Soil-heavy metal pollution in mining areas is one of the problems in the comprehensive treatment of soil environmental pollution. To explore the degree of soil-heavy metal pollution and the human health risk in mining areas, the contents of soil As, Cd, Cu, Cr, Hg, Ni, Pb, and Cr(VI) in an abandoned gold mining area were determined. The geoaccumulation index (I_geo), single-factor pollution index (SPI), Nemerow comprehensive pollution index (NCPI), potential ecological risk index (PERI), and the human health risk assessment model were used to assess the pollution degree and the risk of soil-heavy metal pollution. Finally, the assessment results were used to provide remediation guidance. The results showed that (1) the average contents of As, Cd, Cr, Cu, Hg, and Ni in the mining area exceeded the background values of the soil elements. (2) The mining area was polluted by heavy metals to different degrees and had strong potential ecological hazards. (3) The total carcinogenic risk of heavy metals exceeded the health risk standard. The main components of pollution in the mining area were As, Cd, Cr, and Hg. Results from this study are expected to play a positive role in pollution treatment and the balance between humans and ecology.

Activated carbon can be applied to the treatment of wastewater loading with different types of pollutants. In this paper, a kind of activated carbon in granular form (GAC) was utilized to eliminate antibiotics from an aqueous solution, in which Tetracycline (TC), Thiamphenicol (THI), and Sulfamethoxazole (SMZ) were selected as the testing pollutants. The specific surface area, total pore volume, and micropore volume of GAC were 1059.011 m²/g, 0.625 cm³/g, and 0.488 cm³/g, respectively. The sorption capacity of GAC towards TC, THI, and SMZ was evaluated based on the adsorption kinetics and isotherm. It was found that the pseudo-second-order kinetic model described the sorption of TC, THI, and SMZ on GAC better than the pseudo-first-order kinetic model. According to the Langmuir isotherm model, the maximum adsorption capacity of GAC towards TC, THI, and SMZ was calculated to be 17.02, 30.40, and 26.77 mg/g, respectively. Thermodynamic parameters of ΔG⁰, ΔS⁰, and ΔH⁰ were obtained, indicating that all the sorptions were spontaneous and exothermic in nature. These results provided a knowledge base on using activated carbon to remove TC, THI, and SMZ from water.

Ground-penetrating radar (GPR) is an efficient and nondestructive geophysical method with great potential for detecting soil water content at the farmland scale. However, a key challenge in soil detection is obtaining soil water content rapidly and in real-time. In recent years, deep learning methods have become more widespread in the earth sciences, making it possible to use them for soil water content inversion from GPR data. In this paper, we propose a neural network framework GPRSW based on deep learning of GPR data. GPRSW is an end-to-end network that directly inverts volumetric soil water content (VSWC) through single-channel GPR data. Synthetic experiments show that GPRSW accurately identifies different VSWC boundaries in the model in time depth. The predicted VSWC and model fit well within 40 ns, with a maximum error after 40 ns of less than 0.10 cm³ × cm⁻³. To validate our method, we conducted GPR measurements at the experimental field of the Academy of Agricultural Sciences in Gongzhuling City, Jilin Province and applied GPRSW to VSWC measurements. The results show that predicted values of GPRSW match with field soil samples and are consistent with the overall trend of the TDR soil probe samples, with a maximum difference not exceeding 0.03 cm³ × cm⁻³. Therefore, our study shows that GPRSW has the potential to be applied to obtain soil water content from GPR data on farmland.

A novel, accurate, and precise method is described for simultaneous determination of trace lead (Pb), tin (Sn) and cadmium (Cd) in biological samples by chemical vapor generation (CVG) coupled with non-dispersive atomic fluorescence spectrometry. A chemical vapor generation dual gas–liquid separator system for Pb, Sn and Cd determination assembled with atomic fluorescence spectrometry was proposed. The system consists of two peristaltic pumps as the liquid driver, two gas–liquid separators and an atomic fluorescence detector. In the first gas–liquid separator system, the main Cd vapor and some SnH₄ were carried out with reductant solution I, and in the second gas–liquid separator system, the main PbH₄ and some SnH₄ were carried out with reductant solution II. Cadmium vapor generation was based on hydrochloric acid, cobalt chloride, thiourea and KBH₄ concentrations of the first system, SnH₄ generation was based on hydrochloric acid and KBH₄ concentrations, and PbH₄ was based on hydrochloric acid, potassium ferricyanide and KBH₄ concentrations of the second system. The operating conditions of the instrumentation were optimized, including the flow rates of carrier and shield gas. The conditions of chemical vapor generation for Pb, Sn and Cd were studied in detail. Under optimized experimental conditions, the blank signal was satisfactorily minimized, giving limits of detection of 0.071, 0.058 and 0.002 ng ml⁻¹ for Pb, Sn and Cd respectively. The relative standard deviation (R.S.D.) was respectively 1.3%, 3.4% and 2.9% for 10 ng ml⁻¹ of Pb, Sn and 2 ng ml⁻¹ of Cd (n = 7). Finally, the proposed method was successfully applied to the simultaneous determination of Pb, Sn and Cd in a series of Chinese certified biological reference materials using simple aqueous standard calibration techniques, with analytical results in good agreement with the certified values.