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Quantitative estimation of the PM2.5 removal capacity and influencing factors of urban green infrastructure by Kongming Li; Chunlin Li; Yuanman Hu; Zaiping Xiong; Yongheng Wang is a Environmental Science article available to read on EtoBox.

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Long-term exposure to PM2.5 (fine particulate matter with an aerodynamic diameter <2.5 μm) could cause great harm to human health and sustainable development. It remains a challenge to estimate the long-term PM2.5 removal capacity of nature-based green infrastructure in urban areas. In this paper, the annual PM2.5 removal capacity of urban green infrastructure (UGI) from 2000 to 2019 in Shenyang was estimated based on the PM2.5 dry deposition model. The spatial heterogeneity of annual PM2.5 removal capacity were detected Sen-MK test and local spatial autocorrelations analysis. Then the effects of landscape patterns and socioeconomic variables on PM2.5 removal capacity were explored based on linear regression model. The results illustrated that the PM2.5 removal capacity of UGI increased significantly from 2000 to 2019 in Shenyang, with the amount of PM2.5 removal, PM2.5 removal flux and removal rate increasing by 20.64 Mg/a, 0.0258 g/m2/a, and 0.377 %/a, respectively. The PM2.5 removal capacity of UGI exhibited spatial heterogeneity in the study area. Specifically, the regions experiencing the increase in PM2.5 removal capacity of UGI accounted for majority of the old urban area of

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Author

Kongming Li; Chunlin Li; Yuanman Hu; Zaiping Xiong; Yongheng Wang

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Environmental Science (Physical Sciences)