Particulate Matter (PM2.5) Characterization, Air Quality Level and Origin of Air Masses in an Urban Background in Pretoria

Several sources have been identified as contributing to the concentration of ambient fine particulate matter, which has been associated to a variety of health issues. The chemical characteristics and sources of trace elements in PM_2.5, as well as the air quality index, were investigated in this study. Twenty four-hour fine aerosol particles were collected in an urban area in Pretoria, South Africa, from April 2017 to April 2018. Eighteen trace elements were determined using an XEPOS 5 energy-dispersive X-ray fluorescence (EDXRF) spectrometer, while black and organic carbon were estimated using an optical transmissometer from the samples collected. The HYPLIT model (version 4.9) was used to estimate air mass trajectories. Health risk was calculated by comparing it to the World Health Organization's air quality index (AQI). The overall mean PM_2.5 concentration of the collected sample equals 21 µg/m³. Majority of PM_2.5 exceedances were reported during mid-autumn and winter seasons, as compared to daily WHO guidelines and South African standards. S had the highest concentrations, greater than 1 µg/m³. Ni, Se, Br and Sb showed they were extremely enriched, (EF > 10) and suggestive of anthropogenic or non crustal origin The 24-h PM, soot, BC and OC were significantly different by the geographical origin of air masses (p < 0.05). The AQI showed that 70% of the samples showed levels above the AQI range of good and healthy air. The findings include details on the concentration, composition, and potential sources of fine PM_2.5, which is essential for policy formulation and mitigation strategies in South Africa's fight against air pollution.

Using Low-Cost Measurement Systems to Investigate Air Quality: A Case Study in Palapye, Botswana

Exposure to particulate air pollution is a major cause of mortality and morbidity worldwide. In developing countries, the combustion of solid fuels is widely used as a source of energy, and this process can produce exposure to harmful levels of particulate matter with diameters smaller than 2.5 microns (PM2.5). However, as countries develop, solid fuel may be replaced by centralized coal combustion, and vehicles burning diesel and gasoline may become common, changing the concentration and composition of PM2.5, which ultimately changes the population health effects. Therefore, there is a continuous need for in-situ monitoring of air pollution in developing nations, both to estimate human exposure and to monitor changes in air quality. In this study, we present measurements from a 5-week field experiment in Palapye, Botswana. We used a low-cost, highly portable instrument package to measure surface-based aerosol optical depth (AOD), real-time surface PM2.5 concentrations using a third-party optical sensor, and time-integrated PM2.5 concentration and composition by collecting PM2.5 onto Teflon filters. Furthermore, we employed other low-cost measurements of real-time black carbon and time-integrated ammonia to help interpret the observed PM2.5 composition and concentration information during the field experiment. We found that the average PM2.5 concentration (9.5 µg∙m−3) was below the World Health Organization (WHO) annual limit, and this concentration closely agrees with estimates from the Global Burden of Disease (GBD) report estimates for this region. Sulfate aerosol and carbonaceous aerosol, likely from coal combustion and biomass burning, respectively, were the main contributors to PM2.5 by mass (33% and 27% of total PM2.5 mass, respectively). While these observed concentrations were on average below WHO guidelines, we found that the measurement site experienced higher concentrations of aerosol during first half our measurement period (14.5 µg∙m−3), which is classified as “moderately unhealthy” according to the WHO standard.

An overview of regional and local characteristics of aerosols in South Africa using satellite, ground, and modeling data

We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during austral spring (September-October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM₁₀ concentrations as much as 136 % higher in townships that in industrial areas. We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.

Inferring wavelength dependence of AOD and Ångström exponent over a sub-tropical station in South Africa using AERONET data: influence of meteorology, long-range transport and curvature effect

Aerosol optical properties over a southern sub-tropical site Skukuza, South Africa were studied to determine the variability of the aerosol characteristics using CIMEL Sunphotometer data as part of the AErosol RObotic NETwork (AERONET) from December 2005 to November 2006. Aerosol optical depth (AOD), Ångström exponent (α), and columnar water vapor (CWV) data were collected, analyzed, and compiled. Participating in this network provided a unique opportunity for understanding the sources of aerosols affecting the atmosphere of South Africa (SA) and the regional radiation budget. The meteorological patterns significantly (p<0.05) influenced the amount and size distribution of the aerosols. Results showed that seasonal variation of AOD at 500 nm (AOD500) over the observation site were characterized by low values (0.10-0.13) in autumn, moderate values (0.14-0.16) in summer and winter seasons, and high to very high values (0.18-0.40) during the spring, with an overall mean value of 0.18±0.12. Ångström exponent α(440-870), varied from 0.5 to 2.89, with significant (p<0.0001) seasonal variability. CWV showed a strong annual cycle with maximum values in the summer and autumn seasons. The relationship between AOD, Ångström exponent (α), and CWV showed a strong dependence (p<0.0001) of α on AOD and CWV, while there was no significant correlation between AOD and CWV. Investigation of the adequacy of the simple use of the spectral AOD and Ångström exponent data was used in deriving the curvature (a2) showed to obtain information for determining the aerosol-particle size. The negative a2 values are characterized by aerosol-size dominated by fine-mode (0.1-1 μm), while the positive curvatures indicate abundance of coarse particles (>1 μm). Trajectory cluster analyses revealed that the air masses during the autumn and winter seasons have longer advection pathways, passing over the ocean and continent. This is reflected in the aerosol properties that are derived from the ocean, desert, and anthropogenic activities that include biomass burning and industrial pollution.

Solar absorption by elemental and brown carbon determined from spectral observations

Black carbon (BC) is functionally defined as the absorbing component of atmospheric total carbonaceous aerosols (TC) and is typically dominated by soot-like elemental carbon (EC). However, organic carbon (OC) has also been shown to absorb strongly at visible to UV wavelengths and the absorbing organics are referred to as brown carbon (BrC), which is typically not represented in climate models. We propose an observationally based analytical method for rigorously partitioning measured absorption aerosol optical depths (AAOD) and single scattering albedo (SSA) among EC and BrC, using multiwavelength measurements of total (EC, OC, and dust) absorption. EC is found to be strongly absorbing (SSA of 0.38) whereas the BrC SSA varies globally between 0.77 and 0.85. The method is applied to the California region. We find TC (EC + BrC) contributes 81% of the total absorption at 675 nm and 84% at 440 nm. The BrC absorption at 440 nm is about 40% of the EC, whereas at 675 nm it is less than 10% of EC. We find an enhanced absorption due to OC in the summer months and in southern California (related to forest fires and secondary OC). The fractions and trends are broadly consistent with aerosol chemical-transport models as well as with regional emission inventories, implying that we have obtained a representative estimate for BrC absorption. The results demonstrate that current climate models that treat OC as nonabsorbing are underestimating the total warming effect of carbonaceous aerosols by neglecting part of the atmospheric heating, particularly over biomass-burning regions that emit BrC.