Using Microsoft© Power BI© to visualise Rustenburg local municipality’s air quality data

dc.contributor.authorWright, Caradee Yael
dc.contributor.authorWernecke, Bianca
dc.date.accessioned2021-03-26T10:56:50Z
dc.date.available2021-03-26T10:56:50Z
dc.date.issued2020
dc.description.abstractMicrosoft© Power BI© is a business analytics tool that visualises data in an accessible manner. It creates visual data reports quickly in a series of panels to give an overview of data while still offering access to more sophisticated visualisation methods too. While statistical tools, like R and MatLab, remain the ‘gold standard’ for analysing air quality data, simple methods to visualise data are also helpful. Here, we explored the use of Power BI Desktop© to visualise and interpret air quality data for the Rustenburg Local Municipality. Rustenburg is in the Waterberg-Bojanala Priority Area – the third air pollution priority area for air quality management. Ambient PM10 data for three towns, namely, Thlabane, Marikana and Boiketlong, were obtained for six years (2013-2018) in South Africa. Data underwent quality control before being imported into Power BI©. A four-panel dashboard was generated to show (in) compliance with the daily and annual average South African National Ambient Air Quality Standard for PM10, annual and average concentrations, frequency of exceedances and a summary of data availability by site. Generally, PM10 data quantity and quality were poor and where data were available, concentrations were high. This type of data visualisation tool can be applied with relative ease by Air Quality Officers and Environmental Health Practitioners for a snapshot overview of the air quality in their area of jurisdiction. The interactive dashboard is also useful for making graphics for policy documents and reports.en_ZA
dc.description.departmentGeography, Geoinformatics and Meteorologyen_ZA
dc.description.librarianpm2021en_ZA
dc.description.sponsorshipSouth African Medical Research Council and the National Research Foundation (South Africa).en_ZA
dc.description.urihttps://www.cleanairjournal.org.zaen_ZA
dc.identifier.citationWright, C.Y. & Wernecke, B. 2020, 'Using microsoft© power BI© to visualise rustenburg local municipality's air quality data', Clean Air Journal, vol. 30, no. 1, pp. 1-5.en_ZA
dc.identifier.issn1017-1703 (print)
dc.identifier.issn2410-972X (online)
dc.identifier.other10.17159/caj/2020/30/1.7512
dc.identifier.urihttp://hdl.handle.net/2263/79127
dc.language.isoenen_ZA
dc.publisherNational Association of Clean Airen_ZA
dc.rights© 2020. The Author(s). Published under a Creative Commons Attribution Licence.en_ZA
dc.subjectAir pollutionen_ZA
dc.subjectEnvironmental healthen_ZA
dc.subjectSouth Africa (SA)en_ZA
dc.subjectWaterberg-Bojanala priority areaen_ZA
dc.titleUsing Microsoft© Power BI© to visualise Rustenburg local municipality’s air quality dataen_ZA
dc.typeArticleen_ZA

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