Aiming at the acid mine drainage (AMD) in zinc, copper and other heavy metals treatment difficulties, severe pollution of soil and water environment and other problems. Through the ultrasonic precipitation method, this study prepared fly ash-loaded nano-FeS composites (nFeS-F). The effects of nFeS-F dosage, pH, stirring rate, reaction time and initial concentration of the solution on the adsorption of Zn(II) and Cu(II) were investigated. The data were fitted by Lagergren first and second-order kinetic equations, Internal diffusion equation, Langmuir and Freundlich isotherm models, and combined with SEM, TEM, FTIR, TGA, and XPS assays to reveal the mechanism of nFeS-F adsorption of Zn(II) and Cu(II). The results demonstrated that: The removal of Zn(II) and Cu(II) by nFeS-F could reach 83.36% and 70.40%, respectively (The dosage was 8 g/L, pH was 4, time was 150 min, and concentration was 100 mg/L). The adsorption process, mainly chemical adsorption, conforms to the Lagergren second-order kinetic equation (R2 = 0.9952 and 0.9932). The adsorption isotherms have a higher fitting degree with the Langmuir model (R2 = 0.9964 and 0.9966), and the adsorption is a monolayer adsorption process. This study can provide a reference for treating heavy metals in acid mine drainage and resource utilization of fly ash.

Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado\'s arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique\'s ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.

The feasibility of recovering major and critical elements from acid mine drainage using a pilot-scale electrochemical reactor (ECR) was investigated by assessing elements concentration and species distribution in the liquid and solid phase (sludge) in multistage tests. These were carried out at different electrical currents (18-22 amps) and thus, pH (8-12). The results showed that major metals Al, Cu and Fe were removed from the liquid phase at pH 5.9 while remaining the majority of Zn (57.2 ppm). On the other hand, at pH 7, the effluent was mainly composed of Mn (7.3 ppm). These results were confirmed by the simulation results using the PHREEQC model, which also identified the main chemical species in solution and the precipitates formed after the treatment (oxyhydroxides/sulfates/oxides). The ECR treatment led to sludges with targeted critical elements, some up to 20 times (Co, Be and Sb) higher than their earth\'s crustal abundance. At pH 10, rare earth elements in the sludge targeted Ce, followed by Nd and La. This study is one of the few studies carrying a detailed analysis of the behavioural distribution pattern of these elements at each pH, which opens the door for the potential of recovering these elements.

Empty fruit bunch oil palm (EFBOP) is one of the byproducts after oil palm fruitlet is removed in oil palm processing and is considered as waste. In this study, EFBOP was converted to biochar (BC-EFBOP) at 350-700 °C, with an overarching aim of determining the feasibility of adsorptive removal of manganese (a second dominant element in acid mine drainage) from water. Results showed that with increasing temperature, the BC-EFBOP yield decreased from 44.34% to 26.74%, along with the H/C (0.89%-0.29%) and O/C ratios (0.38%-0.23%), and the carbon content increased (62.7%-73.93%). As evidenced by Fourier Transform InfraRed spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS), abundant oxygen-containing surface functional groups such as hydroxyl (-OH), carboxyl (-COOH), and ether (C-O-C) were retained, and aromatic CC groups were largely generated in the biochar. Pyrolysed biochar at 350 °C (BC350), with the least surface area (0.5 m2 g-1), exhibited the highest Mn2+ adsorption capacity (8.2 mg g-1), whereas for BC700, with the largest surface area (2.19 m2 g-1), had the lowest capacity for Mn2+ (1.2 mg g-1). Regardless of the temperature, solution pH of 5 was found to be optimal for Mn2+ removal from water. The Langmuir isotherm model best described the equilibrium adsorption data with a maximum adsorption capacity of 1.2-8.2 mg g-1 for initial concentrations of 5-250 mg L-1, whereas the adsorption kinetics followed the pseudo-second-order model. There was nearly four-fold increase in Mn2+ ions removal with increased biochar dosage (0.05-0.5 g), at initial Mn2+ concentration of 100 mg L-1. The study showed that a low-cost, environmentally friendly BC-EFBOP with optimal surface chemistry could potentially remediate Mn2+ ions from aqueous media. However, a proper cost-benefit and techno-economic analysis is needed prior to potential pilot scale studies.

Acid mine drainage (AMD) is a well-recognized environmental issue associated with mining production worldwide. The second part of our study aims to assess the protective effect of using a polymer hard layer (PHL) by conducting sulphur-enriched tailing-based column experiments. An oxygen (O2) barrier was simulated using a designed column device filled with different types of tailings. All experimental columns underwent six drying-wetting cycles, and the chemical properties of the tailings and leachate were detected after every cycle. The permeability coefficient of the PHL was only 1.16 × 10- 5 cm/s. Over the entire experimental period, none of the leachates collected from column 4 using the PHL as an O2 barrier. Moreover, the level of redox potential and pH and the contents of heavy metals such as Cu and Zn were stable in PHL covering system. These results show that a PHL is the optimal covering system.

The ecological environment can be severely polluted and destroyed by the acid mine drainage (AMD) generated during the exploration and utilization of minerals. However, neutralized by carbonate rocks (a natural material in Karst regions), the AMD secondary iron flocs containing a large number of iron oxides or hydroxide can be precipitated in AMD. The metal ions, such as antimony (Sb) and arsenic (As), can be effectively removed by these neutralizing products. In this paper, the neutralization reaction of different acid solutions in an iron-antimony-arsenic system was induced by carbonate rocks to explore the removal effect of metals during this neutralization process. Meanwhile, taking the release amounts of iron (Fe), Sb, and As as well as the phase transformation of minerals at different pH levels as stability indexes, we quantitatively analyzed the chemical stability of AMD neutralizing products (secondary iron flocs) containing Sb and As under the typical acid-base environment (pH = 3.0 ~ 9.0) of AMD and other waters. Results showed that the neutralization reaction with carbonate rocks induced the co-precipitation of Fe with Sb and As. When the concentration ratio of Fe, Sb, and As was 30:1:1, the pH of AMD raised from 3.0 to 7.28 within 72 h, and the three elements were removed by 99%, 85%, and 90%, respectively. After soaking the AMD secondary iron flocs in an acid environment (pH = 3.0) for 30 days, the release amount of Fe reached its peak of 0.070 mg/g. Then, when the pH value increased to 4.0, the As and Sb showed their maximum release amounts of 14.90 µg/g and 19.19 µg/g, respectively. In addition, under acidic conditions, these AMD secondary iron flocs were easily transformed into the goethite with better crystallinity and higher structural stability. This study could help reveal the development of the secondary mineral during the treatment of AMD by carbonate rocks and understand the release characteristics of metals from AMD secondary products containing Sb and As, which sheds light on and provides theoretical foundations for the passive treatment of AMD containing these two elements in the future.

Combining environmental isotope analysis with principal component analysis can be an effective method to discriminate the inflows and sources of contamination in mining-affected watersheds. This paper presents a field-scale study conducted at an acid mine drainage (AMD)-contaminated site adjacent to a pyrite mine in South China. Samples of surface water and groundwater were collected to investigate transport in the vadose zone using stable isotopes of oxygen (δ18O) and hydrogen (δD) as environmental tracers. Principal component analysis of hydrogeochemical data was used to identify the probable sources of heavy metals in the AMD. The heavy metal pollution index (HPI) was applied to evaluate the pollution status of heavy metals in the groundwater. The groundwater associated with the Datai reservoir was recharged by atmospheric precipitation and surface water. On the side near the AMD pond, the groundwater was significantly affected by the soluble metals produced by pyrite oxidation. The concentrations of some metals (Al, Mn, and Pb) in all of the samples exceed the desirable limits prescribed by the World Health Organization (Guidelines for drinking-water quality, 4th edn. World Health Organization, Geneva, 2011). Among them, the concentration of Al is more than 30,000 times higher than the desirable limits prescribed by the World Health Organization (2011), and the concentration of Mn is more than 3000 times higher. The HPI values based on these heavy metal concentrations were found to be 10-1000 times higher than the critical pollution index value of 100. These findings provide a reference and guidance for research on the migration and evolution of heavy metals in vadose zone water in AMD-contaminated areas.

In Frongoch Mine (UK), it is unclear the distribution of metals on indigenous algae and whether these species of algae can accumulate metals. This study aimed to investigate the role of indigenous algae for metal removal from acid mine drainage and understand if metals can be adsorbed on the surface of algae or/and bioaccumulated in algae. A sequential extraction procedure was applied for algae samples collected from acid mine drainage (AMD) water to identify the forms in which metals are found in algae. Concentrations of Fe, Pb, Zn, Cu and Cd were evaluated in the algae and AMD samples were collected in June and October 2019. AMDs samples had a pH value ranging between 3.5 and 6.9 and high concentrations of Zn (351 mg/L) and Pb (4.22 mg/L) that exceeded the water quality standards (Water Framework Directive, 2015). Algae Ulothrix sp. and Oedogonium sp. were the two main species in the Frongoch AMDs. The concentrations of metals in algae ranged from 0.007 to 51 mg/g, and the bioconcentration factor of metals decreased in the following order: Fe >  > Pb >  > Cu > Cd > Zn. It was found that Zn, Cu and Cd were adsorbed onto the surface of and bioaccumulated in the algae, while Pb and Fe were mainly bioaccumulated in the algae. Indigenous algae can be considered as a biogeochemical barrier where metals are accumulating and can be used in bioremediation methods. Also, indigenous algae could be used as a bioindicator to assess water pollution at Frongoch Mine and other similar metal mines.

Heavy metal ions are widely recognized for their harmful effects on human health and the environment. Heavy metal ions removal using nanocomposite hydrogel is a promising method for industrial applications and process development owing to their utilization in both kinematic and dynamic adsorption process. There is a need to develop simple, low-cost water purification techniques that use biodegradable bio-based natural polymers like cellulose nanocrystal that have been modified with nanomaterials. These innovative functional cellulose nanocrystals-based nanomaterials have been shown to successfully remove a variety of contaminants from wastewater to acceptable levels. Due to their capacity to hold water in their porous structures, hydrogels are the most commonly used 3D polymer mesh materials for environmental remediation. The application of potential hydrogel for the absorption of Cu2+, Ni2+, Zn2+ and Cd2+ ions from an aqueous solution in a packed bed adsorption column was studied in this work. The adsorbent was studied using FTIR, SEM, XRD and TGA. The influence of breakthrough factors such as bed height (10, 17 and 25 cm) influent concentration (10, 20 and 50 mg/L) and the feed flow rate (10, 20 and 30 mL/min) was assessed. Bed Depth Service Time, Thomas and Yoon-Nelson models were used to fit the experimental data. With an increase in bed height, breakthrough and exhaustion time, the removal efficiency rose to 99.42 ± 0.12 for Cu2+, 99.23 ± 1.16 for Ni2+, 99.36 ± 0.89 for Cd2+ and 98.94 ± 0.48 for Zn2+, but declined with increased flow rate and influent concentration. Better performance was observed at a bed height of 25 cm, an influent metal ion concentration of 10 mg/L and a flow velocity of 10 mL/min. The BDST and Yoon-Nelson models were both successfully used to predict the breakthrough curves of heavy metal ions removal.

Acid mine drainage (AMD) is a serious and persistent environmental pollution problem. At present, many studies have focused on the tailings pond\'s cover systems. This paper introduced the research results of using tin tailings from Laili mountain to make the covering layer of tailings pond. The first part included a detailed description of tailings characterization and acid production potential. On this basis, the hard layer (HL) was prepared and its feasibility as oxidation barrier was evaluated. It was found that when the proportion of tailings waste was 70%, the immobilization efficiency of heavy metals can reach more than 99.45%, and the pH of leaching solution was about 10.8. Moreover, the beneficial effect of solid waste addition on the HL was also verified. This suggests that HL as a post-mining restorative strategy has strong positive influence on pollution control.