Determining broad scale associations between air pollutants and urban forestry: A novel multifaceted methodological approach.

Clicks: 324
ID: 12786
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #79 of 145 articles by views in Environmental pollution (Barking, Essex : 1987)

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 145 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Global urbanisation has resulted in population densification, which is associated with increased air pollution, mainly from anthropogenic sources. One of the systems proposed to mitigate urban air pollution is urban forestry. This study quantified the spatial associations between concentrations of CO, NO₂, SO₂, and PM₁₀ and urban forestry, whilst correcting for anthropogenic sources and sinks, thus explicitly testing the hypothesis that urban forestry is spatially associated with reduced air pollution on a city scale. A Land Use Regression (LUR) model was constructed by combining air pollutant concentrations with environmental variables, such as land cover type and use, to develop predictive models for air pollutant concentrations. Traffic density and industrial air pollutant emissions were added to the model as covariables to permit testing of the main effects after correcting for these air pollutant sources. It was found that the concentrations of all air pollutants were negatively correlated with tree canopy cover and positively correlated with dwelling density, population density and traffic count. The LUR models enabled the establishment of a statistically significant spatial relationship between urban forestry and air pollution mitigation. These findings further demonstrate the spatial relationships between urban forestry and reduced air pollution on a city-wide scale, and could be of value in developing planning policies focused on urban greening.
Reference Key
douglas2019determiningenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ashley N J Douglas, Peter J Irga, Fraser R Torpy
Are you one of these authors? Claim your profile
Journal Environmental pollution (Barking, Essex : 1987)
Year 2019
DOI
S0269-7491(18)33724-2
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.