Nanoscale zero-valent iron particles (NZVI) produced by using green tea (GT) extract as a reductant can remove Cr(VI) from water effectively, which can be utilized in groundwater remediation. In order to define the reaction mechanism and removal effect in the aquifer, in this study, GT-NZVI particles were prepared and measured by some characterization methods to define their surface performance, and then batch and one-dimensional experiments were carried out to reveal the reaction properties of GT-NZVI and Cr(VI) in groundwater. The results showed that the prepared GT-NZVI particles were regular spherical with a diameter of 10–20 nm, which could disperse in water stably. The main component of GT-NZVI was α-Fe with superficial polyphenols as a stabilizer. GT-NZVI suspension had good ability to reduce the Cr(VI) to Cr(III) in water. When the concentration of GT-NZVI was 1 g/L, the removal efficiency of Cr(VI) with an initial concentration of 100 mg/L reached 92.8% in 1 h reaction. In column tests, GT-NZVI passed through the natural sand column successfully with an average outflow percentage of 71.2%. The simulated in-situ reaction zone (IRZ) with GT-NZVI was used to remediate Cr(VI) contaminated groundwater. The outflow concentration of Cr(VI) kept in 0.14–0.32 mg/L corresponding to the outflow rate below 0.32% within 15 days, and the removal efficiency of Cr(VI) by IRZ with GT-NZVI decreased with the increase of aquifer medium particle size, groundwater flow rate and ionic strength. Most of Cr(III) as reduzate was adsorbed or immobilized on the surface or in the lattice of GT-NZVI, which indicated effective immobilization for chromium.

In situ injection of Fe(II)-activated persulfate was carried out to oxidize chlorinated hydrocarbons and benzene, toluene, ethylbenzene, and xylene (BTEX) in groundwater in a contaminated site in North China Plain. To confirm the degradation of contaminants, an oxidant mixture of persulfate, ferrous sulfate, and citric acid was mixed with the main contaminants including 1,2,3-trichloropropane (TCP) and benzene before field demonstration. Then the mixed oxidant solution of 6 m³ was injected into an aquifer with two different depths of 8 and 15 m to oxidize a high concentration of TCP, other kinds of chlorinated hydrocarbons, and BTEX. In laboratory tests, the removal efficiency of TCP reached 61.4% in 24 h without other contaminants but the removal rate was decreased by the presence of benzene. Organic matter also reduced the TCP degradation rate and the removal efficiency was only 8.3% in 24 h. In the field test, as the solution was injected, the oxidation reaction occurred immediately, accompanied by a sharp increase of oxidation–reduction potential (ORP) and a decrease in pH. Though the concentration of pollutants increased due to the dissolution of non-aqueous phase liquid (NAPL) at the initial stage, BTEX could still be effectively degraded in subsequent time by persulfate in both aquifers, and their removal efficiency approached 100%. However, chlorinated hydrocarbon was relatively difficult to degrade, especially TCP, which had a relatively higher initial concentration, only had a removal efficiency of 30%–45% at different aquifers and monitoring wells. These finding are important for the development of injection technology for chlorinated hydrocarbon and BTEX contaminated site remediation.

Previous studies have mostly focused on the adsorption behavior of microplastics for antibiotics in soil or aqueous environments. This study explores the adsorption characteristics of microplastics for antibiotics under groundwater environmental conditions and the influence of typical influencing factors of the groundwater environment (pH, pollutant concentration, aquifer media, dissolved organic matter, and ionic strength) on the adsorption process. Polyethylene (PE) and tetracycline (TC) were selected as typical microplastics and antibiotics in the experiment. The study results showed that the adsorption of TC by PE reached equilibrium at 48 h, and the adsorption kinetics fitted pseudo-second-order kinetics models well. The adsorption isotherm was consistent with the Langmuir model. The adsorption capacity of PE for TC was highest under neutral conditions and positively correlated with the initial concentration of TC. The aquifer media exhibited limited effects on the adsorption process. Fulvic acid (FA) significantly suppressed TC adsorption onto PE, attributable to competitive adsorption mechanisms. TC adsorption on PE initially increased then declined with Ca²⁺ concentration due to Ca²⁺ bridging and competition. This research elucidates the adsorption mechanisms of PE towards TC, providing theoretical basis and reference for assessing the environmental risk of microplastics and antibiotics in groundwater.

To determine the competitive adsorption characteristics and influencing factors of chlorinated and aromatic hydrocarbons on the aquifer medium, toluene, benzene, 1,2−dichloropropane, and 1,2,3−trichloropropane (TCP) were selected as typical pollutants for adsorption tests. The results showed that the adsorption process of pollutants on the aquifer medium conformed to the first−order kinetic and Henry linear model equation, and the adsorption capacity decreased in the order of toluene, benzene, 1,2−dichloropropane, and TCP. Benzene promoted the adsorption of toluene on the aquifer medium, while toluene reduced the adsorption of benzene conversely. 1,2−dichloropropane restrained the adsorption of TCP, and TCP had no significant effect on the adsorption of 1,2−dichloropropane. The adsorption capacity of TCP on the aquifer increased with the concentration of toluene. TCP acted as a stimulus for the adsorption of toluene when the initial concentration of toluene was lower than 2 mg/L. In contrast, TCP served as an inhibitor for the adsorption of toluene on the aquifer medium. Furthermore, the adsorption of all pollutants increased with decreasing medium size. The promotion rates for aromatic and chlorinated hydrocarbons were 7.2~41.1% and 2.7~27.1%, suggesting that the promotion effect on aromatic hydrocarbons was stronger than that on chlorinated hydrocarbons. Natural organic matter (NOM) inhibited the adsorption of pollutants on the aquifer medium (especially for high concentrations of chlorinated hydrocarbons), and the adsorption rate increased by more than 60% when OM decreased from 0.25% to 0.08%. Clay minerals improved the adsorption of organic pollutants in different compound pollution systems, and montmorillonite exhibited a stronger promoting effect than kaolin.

Investigating the spatial distribution of chromium (Cr) in soil is essential for understanding Cr pollution and accurately assessing associated environmental risks. However, field sampling is challenging due to limited sampling points, and the spatial distribution of Cr is affected by multiple complex environmental covariates, thereby restricting model development and prediction accuracy. This study selected the Chizhou–Xuancheng border area in southern Anhui Province as the research region and collected 2035 data points. Machine learning models, including AdaBoost, GBDT, XGBoost, and MLP, were employed to predict Cr concentrations in conjunction with environmental covariates. To address the challenges of sparse sampling data and complex data relationships for Cr prediction, the PHMS-Transformer model is proposed. Featuring a shallow encoder design, configurable pooling strategies, and a lightweight structure, the model significantly reduces the number of parameters and alleviates overfitting under sparse sampling conditions, while the incorporation of multi-head self-attention mechanisms captures complex nonlinear relationships among multi-source environmental variables relevant to Cr. To further enhance model interpretability for Cr prediction, the SHAP model was applied to identify key factors influencing Cr distribution. Comprehensive comparisons indicate that the PHMS-Transformer model achieves superior performance in predicting Cr, demonstrating high accuracy and generalization capability, with clear advantages over traditional methods. These findings offer valuable insights for soil environmental protection and Cr pollution control and possess significant theoretical and practical implications. Soil Cr pollution represents a global environmental challenge, where achieving accurate predictions for Cr is particularly crucial yet difficult in regions with constrained data accessibility. The lightweight, high-precision, and interpretable PHMS-Transformer framework proposed in this study provides an effective technical solution to the widespread challenges of sample sparsity and model complexity inherent in predicting the spatial distribution of soil Cr globally. Therefore, this work offers significant reference value for advancing global soil environmental risk assessment and Cr pollution remediation efforts.