Boron is a special pollutant. Because of its relatively small molecular weight, it can freely penetrate the reverse osmosis membrane in the same way that water molecules can in reverse osmosis during seawater desalination, which affects the effluent quality of desalinated seawater. In this study, a new magnetic adsorption material, MNP-NMDG, was synthesized by combining magnetic nanoparticles (MNPs) of Fe3O4 with N-methyl-d-glucamine with a high selectivity to boron, and MNP-NMDG was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD). The adsorption properties of the MNP-NMDG for boron during seawater desalination under static and dynamic conditions was studied from the aspects of pH, adsorbent dosage, adsorption kinetics, and isotherms. The results showed that according to the breakthrough curve of dynamic adsorption, MNP-NMDG had a high boron-adsorption capacity, and the static adsorption capacity was 9.21 mg/g. The adsorption performance was the best at pH = 9, and the adsorption equilibrium was achieved within 40 min. Boron adsorption conformed to the Freundlich adsorption isotherm and to the pseudo-second-order kinetic model. This composite material not only provides an effective and rapid way to remove boron from desalinated seawater, but also has a shorter removal time and makes it more easily separated using the external magnetic field.

Affected by excessive fertilizer application and livestock breeding, the problem of nitrate pollution in the groundwater in the Mihe alluvial–diluvial fan area is becoming increasingly prominent, which poses a great threat to human production and life. Given this, the risk of nitrate pollution in the shallow groundwater of the Mihe alluvial–diluvial fan is evaluated by introducing a data envelopment analysis (DEA) method. Using this model, 28 groundwater sampling points are selected as the decision-making unit (DMU); the nitrogen and pesticide application rate, livestock and poultry stock, groundwater burial depth, aquifer water abundance, and vegetable planting area are taken as the model input; and the nitrate content is taken as the model output to quantitatively calculate the pollution risk index to form a spatial distribution map of pollution risk. The calculation using the model shows that the average pollution risk index of the study area is 0.382, the spatial variation is 1.12, the pollution risk index gradually decreases from south to north, and agricultural planting and livestock and poultry breeding are the main pollution sources. The calculation of nitrate pollution risk using this model not only enriches the nitrate pollution evaluation model but also provides a basis for further implementing the action of reducing fertilizer use by increasing its efficiency and strengthening the prevention of agricultural diffused pollution.

Surface water and groundwater (SW-GW) are an inseparable whole, having a tightly coupled hydraulic relationship and frequent inter-transformation. As such, the quantitative calculation of water exchange between SW-GW is a difficult challenge. To address this issue, we propose the use of a physically based and distributed hydrological model, called WEP-L, in order to analyze the effects of the SW-GW interaction and its spatiotemporal variation characteristics in the Xiaoqing River basin. We demonstrate that the SW-GW interaction is significantly affected by season. The simulated annual average exchange volume of SW-GW above the control section of Huangtaiqiao Station from 1980 to 2020 is found to be 54.79 m3/s. The exchange volumes of SW-GW in the wet and dry season are 28.69 m3/s and 13.46 m3/s, respectively, accounting for 48.75% and 22.87% of the whole year. In addition, considering two types of climate change scenarios, the exchange capacity of SW-GW increases by 0.42m3/s when the rainfall increases by 5%, while the exchange capacity decreases by only 0.2 m3/s when the temperature increases by 0.2 °C. This study provides insights for the quantification of the SW-GW interaction at the regional scale, which will benefit our understanding of the water cycle and evolution of water resources in Xiaoqing River basin.

The understanding of solute transport in rock fractures is of great importance in many engineering fields. In this study, two groups of experiments on artificial and natural single fractures with different fracture apertures and roughness were conducted to investigate the changes of solute transport regimes. The time fractional advection–dispersion equation (tFADE) as a promising model was applied to describe the anomalous transport. The performance of the classical advection-dispersion equation (ADE) and tFADE was compared according to the fitting precision of breakthrough curves (BTCs). The responses of the fitting parameters in the tFADE to the experimental conditions were also discussed. The results indicated that the non-Fickian transport more likely occurred in the short distance transport, and the larger Peclet number ( Pe ) led to the increase of the exponent of the power-law function in the phase of concentration decline. The tFADE was superior to ADE in capturing the non-Fickian transport especially the tailing behavior. The fractional order of time α in the tFADE was the key parameter to describe the anomalous transport process, and its responding mechanisms of were revealed: the best-fit α decreased with the increase of flow velocity and the decrease of the fracture aperture. The roughness of the single fracture which leads to a complex flow field had a significant effect on the best-fit α . The findings of this study can help for better understanding the effectiveness and physical significance of the tFADE.