Understanding PM_2.5 concentration and removal efficiency variation in urban forest park—Observation at human breathing height

Abstract

To increase our knowledge of PM2.5 concentrations near the surface in a forest park in Beijing, an observational study measured the concentration and composition of PM2.5 in Beijing Olympic Forest Park from 2014 to 2015. This study analyzed the meteorological factors and removal efficiency at 1.5 m above the ground (human breathing height) over the day in the forest. The results showed that the average concentrations of PM2.5 near the surface peaked at 07:00–09:30 and reached their lowest at 12:00–15:00. Besides, the results showed that the annual concentration of PM2.5 in the forest was highest during winter, followed by spring and fall, and was lowest during summer. The main chemical components of PM2.5 near the surface in the forest were SO42− and NO3−, which accounted for 68.72% of all water-soluble ions that we observed. The concentration of PM2.5 in the forest had a significant positive correlation with relative humidity and a significant negative correlation with temperature. The removal efficiency near the surface showed no significant variation through the day or year. In the forest, the highest removal efficiency occurred between 07:00 and 09:30 in summer, while the lowest occurred between 09:30 and 12:00 in winter.

Numerical simulations of the effects of green infrastructure on PM2.5 dispersion in an urban park in Bangkok, Thailand

“…As a result, it was concluded that relative humidity and temperature were the most important meteorological variables influencing PM 2.5 concentration. Previous research ( Deng et al., 2019 ; Yan et al., 2020 ; Liu et al., 2015 ) has found a strong significant association between PM 2.5 and relative humidity and temperature, which is in line with our findings. Other research, on the other hand, had come up with different findings.…”

“…The decrease of boundary layer height and wind speed in the afternoon hours along with the increased source activities during the afternoon rush hour, consequently, resulted in high PM 2.5 concentration during evening hours. Similar trend was observed by the previous studies ( Yan et al., 2020 ; Wang et al., 2014 ; Zhao et al., 2009 ) where they studied the diurnal variation of PM 2.5 concentration in the ambient air in the urban areas.…”

“…PM 2.5 concentration was not significantly associated with wind speed and wind direction, as observed in this study and some previous studies ( Deng et al., 2019 ; Yan et al., 2020 ). These two meteorological variables decide how wind influences the concentration of PM 2.5 in the atmosphere in urban areas.…”

“…Variations in sampling locations, changes in ambient conditions, and the emission sources may be the cause of the differences ( Wu et al., 2018 ). As a result, the variations in the findings may be attributed to the differences in the sites' environments ( Yan et al., 2020 ).…”

“…(2015) where high NO 2 concentrations were observed with high relative humidity and low temperature. Yan et al. (2020) found that PM 2.5 concentration in the Beijing Olympic Forest Park had a significant positive correlation with relative humidity and a significant negative correlation with temperature.…”