To investigate the effects of biogas slurry return-to-field methods, the duration of biogas slurry return to field and the amount of heavy metals brought in from biogas slurry on the accumulation of heavy metals in soil-crop systems, and the importance of factors influencing heavy metal accumulation, 41 papers and 1972 pairs of data were integrated and analyzed. The results showed that the application of biogas slurry alone significantly increased the accumulation of As, Cd, Cr, Cu, and Zn in soil and As and Cr in crops by 20.5%, 15.2%, 25.6%, 18.7%, and 26.3% and 14.6% and 39.5%, respectively, and it had no significant effect on the accumulation of other heavy metals in crops. The combined application of biogas slurry and chemical fertilizers significantly increased the accumulation of soil Cr and Zn by 8.05% and 4.70% and decreased the accumulation of As by crops. Correlation analysis showed that the accumulation rates of soil As, Cd, and Cr were highly significantly and positively correlated (P<0.01) with the duration of biogas slurry return to field and soil organic matter (SOM) content, with correlation coefficients of 0.30, 0.15, and 0.13 and 0.22, 0.27, and 0.22, respectively; they were highly significantly and negatively correlated (P<0.01) with soil pH, with correlation coefficients of 0.16, 0.13, and 0.11, respectively. The heavy metals brought in by biogas slurry return to field promoted the accumulation of As, Cd, and Cr in soil and As, Cd, Cr, and Zn in crops, whereas the accumulation of Cd, Cu, and Zn in soil promoted the accumulation of Cd, Cu, and Zn in crops, with correlation coefficients of 0.45, 0.58, and 0.42, respectively. The main factors of heavy metal accumulation in the soil-crop systems were the duration of biogas slurry return to field, SOM, and soil pH.
Biofuels , Metals, Heavy , Cadmium , Crops, Agricultural , Soil
To determine the risk state distribution, risk level, and risk evolution situation of agricultural non-point source pollution (AGNPS), we built an 'Input-Translate-Output' three-dimensional evaluation (ITO3dE) model that involved 12 factors under the support of GIS and analyzed the spatiotemporal evolution characteristics of AGNPS risks from 2005 to 2015 in Chongqing by using GIS space matrix, kernel density analysis, and Getis-Ord Gi* analysis. Land use changes during the 10 years had a certain influence on the AGNPS risk. The risk values in 2005, 2010, and 2015 were in the ranges of 0.40-2.28, 0.41-2.57, and 0.41-2.28, respectively, with the main distribution regions being the western regions of Chongqing (Dazu, Jiangjin, etc.) and other counties such as Dianjiang, Liangping, Kaizhou, Wanzhou, and Zhongxian. The spatiotemporal transition matrix could well exhibit the risk transition situation, and the risks generally showed no changes over time. The proportions of 'no-risk no-change', 'low-risk no-change', and 'medium-risk no-change' were 10.86%, 33.42%, and 17.25%, respectively, accounting for 61.53% of the coverage area of Chongqing. The proportions of risk increase, risk decline, and risk fluctuation were 13.45%, 17.66%, and 7.36%, respectively. Kernel density analysis was suitable to explore high-risk gathering areas. The peak values of kernel density in the three periods were around 1110, suggesting that the maximum gathering degree of medium-risk pattern spots basically showed no changes, but the spatial positions of high-risk gathering areas somehow changed. Getis-Ord Gi* analysis was suitable to explore the relationships between hot and cold spots. Counties with high pollution risks were Yongchuan, Shapingba, Dianjiang, Liangping, northwestern Fengdu, and Zhongxian, while counties with low risks were Chengkou, Wuxi, Wushan, Pengshui, and Rongchang. High-value hot spot zones gradually dominated in the northeast of Chongqing, while low-value cold spot zones gradually dominated in the Midwest. Our results provide a scientific base for the development of strategies to prevent and control AGNPS in Chongqing.
Zeolites have been widely applied in soil improvement and environment protection. The study on ion specificity during ion exchange equilibrium is of important significance for better use of zeolites. The maximum adsorption capacities of alkali ions during ion exchange equilibrium in the clinoptilolite showed obvious specificity. For alkali metal ions with equivalent valence, the differences in adsorption capacity increased with the decrease of ionic concentration. These results cannot be well explained by the classical theories including coulomb force, ionic size, hydration, dispersion force, classic induction force and surface complexation. We found that the coupling of polarization effects resulted from the quantum fluctuation of diverse alkali metal ions and electric field near the zeolite surface should be the primary reason for specific ion effect during ion exchange in zeolite. The result of this coupling effect was that the difference in the ion dipole moment increased with the increase of surface potential, which further expanded the difference in the adsorption ability between zeolite surface and ions, resulting in different ion exchange adsorption ability at the solid/liquid interface. Due to the high surface charge density of zeolite, ionic size also played an important role in the distribution of ions in the double diffuse layer, which led to an interesting result that distinct differences in exchange adsorption ability of various alkali metal ions were only detected at high surface potential (the absolute value was greater than 0.2 V), which was different from the ion exchange equilibrium result on the surface with low charge density.
Ions , Zeolites/chemistry , Adsorption , Environmental Restoration and Remediation/methods , Ion Exchange , Metals , Sensitivity and Specificity , Soil/chemistry
