Connotation, status, and governance of land ecological security in China's new urbanization: recent advances and future prospects.

The rapid development of China's new urbanization has created favorable conditions for economic growth and social development. Urbanization includes population urbanization and land urbanization, among which land urbanization leads to land ecological security problems. At present, there is a lack of comprehensive understanding of land ecological security in China's new urbanization construction. This paper aims to fill the gap by systematically combing relevant literature on the connotation, status, and governance of land ecological security in China's new urbanization. Literature review shows that China's land ecological security is still at a low level, and the new urbanization construction has significant impacts on land ecological security. Land contamination is the most critical factor threatening land ecological security, and there are differences in the levels of land contamination and types of pollutants in different new urbanization construction forms. According to an example of land ecological security governance with enterprises as the main body and multiple subjects cooperating, the governance of land ecological security needs to integrate a variety of different subjects to coordinate governance. Future research directions should focus on the construction of land ecological security assessment index system, development of land contamination multi-level control technology, and construction of multi-subject collaborative governance model with "government-enterprise-social organization-residents."

Human health risk assessment of groundwater arsenic contamination in Jinghui irrigation district, China.

The groundwater is an important route of human exposure to kinds of contaminants. This study was carried out to investigate the occurrence and spatial distribution of groundwater arsenic in the Jinghui irrigation district in Shaanxi Province, China. The water contamination was assessed for drinking purposes by comparing it to national guidelines, and the impacts of arsenic on human health were quantified using the health risk assessment model recommended by the USEPA. The results show that the concentration of groundwater arsenic ranges from 0.0012 to 0.0190 mg/L (average 0.0054 mg/L), and 2.58% of groundwater exceed the national guidelines of 0.01 mg/L for drinking. The carcinogenic risk of arsenic affecting adults has reached 3.50 × 10-4, significantly exceeding the national guideline (1.00 × 10-4.) The health risks resulting from oral exposure are higher than those of dermal exposure. The carcinogenic risk for adults is higher than that for children, while the non-carcinogenic risk for children is higher than that for adults. The area ratio of the carcinogenic risk is 42.82%, and the area of the non-carcinogenic risk is 69.19%. Groundwater arsenic mainly originates from the discharge of industrial wastewater and the slowly release of natural sediments. The results of this study can help to set up suitable management strategies to guarantee water supply and health safety for local residents.

Assessment of Landslide Susceptibility Using Integrated Ensemble Fractal Dimension with Kernel Logistic Regression Model.

The main aim of this study was to compare and evaluate the performance of fractal dimension as input data in the landslide susceptibility mapping of the Baota District, Yan'an City, China. First, a total of 632 points, including 316 landslide points and 316 non-landslide points, were located in the landslide inventory map. All points were divided into two parts according to the ratio of 70%:30%, with 70% (442) of the points used as the training dataset to train the models, and the remaining, namely the validation dataset, applied for validation. Second, 13 predisposing factors, including slope aspect, slope angle, altitude, lithology, mean annual precipitation (MAP), distance to rivers, distance to faults, distance to roads, normalized differential vegetation index (NDVI), topographic wetness index (TWI), plan curvature, profile curvature, and terrain roughness index (TRI), were selected. Then, the original numerical data, box-counting dimension, and correlation dimension corresponding to each predisposing factor were calculated to generate the input data and build three classification models, namely the kernel logistic regression model (KLR), kernel logistic regression based on box-counting dimension model (KLRbox-counting), and the kernel logistic regression based on correlation dimension model (KLRcorrelation). Next, the statistical indexes and the receiver operating characteristic (ROC) curve were employed to evaluate the models' performance. Finally, the KLRcorrelation model had the highest area under the curve (AUC) values of 0.8984 and 0.9224, obtained by the training and validation datasets, respectively, indicating that the fractal dimension can be used as the input data for landslide susceptibility mapping with a better effect.

Heavy Metal Pollution and Ecological Risk Assessment of the Agriculture Soil in Xunyang Mining Area, Shaanxi Province, Northwestern China.

Mining is considered to be one of the most significant sources of environmental pollution with regard to heavy metals. Mineral mining causes large quantities of mercury, cadmium, and other elements to be released into the environment and naturally poses a serious threat to environment. This paper will analyze the pollution status of agricultural soil caused by the mining of heavy metals in various mining areas in the Xunyang County in the Shaanxi Province of China, an area in famous for its resource mining. Equally, it will look at the potential ecological risk assessment process that is used to analyze the ecological risks of mining heavy metals in agricultural soil located in the surrounding areas. Based on the soil investigation, As pose a moderate ecological risk on the Au mining area. In addition, the Hg metals pose a significantly high potential ecological risk and Cd metals pose a considerable potential ecological risk on the Hg mining area. In the Pb-Zn mining area, a significantly high potential ecological risk was mainly posed by Cd. These results suggest that many heavy metals pose a high potential ecological risk on the agricultural soil in these three mining areas in the Xunyang County, and may cause elevated heavy metal contents in crops, eventually jeopardizing the health of local residents who consume food grown in polluted soil.