A review and evaluation of intraurban air pollution exposure models.
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.
Division of Biostatistics, Departments of Preventive Medicine and Geography, University of Southern California, 1540 Alcazar Street, CHP-220, Los Angeles, CA 90089, USA. jerrett@usc.edu
Michael
M
Jerrett
Altaf
A
Arain
Pavlos
P
Kanaroglou
Bernardo
B
Beckerman
Dimitri
D
Potoglou
Talar
T
Sahsuvaroglu
Jason
J
Morrison
Chris
C
Giovis
D000393:Air Pollutants / Q000032:analysis* / Q000506:poisoning*; D004781:Environmental Exposure; D004782:Environmental Health; D004784:Environmental Monitoring / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results; D018570:Risk Assessment; D014505:Urban Population
D000393:Air Pollutants