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.

The non-coordination between the socio-economic systems and ecosystems of a region is a crucial obstacle to sustainable development. To reveal the relationships between complex urban systems and achieve the goal of sustainable and coordinated urban development, we constructed a coupling coordination degree model (CCDM) and coupling angle model (CAM) and analyzed the degree of coupling coordination and evolution process among the population, water resources, economy, and ecology (PWEE) system of the Tuha region for 2005–2020. The results indicated that: (1) During 2005–2020, the comprehensive development index (CDI) of the population, water resources and economy subsystems was 0.21–0.65, with the three subsystems portraying an overall increase; the average values of the RSEI at five-year intervals were 0.29, 0.28, 0.28, and 0.26, indicating a downward trend in the environmental quality. (2) The coupling coordination effect of the PWEE system portrayed a low level; the coupling coordination degree (CCD) values were 0.28–0.58, portraying a fluctuating upward trend. The level of CCD increased from low disorder to marginal coordination. (3) The PWEE system’s scissor difference reflects large evolutionary characteristics. The ecological support capacity was not observed until the late stage. We conclude that the PWEE composite system of the region is in a stage of disordered development. These findings significantly bolster the theoretical underpinnings of sustainable development studies, offering essential scientific theories and methodological frameworks for crafting sustainable development policies tailored to urban systems in the Tuha region.

Due to the rapid urbanization and global climate change, arid and semi-arid regions are becoming more vulnerable to the growing disparity between the supply and demand of ecosystem services. Conventional ecological risk assessments have predominantly emphasized landscape pattern analysis, often overlooking considerations related to human well-being. This study focuses on the Xinjiang Uygur Autonomous Region (XUAR) and examines four key ecosystem services: water yield (WY), soil retention (SR), carbon sequestration (CS), and food production (FP). Using the InVEST model, geographic information system (GIS) spatial analysis, and statistical methods, we quantify the supply-demand dynamics of these ecosystem services and identify the risk classification of ecosystem service supply-demand (ESSD) using the Self-Organizing Feature Map (SOFM) method. The results show that: (1) From 2000 to 2020, the supply and demand of WY in XUAR increased from 6.02 × 10¹⁰ m³ and 8.6 × 10¹⁰ m³ to 6.17 × 10¹⁰ m³ and 9.17 × 10¹⁰ m³, respectively; SR supply and demand decreased from 3.64 × 10⁹ t and 1.15 × 10⁹ t to 3.38 × 10⁹ t and 1.05 × 10⁹ t, respectively; CS supply and demand rose from 0.44 × 10⁸ t and 0.56 × 10⁸ t to 0.71 × 10⁸ t and 4.38 × 10⁸ t, respectively; and FP supply and demand increased from 9.32 × 10⁷ t and 0.69 × 10⁷ t to 19.8 × 10⁷ t and 0.97 × 10⁷ t, respectively. A clear spatial differentiation in ESSD was observed, with higher supply areas mainly located along river valleys and waterways, while demand is concentrated in the central cities of oases. (2) The deficit areas for WY and SR are large and show a gradual expansion, while the deficit areas for CS and FP are small and shrinking. (3) The supply-demand ratio combined with the supply-demand trend index identifies four types of bundles in the study area: B1 (WY-SR-CS high-risk), B2 (WY-SR high-risk), B3 (integrated high-risk), and B4 (integrated low-risk), with B2 being dominant. Based on these findings, ecological management recommendations are proposed for different bundles based on ESSDR classifications. This study provides a comprehensive ecological risk assessment grounded in ESSD, offering important perspectives for ecological management in arid and semi-arid regions.

In the context of sustainable urban development, elucidating urban heat island (UHI) dynamics in arid regions is crucial. By thoroughly examining the characteristics of UHI variations and potential driving factors, cities can implement effective strategies to reduce their impacts on the environment and public health. However, the driving factors of a UHI in arid regions remain unclear. This study analyzed seasonal and diurnal variations in a surface UHI (SUHI) and the potential driving factors using Pearson’s correlation analysis and an Optimal Parameters-Based Geographic Detector (OPGD) model in 22 cities in Xinjiang, northwest China. The findings reveal that the average annual surface urban heat island intensity (SUHII) values in Xinjiang’s cities were 1.37 ± 0.86 °C, with the SUHII being most pronounced in summer (2.44 °C), followed by winter (2.15 °C), spring (0.47 °C), and autumn (0.40 °C). Moreover, the annual mean SUHII was stronger at nighttime (1.90 °C) compared to during the daytime (0.84 °C), with variations observed across seasons. The seasonal disparity of SUHII in Xinjiang was more significant during the daytime (3.91 °C) compared to nighttime (0.39 °C), with daytime and nighttime SUHIIs decreasing from summer to winter. The study also highlights that the city size, elevation, vegetation cover, urban form, and socio-economic factors (GDP and population density) emerged as key drivers, with the GDP exerting the strongest influence on SUHIIs in cities across Xinjiang. To mitigate the UHI effects, measures like urban environment enhancement by improving surface conditions, blue–green space development, landscape optimization, and economic strategy adjustments are recommended.

In recent years, soil heavy metal pollution has become an important issue of general concern because it is an important factor that threatens the soil environment. To assess the risk of the human health of the people living in the economic belt on the northern slope of the eastern Tianshan Mountains, and provide guidance for pollution control and risk prevention, the northern slope of the eastern Tianshan Mountains was selected as the study area, and six heavy metals (i.e., Zn, Cu, Cr, Pb, and Hg) were measured. The results revealed that the Cu, Pb, Hg, and As contents of the soil exceeded the soil background value of Xinjiang by 1.02, 4.10, 1.76, and 7.98 times, respectively. The Zn and Cr contents were lower than the limits of regional soil standards. Based on the pollution assessment using the pollution index (PI), values indicate that the levels of Zn and Cr pollution were low, those of Cu and Hg pollution were moderate, and those of Pb and As pollution were high. The health risk assessment results revealed that there are non-carcinogenic risks to children. The carcinogenic health risks posed by the heavy metals in this region are higher than the threshold (10⁻⁴), indicating that they pose a hazard to human health. The results of this research provide a theoretical basis and reference for soil heavy metal pollution control and human health risk management in this area.