Atmospheric Particle Distribution on Tree Leaves in Different Urban Areas of Aksu City, Northwest China

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Abstract

Residents in arid regions of northwest China, where dust storms are more common, are continually exposed to air pollution particularly fine particles of PM2.5 and PM10, causing health hazards to residents. Urban greening species have a strong dust retention capacity which is also available in arid conditions and should be chosen to reduce the impact of air pollution on people and the urban environment. In this paper, three common tree species in four different functional areas: Transportation area (TA), Residential area (RA), Industrial area (IA), and Clean area (CA) of Aksu City were selected to measure their foliar dust to select the matching trees for appropriate sites. The dust particle size distribution for PM2.5 and PM10 was analyzed to explore the particle size difference between foliar dust and natural landing dust. The largest particle size was recorded in IA (168.56 μm), while the smallest was found in CA (43.25 μm). Furthermore, Salix babylonica (S. babylonica) absorbed the highest PM2.5 and PM10, 0.15% and 1.39% respectively; while Ulmus densa (U. densa) absorbed the least PM2.5 and PM10, 0.08% and 0.37%. Platanus acerifolia (P. acerifolia) foliar dust particle density was the highest, and has stable dust retention capacity, while, S. babylonica foliar dust particulate density is the lowest under the same conditions (height/location, pollution exposition, weather). Our findings concluded that the average values of dust diameters in the four areas differed significantly. It is concluded that P. acerifolia is the best performer in removing dust in different functional urban areas and S. babylonica was more suitable for CA because of having the capacity to remove fine particle matter.

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APA

Nurmamat, K., Halik, Ü., Baidourela, A., & Aishan, T. (2022). Atmospheric Particle Distribution on Tree Leaves in Different Urban Areas of Aksu City, Northwest China. Nature Environment and Pollution Technology, 21(2), 921–929. https://doi.org/10.46488/NEPT.2022.v21i02.055

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