Analysis of Air Pollution in Urban Areas with Airviro Dispersion Model—A Case Study in the City of Sheffield, United Kingdom

Two air pollutants, oxides of nitrogen (NOx) and particulate matter (PM<sub>10</sub>), are monitored and modelled employing Airviro air quality dispersion modelling system in Sheffield, United Kingdom. The aim is to determine the most significant emission sources and their spatial variab...

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Bibliographic Details
Main Authors: Said Munir, Martin Mayfield, Daniel Coca, Lyudmila S Mihaylova, Ogo Osammor
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/11/3/285
Description
Summary:Two air pollutants, oxides of nitrogen (NOx) and particulate matter (PM<sub>10</sub>), are monitored and modelled employing Airviro air quality dispersion modelling system in Sheffield, United Kingdom. The aim is to determine the most significant emission sources and their spatial variability. NOx emissions (ton/year) from road traffic, point and area sources for the year 2017 were 5370, 6774, and 2425, whereas those of PM<sub>10</sub> (ton/year) were 345, 1449, and 281, respectively, which are part of the emission database. The results showed three hotspots of NOx, namely the Sheffield City Centre, Darnall and Tinsley Roundabout (M1 J34S). High PM<sub>10</sub> concentrations were shown mainly between Sheffield Forgemasters International (a heavy engineering steel company) and Meadowhall Shopping Centre. Several emission scenarios were tested, which showed that NOx concentrations were mainly controlled by road traffic, whereas PM<sub>10</sub> concentrations were controlled by point sources. Spatiotemporal variability and public exposure to air pollution were analysed. NOx concentration was greater than 52 &#181;g/m<sup>3</sup> in about 8 km<sup>2</sup> area, where more than 66 thousand people lived. Models validated by observations can be used to fill in spatiotemporal gaps in measured data. The approach used presents spatiotemporal situation awareness maps that could be used for decision making and improving the urban infrastructure.
ISSN:2073-4433