1. ^aDivision of Biostatistics, Departments of Preventive Medicine and Geography, University of Southern California, 1540 Alcazar Street, CHP-220, Los Angeles, California, USA
2. ^bSchool of Geography and Geology, Hydrometeorology and Climatology Research Group, McMaster University, Hamilton, Ontario, Canada
3. ^cSchool of Geography and Geology, McMaster Institute of Environment and Health, McMaster University, Hamilton, Ontario, Canada
4. ^dSchool of Geography and Geology, McMaster University, Hamilton, Ontario, Canada
5. ^eSchool of Computer Science, Carleton University, Ottawa, Ontario, Canada

Correspondence: Dr. Michael Jerrett, Division of Biostatistics, Departments of Preventive Medicine and Geography, University of Southern California, 1540 Alcazar Street, CHP-220, Los Angeles, CA 90089-9011, USA. Tel.: +1-323-442-1260; Fax: +1-323-442-2349; E-mail: jerrett@usc.edu

Received 8 August 2003; Accepted 3 April 2004; Published online 4 August 2004.

Abstract

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity–space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.