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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-112
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-112
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Apr 2019

Research article | 08 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Traffic-related air pollution near roadways: discerning local impacts from background

Nathan Hilker1, Jonathan M. Wang1, Cheol-Heon Jeong1, Robert M. Healy2, Uwayemi Sofowote2, Jerzy Debosz2, Yushan Su2, Michael Noble2, Anthony Munoz2, Geoff Doerksen3, Luc White4, Céline Audette4, Dennis Herod4, Jeffrey R. Brook1,5, and Greg J. Evans1 Nathan Hilker et al.
  • 1Southern Ontario Centre for Atmospheric Aerosol Research, Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, M5S 3E5, Canada
  • 2Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment Conservation and Parks, Etobicoke, ON, M3P 3V6, Canada
  • 3Air Quality Policy and Management Division, Metro Vancouver, Burnaby, BC, V5H0C6, Canada
  • 4Air Quality Research Division, Environment and Climate Change Canada, Ottawa, ON, K1A0H3, Canada
  • 5Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, M3H5T4, Canada

Abstract. Adverse health outcomes related to exposure to air pollution have gained much attention in recent years, with a particular emphasis on traffic-related pollutants near roadways, where concentrations tend to be most severe. As such, many projects around the world are being initiated to routinely monitor pollution near major roads. Understanding the extent to which local on-road traffic directly affects these measurements, however, is a challenging problem, and a more thorough comprehension of it is necessary to properly assess its impact on near-road air quality. In this study, a set of commonly measured air pollutants (black carbon; carbon dioxide; carbon monoxide; fine particulate matter, PM2.5; nitrogen oxides; ozone; and ultrafine particle concentrations) were monitored continuously between June 01st, 2015 and March 31st, 2017 at six stations in Canada: two near-road and two urban background stations in Toronto, Ontario, and one near-road and one urban background station in Vancouver, British Columbia. Three methods of differentiating between local and background concentrations at near-road locations were tested: 1) differences in average pollutant concentrations between near-road and urban background station pairs, 2) differences in downwind and upwind pollutant averages, and 3) interpolation of rolling minima to infer background concentrations. The latter two methods use near-road data only, and were compared with method 1, where an explicit difference was measured, to assess accuracy and robustness. It was found that method 2 produced average local concentrations that were biased high by a factor of between 1.4 and 1.7 when compared with method 1 and was not universally feasible, whereas method 3 produced concentrations that were in good agreement for all pollutants except ozone and PM2.5, which are generally secondary and regional in nature. The results of this comparison are intended to aid researchers in the analysis of data procured in future near-road monitoring studies. Lastly, upon determining these local pollutant concentrations as a function of time, their variability with respect to wind speed (WS) and wind direction (WD) was assessed. With the exception of ozone and PM2.5, local pollutant concentrations were enhanced by a factor of 2 relative to their mean in the case of stagnant winds and were shown to be proportional to WS−0.6). Downwind conditions enhanced local concentrations by a factor of ~ 2 relative to their mean, while upwind conditions suppressed them by a factor of ~ 4.

Nathan Hilker et al.
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Status: final response (author comments only)
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Nathan Hilker et al.
Nathan Hilker et al.
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Short summary
Increased interest in monitoring air quality near roadways, combined with traffic's often unclear contribution to elevated concentrations, has created a need for better interpretation of these data. Using two years of measurements collected during a near-road monitoring project in Canada, this paper contrasts three methods for estimating the fraction of roadside pollution resulting from on-road traffic. Robustness of these methods was compared with tandem measurements at background locations.
Increased interest in monitoring air quality near roadways, combined with traffic's often...
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