Identifying inequitable exposure to toxic air pollution in racialized and low-income neighbourhoods to support pollution prevention

Submitted: 15 December 2014
Accepted: 15 December 2014
Published: 1 May 2013
Abstract Views: 4448
PDF: 2053
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Numerous environmental justice studies have confirmed a relationship between population characteristics such as low-income or minority status and the location of environmental health hazards. However, studies of the health risks from exposure to harmful substances often do not consider their toxicological characteristics. We used two different methods, the unit-hazard and the distance-based approach, to evaluate demographic and socio-economic characteristics of the population residing near industrial facilities in the City of Toronto, Canada. In addition to the mass of air emissions obtained from the national pollutant release inventory (NPRI), we also considered their toxicity using toxic equivalency potential (TEP) scores. Results from the unit-hazard approach indicate no significant difference in the proportion of low-income individuals living in host versus non-host census tracts (t(107) = 0.3, P = 0.735). However, using the distance-based approach, the proportion of low-income individuals was significantly higher (+5.1%, t(522) = 6.0, P <0.001) in host tracts, while the indicator for racialized communities (visible minority) was 16.1% greater (t(521) = 7.2, P <0.001) within 2 km of a NPRI facility. When the most toxic facilities by non-carcinogenic TEP score were selected, the rate of visible minorities living near the most toxic NPRI facilities was significantly higher (+12.9%, t(352) = 3.5, P = 0.001) than near all other NPRI facilities. TEP scores were also used to identify areas in Toronto that face a double burden of poverty and air toxics exposure in order to prioritise pollution prevention.

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Kershaw, S., Gower, S., Rinner, C., & Campbell, M. (2013). Identifying inequitable exposure to toxic air pollution in racialized and low-income neighbourhoods to support pollution prevention. Geospatial Health, 7(2), 265–278. https://doi.org/10.4081/gh.2013.85