Estimating particulate matter (PM) concentrations from a meteorological index for data-scarce regions : a pilot study

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dc.contributor.author De Lange, Anzel
dc.contributor.author Garland, Rebecca M.
dc.contributor.author Dyson, Liesl L.
dc.date.accessioned 2019-09-13T14:33:22Z
dc.date.issued 2019-09
dc.description.abstract In regions where air quality data are scarce or access thereto is limited, a comprehensive understanding of air pollution is hindered by a lack of emission data and ambient air pollution measurements. Therefore, in this pilot study, we assess the feasibility of estimating particulate matter (PM) mass concentrations from a meteorological index. Measured PM concentrations from air quality monitoring stations (2013–2016) situated in and around South African air pollution priority areas were analysed. Simulated meteorological parameters were used to calculate the newly-developed Air Dispersion Potential (ADP) index, which describes the meteorological potential for pollution dispersion in the atmosphere. For most conditions, there exists weak (r = 0.1–0.29) to moderate (r = 0.30–0.49) correlations between the ADP index and PM classes. At the three stations with adequate data availability, it was found that the ADP index was relatively successful in predicting conditions of high PM concentrations. An investigation of the effect of meteorological conditions on the diurnal variation of PM concentrations led to both the quantification of this effect, and the realization that at these diverse sites, up to 29% of variation in hourly PM concentrations can be explained by variations in meteorology. The application of the index in this way can play an important role in air quality management by quantifying the impacts of meteorological drivers on PM peaks. en_ZA
dc.description.department Geography, Geoinformatics and Meteorology en_ZA
dc.description.embargo 2020-09-01
dc.description.librarian hj2019 en_ZA
dc.description.sponsorship SASOL through the Laboratory for Atmospheric Studies (LAS) at the University of Pretoria. en_ZA
dc.description.uri https://www.elsevier.com/locate/apr en_ZA
dc.identifier.citation De Lange, A., Garland, R.M. & Dyson, L.L. 2019, 'Estimating particulate matter (PM) concentrations from a meteorological index for data-scarce regions : a pilot study', Atmospheric Pollution Research, vol. 10, no. 5, pp. 1553-1564. en_ZA
dc.identifier.issn 1309-1042 (online)
dc.identifier.other 10.1016/j.apr.2019.05.004
dc.identifier.uri http://hdl.handle.net/2263/71349
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2019 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Atmospheric Pollution Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Atmospheric Pollution Research, vol. 10, no. 5, pp. 1553-1564, 2019. doi : 10.1016/j.apr.2019.05.004. en_ZA
dc.subject Air pollution en_ZA
dc.subject South Africa (SA) en_ZA
dc.subject Particulate matter (PM) en_ZA
dc.subject Pollution dispersion en_ZA
dc.subject Air dispersion potential (ADP) en_ZA
dc.subject Meteorological parameters en_ZA
dc.title Estimating particulate matter (PM) concentrations from a meteorological index for data-scarce regions : a pilot study en_ZA
dc.type Postprint Article en_ZA


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