Human health risks of exposure to fine particles (PM2.5) from the gold mine tailings in the community of eMbalenhle, South Africa

Abstract

South Africa is home to some of the world’s largest gold mines and contributes significantly to global gold production. However, gold mining activities generate waste in the form of soil, which is stored as Tailing Storage Facilities (TSFs). Gold mine TSFs are a source of ambient PM2.5. PM2.5 is particulate matter with a diameter of 2.5 micrometers or smaller. Epidemiological studies have found that exposure to fine particulate matter (PM2.5) poses potential human health risks. The human health risks posed by exposure to PM2.5 include respiratory, cardiovascular and cerebrovascular diseases. PM2.5 and heavy metals are transported from their sources to receptors. Mining activities are also a source of heavy metals in nearby soils. The most common heavy metals found in soil are Lead (Pb), Mercury (Hg), Cadmium (Cd), Manganese (Mn), Nickel (Ni), Zinc (Zn) and Arsenic (As). The heavy metals find their way to the ground, thus contaminating the soil. This study aimed to assess the potential human health risks associated with exposure to PM2.5 in the community of eMbalenhle which is near gold mine TSFs. The study was divided into four objectives, 1) to assess the PM2.5 spatial and temporal variations at the source (TSFs) and receptor (community), 2) to determine the atmospheric dispersion of PM2.5 emissions from gold mine TSFs to nearby communities, 3) to determine the concentrations of heavy metals in the soils collected within the mining area and identifying their sources, 4) to assess the potential human health risks associated with exposure to PM2.5 in the community of eMbalenhle. Ambient PM2.5 concentrations were monitored over a year (07 February 2022 to 07 February 2023) using Clarity Node-S Low-Cost Monitors (LCMs). Meteorological data (wind speed, wind direction, solar radiation, atmospheric radiation, rain, relative humidity, and temperature) for the same period were sourced from the South African Air Quality Information System (SAAQIS). Statistical analyses were performed using the Openair packages in R Studio (version 4.0.2) and Stata software (version 18). The American Meteorological Society Environmental Protection Agency Regulatory Model (AERMOD), coupled with meteorological information from the Weather Research Forecasting (WRF) model, was applied to predict the ground-level concentrations of PM2.5. The Inductively Coupled Plasma Mass Spectrometry (ICP-MS) method was used to analyze the heavy metals in the soil samples. The samples were prepared in a 1% Nitric Acid (HNO3) matrix. About 0.5% Hydrochloric acid (HCl) was routinely added to soil samples to ensure the iii stability of the heavy metals. The Absolute Principal Components Score - Multiple Linear Regression (APCS-MLR) Model was used to calculate the contribution rate of the heavy metals at each sampling point. The Enrichment Factor (EF) and Contamination Factor (CF) were calculated to determine whether the heavy metals in the soil samples originated from natural sources or were influenced by anthropogenic activities. The Upper Earth’s Crust (UEC) values were used as the soil background values of heavy metals. Mn was chosen as the reference element. The Probabilistic Human Health Risk Assessment (PHHRA) was applied to estimate cancer risks in four population subgroups (toddlers, children, adults and elderly). The results showed that PM2.5 concentrations were higher in Winter and lower in Summer at both the community site and gold mine TSFs. The average daily (24-hour) PM2.5 concentrations at the community site and gold mine TSFs were 19.24 and 9.70 μg/m³, respectively. The daily PM2.5 concentrations at the community site exceeded the South African National Ambient Air Quality Standard (NAAQS) of 40 μg/m3 twenty-six (26) times and the World Health Organisation (WHO) guidelines of 15 μg/m3 hundred and eighty-one times (181) times. The daily (24-hour) NAAQS was not exceeded at the gold mine TSFs; however, the WHO guideline was exceeded 85 times. Although the higher PM2.5 concentrations were recorded in the community compared to the gold mine TSFs, local PM2.5 sources could have contributed to the elevated concentrations. The dispersion model indicated a maximum PM2.5 24-hour average concentration of 11ug/m3 and; maximum annual average of 3.4 ug/m3 at the 99th percentile (worst-case scenario). The predicted concentrations were below both the national, Environmental Protection Agency (EPA) NAAQS and World Health Organization (WHO) guidelines. The mean Cr, As, Pb, U, and Au concentrations were higher in TSFs (89.2±58.8, 22.9±25.7, 10±10, 5.72±4.78, and 0.53±0.54 mg/kg) compared to residential sites (79.7±24.6, 2.6±1,33, 8.98±5.05,1.55±1.42, and 0.08 ±0.07 mg/kg), respectively. There were a significant difference in Mn concentrations (rrb = 0.833, p = 0.038) between the residential sites and TSFs. Results of the APCS-MLR of the heavy metals concentrations at the TSFs sites indicated that Au (92.7%), As (93.3%), U (93.3%) and Cr (88.3%) mainly originated from mining activities. The study findings confirmed that TSFs are basically waste soil and may have affected the surroundings. The PHHRA results indicated that the Hazard Quotient (HQ) was highest at the 95th percentile for all subgroups. Using the SA NAAQS, the HQ was estimated to be 0.9 for all subgroups, iv indicating safe levels. When utilizing the EPA NAAQS, a value of 2.5 was reported, while the WHO guidelines recorded the highest HQ of 3.5, indicating unsafe levels. This demonstrated that the South African NAAQS underestimated exposure to PM2.5. For both male and female elders, the Cancer Risk (CR) was approximately 1 in 10, meaning that about 100,000 out of 1,000,000 exposed elders were at an increased risk of developing cancer over their lifetime. The study had four (4) recommendations based on each objective, 1) revising the current NAAQS to adopt more stringent measures and align them to international benchmarks to safeguard the public from adverse health effects due to PM2.5 exposure, 2) future studies should focus on the dispersion and source apportionment of PM2.5 to quantify the contribution of various sources in eMbalenhle, 3) integrating other methods alongside bulk sampling and APCS-MLR in future studies to capture heterogeneity within the soil matrix and improve source apportionment resolution 4) carry out an elemental characterization of soil particles and estimate the health risks associated with chronic exposures in these communities