Search Results (8)

Ecosystem services (ESs) underpin human well-being and regional development by linking ecological processes with human land–use activities. However, for arid oasis urban agglomerations, evidence remains limited on long-term ES changes, landscape-type contributions, and future responses under alternative development pathways. We quantified five ESs in the UCS from 1990 to 2020 using InVEST and statistical allocation methods and related the resulting service maps to landscape-type contributions and service-pair relationships. The PLUS model generated 2030 land–use pathways, which were used to compare ES responses under BAU, ED, and EP scenarios. The LEAS module identified how climatic, socioeconomic, topographic, and accessibility factors contributed to land–use expansion and thereby indirectly shaped ES patterns. The results show that (1) from 1990 to 2020, food production (FP) increased with fluctuations from 16.30 to 62.06 t·km⁻², whereas water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ) declined by 27.8%, 5.7%, 27.0%, and 5.4%, respectively; (2) the five ecosystem services showed clear spatial heterogeneity, with food production characterized by high values in the central oasis plain and low values in the northern and southern parts, whereas the other four services showed a south-high/north-low gradient; forestland, grassland, and water bodies were the major landscape types supporting ecosystem-service supply; (3) ecosystem-service interactions changed dynamically: FP showed clear Pearson trade-offs with HQ and weak trade-offs with SC, whereas WY-CS, WY-SC, CS-SC, SC-HQ, WY-HQ, and CS-HQ were mainly synergistic; FP-WY and FP-CS also showed positive Pearson correlations, indicating that food-production expansion in oasis areas was partly coupled with water-resource and cropland–related carbon-storage patterns; and (4) the 2030 scenario simulations showed differentiated responses: under BAU and ED, FP remained nearly stable or slightly decreased, whereas WY, CS, SC, and HQ increased slightly; under EP, all five services improved relative to 2020, with FP, WY, CS, SC, and HQ increasing by approximately 4.08%, 2.33%, 3.13%, 9.60%, and 0.79%, respectively, making EP the most favorable pathway for enhancing ecosystem-service supply and mitigating FP-related trade-offs. The results identify where provisioning gains conflict with water, soil, carbon, and habitat functions and provide a basis for differentiated oasis management in Urumqi, Changji, Shihezi, and Wujiaqu. Full article

This study utilizes backward trajectory cluster analysis, the Potential Source Contribution Function (PSCF), Concentration Weighted Trajectory (CWT), and a random forest model to investigate the pollution characteristics of PM_2.5 and PM₁₀ in the “Urumqi-Changji Hui Autonomous Prefecture-Shihezi-Wujiaqu (U-C-S)” urban agglomeration. Findings indicate that on an annual basis, higher PM_2.5 concentrations are observed in the central part of the “U-C-S” urban agglomeration, southern Wujiaqu, and the Shihezi area, whereas PM₁₀ concentrations are lower in the high-altitude regions of the Tianshan and Bogda Mountains. Seasonally, both PM_2.5 and PM₁₀ concentrations significantly increase during winter, with summer exhibiting the best air quality. On a monthly scale, Urumqi’s central urban area shows a marked rise in PM_2.5 concentrations during winter, attributed to coal heating and stable weather conditions. Weekly patterns reveal higher pollution levels on weekdays compared to weekends. Daily data show that PM_2.5 concentrations are notably higher in winter compared to other periods, while elevated PM₁₀ levels in spring are primarily due to dust storms. Cluster analysis indicates that seasonal airflow paths significantly influence particulate matter concentrations. PSCF and CWT analyses demonstrate that the most severe PM_2.5 pollution in winter is concentrated in the northern part of the Bayingolin Mongol Autonomous Prefecture, southern Yining City, and across all areas of Urumqi. The random forest model provides robust predictions of particulate matter concentrations, aiding in the understanding and mitigation of future pollution trends. This study offers valuable insights for atmospheric particulate matter pollution research in the Xinjiang region and serves as a reference for similar urban agglomerations. Full article

Understanding the responses of vegetation phenology to natural and human disturbances is essential for better understanding ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer data and products were used together with other relevant data to analyse vegetation phenological responses to urbanisation and natural factors in the major urban agglomerations of the Urumqi-Changji, Shihezi-Manasi, and Wusu-Kuidun-Dushanzi regions on the Urban Agglomeration on the Northern Slope of the Tianshan Mountains (UANSTM). Vegetation phenology distributed along an urban-rural gradient showed distinct variability, with start of growing season (SOS), end of growing season (EOS), and growing season length (GSL) occurring earlier, later, and longer, respectively, in urban areas than those in suburban and rural areas. In the Urumqi-Changji region, the earliest SOS, the later EOS, and the longest GSL occurred. Surface urban heat island intensity (SUHII) was most pronounced in the Urumqi-Changji region, with a heat island intensity of 1.77–3.34 °C. Vegetation phenology was influenced by both urbanisation and natural factors, whose contributions were 44.2% to EOS and 61.8% to SOS, respectively. The results of this study emphasise the importance of quantifying the vegetation phenological responses to human disturbances, including climate change, along the urban-rural gradient on the UANSTM. Full article

This study aims to clarify the vulnerability characteristics of the ecological–economic–social system of oasis city clusters in arid zones, promote the deepening of research on the sustainable development of urban clusters, and provide crucial practical reference significance for solving the series of problems brought about by urbanization. This article takes the arid zone oasis city cluster, the Urumqi–Changji–Shihezi urban agglomeration, as the research object and constructs an indicator system from three dimensions of ecological environment, regional economic, and social development, and adopts the comprehensive index method, GeoDetector, the GM(1, 1) gray prediction model, and other methods to study the vulnerability pattern and spatial and temporal changes of the urban cluster from 2009 to 2018. The results show that (1) from 2009 to 2018, the change in the integrated ecological–economic–social system vulnerability index of the Urumqi–Changji–Shihezi urban agglomeration shows a general downward trend, followed by significant differences in the vulnerability of each dimension, with an average vulnerability index of 1.8846, 1.6377, and 0.9831 for the social vulnerability, regional economic, and ecological environment dimensions, respectively; (2) the evolution of the spatial pattern of changes in the vulnerability index of different systems in each region of the Urumqi–Changji–Shihezi urban agglomeration tends to change from large to slight spatial differences, in which the social and ecological environmental vulnerability changes are more prominent in addition to the vulnerability changes of the regional economy; (3) parkland area per capita, arable land area per capita, GDP per capita, social fixed asset investment, population density, and urban road area per capita are the main drivers of decreasing vulnerability of ecological–economic–social systems in urban agglomerations; (4) by predicting and calculating the vulnerability index of each region of the ecological–economic–social system of urban agglomerations, it is found that the vulnerability index of urban agglomerations will show a decreasing trend from 2009 to 2018, and the difference of the vulnerability index between systems will narrow; (5) finally, targeted countermeasures and suggestions to reduce the vulnerability of ecological–economic–social systems are proposed to provide scientific references for the sustainable development of arid oasis cities. Full article

Accurately capturing the changing patterns of ecological quality in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM) and researching its significant impacts responds to the requirements of high-quality sustainable urban development. In this study, the spatial and temporal distribution patterns of remote sensing ecological index (RSEI) were obtained by normalization and PCA transformation of four basic indicators based on Landsat images. It then employed geographic detectors to analyze the factors that influence ecological change. The result demonstrates that: (1) In the distribution of land use conversions and degrees of human disturbance, built-up land, principally urban land, and agricultural land, represented by dry land, are rising, while the shrinkage of grassland is the most substantial. The degree of human disturbance is increasing overall for glaciers. (2) The overall ecological environment of the northern slopes of Tianshan is relatively poor. Temporally, the ecological quality changes and fluctuates, with an overall rising trend. Spatially, ecological quality is low in the north and south and high in the center, with high values concentrated in the mountains and agriculture and low values in the Gobi and desert. However, on a large scale, the ecological quality of the Urumqi–Changji–Shihezi metropolitan area has worsened dramatically compared to other regions. (3) Driving factor detection showed that LST and NDVI were the most critical influencing factors, with an upward trend in the influence of WET. Typically, LST has the biggest influence on RSEI when interacting with NDVI. In terms of the broader region, the influence of social factors is smaller, but the role of human interference in the built-up area of the oasis city can be found to be more significant at large scales. The study shows that it is necessary to strengthen ecological conservation efforts in the UANSTM region, focusing on the impact of urban and agricultural land expansion on surface temperature and vegetation. Full article

Analyses of landscape patterns, analyses of land-use/land-cover evolution characteristics, and a driving force analysis during the expansion of urban agglomerations can assist urban agglomerations in solving ecological and environmental problems; moreover, these tools can provide a reference for urban land-use structure optimization and urban landscape planning. In this study, the rapid urbanization and urban agglomeration of small- and medium-sized cities were evaluated; specifically, the urban agglomeration of the northern slopes of the Tianshan Mountains (UANSTM) was assessed. Using multi-period (1995, 2000, 2005, 2010, 2015, 2018) land-use data and statistical yearbook data, we calculated the landscape index and comprehensive land-use degree index using the Moran index and geographic probe methods. We studied the expansion patterns and spatial distribution patterns of urban land and quantitatively explored the influence mechanisms of natural and socioeconomic factors on the degree of land use to clarify the characteristics and driving forces of land-use evolution. The results show the following: the area of urban land continued to increase between 1995 and 2018; the dominance of the landscape indexes within each time period changed with urban development; and intra-urban landscape heterogeneity is gradually increasing. In terms of the spatial and temporal distribution of the degree of land use, the expansion of urban agglomeration is centered on the city of Urumqi, spreading towards the cities of Changji and Shihezi; the rest of the counties and cities are fast urban-expansion zones. Under the influence of multiple source factors, the expansion of the UANSTM depends on the distribution of oases, which is mainly influenced by the distribution of vegetation and the density of the river network and can only rely on the ecological carrying capacity of oases for production and life. The results of the study can provide a basis for decision-making processes surrounding the future layout of the UANSTM ecological environment. Full article

Changes in land surface temperature (LST) can have serious impacts on the water cycle and ecological environment evolution, which in turn threaten the sustainability of ecosystems. The urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM) is located in the arid and semi-arid regions of northwest China, with an extremely fragile ecological environment and sensitive to climate change. However, studies on the LST of the UANSTM have not received much attention. Therefore, this study explored the spatial distribution pattern, fluctuation characteristics, and influencing factors of the LST of the UANSTM from 2005 to 2021 based on MODIS time series LST data and the geo-detector model with optimal parameters. The results show that the UANSTM is dominated by medium- and high-temperature classes, with high- and extremely high-temperature classes clustered in Turpan City. The daytime and nighttime LST patterns are significantly different, with a typical “daytime cold island and nighttime heat island” feature in the oasis region. During 2005–2021, LST fluctuated greatly in the northwestern part of the UANSTM, with LST showing an increasing trend during both daytime and nighttime, and the warming rate was more intense during daytime than nighttime. The increasing trend of LST in Urumqi, Changji Hui Autonomous Prefecture, Shihezi, and Wujiaqu is very significant and will remain consistent in the future. Precipitation, DEM, and AOD are the most important influencing factors of LST in the UANSTM, where precipitation and DEM are negatively correlated with LST, and AOD is positively correlated with LST. Land cover factors (LULC, NDVI,, and NDBSI) are the next most influential, and socioeconomic factors (NTL, GDP, and POP) are the least influential. The results of this study can provide a scientific reference for the conservation and sustainable development of the ecological environment of the UANSTM. Full article

With industrial integration accelerating in domestic and foreign enterprise, industrial integration is becoming the only way for regional development to break through its bottleneck. Compared with advanced foreign enterprises, there exists a significant gap in regional industrial integration, especially in the urban agglomeration of the energy chemical industries of Urumqi-Changji-Shihezi in Xinjiang. Findings from field visits and quantitative analysis show that the energy chemical industry in urban agglomeration is in a state of dispersed distribution, serious convergence in industrial structure, low level of specialization, and weak collaborative relationships. These issues seriously hamper the sustainable development of urban agglomeration. Specific actions aimed at these problems and the development bottleneck mainly include the integration of industrial parks in the central city and integration orientation on the level of urban agglomeration. Only by speeding up the pace of industry integration can Urumqi-Changji-Shihezi’s urban agglomeration maintain and improve its market competitiveness. Accordingly, it can promote innovation and sustainability in the energy chemical industry and improve the overall level of development. Full article