Distribution of heavy metals in surface soil near a coal power production unit: potential risk to ecology and human health

Artisanal mining of monazite and cassiterite in the Amazon: Potential risks of rare earth elements for the environment and human health

Artisanal mining is intensely carried out in developing countries, including Brazil and especially in the Amazon. This method of mineral exploration generally does not employ mitigation techniques for potential damages and can lead to various environmental problems and risks to human health. The objectives of this study were to quantify the concentrations of rare earth elements (REEs) and estimate the environmental and human health risks in cassiterite and monazite artisanal mining areas in the southeastern Amazon, as well as to understand the dynamics of this risk over time after exploitation. A total of 35 samples of wastes classified as overburden and tailings in active areas, as well as in areas deactivated for one and ten years were collected. Samples were also collected in a forest area considered as a reference site. The concentrations of REEs were quantified using alkaline fusion and ICP-MS. The results were used to calculate pollution indices and environmental and human health risks. REEs showed higher concentrations in anthropized areas. Pollution and environmental risk levels were higher in areas deactivated for one year, with considerable contamination factors for Gd and Sm and significant to extreme enrichment factors for Sc. Human health risks were low (< 1) in all studied areas. The results indicate that artisanal mining of cassiterite and monazite has the potential to promote contamination and enrichment by REEs.

Concentration, speciation and risk effects of multiple environmentally sensitive trace elements in respirable fine-grained fly ash

Respirable fine-grained fly ash (RFA) is captured very inefficiently by existing air purification devices of power plant, leading to increasing concerns regarding their migration and subsequent interaction with body due to fine particle size and its complex toxic composition. Trace elements of RFA in three groups with five different sizes between 8-13 µm were analyzed in terms of available concentration, speciation and risk effects. The concentration, pollution level and ecological risk level of elements in RFA were related to particle sizes. Chronic non-carcinogenic effect risk (NER) and carcinogenic effect risk (CER) were negatively correlated with particle size. The individual weight of exposed subjects, corresponding trace elements concentration and ingestion rate in RFA were three significant variables influencing CER. NER and CER had a tenfold exaggerated effect when calculated using total element concentration of RFA. In addition to individual differences and exposure conditions, trace element properties, speciation and available concentration were the dominant factor responsible for ecological and environmental effects of trace elements in RFA, following the order As>Ni, Mn>Cr>Pb>Cu>Zn. Results of this work highlight the effects and differences of trace elements in RFA on ecology and health, and provide a basis for further pollution control and human health warning.

Environmental impacts of Indian coal thermal power plants and associated human health risk to the nearby residential communities: A potential review

Worldwide, harmful emissions from coal power plants cause many illnesses contribute to premature deaths burden. Despite its high impact on human health and being a major source of toxic pollutants, coal has been considered a component of global energy for decades. Hence, this work was envisaged to understand the rising environmental and multiple health issues from coal power plants. Studies on the adverse impacts of coal power plants on the environment, including soil, surface water, groundwater and air, were critically evaluated. The health risk from exposure to different pollutants and toxic metals released from the power plant was also demonstrated. The study also highlighted the government initiatives and policies regarding coal power operation and generation. Lastly, the study focused on guiding coal power plant owners and policymakers in identifying the essential cues for the risk assessment and management. The current study found an association between environmental and human health risks due to power generation, which needs intervention from the scientific and medical fields to jointly address public concerns. It is also suggested that future research should concentrate on exposure assessment techniques by integrating source-identification and geographic information systems to assess the health effects of different contaminants from power plants and to mitigate their adverse impact.

Exploring the association of metal mixture in blood to the kidney function and tumor necrosis factor alpha using machine learning methods

This research aimed to approach relationships between metal mixture in blood and kidney function, tumor necrosis factor alpha (TNF-α) by machine learning. Metals levels were measured by Inductively Couple Plasma Mass Spectrometry in blood from 421 participants. We applied K Nearest Neighbor (KNN), Naive Bayes classifier (NB), Support Vector Machines (SVM), random forest (RF), Gradient Boosting Decision Tree (GBDT), Categorical boosting (CatBoost), eXtreme Gradient Boosting (XGBoost), Whale Optimization-based XGBoost (WXGBoost) to identify the effect of plasma metals, TNF-α, and estimated glomerular filtration rate (eGFR by CKD-EPI equation). We conducted not only toxic metals, lead (Pb), arsenic (As), cadmium (Cd) but also included trace essential metals, selenium (Se), copper (Cu), zinc (Zn), cobalt (Co), to predict the interaction of TNF-α, TNF-α/white blood count, and eGFR. The high average TNF-α level group was observed among subjects with higher Pb, As, Cd, Cu, and Zn levels in blood. No associations were shown between the low and high TNF-α level group in blood Se and Co levels. Those with lower eGFR group had high Pb, As, Cd, Co, Cu, and Zn levels. The crucial predictor of TNF-α level in metals was blood Pb, and then Cd, As, Cu, Se, Zn and Co. The machine learning revealed that As was the major role among predictors of eGFR after feature selection. The levels of kidney function and TNF-α were modified by co-exposure metals. We were able to acquire highest accuracy of over 85% in the multi-metals exposure model. The higher Pb and Zn levels had strongest interaction with declined eGFR. In addition, As and Cd had synergistic with prediction model of TNF-α. We explored the potential of machine learning approaches for predicting health outcomes with multi-metal exposure. XGBoost model added SHAP could give an explicit explanation of individualized and precision risk prediction and insight of the interaction of key features in the multi-metal exposure.

Evaluation of groundwater for drinking and irrigation applications concerning physicochemical and ionic parameters through multiple indexing approach: a case study around the industrial zone, Punjab, India

The seasonal quality of groundwater and its appropriateness for drinking and irrigation were assessed using a multiple indexing approach in this study. Physicochemical and ionic parameters were examined in groundwater samples near the industrial zone of Rupnagar, Punjab. To assess groundwater quality, water quality index (WQI) and pollution index were used. The Durov's, piper, wilcox and stiff diagrams were plotted to understand the hydro-chemistry. Similarly, the irrigation indices, i.e., salinity hazard, sodium adsorption ratio, soluble sodium percentage (Na%), magnesium adsorption ratio, residual sodium carbonate, permeability index and Kelley's ratio were applied to ascertain the water quality for agricultural purposes. As a result, total hardness, calcium (Ca²⁺), magnesium (Mg²⁺) and fluoride (F^-) were found above the standard permissible limits. WQI analysis showed 12% samples of pre-monsoon (PRE-M) and 28% samples of post-monsoon (POS-M) were of poor quality, which may pose health risks. Hydrochemistry revealed the predominance of Ca²⁺, Na⁺, Mg²⁺ and HCO₃^- ions in the groundwater attributed to natural and anthropogenic sources. Piper diagram revealed Ca²⁺-Mg²⁺-Cl^-, Na⁺-Cl^-, Ca²⁺-Na⁺- HCO₃^-, Ca²⁺- HCO₃^- and Ca²⁺-Cl, Ca²⁺-HCO₃^- water types exist in the study area. USSL diagram showed that the samples from both seasons come under the low salinity hazard. In addition, total dissolved solids and electrical conductivity showed a strong positive association, indicating the saline nature of groundwater. Furthermore, hierarchical clustering classified groundwater into three groups (I, II and III), revealing that groundwater quality varies due to natural and anthropogenic effects. Based on the findings, the groundwater was found marginally suitable for drinking and irrigation purposes. It is therefore recommended that the groundwater is examined on a regular basis in order to maintain its quality.

Distribution, sources and health risks of heavy metals in indoor dust across China

The potential effects of heavy metals on human health have attracted increasing attention as most people spend up to 90% of their time indoors. Human exposure to heavy metals in indoor dust have only been characterised for limited regions in China, and full-scale data for different functional areas are not available. Therefore, this review analysed the concentrations, contamination characteristics, and potential health risks of seven heavy metals (including zinc (Zn), lead (Pb), copper (Cu), chromium (Cr), nickel (Ni), arsenic (As), and cadmium (Cd)) in indoor dust at 3392 sampling sites in 55 cities across 27 provincial regions of China based on literature data. Results revealed that the median heavy metal concentrations in indoor dust throughout China decreased in the following order: Zn > Pb > Cu > Cr > Ni > As > Cd. Traffic emissions and decorative materials are the primary sources of heavy metal pollution in indoor dust. No considerable non-carcinogenic risk was found for Zn, Cu, Cr, Ni, and Cd in indoor dust, while Pb and As exhibited potential non-carcinogenic risks to children, primarily distributed in cities across Southern China. Meanwhile, the carcinogenic risks posed by Cr and Ni were higher than those posed by As and Cd, especially in Southern China. Therefore, effective measures in Southern China should prioritised for controlling Pb, Cr, Ni and As pollution in indoor dust to reduce human health risk. This review is useful for policy decision-making and protecting human from exposure to heavy metals in indoor dust across China.

Heavy metal levels in the soil near typical coal-fired power plants: partition source apportionment and associated health risks based on PMF and HHRA

In this study, five priority metals recommended by the Ministry of Ecology and Environment of China (MEEC) were investigated. In the Bijie region of Guizhou Province, three typical coal-fired power plants were chosen as the research locations. A combination of 24 soil samples was obtained at various distances and depths from the point source of contamination. The authors found that the average contents of As, Cd, Cr, Ni, and Pb were 14.15, 1.52, 16.80, 40.71, and 53.00 mg kg^-1, respectively, with Cd and Pb pollution prominent. In another, soil heavy metal (SHM) content tends to increase or decrease dependently with the increase of sampling distance and depth, with total concentrations ranging from 77.14 to 157.33 mg kg^-1. Combining PCA and PMF models, the number of source factors was determined more clearly and accurately using PCA, and the Q-value of PMF was used for validation. The PCA-PMF indicated that the primary anthropogenic sources were transportation-related activities and emissions from coal combustion. The health risks of SHMs under three different exposure routes were then assessed using the HHRA. The findings showed the five HMs in order of non-carcinogenic risk were As > Pb > Cr > Ni > Cd. The comprehensive non-carcinogenic risk for children under the oral intake route around plant B and C was greater than 1, pointing to a potential health risk to children from the soils. The carcinogenic risk of HM was less than 1.00E-04 for both single-factor and multifactor under all three exposure routes, which is below the tolerable limit.

The multiple value characteristics of fly ash from Indian coal thermal power plants: a review

Coal-powered thermal plants are the primary source of energy production around the globe. More than half (56.89%) of the Indian power plants use coal for power production. Coal burning in power plants results in coal combustion residuals, which contain coal fly ash (CFA) that is recognized as principle by-product. CFA is difficult to characterize due to its broad compositional variation. Hence, the present article summarizes the various physical, chemical, mineralogical, and petrological characterizations of CFA to its use in different applications. Indian coal thermal power plants are found to release two types of CFA: F (fine) and C (coarse). CFA particles are identified as unburned carbon particles with a large fraction of silica oxides, alumina oxides, and iron oxides with a small fraction of calcium oxide (CaO). Morphologically, CFA particles are spherical, with large carbon molecules and a smooth texture surface. In terms of mineralogy; quartz, mullite, magnetite, and hematite are the dominant mineral phases of CFA and tend to be non-plastic, with permeability levels ranging from 8 × 10^-6 to 1.87 × 10^-4 cms^-1. Petrographically, CFA is enriched in inertinite and liptinites as well as collotelinite, collodetrinite, and vitrodetrinite particles. Moreover, CFA is found to be composed of various organic and inorganic particles. By virtue of multiple characterizations, it has been utilized in several applications for decades, which is still quite limited. Therefore, current study aim to provide helpful insights into the potential use of CFA-derived products in different ways to increase sustainability.