4.7 Article

Associations between socioeconomic status and ultrafine particulate exposure in the school commute: An environmental inequality study for Toronto, Canada

期刊

ENVIRONMENTAL RESEARCH
卷 192, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2020.110224

关键词

Ultrafine particulate matter; Dosage; Children; Commuting; Socioeconomic status; Environmental inequality

资金

  1. Natural Sciences and Engineering Research Council of Canada [RGPIN-2018-04845]
  2. Environment and Climate Change Canada

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The study explored the exposure patterns of ultrafine particulate matter (UFP) in Toronto, Canada, revealing significant associations with socioeconomic factors such as income, government transfer dependence, immigration status, and education rates. These findings suggest unique patterns of inequality for UFPs compared to other pollutants in the Toronto-based literature, emphasizing the need for further research on UFP dosage from an environmental inequality perspective.
Ultrafine particulate matter (UFP) air pollution is unevenly distributed across urban environments. Disparities in routine activity patterns, such as the exposure risk we face at work or on the commute, can contribute to chronic exposure-related health outcomes that place excess burdening on vulnerable population groups. In Canada, there is disagreement in the literature on the nature of these exposure-related inequalities, and our understanding of disparities associated with specific activity patterns such as commuting is limited. In the context of UFP specific exposure, these relationships are almost entirely unexplored in the environmental inequality literature. Our study presents an exploratory analysis of UFP exposure patterns in Toronto, Canada. We examined UFP dosage disparities experienced by children during routine school commutes. We estimated single trip dosages that accounted for variation in ambient UFP concentration, route morphology (distance, slope) and their effect on inhalation rate and trip duration. We aggregated these values at the dissemination-area level and collected socioeconomic status descriptors from the 2016 census. Our OLS model showed significant spatial autocorrelation (MI = 0.59, p < 0.001), and we instead applied a spatial error model to account for spatial effects in our dataset. We identified significant associations related to median income (beta = -0.087, p < 0.05), government transfer dependence (beta = -0.107, p < 0.005), immigration status (beta = 0.119, p < 0.001), and education rates (beta = -0.059, p < 0.05). Our results diverged from other pollutants in Toronto-based literature and could indicate that UFPs exhibit unique patterns of inequality. Our findings suggest a need to further study UFP dosage from an environmental inequality perspective.

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