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Effect of Different Plant Communities on Fine Particle Removal in an Urban Road Greenbelt and Its Key Factors in Nanjing, China

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  • Congzhe Liu

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
    Jin Pu Research Institute, Nanjing Forestry University, Nanjing 210037, China
    Research Center for Digital Innovation Design, Nanjing Forestry University, Nanjing 210037, China)

  • Anqi Dai

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Yaou Ji

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Qianqian Sheng

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
    Jin Pu Research Institute, Nanjing Forestry University, Nanjing 210037, China
    Research Center for Digital Innovation Design, Nanjing Forestry University, Nanjing 210037, China
    Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China)

  • Zunling Zhu

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
    Jin Pu Research Institute, Nanjing Forestry University, Nanjing 210037, China
    Research Center for Digital Innovation Design, Nanjing Forestry University, Nanjing 210037, China
    Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China)

Abstract

Determining the relationships between the structure and species of plant communities and their impact on ambient particulate matter (PM) is an important topic in city road greenbelt planning and design. The correlation between the distribution of plant communities and ambient PM concentrations in a city road greenbelt has specific spatial patterns. In this study, we selected 14 plant-community-monitoring sites on seven roads in Nanjing as research targets and monitored these roads in January 2022 for various parameters such as PM with aerodynamic diameters ≤10 µm (PM 10 ) and PM with aerodynamic diameters ≤2.5 µm (PM 2.5 ). We used a spatial model to analyze the relationship between the concentrations of ambient PM 10 and PM 2.5 and the spatial heterogeneity of plant communities. The consequences revealed that the composition and species of plant communities directly affected the concentrations of ambient PM. However, upon comparing the PM concentration patterns in the green community on the urban road, we found that the ability of the plant community structures to reduce ambient PM is in the order: trees + shrubs + grasses > trees + shrubs > trees + grasses > pure trees. Regarding the reduction in ambient PM by tree species in the plant community (conifer trees > deciduous trees > evergreen broad-leaved trees) and the result of the mixed forest abatement rate, coniferous + broad-leaved trees in mixed forests have the best reduction ability. The rates of reduction in PM 10 and PM 2.5 were 14.29% and 22.39%, respectively. We also found that the environmental climate indices of the road community, temperature, and traffic flow were positively correlated with ambient PM, but relative humidity was negatively correlated with ambient PM. Among them, PM 2.5 and PM 10 were significantly related to temperature and humidity, and the more open the green space on the road, the higher the correlation degree. PM 10 is also related to light and atmospheric radiation. These characteristics of plant communities and the meteorological factors on urban roads are the foundation of urban greenery ecological services, and our research showed that the adjustment of plant communities could improve greenbelt ecological services by reducing the concentration of ambient PM.

Suggested Citation

  • Congzhe Liu & Anqi Dai & Yaou Ji & Qianqian Sheng & Zunling Zhu, 2022. "Effect of Different Plant Communities on Fine Particle Removal in an Urban Road Greenbelt and Its Key Factors in Nanjing, China," Sustainability, MDPI, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:156-:d:1011394
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