Research article Intra-urban variability of PM2.5in a dense, low-income settlement on the South African Highveld

Abstract

High concentrations of the ambient particulate matter remain a concern on the South African Highveld, particularly in densely populated low-income settlements. These areas have several local emission sources that contribute to poor air quality and are often located close to industrial and other urban areas. The local sources vary in magnitude, space, and time. In South Africa, little has been done to assess the impacts of spatiotemporal variability on the credibility of using isolated ambient observations for regulatory purposes. This study aims to evaluate the intra-urban variability of ambient PM2.5concentrations in a dense, low-income community. Ambient fine particulate matter (PM2.5) in distinct microenvironments of KwaZamokuhle were simultaneously measured at 4 sites between March and June 2018. These measurements were collected using one permanent ambient monitoring station (AMS) and a temporary network of three E-BAM monitors (Site 2, Site 3, and Site 4). Moreover, the 2011 Census spatial data was used to assess socioeconomic conditions impacting PM2.5concentrations in areas surrounding each monitoring station. The daily PM2.5concentrations at AMS, Site 2, Site 3, and Site 4 varied from 10 to 86 μg.m-3, 10 to 103 μg.m-3, 11 to 101 μg.m-3, and 9 to 113 μg.m-3, respectively. Extreme PM2.5concentrations which exceeded the 24h PM2.5NAAQS of 40 μg.m-3were seen during the cold period (May and June); meanwhile, the warm period (March and April) recorded relatively lower PM2.5episodes across different sections of KwaZamokuhle. During May- June, the highest diurnal concentrations of hourly averaged ambient PM2.5were recorded at Site 4, in a downward sequence, followed by Site 3, Site 2, and AMS. It was further found that informal dwellings and solid fuel reliant houses are widely concentrated at Site 4 thus, indicating exposure inequalities across the community. This study, therefore, highlights the complexity of quantifying ambient air quality in an area where several local emission sources vary in space and time. Attempts to use monitoring data from a single station to assess ambient air quality, quantify human exposure, or evaluate the potential impacts of mitigation strategies in dense, low-income settlements should be done with care.