Soil contamination soils of by heavy metals (HMs) poses serious threats to the soil environment and enters the human body through exposure pathways such as ingestion and skin contact, posing a threat to human health. The purpose of this study was to analyze the sources and contributions of soil HMs, and to quantitatively assess the human health risks of soil HMs to different populations (i.e. children, adult females and adult males), and to analyze the human health risks caused by various sources of sensitive populations. 170 topsoil (0–20 cm) were collected from Fukang, Jimsar and Qitai on the northern slope of Tianshan Mountains in Xinjiang, China, and the contents of Zn, Cu, Cr, Pb and Hg were determined. This study used the Unmix model and a health-risk assessment (HRA) model to assess the human health risks of five HMs. The results showed that: (1) The mean values of Zn and Cr were lower than the background values of Xinjiang, the mean values of Cu and Pb were slightly higher than the background values of Xinjiang but lower than the national standard, and the mean value of Hg and Pb was higher than the background value of Xinjiang and the national standard. (2) The sources of soil HMs in the region were mainly traffic, natural, coal, and industrial sources. Moreover, the HRA model combined with Monte Carlo simulation showed similar trends in the health-risk status of all population groups in the region. Probabilistic HRA revealed that noncarcinogenic risks were acceptable for all populations (HI < 1) while carcinogenic risks were high (children: 77.52%; female: 69.09%; male: 65.63%). For children, carcinogenic risk from industrial and coal sources exceeded the acceptable threshold by 2.35 and 1.20 times, respectively, and Cr was the main element contributing to human carcinogenic risk. These findings suggest that carcinogenic risks from coal-based Cr emissions cannot be ignored, and the study area should aim to control Cr emissions from industrial sources. The results of this study provide support for the prevention of human health risks and the control of soil HMs pollution across different age groups.

Significant anthropogenic and biophysical changes have caused fluctuations in the soil salinization area of the Keriya Oasis in China. The Driver-Pressure-State-Impact-Response (DPSIR) sustainability framework and Bayesian networks (BNs) were used to integrate information from anthropogenic and natural systems to model the trend of secondary soil salinization. The developed model predicted that light salinization (vegetation coverage of around 15–20%, soil salt 5–10 g/kg) of the ecotone will increase in the near term but decelerate slightly in the future, and that farmland salinization will decrease in the near term. This trend is expected to accelerate in the future. Both trends are attributed to decreased water logging, increased groundwater exploitation, and decreased ratio of evaporation/precipitation. In contrast, severe salinization (vegetation coverage of around 2%, soil salt ≥20 g/kg) of the ecotone will increase in the near term. This trend will accelerate in the future because decreased river flow will reduce the flushing of severely salinized soil crust. Anthropogenic factors have negative impacts and natural causes have positive impacts on light salinization of ecotones. In situations involving severe farmland salinization, anthropogenic factors have persistent negative impacts.

Soil salinity is one of the major factors causing land degradation and desertification on earth, especially its important damage to farming activities and land-use management in arid and semiarid regions. The salt-affected land is predominant in the Keriya River area of Northwestern China. Then, there is an urgent need for rapid, accurate, and economical monitoring in the salt-affected land. In this study, we used the electrical conductivity (EC) of 353 ground-truth measurements and predictive capability parameters of WorldView-2 (WV-2), such as satellite band reflectance and newly optimum spectral indices (OSI) based on two dimensional and three-dimensional data. The features of spectral bands were extracted and tested, and different new OSI and soil salinity indices using reflectance of wavebands were built, in which spectral data was pre-processed (based on First Derivative (R-FD), Second Derivative (R-SD), Square data (R-SQ), Reciprocal inverse (1/R), and Reciprocal First Derivative (1/R-FD)), utilizing the partial least-squares regression (PLSR) method to construct estimation models and mapping the regional soil-affected land. The results of this study are the following: (a) the new OSI had a higher relevance to EC than one-dimensional data, and (b) the cross-validation of established PLSR models indicated that the β-PLSR model based on the optimal three-band index with different process algorithm performed the best result with R²_V = 0.79, Root Mean Square Errors (RMSE_V) = 1.51 dS·m⁻¹, and Relative Percent Deviation (RPD) = 2.01 and was used to map the soil salinity over the study site. The results of the study will be helpful for the study of salt-affected land monitoring and evaluation in similar environmental conditions.

Irrigation salinity is a common environmental threat for sustainable development in the Keriya Oasis, arid Northwest China. It is mainly caused by unreasonable land management and excessive irrigation. The aim of this study was to assess and map the salinity risk distribution by developing a composite risk index (CRI) for seventeen risk parameters from traditional and scientific fields, based on maximizing deviation method and analytic hierarchy process, the grey relational analysis and the Pressure-State-Response (PSR) sustainability framework. The results demonstrated that the northern part of the Shewol and Yeghebagh village has a very high salinity risk, which might be caused by flat and low terrain, high subsoil total soluble salt, high groundwater salinity and shallow groundwater depth. In contrast, the southern part of the Oasis has a low risk of salinity because of high elevation, proper drainage conditions and a suitable groundwater table. This achievement has shown that southern parts of the Oasis are suitable for irrigation agriculture; for the northern area, there is no economically feasible solution but other areas at higher risk can be restored by artificial measures. Therefore, this study provides policy makers with baseline data for restoring the soil salinity within the Oasis.

The Xinjiang Zhundong Economic and Technological Development Zone, which contains the largest coalfield in China, is a mega energy base for west–east gas transmission and outbound electricity transmission in China; however, resource exploitation and the region’s arid climate have led to the region’s ecological environment being increasingly vulnerable. The morphological spatial pattern analysis (MSPA) method and landscape connectivity were used in this study to identify the ecological sources and extract the ecological corridors and ecological nodes based on the minimum cumulative resistance (MCR) model, used to construct the landscape ecological security pattern in the Zhundong region from 2016 to 2021. The results show that (a) from 2016 to 2021, the area of ecological sources increased by 117.86 ha and the distribution density of which decreased from the southern-central region to the northern and northwestern regions. (b) From 2016 to 2021, the number of ecological corridors and ecological nodes decreased, and the ecological corridors with dense distributions in the south gradually moved to the north and west. The length of the ecological corridors in the south gradually became longer, and the number of ecological corridors connecting the east and west in the north increased. (c) The landscape ecological security pattern of the Zhundong region was constructed by “a network and multiple points” using the model of ecological sources–ecological corridors–ecological nodes. The findings of this study provide a scientific foundation for the construction of an ecological security development plan and the ecologically protective development of coal resources in Zhundong.

In typical semi-arid areas, the timely and effective monitoring and evaluation of soil heavy metal pollution are of critical importance to prevent soil deterioration and achieve the sustainable use of soil resources. To further understand the degree of soil heavy metal pollution in different functional areas, we studied the soil heavy metal pollution on the northern slope of the eastern Tianshan Mountains in Xinjiang. We collected 104 surface soil samples from typical commercial (A), industrial (B), and agricultural (C) areas with different land-use patterns. The contents of Zn, Cu, Cr, Pb, As, and Hg in the soil of different functional areas were evaluated using the geo-accumulation index, the single-factor pollution index, and potential ecological risk. The results showed that the contents of Pb, As, and Hg in soils of different functional areas exceeded 4.47, 8.03, and 1.5 times the background values of Xinjiang soil, respectively. The average contents of Zn, Cu, and Cr were lower than the background values of Xinjiang soil. Except for As in different functional areas, the contents of the other elements in the different functional areas reached the level of soil environmental quality standards in China (GB15618-2018). The geo-accumulation index of heavy metals in different functional areas was in the order of Area C > Area A > Area B, indicating that Area C was the most polluted. The results of the single-factor pollution index showed that the pollution levels of Pb, As, and Hg were higher, and the pollution levels of Cr, Cu, and Zn were lower. The results of the potential ecological risk index showed that the northwest of Area A was higher, the southeast of Area B was more polluted, and the central and eastern parts of Area C were more polluted. From the perspective of spatial distribution, the spatial distribution characteristics of Zn and Cr elements in different functional areas are consistent, but the spatial distribution characteristics of Cu, Pb, As, and Hg in different functional areas are quite different. The high values of these four elements are mainly distributed in residential areas, factories, and metal smelters. It is necessary to divide the functional areas based on different land-use patterns, and the prevention of soil single-element and heavy metal pollution in different functional areas is reasonable for land resources and provides a scientific basis for the effective planning of quality assurance.