Does the Spatial Pattern of Plants and Green Space Affect Air Pollutant Concentrations? Evidence from 37 Garden Cities in China

Chengkang Wang; Mengyue Guo; Jun Jin; Yifan Yang; Yujie Ren; Yang Wang; Jiajie Cao

doi:10.3390/plants11212847

Does the Spatial Pattern of Plants and Green Space Affect Air Pollutant Concentrations? Evidence from 37 Garden Cities in China

Plants (Basel). 2022 Oct 26;11(21):2847. doi: 10.3390/plants11212847.

Authors

Chengkang Wang¹, Mengyue Guo¹, Jun Jin², Yifan Yang¹, Yujie Ren³, Yang Wang⁴, Jiajie Cao¹

Affiliations

¹ College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China.
² Research Institute of Architecture, Southeast University, Nanjing 210096, China.
³ Graduate School of Human-Environment Studies, Kyushu University, Fukuoka 819-0395, Japan.
⁴ State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.

Abstract

Relevant studies have demonstrated that urban green spaces composed of various types of plants are able to alleviate the morbidity and mortality of respiratory diseases, by reducing air pollution levels. In order to explore the relationship between the spatial pattern of urban green spaces and air pollutant concentrations, this study takes 37 garden cities with subtropical monsoon climate in China as the research object and selects the urban air quality monitoring data and land use type data in 2019 to analyze the relationship between the spatial pattern and the air pollutant concentration through the landscape metrics model and spatial regression model. Moreover, the threshold effect of the impact of green space on air pollutant concentrations is estimated, as well. The results showed that the spatial pattern of urban green space was significantly correlated with the concentrations of PM_2.5 (PM with aerodynamic diameters of 2.5 mmor less), NO₂ (Nitrogen Dioxide), and SO₂ (Sulfur dioxide) pollutants in the air, while the concentrations of PM₁₀ (PM with aerodynamic diameters of 10 mmor less) pollutants were not significantly affected by the green space pattern. Among them, the patch shape index (LSI), patch density (PD) and patch proportion in landscape area (PLAND) of forest land can affect the concentration of PM_2.5, NO₂, and SO₂, respectively. The PLAND, PD, and LSI of grassland and farmland can also have an additional impact on the concentration of SO₂ pollutants. The study also found that there was a significant threshold effect within the impact mechanism of urban green space landscape pattern indicators (LSI, PD, PLAND) on the concentrations of PM_2.5, NO₂, and SO₂ air pollutants. The results of this study not only clarified the impact mechanism of the spatial pattern of urban green space on air pollutant concentrations but also provided quantitative reference and scientific basis for the optimization and updating of urban green space to promote public health.

Keywords: air pollution; landscape pattern; public health; quantitative analysis; threshold effect; urban green spaces.

Grants and funding

This research was funded by the National Key R&D Program of China (Funder: Jun Jin; Funding No.: 2020YFD1100405); the National Natural Science Foundation of China (Funder: Jiajie Cao; Funding No.: 32071832); the Humanity and Social Sciences Youth Foundation of the Ministry of Education of China (Funder: Chengkang Wang; Funding No.: 18YJCZH167) and the Natural Science Foundation of Jiangsu Province (Funder: Chengkang Wang; Funding No.: BK20190751).