Study on the Correlation Mechanism between the Living Vegetation Volume of Urban Road Plantings and PM 2.5 Concentrations

Congzhe Liu, Anqi Dai, Huihui Zhang, Qianqian Sheng () and Zunling Zhu ()
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Congzhe Liu: School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Anqi Dai: School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Huihui Zhang: School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Qianqian Sheng: School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Zunling Zhu: School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China

Sustainability, 2023, vol. 15, issue 5, 1-17

Abstract: To study the effects of species diversity of different urban road green space on PM 2.5 reduction, and to provide a theoretical basis for the optimal design of urban road plantings. Different combinations of road plantings in Xianlin Avenue of Nanjing were used as sample areas, and 3–6 PM 2.5 monitoring points were set up in each sample area. The monitoring points were setup at 10, 20, 30, 40, 50, and 60 m from the roadbed for detecting PM 2.5 concentrations in different sample areas. Moreover, the living vegetation volume of each sample area was calculated. The coupling relationship between the living vegetation volumes and PM 2.5 concentrations in different sample areas was evaluated by regression fitting and other methods. PM 2.5 concentrations among different sample areas were significantly different. PM 2.5 concentrations were higher in the morning than in the afternoon, while the differences were not significant. The living vegetation volumes of the eight sample areas varied from 2038.73 m 3 to 15,032.55 m 3 . Affected by different plant configurations, the living vegetation volumes in the sample areas showed obvious differences. The S2 and S6 sample area, which was consisted a large number of shrubshave better PM 2.5 reduction capability. The fitting curve of living vegetation volumes and PM 2.5 concentrations in sample areas of S1 and S3–S8 can explain 76.4% of the change in PM 2.5 concentrations, which showed significant fitting. The fitting relationship between living vegetation volumes and PM 2.5 concentrations in different road green space is different owing to different compositions of plantings. With the increase in living vegetation volumes, their fitting functions first increase and then decrease in a certain range. It is speculated that only when the living vegetation volume exceeds a certain range, it will promote PM 2.5 reduction.

Keywords: road green space; living vegetation volume; PM 2.5; fitting relationship (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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