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Chinese Journal of Ecology ›› 2022, Vol. 41 ›› Issue (10): 2035-2042.doi: 10.13292/j.1000-4890.202209.006

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Spatiotemporal distribution characteristics of air pollutants in urban street canyons as observed by mobile monitoring.

CUI Ai-wei1,2,3, MIAO Chun-ping1,2, HE Huan4, XIONG Zai-ping1, HU Yuan-man1,2,3, CHEN Wei1,2,3*#br#

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  1. (1Chinese Academy of Sciences Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2Shenyang Arboretum, Chinese Academy of Sciences, Shenyang 110016, China; 3University of Chinese Academy of Sciences, Beijing 100049, China; 4International School, Shenyang Jianzhu University, Shenyang 110168, China).

  • Online:2022-10-10 Published:2022-10-13

Abstract: To explore the variation of air pollutant concentration and the influence of meteorological factors on air pollutant concentration in urban street canyon, we used portable air pollution monitoring equipment to detect five kinds of air pollutants (CO, SO2, PM1, PM2.5, and PM10) in the Qingnian Street of Shenyang during the peak and off peak periods under clean weather and polluted weather. Pearson correlation analysis was used to assess the influence of meteorological factors on the mass concentrations of five air pollutants. The results showed that the distribution of air quality index (AQI) in the Qingnian Street had significant spatial and temporal variations over short-term. The spatial distribution of AQI showed a pattern of “high in the north and low in the south” under clean weather, and a pattern of “high in the south and low in the north” under polluted weather, with high pollutant concentration at road intersections. Temporally, the concentrations of the five pollutants were higher under polluted weather than that under clean weather. They were the highest in peak commuting time and the lowest in off peak commuting time. The concentrations of air pollutants were significantly positively correlated with air temperature and relative humidity, and negatively correlated with air pressure in clean weather. In polluted weather, air temperature was negatively correlated with PM1; relative humidity was negatively correlated with SO2 and CO concentrations, positively correlated with PM2.5 and PM10 concentrations; and pressure was negatively correlated with CO, SO2, PM1 and PM2.5 concentrations. This study provided a reference for future studies on air pollution control and regional air pollutant transport in street canyons.


Key words: air pollutant, urban street canyon, mobile monitoring, spatial and temporal distribution, Pearson correlation analysis, Shenyang.