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A GIS–Environmental Justice Analysis of Particulate Air Pollution in Hamilton, Canada

Author

Listed:
  • Michael Jerrett

    (School of Geography and Geology, and McMaster Institute of Environment and Health, McMaster University, 1280 Main Street, West Hamilton, Ontario, Canada L8S 4K1)

  • Richard T Burnett

    (Health Canada, 200 Environmental Health Centre, Health Canada, Tunney's Pasture, Ottawa, Canada K1A 0L2)

  • Pavlos Kanaroglou
  • John Eyles
  • Norm Finkelstein
  • Chris Giovis
  • Jeffrey R Brook

    (Air Quality Processes Research Division, Meteorological Service of Canada, 4905 Dufferin Street, Toronto, Ontario, Canada M3H 5T4)

Abstract

The authors address two research questions: (1) Are populations with lower socioeconomic status, compared with people of higher socioeconomic status, more likely to be exposed to higher levels of particulate air pollution in Hamilton, Ontario, Canada? (2) How sensitive is the association between levels of particulate air pollution and socioeconomic status to specification of exposure estimates or statistical models? Total suspended particulate (TSP) data from the twenty-three monitoring stations in Hamilton (1985–94) were interpolated with a universal kriging procedure to develop an estimate of likely pollution values across the city based on annual geometric means and extreme events. Comparing the highest with the lowest exposure zones, the interpolated surfaces showed more than a twofold increase in TSP concentrations and more than a twentyfold difference in the probability of exposure to extreme events. Exposure estimates were related to socioeconomic and demographic data from census tract areas by using ordinary least squares and simultaneous autoregressive (SAR) models. Control for spatial autocorrelation in the SAR models allowed for tests of how robust specific socioeconomic variables were for predicting pollution exposure. Dwelling values were significantly and negatively associated with pollution exposure, a result robust to the method of statistical analysis. Low income and unemployment were also significant predictors of exposure, although results varied depending on the method of analysis. Relatively minor changes in the statistical models altered the significant variables. This result emphasizes the value of geographical information systems (GIS) and spatial statistical techniques in modelling exposure. The result also shows the importance of taking spatial autocorrelation into account in future justice – health studies.

Suggested Citation

  • Michael Jerrett & Richard T Burnett & Pavlos Kanaroglou & John Eyles & Norm Finkelstein & Chris Giovis & Jeffrey R Brook, 2001. "A GIS–Environmental Justice Analysis of Particulate Air Pollution in Hamilton, Canada," Environment and Planning A, , vol. 33(6), pages 955-973, June.
    • Handle: RePEc:sae:envira:v:33:y:2001:i:6:p:955-973
    DOI: 10.1068/a33137
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    References listed on IDEAS

    as
    1. Birch, Stephen & Jerrett, Mike & Eyles, John, 2000. "Heterogeneity in the determinants of health and illness: the example of socioeconomic status and smoking," Social Science & Medicine, Elsevier, vol. 51(2), pages 307-317, July.
    2. repec:cup:cbooks:9780521311120 is not listed on IDEAS
    3. repec:cup:cbooks:9780521322249 is not listed on IDEAS
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    Cited by:

    1. Sara E Grineski & Timothy W Collins, 2010. "Environmental Injustices in Transnational Context: Urbanization and Industrial Hazards in El Paso/Ciudad Juárez," Environment and Planning A, , vol. 42(6), pages 1308-1327, June.
    2. Higgins, Christopher D. & Adams, Matthew D. & Réquia, Weeberb J. & Mohamed, Moataz, 2019. "Accessibility, air pollution, and congestion: Capturing spatial trade-offs from agglomeration in the property market," Land Use Policy, Elsevier, vol. 84(C), pages 177-191.
    3. Niamh K Shortt & Esther Rind & Jamie Pearce & Richard Mitchell, 2014. "Integrating Environmental Justice and Socioecological Models of Health to Understand Population-Level Physical Activity," Environment and Planning A, , vol. 46(6), pages 1479-1495, June.
    4. Hanneke Kruize & Mariël Droomers & Irene Van Kamp & Annemarie Ruijsbroek, 2014. "What Causes Environmental Inequalities and Related Health Effects? An Analysis of Evolving Concepts," IJERPH, MDPI, vol. 11(6), pages 1-21, May.
    5. Michael Buzzelli & Michael Jerrett, 2004. "Racial Gradients of Ambient Air Pollution Exposure in Hamilton, Canada," Environment and Planning A, , vol. 36(10), pages 1855-1876, October.
    6. Thoreau R Tooke & Brian Klinkenberg & Nicholas C Coops, 2010. "A Geographical Approach to Identifying Vegetation-Related Environmental Equity in Canadian Cities," Environment and Planning B, , vol. 37(6), pages 1040-1056, December.
    7. C.I. Beattie & J.W.S. Longhurst & N.K. Woodfield, 2002. "A Comparative Analysis of the Air Quality Management Challenges and Capabilities in Urban and Rural English Local Authorities," Urban Studies, Urban Studies Journal Limited, vol. 39(13), pages 2469-2483, December.
    8. Jamie Pearce & Simon Kingham & Peyman Zawar-Reza, 2006. "Every Breath You Take? Environmental Justice and Air Pollution in Christchurch, New Zealand," Environment and Planning A, , vol. 38(5), pages 919-938, May.
    9. Gordon Mitchell & Danny Dorling, 2003. "An Environmental Justice Analysis of British Air Quality," Environment and Planning A, , vol. 35(5), pages 909-929, May.

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