Methods to quantify particle air pollution removal by urban vegetation: A review

Among the ecosystem services provided by urban forests, the air quality amelioration is particularly relevant. The high level of air pollution in modern cities and the indirect involvement of particulate matter (PM) in the spread of COVID-19 have exacerbated the air quality issue worldwide. However,...

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Asıl Yazarlar: Irene Vigevani, Denise Corsini, Sebastien Comin, Alessio Fini, Francesco Ferrini
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Elsevier 2024-01-01
Seri Bilgileri:Atmospheric Environment: X
Konular:
Online Erişim:http://www.sciencedirect.com/science/article/pii/S2590162123000333
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author Irene Vigevani
Denise Corsini
Sebastien Comin
Alessio Fini
Francesco Ferrini
author_facet Irene Vigevani
Denise Corsini
Sebastien Comin
Alessio Fini
Francesco Ferrini
author_sort Irene Vigevani
collection DOAJ
description Among the ecosystem services provided by urban forests, the air quality amelioration is particularly relevant. The high level of air pollution in modern cities and the indirect involvement of particulate matter (PM) in the spread of COVID-19 have exacerbated the air quality issue worldwide. However, in the estimation of urban vegetation effectiveness in particle air pollution removal, there is a lack of a standard procedure. Different methods are used for this purpose, making the comparison across different studies difficult. Therefore, there is a need of an extensive review, aimed at: i) identifying the existing direct methods to quantify this ecosystem service, ii) assessing their pros and cons, accuracy and reliability, sustainability, and iii) laying the foundations to create a standard method, commonly and universally recognized. We identified and meticulously assessed five main direct metrics: the gravimetric method (G, 40%), aerosol monitor (AM, 20.5%), wind tunnels and deposition chambers (WT&CH, 19.5%), Scanning Electron Microscopy (SEM, 14%) and Saturation Isothermal Remanent Magnetization (SIRM, 6%). This work provides a crystal picture and a critical framework of the last thirty years literature on this topic and lays the foundations to create a common and shareable approach to quantify the air PM mitigation potential of the urban vegetation. This will be useful to guide researchers and urban planners in shaping greener, healthier, and more sustainable cities.
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spelling doaj.art-558db6a0c3aa4a25bf674f76367ecacc2024-03-10T05:12:42ZengElsevierAtmospheric Environment: X2590-16212024-01-0121100233Methods to quantify particle air pollution removal by urban vegetation: A reviewIrene Vigevani0Denise Corsini1Sebastien Comin2Alessio Fini3Francesco Ferrini4Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144, Florence, Italy; Department of Sciences, Technologies and Society, University School for Advanced Studies IUSS Pavia, 27100, Pavia, Italy; Corresponding author. Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144, Florence, Italy.Department of Agricultural and Environmental Sciences—Production, Landscape, Agroenergy, University of Milan, 20133, Milan, ItalyDepartment of Agricultural and Environmental Sciences—Production, Landscape, Agroenergy, University of Milan, 20133, Milan, ItalyDepartment of Agricultural and Environmental Sciences—Production, Landscape, Agroenergy, University of Milan, 20133, Milan, ItalyDepartment of Agriculture, Food, Environment and Forestry, University of Florence, 50144, Florence, ItalyAmong the ecosystem services provided by urban forests, the air quality amelioration is particularly relevant. The high level of air pollution in modern cities and the indirect involvement of particulate matter (PM) in the spread of COVID-19 have exacerbated the air quality issue worldwide. However, in the estimation of urban vegetation effectiveness in particle air pollution removal, there is a lack of a standard procedure. Different methods are used for this purpose, making the comparison across different studies difficult. Therefore, there is a need of an extensive review, aimed at: i) identifying the existing direct methods to quantify this ecosystem service, ii) assessing their pros and cons, accuracy and reliability, sustainability, and iii) laying the foundations to create a standard method, commonly and universally recognized. We identified and meticulously assessed five main direct metrics: the gravimetric method (G, 40%), aerosol monitor (AM, 20.5%), wind tunnels and deposition chambers (WT&CH, 19.5%), Scanning Electron Microscopy (SEM, 14%) and Saturation Isothermal Remanent Magnetization (SIRM, 6%). This work provides a crystal picture and a critical framework of the last thirty years literature on this topic and lays the foundations to create a common and shareable approach to quantify the air PM mitigation potential of the urban vegetation. This will be useful to guide researchers and urban planners in shaping greener, healthier, and more sustainable cities.http://www.sciencedirect.com/science/article/pii/S2590162123000333Urban vegetationAir PM removalGravimetric methodSEMAerosol monitorWind tunnel
spellingShingle Irene Vigevani
Denise Corsini
Sebastien Comin
Alessio Fini
Francesco Ferrini
Methods to quantify particle air pollution removal by urban vegetation: A review
Atmospheric Environment: X
Urban vegetation
Air PM removal
Gravimetric method
SEM
Aerosol monitor
Wind tunnel
title Methods to quantify particle air pollution removal by urban vegetation: A review
title_full Methods to quantify particle air pollution removal by urban vegetation: A review
title_fullStr Methods to quantify particle air pollution removal by urban vegetation: A review
title_full_unstemmed Methods to quantify particle air pollution removal by urban vegetation: A review
title_short Methods to quantify particle air pollution removal by urban vegetation: A review
title_sort methods to quantify particle air pollution removal by urban vegetation a review
topic Urban vegetation
Air PM removal
Gravimetric method
SEM
Aerosol monitor
Wind tunnel
url http://www.sciencedirect.com/science/article/pii/S2590162123000333
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