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Research Article

Effects of traffic and urban parks on PM10 and PM2.5 mass concentrations

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Pages 5635-5647 | Received 25 Feb 2019, Accepted 23 Jul 2019, Published online: 03 Oct 2019
 

ABSTRACT

Sunny and windless afternoons of September, October, and November of 2018 were selected to monitor mass concentrations of PM10 and PM2.5 along primary roads in Shenyang, China. These data were compared with background concentrations of PM10 and PM2.5 from mobile air quality stations to better define the effects of traffic and location on PM pollution in this urban setting. The lowest concentration of PM10 recorded was 25.414 μg/m3, while the lowest concentration of PM2.5 was 53.195 μg/m3. Mass concentrations of PM10 and PM2.5 reached minimum values around 16:00 but were relatively stable between 12:00 and 18:00. Changes in PM10 and PM2.5 under sunny and windless conditions showed significant positive correlations with traffic flow rates (p < .01). We also observed significant differences between PM10 and PM2.5 levels under different traffic flows. PM10 and PM2.5 levels also varied significantly among monitoring locations that were proximal or distant to parklands, with marked reductions in both PM10 and PM2.5 levels close to parks. Both traffic flow and parkland proximity significantly affected PM10 and PM2.5 mass concentrations in Shenyang (p < .05). Regression models for these two influential factors were formulated to facilitate ongoing urban pollution control. Future work will address the influence of season, secondary roads, and park size on PM10 and PM2.5 levels in urban environments.

Acknowledgments

This research was supported by Nature Science Foundation of Liaoning Province (20180550535) and National Nature Science Foundation of China (31470031). We thank Dr. Trudi Semeniuk from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [31470031];Natural Science Foundation of Liaoning Province [20180550535].

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