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Creating National Air Pollution Models for Population Exposure Assessment in Canada Hystad, Perry; Setton, Eleanor; Cervantes, Alejandro; Poplawski, Karla; Deschenes, Steeve; Brauer, Michael (Of University of British Columbia); van Donkelaar, Aaron; Lamsal, Lok; Martin, Randall; Jerrett, Michael; Demers, Paul
Abstract
Background: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited. Methods: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.5 μm (PM₂.₅)], nitrogen dioxide (NO₂), benzene, ethylbenzene, and 1,3‑butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO₂ and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure. Results: The national NO₂ model explained 73% of the variability in fixed-site monitor concentrations, PM₂.₅ 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO₂ model predicted, on average, 43% of the within-city variability in the independent NO₂ data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM₂.₅, 23.37 for NO₂, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene. Conclusions: The national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.
Item Metadata
Title |
Creating National Air Pollution Models for Population Exposure Assessment in Canada
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Creator | |
Date Issued |
2011-08
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Description |
Background: Population exposure assessment methods that capture local-scale pollutant variability
are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes.
Currently, such exposure methods are limited.
Methods: We created 2006 national pollutant models for fine particulate matter [PM with
aerodynamic
diameter ≤ 2.5 μm (PM₂.₅)], nitrogen dioxide (NO₂), benzene, ethylbenzene, and
1,3‑butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression
models, we incorporated satellite estimates and geographic predictor variables to capture background
and regional pollutant variation and used deterministic gradients to capture local-scale variation.
The national NO₂ and benzene models are evaluated with independent measurements from
previous land use regression models that were conducted in seven Canadian cities. National models
are applied to census block-face points, each of which represents the location of approximately 89
individuals, to produce estimates of population exposure.
Results: The national NO₂ model explained 73% of the variability in fixed-site monitor concentrations,
PM₂.₅ 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO₂ model
predicted, on average, 43% of the within-city variability in the independent NO₂ data compared
with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models
performed poorly in predicting within-city benzene variability. Based on our national models, we
estimated Canadian ambient annual average population-weighted exposures (in micrograms per
cubic meter) of 8.39 for PM₂.₅, 23.37 for NO₂, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09
for 1,3-butadiene.
Conclusions: The national pollutant models created here improve exposure assessment compared
with traditional monitor-based approaches by capturing both regional and local-scale pollution
variation. Applying national models to routinely collected population location data can extend land
use modeling techniques to population exposure assessment and to informing surveillance, policy,
and regulation.
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Subject | |
Geographic Location | |
Genre | |
Type | |
Language |
eng
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Date Available |
2015-10-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0220728
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URI | |
Affiliation | |
Citation |
Hystad, Setton, Cervantes, Poplawski, Deschenes, Brauer, . . . Demers. (2011). Creating national air pollution models for population exposure assessment in canada. Environmental Health Perspectives, 119(8), 1123-1129.
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Publisher DOI |
10.1289/ehp.1002976
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Environmental Health Perspectives
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada