Scale-dependent effects of urban greenspace on particulate matter air pollution

Yakai Lei, G. Matt Davies, Huan Jin, Guohang Tian, Gunwoo Kim

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Atmospheric particulate matter (PM) pollution has become a major global public health concern, particularly in urbanizing and rapidly developing nations such as China. Health effects from PM pollution include increases in cardiovascular and respiratory illnesses and problems during pregnancy and child development. Developing methods to mitigate PM pollution is a major priority for urban planning. Urban forests and other greenspaces are known to have both direct and indirect effects on PM concentrations, but uncertainty remains about how best to design greenspaces to reduce PM loads. This is partly because of contrasting effects that have been observed at different spatial scales. We used high-resolution satellite imagery and two years of daily PM concentration data from nine national air pollution monitoring stations in Zhengzhou, China, to examine the relative importance of seasonal cycling and greenspace effects on PM concentrations. We described patterns of urban greenspace at multiple spatial scales (buffer radii of 0.5 km – 3 km) using 15 different landscape pattern metrics. Multivariate methods (cluster analysis, principal component analysis) were used to process these into a smaller number of uncorrelated descriptors that described major patterns of variation in greenspaces. Linear mixed models were used to model seasonal cycling and greenspace effects on PM10 and PM2.5 concentrations for each spatial scale. We found that: 1) monthly mean, maximum, and standard deviations of concentrations of both PM2.5 and PM10 showed stationarity across seasons and months, being greatest in winter and smallest in summer; 2) urban greenspace patterns did not significantly affect PM2.5 concentrations; 3) increasing the overall abundance of greenspace, and percentage of large greenspace patches, at almost all scales significantly reduced PM10 concentrations; and 4) at larger spatial scales, increasing the amount of contact between the edges of greenspace patches and the surrounding urban area could reduce PM10 concentrations. In the context of urban planning and renewal, it may be possible to reduce PM10 pollution by carefully planning the shape and layout of greenspace networks across scales.

Original languageEnglish
Article number127089
JournalUrban Forestry and Urban Greening
Volume61
DOIs
StatePublished - 2021 Jun
Externally publishedYes

Keywords

  • China
  • FRAGSTATS
  • Landscape pattern
  • PMPM
  • Planning
  • Seasonality

Fingerprint

Dive into the research topics of 'Scale-dependent effects of urban greenspace on particulate matter air pollution'. Together they form a unique fingerprint.

Cite this