Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment.

Autor: Bousiotis D; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. Electronic address: d.bousiotis@bham.ac.uk., Damayanti S; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK., Baruah A; Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena, 41125, Italy; University School of Advanced Studies IUSS Pavia, Palazzo Del Brotello, Pavia, 27100, Italy., Bigi A; Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena, 41125, Italy., Beddows DCS; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK., Harrison RM; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK., Pope FD; School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. Electronic address: f.pope@bham.ac.uk.
Jazyk: angličtina
Zdroj: Environment international [Environ Int] 2024 Nov; Vol. 193, pp. 109069. Date of Electronic Publication: 2024 Oct 11.
DOI: 10.1016/j.envint.2024.109069
Abstrakt: Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM 2.5 and PM 1 concentrations. In contrast, PM 10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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