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A spatial and temporal analysis of neighborhood air quality in downtown Vancouver

University of British Columbia

Rapid urban densification and an enhanced understanding of the health consequences of intra-urban air pollution exposure variability has led to a need for accurate estimation of traffic-related air pollution (TRAP) exposures, including temporal and spatial variability. To address this goal, a wireless real-time air pollution monitor was evaluated and the effect of street canyon geometry on TRAP levels was assessed. The AQMesh wireless monitor (with sensors for CO, NO, NO₂, O₃ and SO₂)—was evaluated in a co-location study with regulatory air quality monitoring stations in London, England and Vancouver, Canada. The amount of variability (R²) explained by AQMesh sensors (algorithm version 3.0) ranged from 0.02% to 34.5% in Vancouver and 1.5% to 82.3% in London. Sensors for NO₂ and O₃ displayed the highest accuracy while the CO sensor accuracy was much weaker. AQMesh, as examined in this co-location, was not sufficiently robust for use in regulatory applications. A simple GIS-based model for the identification of potential street canyons where TRAP levels may be elevated was created using 3D building information, aspect ratio and the prevailing wind direction. The model was evaluated in a mobile monitoring campaign in which particulate matter smaller than 2.5 micrometers (PM2.5) and particle number concentration (PNC) were measured along 4 road segments: canyon high traffic (C HT), canyon low traffic (C LT), non-canyon high-traffic (NC HT) and non-canyon low traffic (NC LT). A linear mixed effects model found the effect estimates for C LT (i.e. the effect of canyon) to be 8% higher for PM2.5 and 17% higher for PNC when compared to the reference road segment category, NC LT. In comparison, the effect estimates for NC HT (i.e. the effect of traffic) was 16% higher for PM2.5 and 34% higher for PNC when compared to NC LT. This research suggests that the impact of traffic may be greater than the impact of street canyons in determining TRAP exposures.

Text

2017-08-14

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/62591

Occupational and Environmental Hygiene

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/