Since 1960, water and land resource development in the Aral Sea Basin has led to a surge in socio-economic water consumption and resulted in about 50% shrinkage of the Aral Sea until 1990, which is also known as the Aral Sea Crisis. However, the spatial and temporal changes in socio-economic water consumption are still unclear. Based on the multi-source acquisition of Aral Sea Basin national/state water resource and socio-economic data during 1960-2016, this paper used the system dynamics model to simulate and analyze the characteristics of the socio-economic and water use changes in the Aral Sea Basin and forecasted the socio-economic water use in 2016-2030 under multi-scenarios. The population and GDP in the Aral Sea Basin increased rapidly, by 267% and 1100% respectively, during the study period. The socio-economic water consumption increased from 41 km³ in 1960 to 91 km³ in 2016. The socio-economic water consumption of Kazakhstan and Uzbekistan increased rapidly before the collapse of the Soviet Union, and decreased afterwards. The socio-economic water consumption in Turkmenistan and Tajikistan continued to grow in the past 60 years. The benefits of industrial and agricultural water use in the basin increased significantly after the collapse of the Soviet Union, but remained at a relatively low level. The future forecasts show that if the existing socio-economic water use efficiency and cropland continue to increase (S1), the socio-economic water consumption in the Aral Sea Basin will reach 96.2 km³ by 2030. Under the S10 scenario that the drip irrigation penetration rate reaches 70% and the cropland remains unchanged, the socio-economic water consumption will drop to 68.1 km ³, which can effectively alleviate the crisis in the study area.

Exploring the nonlinear effects and driving mechanism of multidimensional urbanization on PM_2.5 concentrations is of great significance in the high-quality development of urban agglomerations. This paper uses inverse distance weighted spatial interpolation, spatial autocorrelation and standard deviational ellipse to analyze the spatiotemporal heterogeneity of PM_2.5 concentrations in the Yangtze River Delta. It also applies the systematic dynamic panel regression model to explore the nonlinear effects and driving mechanism of multidimensional urbanization on PM_2.5 concentrations based on the remote sensing images and statistical data of urban panels in the study area from 2000 to 2017. The main conclusions are as follows: (1) From 2000 to 2017, the pollution level caused by PM_2.5 concentrations evolved from low to high. Overall, the PM_2.5 concentrations showed a spatial trend of increasing from southeast to northwest. (2) The PM_2.5 concentrations exhibited significant spatial agglomeration and correlation characteristics. Meanwhile, the centroid of the PM_2.5 concentrations generally shifted from southeast to northwest, and the PM_2.5 concentrations tended to be dispersed in the east-west direction, while in contrast they were gradually polarized in the north-south direction. (3) There were significant differences in the impact of different development stages of the urbanization subsystem on the PM_2.5 concentrations. The economic urbanization exhibits an inverted N relationship with the PM_2.5 concentrations, which indicates that an Environmental Kuznets Curve (EKC) existed between the economic urbanization and PM_2.5 concentrations. When the per capita GDP exceeds RMB 63,709 yuan, economic urbanization will have a restraining effect on the PM_2.5 concentrations. This illustrates the fact that the improvement of urban development quality and transformation of urban development methods are the key to controlling PM_2.5 pollution. However, the relationship among population urbanization, land urbanization and PM_2.5 concentrations is only the left part of the inverted U curve, which indicates that population urbanization and land urbanization are still at a certain distance from the inflection point of air quality improvement. Last but not least, the population size, foreign investment and industrial structure all have a significant positive effect on PM_2.5 concentrations, while environmental regulations have a significant negative effect on PM_2.5 concentrations. It is worth noting that the spatiotemporal heterogeneity of PM_2.5 concentrations is formed under the interactive overlay and cycle accumulation of socioeconomic factors, government regulations, and other factors in this region. Among them, socioeconomic factors play a leading role. This paper provides a new research perspective to explore the effects of multidimensional urbanization on PM_2.5 concentrations, so that we can achieve coordination between environmental protection and urban sustainable development in the Yangtze River Delta.

Eurasia mainland cultural exchange has been at the center of the international concern, especially after the Belt and Road Initiative was proposed. The unique geographical location of the Qinghai-Tibet Plateau made it important to strengthen the cultural exchange between the East and the West. This paper uses natural geographical factors and cultural sites in various time periods as data sources, based on cyclic cumulative analysis of the lowest cost path-multipoint connectivity, and GIS spatial analysis (R language) to construct cultural exchange routes from the Neolithic to Bronze Age. We constructed 27 routes in the Neolithic Age with a total length of 6000 km and 30 routes in the Bronze Age with a total length of 7800 km. During the Neolithic Age, the cultural exchange routes mainly exhibited a crescent form along the Northeast-East-Southeast-Southwest margin. By the Bronze Age, the cultural exchange routes expanded to the hinterland in a net form, due to the development of cultural exchange between the settlements. The reconstructed route testified the dissemination path of colored pottery, millet, jade, sheep, wheat and bronze technology, and concretized these archaeologically conceptualized roads. In addition, this paper identified that evolution of the early plateau route was significantly influenced by climate, and also influenced by agricultural technology, introduction of domesticated livestock.