An emerging pollutant, diatrizoate (DTZ) has been frequently detected in aqueous solution. Unique reticular peanut shell biochar (BC)-supported nano zero-valent iron (nZVI) composite (nZVI/BC) was successfully synthesized and used as a catalyst for activating persulfate (PS) to promote the removal of DTZ. The structure and morphology of the nanocomposite materials were characterized by scanning electron microscopy, X-ray diffraction, Brunauer-Emmett-Teller measurements, and Fourier transform infrared spectroscopy. The degradation of DTZ (20 mg L⁻¹) was achieved by activating PS with the nanocomposite material. The removal of DTZ reached nearly 100% using 25 mM PS and 0.45 g L⁻¹ nZVI/2BC (mass ratio of nZVI and BC at 1:2) nanocomposite material at pH 3.0 and 25 °C. Influencing factors, such as dosages of nZVI/2BC and PS, temperature, and pH were also investigated. The mechanisms of PS activation with nZVI/2BC were discussed, including BC property, electron transfer, and the identification of free radicals in the reaction. The findings demonstrated that nZVI/BC-PS (peanut shell BC-supported nZVI activating PS) is a promising material for the treatment of refractory organic pollutants.

Organochlorine pesticides (OCPs) were typical persistent organic pollutants that posed great hazards and high risks in soil. In this study, a peanut shell biochar-loaded nano zero-valent iron (BC/nZVI) material was prepared in combination with soil indigenous microorganisms to enhance the degradation of α-hexachlorocyclohexane(α-HCH) and γ-hexachlorocyclohexane(γ-HCH) in water and soil. The effects of BC/nZVI on indigenous microorganisms in soil were investigated based on the changes in redox potential and dehydrogenase activity in the soil. The results showed as follows: (1) The specific surface area of peanut shell biochar loaded with nano-zero-valent iron was large, and the nano-zero-valent iron particles were evenly distributed on the peanut shell biochar; (2) peanut shell BC/nZVI had a good degradation effect on α-HCH and γ-HCH in water, with degradation rates of 64.18% for α-HCH and 91.87% for γ-HCH in 24 h; (3) peanut shell BC/nZVI also had a good degradation effect on α-HCH and γ-HCH in soil, and the degradation rates of α-HCH and γ-HCH in the 1% BC/nZVI reached 55.2% and 85.4%, second only to 1% zero-valent iron. The degradation rate was the fastest from 0 to 7 days, while the soil oxidation-reduction potential (ORP) increased sharply. (4) The addition of BC/nZVI to the soil resulted in a significant increase in dehydrogenase activity, which further promoted the degradation of HCHs; the amount of HCHs degradation was significantly negatively correlated with dehydrogenase activity. This study provides a remediation strategy for HCH-contaminated sites, reducing the human health risk of HCHs in the soil while helping to improve the soil and increase the activity of soil microorganisms.

Heavy metals in the ocean exist in various media and assessing heavy metal pollution in the multimedia in seawater is important for proposing effective strategies to protect marine ecosystem health. However, comprehensive coastal pollution assessments and SSD-based assessments of heavy metals have been limited from an international perspective. This study discusses the distribution, sources, interactions, associated environmental factors, and potential ecological risks related to heavy metal pollution. To attain this objective, several tools and models were considered. The partition coefficient between sediment and water was used to understand the ability of heavy metals to be adsorbed from seawater by sediment. The water quality index was applied to evaluate the comprehensive heavy metal pollution at different sampling sites. The species diversity index was calculated by calculating the concentration of chlorophyll a. The geo-accumulation and potential ecological risk indexes were employed for the sediments’ general pollution characteristic of heavy metals. Species sensitivity distribution was used for ecological risk evaluation. The results indicated that heavy metal pollution and ecological risk (Cu, Pb, Zn, Cd, As, Cr and Hg) are not serious, and the pollution conditions remain safe. Only Cu, Pb, and Hg concentrations in seawater exceed the Nation Class I Water Quality Standard. The concentrations of heavy metals showed significant spatial characteristics. Fisheries activities and industrial effluent discharges were identified as the main anthropogenic sources. This study provides a comprehensive assessment of heavy metals in multi-media, and the results will provide valuable information for nearshore ecological management and risk avoidance.

Environmental magnetism parameters have become a useful tool in addressing environmental issues. Due to the rapid, sensitive, economical and non-destructive characteristics of environmental magnetism, the present contribution focuses on magnetism parameters as proxy for heavy metal pollution, especially from their relationship with contents of heavy metal. We evaluated heavy metals pollution and examined environmental magnetism in the Dexing section of the Le’an River. The pollution load index (PLI) of Cr, Pb, As, Cu and Zn, as well as the concentration of other heavy metals, were analyzed, and the magnetic indexes of various sediments were analyzed. The results showed that the concentrations of all heavy metals far exceeded the local background values, and that the average contamination factor of Cu was as high as 22.88, making it the element of most serious contamination. The problem of heavy metal pollution near the mine is very serious. The content of magnetic minerals in sediments of Le’an River is relatively high and the composition of magnetic minerals is relatively stable. The stable-single domin (SSD) content is high at S1 and S10, indicating that ferromagnetic mineral content is relatively rich here, which dominates the magnetic characteristics of the sample. In general, it was found that environmental magnetism indicators did not exist in the Dexing section of the Le’an River that could clearly indicate the concentration of heavy metal pollution. Only a few heavy metals can be effectively indicated by magnetic parameters. IRM_-20mT and S_-ratio can be used as indicators of Cr, Pb, As, Cu and Zn, but they are not accurate. The correlation between Sr and magnetic indexes IRM_200mT, IRM_300mT, SIRM, IRM_-300mT and HIRM is significant, which can be used as an indicator of Sr concentration. IRM_20mT can also be used as an indicator of Hg concentration.

In this study, a modified fir barks (MFB) was prepared by mixing fir barks (FB) and white-rot fungi (Phanerodontia chrysosporium) under aerobic fermentation. The potential of MFB for Cd2+ adsorption was investigated by batch experiments combined with kinetic, isotherm, and thermodynamics analyses. The results revealed that the modification greatly increased the porous structures on the surfaces of fir barks and the surface area of MFB was much higher than that of FB. As a result, the adsorption capacity of Cd2+ on MFB (17.4 mg g-1) was more than two times higher than that on FB (7.2 mg g-1), and the adsorption of Cd2+ on MFB was controlled by physisorption and chemisorption. The immobilization of Cd by MFB in a contaminated agricultural soil was also investigated. The effect of MFB on the bioavailability of Cd was investigated using a leaching test (the European standard EN 12457-2) combined with a typical sequential extraction procedure (the community bureau of reference, BCR). The experimental results showed that the Cd leachability was reduced by 71% when the added MFB dosage was 30 mg g-1. Besides, the MFB amendment could transform Cd from unstable geochemical fractions into more stable fractions. In total, the MFB, as a chemical-free and eco-friendly material, could be potentially employed for in-situ remediation of Cd-contaminated agricultural soils.

Groundwater nitrate (NO₃⁻) pollution is a critical environmental challenge with direct implications for human health. In this work, we propose a comprehensive analytical framework that integrates multi-model intercomparison, interpretable machine learning techniques, and quantitative health risk evaluation to tackle the pressing groundwater nitrate governance dilemmas in Handan City, a representative urban area in North China. Based on 157 groundwater samples and 17 hydrochemical parameters, comparative analysis of three state-of-the-art machine learning algorithms showed that the Light Gradient Boosting Machine (LightGBM) algorithm outperformed all counterparts, delivering the optimal predictive performance (R² = 0.753, RMSE = 3.67). SHapley Additive exPlanations (SHAP) analysis identified F⁻, Ca²⁺, Cl⁻, K⁺, total hardness, and Mg²⁺ as dominant factors influencing groundwater NO₃⁻ concentrations, reflecting the combined effects of carbonate dissolution, nitrification, and anthropogenic inputs. Subsequently, we performed a health risk assessment based on the standard methodological framework issued by the United States Environmental Protection Agency (USEPA), and the results indicated that children were the most vulnerable group, with hazard quotient (HQ, a non-carcinogenic risk indicator) values reaching 1.07 in the western mountainous region, exceeding the safety threshold (HQ > 1). These findings clarify the pollution mechanisms and spatial heterogeneity, and provide targeted policy guidance for groundwater protection as well as the safeguarding of public health.