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

Douglas, ANJ; Irga, PJ; Torpy, FR

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

Douglas, ANJ Irga, PJ

Torpy, FR

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Publication Type:: Journal Article
Citation:: Environmental Pollution, 2019, 247 pp. 474 - 481
Issue Date:: 2019-04-01

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Field	Value	Language
dc.contributor.author	Douglas, ANJ	en_US
dc.contributor.author	Irga, PJ https://orcid.org/0000-0001-5952-0658	en_US
dc.contributor.author	Torpy, FR https://orcid.org/0000-0002-9137-6948	en_US
dc.date.available	2018-12-31	en_US
dc.date.issued	2019-04-01	en_US
dc.identifier.citation	Environmental Pollution, 2019, 247 pp. 474 - 481	en_US
dc.identifier.issn	0269-7491	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135084
dc.description.abstract	© 2019 Elsevier Ltd 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.	en_US
dc.relation.ispartof	Environmental Pollution	en_US
dc.relation.isbasedon	10.1016/j.envpol.2018.12.099	en_US
dc.subject.classification	Environmental Sciences	en_US
dc.subject.mesh	Air Pollutants	en_US
dc.subject.mesh	Cities	en_US
dc.subject.mesh	Air Pollution	en_US
dc.subject.mesh	Environmental Monitoring	en_US
dc.subject.mesh	Forestry	en_US
dc.subject.mesh	Particulate Matter	en_US
dc.title	Determining broad scale associations between air pollutants and urban forestry: A novel multifaceted methodological approach	en_US
dc.type	Journal Article
utslib.citation.volume	247	en_US
utslib.for	0502 Environmental Science and Management	en_US
utslib.for	0102 Applied Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	247	en_US

Abstract:

© 2019 Elsevier Ltd 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.

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http://hdl.handle.net/10453/135084