with PM10 and ozone and evaluate the impact of accounting for spatio-temporal structure of the pollution data. We find a significant positive association between socio-economic disadvantage and pollution for levels of PM10, but not ozone. The inclusion of the spatio-temporal element in the modelling results in improved weaker estimates of this association but this does not alter results substantially. These findings confirm the robustness of previous studies that found signs of environmental injustice where spatio-temporal variations have not been explicitly considered, confirming that targeted policies to reduce pollution in socio-economically disadvantaged areas are required.

AB - Environmental injustice refers to the unequal burden of pollutants on groups with lower socioeconomic status. An increasing number of studies have identified associations between high levels of pollution and socioeconomic disadvantage. However, few studies have controlled adequately for spatio-temporal variations in pollution. This study uses a Bayesian approach to explore the association between socioeconomic disadvantage and pollution in Mexico City Metropolitan Area. We quantify the association of socioeconomic disadvantage with PM10 and ozone and evaluate the impact of accounting for spatio-temporal structure of the pollution data. We find a significant positive association between socio-economic disadvantage and pollution for levels of PM10, but not ozone. The inclusion of the spatio-temporal element in the modelling results in improved weaker estimates of this association but this does not alter results substantially. These findings confirm the robustness of previous studies that found signs of environmental injustice where spatio-temporal variations have not been explicitly considered, confirming that targeted policies to reduce pollution in socio-economically disadvantaged areas are required.

KW - environmental justice

KW - Air Pollution

KW - Socio-economic disadvantage

KW - Bayesian analysis

U2 - 10.1007/s00267-023-01905-x

DO - 10.1007/s00267-023-01905-x

M3 - Article

SN - 0364-152X

JO - Environmental Management

JF - Environmental Management

ER -