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Quantifying particulate matter reduction and their deposition on the leaves of green infrastructure

Abhijith, K.V. and Kumar, Prashant (2020) Quantifying particulate matter reduction and their deposition on the leaves of green infrastructure Environmental Pollution, 265, 114884.

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The green infrastructure (GI) is identified as a passive exposure control measure of air pollution. This work examines particulate matter (PM) reduction by a roadside hedge and its deposition on leaves. The objectives of this study are to (i) quantify the relative difference in PM concentration in the presence of GI and at an adjacent clear area; (ii) estimate the total mass and number density of PM deposited on leaves of a hedge; (iii) ascertain variations in PM deposition at adult (1.5m) and child (0.6 m) breathing levels on either side of a hedge; (iv) illustrate the relationship between PM deposition to leaves and ambient PM concentration reductions; and (v) quantify the elemental composition of collected particles of the leaves on different heights and sides of hedge. PM reduction of 2–9% was observed behind hedge compared to a clear area and followed a trend of ΔPM1 ˃ΔPM10 ˃ΔPM2.5. Counting of particles was found to be an effective method to quantify deposition than weighting methods. Sub-micron particles (PM1) dominated particle deposition on leaves at all sampling points on both sides of the hedge. PM mass deposition and number concentration to the leaves on traffic-facing side was up to 36% and 58% higher at 0.6m compared with 1.5m height, respectively. Such a difference was absent on the backside of the hedge. The SEM-EDS analysis showed up to 12% higher traffic-originated particles deposited to leaves on the traffic-facing side compared to the backside. The naturally occurring particles dominated in identified particles on leaf samples from all collection points on the hedge. These new evidence expand our understanding of PM reduction of GI in the near-road environment and its variations in particle deposition, depending on height and sides of GI, which could allow a better parameterisation of dispersion-deposition models for GI assessment at micro-scale.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Civil and Environmental Engineering
Authors :
Abhijith, K.V.
Date : October 2020
Funders : European Community's H2020 Programme (H2020-SC5-04-2015), Engineering and Physical Sciences Research Council (EPSRC)
DOI : 10.1016/j.envpol.2020.114884
Grant Title : iSCAPE (Improving Smart Control of Air Pollution in Europe)
Copyright Disclaimer : © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Uncontrolled Keywords : Green infrastructure; Particulate matter; PM Deposition; Exposure mitigation; Leaf characteristics
Depositing User : Clive Harris
Date Deposited : 12 Jun 2020 13:54
Last Modified : 12 Jun 2020 13:54

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