Modelling of Air Pollution and Evaluation of the Human Health Implication in Phalaborwa, Mopani District, South Africa

PhDENVDepartment of Geography and Environmental SciencesAir pollution has increased public health concerns and is currently a scientific research interest in both developed and developing countries due to its critical impacts being instigated on man, animals, water, and the entire environment. Thus, may become the major environmental basis of mortality worldwide. Availability of multiple sources from various economic growth has posed negative impact given opportunities for policy reduction and the context for policy creation. This study was aimed at investigating air pollution levels and the associated human health implication in Phalaborwa, Mopani District, South Africa. Emission inventories were developed within Phalaborwa region to identify and quantify the major emissions sources (including domestic solid fuels, vehicles, mining, fugitive, and biomass burning) of criteria pollutants using United State Environmental Protection Agency (US EPA) methodology. The emission factors used for each source were adopted from literature. Spatio-temporal distribution as well as the impact of meteorological data on the particulate matter were studied using statistical functions (R statistical tools) and Kruskal Wallis test, respectively. The potential sources were studied using bipolar variations. The American Meteorological Environmental Protection Agency Regulatory Model (AERMOD) dispersion modelling was used to model the dispersion of major emission sources of PM2.5 and PM10 within the community. The AERMOD model uses the five pathways including control, sources, receptor, meteorological and output to generate the spatial and temporal variation of pollutant concentrations. The percentage relative source contribution and the seasonal contributions were studied using Microsoft Excel package version 2305. Sensitive receptor locations were chosen to estimate their concentrations. The potential health risk of the studied pollutants was estimated using US EPA methodology known as human health risk assessment tool (HHRA). The emission sources identified were domestic burning, mining, fugitive dust, open biomass burning and vehicle. Annual estimated emission of PM2.5, PM10, SO2, NOx and CO in the area are 1.1, 3.4, 0.1, 0.5, and 2.2 ktons/yr, respectively. Mining sources were identified as the highest contributor to all the pollutants studied except PM2.5. The highest emitted pollutant is PM10 (47%) which shows the generation of dust while the least emitted pollutant is SO2 (1.5%) as its emissions is majorly from the mining source. Thus, fine particulate and dust emissions exist within the Phalaborwa region. The diurnal variation for measured PM2.5 and PM10 showed two major peaks matching morning and evening, while the monthly peak showed the maximum peak during winter season. Spearman rank correlation analysis of PM2.5 and PM10 established a strong positive association of 0.90. The Kruskal Wallis test showed that the meteorological variables have high influence during winter season (test statistics is 31401 at P < 0.001). The potential source of the emission are open bare places, paved roads occurring from south-east wind vi direction. The spatial and temporal dispersion of the model showed high concentration at surface of the mine and tailings. The validation of the model performed by comparison of the observed and modelled concentrations using fractional bias (FB), fractions of predictions (FAC2), and normalised mean square error (NMSE). AERMOD evaluation showed good agreement between the observed and modelled concentrations. The relative contribution results showed that wind-blown dust significantly contributed 71% and 52% to the predicated total PM2.5 and PM10 concentration, respectively. The least contributor to the total predicted concentration were biomass burning source (PM2.5 with 4%) and residential wood burning (PM10 with 1%). Moreover, the seasonal contribution indicated that windblown dust contributed largely to winter season, domestic wood burning also exhibited minimum contribution during winter, while biomass burning contributed to autumn season for both pollutants. For the health studies, the daily PM2.5 (17.49 μg/m3) and PM10 (40.42 μg/m3) as well as the annual PM2.5 (11.74 μg/m3) and PM10 (26.06 μg/m3) measured average concentrations were below the 24-hours PM2.5 and PM10 (40, 75 μg/m3) and yearly (20, 40 μg/m3) South African National Ambient Air Quality Standards (NAAQS), respectively. The measured concentrations were above the daily (15 μg/m3) and annual (5 μg/m3) World health Organisation (WHO) guidelines except PM10 daily concentration that is below. The hazard quotient for chronic exposure under the normal and worst-case situation would likely have negative effects in all exposed age group (HQ >1) for the measured predicted concentration. Moreover, the study contributes for the first time the identification and estimation of emissions from solid fuel use, their determining factor factors to promoting modern energy, linking to sustainable development goal 7 (SDG 7). The interactions of major sources of air pollutants within Phalaborwa region has been established. The outcome of the modelling scenarios from the sources will promote safe human settlement (SDG 11). The estimation of probable health risk will aid the health and wellbeing of the community residents (SDG 3). Thus, it is recommended that development of framework to reduce pollutions and provide evidence-based recommendations to lower air pollution from such as windblown dust, domestic burning, vehicular movement, and tailings is necessary. Also, more potable, and mobile devices adaptable for real time air pollution monitoring is necessary. This will complement the function of stationary air pollution monitoring instrument, particularly, in identified sensitive locations with high concentrations. Additionally, green solutions to air pollution reduction using high air pollution tolerance trees or plants and performance indices around untarred road as well as unvegetated bare soils are recommended in rural areas.NR