Spatiotemporal Perspectives on Air Pollution and Environmental Justice in Hamilton, Canada, 1985–1996

Abstract

This article addresses two questions: (1) How do spatiotemporal changes in air pollution levels-specifically, total suspended particulates (TSP)-rise or fall with socioeconomic status? (2) A critical equity interpretation of environmental policy then motivates this question: does the pursuit of average regional reductions in pollution benefit those who need improvements least, benefit those who need improvements most, or maintain the status quo? TSP data are drawn from networks of monitoring stations operated in 1985, 1990, and 1995. The monitoring data are interpolated with a kriging algorithm to produce estimates of likely pollution distribution throughout Hamilton. Exposure is related to socioeconomic status (SES) variables at the census tract level for corresponding years-1986, 1991, and 1996-and associations are tested with ordinary least squares (OLS) and spatial regression models. The results show that whether TSP rises or falls, injustice persists but becomes less pronounced over time. Among all SES indicators, dwelling value consistently predicts TSP levels for all years, suggestive of a land-rent/ spatial-externalities dynamic. As we move forward in time, it becomes increasingly difficult to differentiate airpollution exposure among Hamilton neighborhoods, as industrial TSP sources become more dispersed in the region and transportation pollution becomes relatively more important. We conjecture that more equitable distributions of air pollution have resulted more from post-Fordist industrial and spatial restructuring than from environmental policy intervention. Injustice in Hamilton and its apparent relationship with changing industrial structure appear similar to results in the United States and speak to a continental, intraurban environmental-justice experience.

Perceptions of Air Quality and Sense of Place among Women in Northeast Hamilton, Ontario, Canada

“…Past studies in Hamilton have shown a negative relationship between socio-economic status and exposure to air pollution (Jerrett et al, 2001;Buzzelli et al, 2003;Buzzelli & Jerrett, 2004). Some evidence suggests that certain visible minority groups may also be disproportionately exposed (Buzzelli & Jerrett, 2004).…”

Linking Health Inequality and Environmental Justice: Articulating a Precautionary Framework for Research and Action

“…15,16 These findings have served to mobilize a new form of environmental activism, organized around the pursuit of environmental justice. This movement, particularly in the United States, has emphasized the fight against environmental racism-that is, policies and practices that place facilities and pollution more frequently in the vicinity of people of color.…”

Transboundary air pollution and environmental justice: Vancouver and Seattle compared

“…Disadvantaged communities are defined by common markers of social disparities including income (Evans and Kantrowitz 2002), ethnicity and race (Bhat 2005;Green et al 2004;Morello-Frosch and Jesdale 2006;Apelberg et al 2005;Mirabelli et al 2006), employment (Cummins et al 2005), education (Buzzelli et al 2006) and family status (Buzzelli et al 2003). Studies of environmental justice are inherently spatial in nature (Sheppard et al 1999) requiring the selection of an appropriate spatial methodology for analyzing the relationship between population and environmental characteristics.…”

“…The correlation of each SES variable with NO 2 was investigated first and variables were kept if they took the hypothesized/expected sign in both correlation and OLS models. To test the efficacy of the prediction models, we evaluated whether selected variables were collinear based on variance inflation factors (VIFs) and whether the model results had spatial autocorrelation (Buzzelli et al 2003). If the models display spatial autocorrelation, least squares estimators may be biased and inconsistent; an aspect of spatial data that ought to be addressed in multivariate regression (Getis 1990).…”