Huangshui River (HSR) is the mother river of Qinghai province. Croplands and grasslands cover more than 76% of the total area, and highland agriculture and animal husbandry are the dominant industries. The use of pesticides, fertilizers, and feed additives increases the risk of heavy metal (HM) contamination. In this study, the concentration of HMs in the main stream and tributaries of HSR were investigated. The Positive Matrix Factorization model was used for source apportionment, and Health Risk Assessment method was used to assess the human health risks. To further analyze the effect of agriculture and animal husbandry on aquatic environment and human health, we considered agriculture and animal husbandry as two factors in the source apportionment process, defined the effect of the factors, established the calculation formula, and quantified the effects. The results show that the overall situation of aquatic environment in HSR is good; natural processes, traffic tail gas and atmospheric deposition, agricultural planting, industrial wastewater discharge, and animal husbandry are the main sources of HMs in the water. These HMs present noncarcinogenic and carcinogenic risks for infants. A total effect of agricultural and animal husbandry on HMs or HI in HSRB is approximately 20%, while on TCR is 40%. However, the effects of agriculture on the hazard quotient of arsenic, carcinogenic risk of nickel and lead, and that of animal husbandry on carcinogenic risk of cadmium were significant. This study can provide a theoretical basis for local managers of agriculture and animal husbandry to perform their work effectively.

To overcome the negative impact on the rheological and filtration loss properties of drilling fluids caused by elevated temperature and salts contamination, which are common in ultradeep or geothermal drilling operations, it is imperative to develop highly efficient additives used in the water-based drilling fluid. In this study, a zwitterionic copolymer P (AM/DMC/AMPS/DMAM, ADAD) was synthesized by using acrylamide (AM), cationic monomer methacrylatoethyl trimethyl ammonium chloride (DMC), anionic monomer 2-acrylamide-2-methyl propane sulfonic acid (AMPS), and N,N-dimethylacrylamide (DMAM) through free radical copolymerization. The copolymer was characterized by ¹H Nuclear Magnetic Resonance (NMR), Fourier transform infrared spectroscopy (FTIR), elemental analysis, thermogravimetric analysis (TGA), and zeta potential. The rheological behavior, filtration properties, and the performance exposure to salt or calcium contamination in water-based drilling fluid were investigated. The bentonite/polymer suspension showed improved rheological and filtration properties even after aging at 160 °C or a high concentration of salt and calcium. The filtration loss can be greatly reduced by more than 50% (from 18 mL to 7 mL) by the inclusion of 2.0 wt% copolymer, while a slight increase in the filtrate loss was observed even when exposed to electrolyte contamination. Particle size distribution and zeta potential further validate the idea that zwitterionic copolymer can greatly improve the stability of base fluid suspension through positive group enhanced anchoring on the clay surface and repulsion force between negative particles. Moreover, this study can be directed towards the design and application of zwitterionic copolymer in a water-based drilling fluid.

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation.

In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based on the laws of reflection in geometric optics, model of GNSS signal-to-noise (SNR) observation for the tilt surface, which results from differential subsidence of ground points, is derived. Semi-cycle SNR observations fitting method is used to determine the phase of the SNR series. Phase variation of the SNR series is used to calculate reflector height of ground specular reflection point. Based on the reflector height and ground tilt angle, an iterative algorithm is proposed to determine coefficients of PIM, and thus subsidence of the ground reflection point. By using the low-cost navigational GNSS receiver and antenna, an experimental campaign was conducted to validate the proposed method. The results show that, when the maximum subsidence is 3076 mm, the maximum relative error of the proposed method-based subsidence estimation is 5.5%. This study also suggests that, based on the proposed method, the navigational GNSS instrument can be treated as a new type of sensor for continuously measuring ground subsidence deformation in a cost-effective way.

For deep underground coal mining ecosystems, research on microbial communities and geochemical characteristics of sediments in different functional zones is lacking, resulting in the knowledge of zone-level mine water pollution prevention and control being narrow. In this study, we surveyed the geochemical distinctions and microbial communities of five typical functional zones in a representative North China coalfield, Xinjulong coal mine. The data indicated that the geochemical compounds and microbial communities of sediments showed distinguishing features in each zone. The microbial community richness and diversity were ranked as follows: surface water > rock roadways > sumps > coal roadways ≥ goafs. Canonical Correlation Analysis (CCA), Spearman correlation and co-occurrence network analysis demonstrated that microbial communities were sensitive and closely related to hydrochemical processes. The microbial community distribution in the underground mine was closely related not only to nutrient elements (i.e., C, S, P and N), but also to redox-sensitive substances (i.e., Fe and As). When it comes to mine water pollution prevention and control, the central zones are goafs. With the increase in goaf closure time, total nitrogen (TN), total organic carbon (TOC) and total sulfur (TS) decreased, but As, Fe and total phosphorus (TP) gradually increased, and the characteristic pollutant SO₄²⁻ concentration in water samples decreased. Additionally, the sulfate-reducing bacteria (SRB) had relatively higher proportions in goafs, suggesting goafs were able to purify themselves. In practical engineering, in situ nitrogen injection technology used to expel oxygen and create an anaerobic environment can be implemented to enhance SRB reducing sulfate in goafs. Meanwhile, because coal mine pollution discharge generally only discharges mine water and leaves sediment underground, the pollutants can be transferred to the sediment by strengthening the relevant reactions including the heavy metal solidification and stabilization function of bacteria.