Yao, M., Smith, M. and Peng, C. orcid.org/0000-0001-8199-0955 (2025) Modelling the effects of vegetation and urban form on air quality in real urban environments: A systematic review of measurements, methods, and predictions. Urban Forestry & Urban Greening, 105. 128693. ISSN 1618-8667
Abstract
Air pollution poses a significant threat to public health and well-being. In recent decades, researchers have used direct measurements and predictive modelling to assess urban air quality. However, the impact of vegetation and urban form on air quality remains uncertain, particularly regarding their interconnected roles. This paper systematically reviews studies on real urban environments, focusing on how vegetation and urban form influence air quality assessment and prediction. It highlights key variables and their importance, as reported in the literature, and identifies areas needing further research to improve predictions of vegetation’s effects on urban air quality in relation to urban morphology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Urban Forestry & Urban Greening is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Urban air quality; Air pollutants; Vegetation indices; Urban morphological indicators; Air quality predictions |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture and Landscape |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 31 Jan 2025 16:09 |
Last Modified: | 12 Mar 2025 12:47 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.ufug.2025.128693 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:222758 |