Data gaps will leave scientists ‘in the dark’ : how load shedding is obscuring our understanding of air quality

We are excited to announce that the repository will soon undergo an upgrade, featuring a new look and feel along with several enhanced features to improve your experience. Please be on the lookout for further updates and announcements regarding the launch date. We appreciate your support and look forward to unveiling the improved platform soon.

Show simple item record

dc.contributor.author Wright, Caradee Yael
dc.contributor.author Benyon, Matthew
dc.contributor.author Mahlangeni, Nomfundo
dc.contributor.author Kapwata, Thandi
dc.contributor.author Laban, Tracey
dc.contributor.author Garland, Rebecca M.
dc.date.accessioned 2023-11-07T10:46:03Z
dc.date.available 2023-11-07T10:46:03Z
dc.date.issued 2023-09
dc.description.abstract SIGNIFICANCE : South Africa’s scheduled power outages, commonly known as load shedding, are increasing each year due to instability and poor performance of the existing fleet of power stations supplying electricity. The power provider projects that there will be load shedding every week for the next year. Data availability from the existing air quality monitoring stations infrastructure is already sparse over South Africa. Increased load shedding exacerbates this issue as power outages disrupt equipment operation. The collection of long-term and continuous ambient air quality data is needed for air quality-related research, policy and strategy development, and air quality management. The introduction of air quality monitors that are reliable and climate-friendly, such as passive samples, rechargeable battery-powered sensors and renewable energy powered sensors, might be interim interventions to ensure continuous data collection. en_US
dc.description.department Geography, Geoinformatics and Meteorology en_US
dc.description.librarian hj2023 en_US
dc.description.sponsorship University of Leicester, South African Medical Research Council, South African National Treasury. en_US
dc.description.uri http://www.sajs.co.za en_US
dc.identifier.citation Wright, C. Y., Benyon, M., Mahlangeni, N., Kapwata, T., Laban, T., & Garland, R. M. (2023). Data gaps will leave scientists ‘in the dark’: How load shedding is obscuring our understanding of air quality. South African Journal of Science, 119(9/10). https://doi.org/10.17159/sajs.2023/16009. en_US
dc.identifier.issn 0038-2353 (print)
dc.identifier.issn 1996-7489 (online)
dc.identifier.other 10.17159/sajs.2023/16009
dc.identifier.uri http://hdl.handle.net/2263/93183
dc.language.iso en en_US
dc.publisher Academy of Science of South Africa en_US
dc.rights © 2023. The Author(s). Published under a Creative Commons Attribution Licence. en_US
dc.subject Air pollution en_US
dc.subject Air quality management en_US
dc.subject Environmental health en_US
dc.subject Rolling blackouts en_US
dc.subject South Africa (SA) en_US
dc.subject SDG-11: Sustainable cities and communities en_US
dc.title Data gaps will leave scientists ‘in the dark’ : how load shedding is obscuring our understanding of air quality en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record