Geospatial analysis of residential proximity to open-pit coal mining areas in relation to micronuclei frequency, particulate matter concentration, and elemental enrichment factors

Micronuclei frequency and exposure to chemical mixtures in three Colombian mining populations

The Colombian mining industry has witnessed significant growth. Depending on the scale and mineral extracted, complex chemical mixtures are generated, impacting the health of occupationally exposed populations and communities near mining projects. Increasing evidence suggests that chromosomal instability (CIN) is an important link between the development of certain diseases and exposure to complex mixtures. To better understand the effects of exposure to complex mixtures we performed a biomonitoring study on 407 healthy individuals from four areas: three located in municipalities exploiting different-scale mining systems and a reference area with no mining activity. Large, medium, and small-scale mining systems were analyzed in Montelibano (Córdoba), artisanal and small-scale mining (ASGM) in Nechí (Antioquia), and a closed mining system in Aranzazu (Caldas). The reference area with no mining activity was established in Montería (Córdoba). ICP-MS measured multi-elemental exposure in hair, and CIN was evaluated using the cytokinesis-block micronucleus technique (MNBN). Exposure to mixtures of chemical elements was comparable in workers and residents of the mining areas but significantly higher compared to reference individuals. In Montelibano, increased MNBN frequencies were associated with combined exposure to Se, Hg, Mn, Pb, and Mg. This distinct pattern significantly differed from other areas. Specifically, in Nechí, Cr, Ni, Hg, Se, and Mg emerged as the primary contributors to elevated frequencies of MNBN. In contrast, a combination of Hg and Ni played a role in increasing MNBN in Aranzazu. Interestingly, Se consistently correlated with increased MNBN frequencies across all active mining areas. Chemical elements in Montelibano exhibit a broader range compared to other mining zones, reflecting the characteristics of the high-impact and large-scale mining in the area. This research provides valuable insights into the effects of exposure to chemical mixtures, underscoring the importance of employing this approach in the risk assessment of communities, especially those from residential areas.

Emissions monitoring and carcinogenic risk assessment of PM10-bounded PAHs in the air from Candiota's coal activity area, Brazil

The city of Candiota contains a great amount of coal resources. Coal activities, including coal combustion, are major releasers of polycyclic aromatic hydrocarbons (PAHs). The PAHs are considered priority air pollutants regarding their large carcinogenic potential. So, the carcinogenic risk assessment of populations living near areas with PAH sources is mandatory. This study aimed to evaluate the carcinogenic health risk of the PAH inhalation exposure of individuals living in Candiota City. A total of 158 individuals were enrolled in the study. Monitoring of PAH and meteorological parameters were carried out, and the health risk assessment was determined through the benzo(a)pyrene equivalent toxic equivalent quotient (BaP-TEQ) and the incremental lifetime cancer risk (ILCR) estimation. The coal activity area of Candiota demonstrated an annual PAH concentration of 27.7 ng/m³, PM10 concentration of 26.3 µg/m³, SO₂ concentration of 9.5 µg/m³, a BaP-TEQ value of 0.3 ng/m³, and a daily inhalation of 62.4 ng/day. The comparison among seasons showed no difference in PAH concentration and BaP-TEQ. It was observed ILCR values of 2.8 × 10^-6 and 2.6 × 10^-6 for estimation based on reference and real values, respectively, and these levels were above the reference limit of 10^-6, indicating cancer risk. Therefore, an epidemiological survey of cancer cases in the region and its relationship with environmental exposure and air pollutants levels must be required.

Empirical relationship between chromosomal damage and airborne particulate matter: A systematic review and meta-analysis of studies in exposed populations

Ambient particulate matter (PM) has gained significant attention as an environmental risk factor for human health. Although the association between ambient PM and micronucleus (MN) induction has been investigated, the quantitative association of PM and genomic instability is inconclusive. We conducted a systematic review and meta-analysis to study the association between PM exposure and MN endpoint. Four databases were systematically searched for studies published up to November 2022, to find papers investigating the relationship between ambient PM and MN induction. Random effect models were conducted to estimate the overall effect based on the Ratio of Means (RoM) with 95% confidence intervals (95% CIs). Subgroup analysis, funnel plot, and Egger and Begg tests, were also performed. Twenty-three studies across nine countries, including 4450 participants, were included. A meta-RoM of 2.13 for MN (95% CI 1.63-2.79) was observed for individuals exposed to ambient PM compared to non-exposed. A significant difference in the subgroup test was found for buccal cells (3.16, 95% CI 2.20-4.52) and low economy level (3.61, 95% CI 1.44-9.01). Our meta-analysis suggests the presence of an association between PM exposure and the frequency of MN and identified the kind of cells and economic status as possible effect modifiers. The use of effective methods, such as the MN assay, enables identification of early genetic damage in humans, which in turn may anticipate the risk of developing respiratory diseases, including lung cancer.

Chemical Composition and Toxicity of PM10 and PM0.1 Samples near Open-Pit Mines and Coal Power Stations

Particulate matter (PM) <10 μm in size represents an extremely heterogeneous and variable group of objects that can penetrate the human respiratory tract. The present study aimed to isolate samples of coarse and ultrafine PM at some distance from polluting industries (1−1.5 km from the border of open-cast mines). PM was collected from snow samples which allowed the accumulation of a relatively large amount of ultrafine particles (UFPs) (50−60 mg) from five objects: three open-cast mines, coal power plants, and control territories. The chemical composition of PM was examined using absorption spectroscopy, luminescence spectroscopy, high-performance liquid chromatography, X-ray diffraction (XRD), and X-ray fluorescence (XRF) analyses of solid particle material samples. Toxicity was assessed in human MRC-5 lung fibroblasts after 6 h of in vitro exposure to PM samples. The absorption spectra of all the samples contained a wide non-elementary absorption band with a maximum of 270 nm. This band is usually associated with the absorption of dissolved organic matter (DOM). The X-ray fluorescence spectra of all the studied samples showed intense lines of calcium and potassium and less intense lines of silicon, sulfur, chlorine, and titanium. The proliferation of MRC-5 cells that were exposed to PM0.1 samples was significantly (p < 0.01) lower than that of MRC-5 cells exposed to PM10 at the same concentration, except for PM samples obtained from the control point. PM0.1 samples—even those that were collected from control territories—showed increased genotoxicity (micronucleus, ‱) compared to PM10. The study findings suggest that UFPs deserve special attention as a biological agent, distinct from larger PMs.

Mapping the Morbidity Risk Associated with Coal Mining in Queensland, Australia

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.

Intergenerational effects of coal dust on Tribolium castaneum, Herbst

Coal dust is a primary air contaminant from coal mining operations that produces harmful health effects. However, it is unclear to what extent its detrimental properties would impact future generations, and whether alterations in the progenies might be concentration-dependent. The aim of this study was to determine the intergenerational effects of chronic exposure to coal dust on the red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), at three life stages. Groups of fifty adult insects were exposed during 30 days at different concentrations of coal dust mixed with ground oats as food substrate (0, 0.25, 0.5, 1.0 and 2.0% weight/weight), both with a particle size <38 μm. The LC₅₀ for F0 insects was 1.07%, whereas for larvae and adults from F1, values were 0.53 and 0.89%, respectively. Pathological findings assessed at F1 revealed a coal dust concentration-dependent frequency of several morphological abnormalities, including larvae without antenna or extremities, lack of T1, T2, T3 legs, loss of urogomphi, and the presence of abnormal protuberances. It was found that a considerable number of F1 larvae derived from parental beetles did not achieve a complete conversion into the next growth stage. Pupae with undeveloped eyes and adults with malformed elytra, as well as necrosis, were recurrently observed at high concentrations. Finally, adults exposed to 1% coal dust overexpressed genes related to oxidative stress (nuclear factor erythroid 2-related factor 2, Nrf2) and synaptic transmission (GABA-gated ion channel, Grd). In short, coal dust particles induced intergenerational effects on T. castaneum, highlighting the need to further study the impact of this airborne pollutant on wildlife and human populations.

Air Pollution Emissions 2008-2018 from Australian Coal Mining: Implications for Public and Occupational Health

Occupational exposure limits for respirable coal dust are based on exposure during working hours, but coal miners may experience additional community-based exposures during nonworking hours. We analyzed Australia National Pollutant Inventory (NPI) data for the years 2008–2018 to estimate air pollutants (metals, nitrogen oxides, particulate matter ≤ 10 micrometers (PM10) and ≤2.5 micrometers (PM2.5)) originating from coal mines. PM10 levels from community-based air monitors in Queensland and New South Wales were also compared between mining and nonmining communities. Results indicated that tons of coal mined increased over the study period, and that levels of particulate matter, metals, and nitrogen oxides increased significantly over time as well. Coal mines accounted for 42.1% of national PM10 air emissions from NPI sites. PM2.5 from coal mines accounted for 19.5% of the national total, metals for 12.1%, and nitrogen oxides for 10.1%. Coal mining occurred in 57 different post codes; the 20 coal-mining post codes with the highest PM10 emissions were home to 160,037 people. Emissions of all studied pollutants were significantly higher from coal mining sites than from other types of NPI sites. Results from community-based air monitoring stations indicated significantly higher population PM10 exposure in coal mining communities than in nonmining communities. The health of the public at large is impacted by coal mining, but to the extent that miners also live near coal mining operations, their total exposure is underestimated by consideration of exposure only during working hours.

Assessment of mining impacts on environment in Muğla-Aydın (SW Turkey) using Landsat and Google Earth imagery

Mining activities are important for the country's economy, but they cause serious threats to the environment. The geology of SW Turkey comprises Southern (Çine) Submassif of Menderes Metamorphic Massif and the Lycian Nappes. These geological units are unconformably overlain by lignite-bearing Miocene deposits, Upper Miocene-Pliocene conglomerates and Quaternary alluvial deposits. The aim of this study is to determine the geospatial change of mining activities in the Muğla-Aydın provinces, SW Turkey. For this purpose, Landsat-5 TM, Landsat-7 ETM, Landsat-8 OLI and Google Earth satellite image data for 1984, 1994, 2004, 2014 and 2018 have been used for change detection analysis. In 1984, only a Miocene lignite quarry was excavated. Then, in 1994, operations for the excavation of feldspar-quartz and marble quarries were started, and from 2004 to 2014, mining activities significantly accelerated. An aerial image of 2018 shows that an area of about 3800 ha has been exploited by mining at 149 quarries. Considering access roads to quarries, plants and dam reservoirs, the human impact extends over 3800 ha. The study area is home to several archaeological sites and endemic biota. Thus, there is an urgent need for the relocation and protection of archaeological heritages and endemic biota by creating special zones. Additionally, the rich geomorphologic features in the study area that require millions of years to form are at risk of totally disappearing.

Predicting the hormesis and toxicological interaction of mixtures by an improved inverse distance weighted interpolation

The prediction of toxicological interactions and hormesis of chemical mixtures is important because organisms are mostly exposed to numerous contaminants and typically to low dose of these mixtures, and it is still a challenge. Although many models have been developed to predict the mixture toxicities such as concentration addition (CA) and independent action (IA), they cannot solve these challenges perfectly. This study has developed an improved inverse distance weighted (IDW) interpolation for prediction of the mixture toxicities. IDW uses the mixture and the single compound as scatter points in space, and the space can be constructed by the concentration axes of various components in the mixture system. Some known mixtures (or the single compound) closest to the unknown mixture are selected as interpolation nodes. To be more accurate in calculation, a new normalization method for concentration has been proposed through dividing the concentration of the mixture and the single compound by the respective EC₅₀ values. Sixteen binary mixture systems are selected for leave-one-out cross-validation and three binary mixture systems are selected for external validation. The results show that the accuracy of IDW is ≥95% for three types of mixtures including no hormetic component, one hormetic component (show no toxicological interaction), and two hormetic components. The IDW also show higher prediction accuracy than that of CA and IA. The IDW developed in this study can be used to predict the toxicity of various mixture systems, thus providing predictive information for chemical mixtures risk assessment.

Similarities and differences in PM10 and PM2.5 concentrations, chemical compositions and sources in Hefei City, China

Atmospheric particulates were sampled in Hefei City, China from October 2016 to January 2017 to compare chemical compositions and sources of PM_2.5 (particle size smaller than 2.5 μm) and PM₁₀ (particle size smaller than 10 μm). The mean levels of PM_2.5 and PM₁₀ were 81 and 109 μg/m³, which are higher than the health threshold levels regulated by national and international standards. During the sampling period, AQI (Air Quality Index) was strongly correlated with PM_2.5 (Pearson's coefficient r = 0.94) rather than PM₁₀ concentrations. The PM_2.5/PM₁₀ ratios were approximately 0.7, revealing the characteristics of fine particle pollution. Pollution elements (S, Zn, Cu and Pb) took up a large proportion of the composition and had high enrichment factors of 437, 385, 20 and 53, respectively, in PM₁₀. Coal combustion and high-tech manufacture industry discharges were suggested to be the main pollution sources of both PM_2.5 and PM₁₀. The PM_2.5/PM₁₀ ratios of anthropogenic element concentrations were much higher than ratios of earth crust element. As compared to PM₁₀, S and Pb in PM_2.5 had larger EFs, indicating that pollution elements were predominantly enriched in PM_2.5. Furthermore, a paired sample t-test confirmed similar sources of PM_2.5 and PM₁₀. Our study provides basic database to evaluate the heavy metal pollution status of atmospheric particulates in Chinese cities.

Impact of the Coal Mining on the Spatial Distribution of Potentially Toxic Metals in Farmland Tillage Soil

Coal mining areas are prone to hazardous element contamination because of mining activities and the resulting wastes, mainly including Cr, Ni, Cu, Zn, Cd and Pb. This study collected 103 samples of farmland tillage soil surrounding a coal mine in southwestern Shandong province and monitored the heavy metal concentrations of each sample by inductively coupled plasma mass spectrometer (ICP-MS). Statistics, geostatistics, and geographical information systems (GIS) were used to determine the spatial pattern of the potentially toxic metals above in the coal mining area. The results show that the toxic metal concentrations have wide ranges, but the average values for Cr, Ni, Cu, Zn, Cd and Pb are 72.16, 29.53, 23.07, 66.30, 0.14 and 23.71 mg Kg-1, which mostly exceed the natural soil background contents of Shandong Province. The element pairs Ni-Cu, Ni-Zn, and Cu-Zn have relatively high correlation coefficients (0.805, 0.505, 0.613, respectively). The Kriging interpolation results show that the contents of soil toxic metals are influenced by coal mining activities. Moreover, micro-domain variation analysis revealed the toxic metals in the typical area of the coal transportation line. These findings offer systematic insight into the influence of coal mining activities on toxic metals in farmland tillage soil.