An ultra-spatially resolved method to quali-quantitative monitor particulate matter in urban environment

Monitoring the amount and composition of airborne particulate matter (PM) in the urban environment is a crucial aspect to guarantee citizen health. To focus the action of stakeholders in limiting air pollution, fast and highly spatially resolved methods for monitoring PM are required. Recently, the trees’ capability in capturing PM inspired the development of several methods intended to use trees as biomonitors; this results in the potential of having an ultra-spatially resolved network of low-cost PM monitoring stations throughout cities, without the needing of on-site stations. Within this context, we propose a fast and reliable method to qualitatively and quantitatively characterize the PM present in urban air based on the analysis of tree leaves by scanning electron microscopy combined with X-ray spectroscopy (SEM/EDX). We have tested our method in the Real Bosco di Capodimonte urban park (Naples, Italy), by collecting leaves from Quercus ilex trees along transects parallel to the main wind directions. The coarse (PM10–2.5) and fine (PM2.5) amounts obtained per unit leaf area have been validated by weighting the PM washed from leaves belonging to the same sample sets. PM size distribution and elemental composition match appropriately with the known pollution sources in the sample sites (i.e., traffic and marine aerosol). The proposed methodology will then allow the use of the urban forest as an ultra-spatially resolved PM monitoring network, also supporting the work of urban green planners and stakeholders. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Authors
Baldacchini C.1, 2 , Sgrigna G.1 , Clarke W.3 , Tallis M.3 , Calfapietra C. 1, 4
Publisher
Springer Science + Business Media
Number of issue
18
Language
English
Pages
18719-18729
Status
Published
Volume
26
Year
2019
Organizations
  • 1 National Research Council, Institute of Research on Terrestrial Ecosystems, Via G. Marconi 2, Porano, TR 05010, Italy
  • 2 Biophysics and Nanoscience Centre, DEB, Università degli Studi della Tuscia, Largo dell’Università, Viterbo, 01100, Italy
  • 3 School of Biological Sciences, University of Portsmouth, King Henry Building, King Henry 1 Street, Portsmouth, PO1 2DY, United Kingdom
  • 4 Department of Landscape Design and Sustainable Ecosystems, Agrarian-technological Institute, 30 RUDN University, Miklukho-Maklaya Str., 6, Moscow, 117198, Russian Federation
Keywords
Air quality; Energy-resolved X-ray spectroscopy; Particulate matter; Pollution monitoring; Scanning electron microscopy; Urban forest
Date of creation
19.07.2019
Date of change
19.07.2019
Short link
https://repository.rudn.ru/en/records/article/record/38607/
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