Recent climate change and vegetation greening have important implications for global terrestrial hydrological cycles and other ecosystem functions, raising concerns about the watershed water supply capacity for large water diversion projects. To address this emerging concern, we built a hybrid model based on the Coupled Carbon and Water (CCW) and Water Supply Stress Index (WaSSI) models and conducted a case study on the upper Han River basin (UHRB) in Central China that serves as the water source area to the middle route of the South-to-North Water Diversion Project (SNWDP). Significant vegetation greening occurred in the UHRB during 2001–2018, largely driven by the widespread afforestation in the region, with the normalized difference vegetation index increasing at a rate of 0.5±0.1 % yr⁻¹ (p<0.05) but with no significant trends in climate during the same period (albeit with large interannual variability). Annual water yield greatly decreased, and vegetation greening alone induced a significant decrease in water yield of 3.2±1.0 mm yr⁻¹ (p<0.05). Vegetation greening could potentially reduce the annual water supply by 7.3 km³ on average, accounting for 77 % of the intended annual water diversion volume of the SNWDP. Although vegetation greening can bring enormous ecosystem goods and services (e.g., carbon sequestration and water quality improvement), it could aggravate the severity of hydrological drought. Our analysis indicated that vegetation greening in the UHRB reduced about a quarter of water yield on average during drought periods. Given the future warming and drying climate is likely to continue to raise evaporative demand and exert stress on water availability, the potential water yield decline induced by vegetation greening revealed by our study needs to be taken into account in the water resources management over the UHRB while reaping other benefits of forest protection and ecological restoration.

In the process of rapid development of economic globalization and regional integration, the importance of urban agglomeration has become increasingly prominent. It is not only the main carrier for countries and regions to participate in international competition, but also the main place to promote regional coordination and sustainable development. Coordinated economic, environmental, tourism and traffic development is very necessary for sustainable regional development. However, the existing literature lacks research on coupling coordination of the Economy–Environment–Tourism–Traffic (EETT) system in urban agglomeration. In this study, in order to fill this gap, we establish the index system from four dimensions of economy, environment, tourism and traffic, and select the influencing factors from the natural and human perspectives to exam the spatio-temporal changes and influencing factors in the coupling coordination of the EETT system using an integrated method in the Middle Reaches of Yangtze River Urban Agglomerations (MRYRUA), China. The results indicate that the coupling coordination degree of the EETT system transitioned from the uncoordinated period to the coordinated period, while it showed an increasing trend on the whole from 1995 to 2017. The spatial agglomeration effect has been positive since 2010, while “High–High” and “Low–High” agglomeration regions were transferred from the east to the south. Land used for urban construction as a percentage of the urban area and vegetation index has a great impact on the coupling coordination degree. These results provide important guidance for the formulation of integration and coordinated development policy in the MRYRUA, and then increase China’s international competitiveness by improving the contribution of urban agglomerations to GDP.

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha–Zhuzhou–Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

The United Nations Educational, Scientific and Cultural Organization (UNESCO) Global Geoparks (UGGp) and geotourism activities not only improve people’s scientific quality by popularizing geoscience knowledge, but also play important roles in protecting precious geoheritages and promoting the development of regional economies. However, tourism activities also have a negative impact on the local ecological environment, placing the regional ecological system under great pressure. Therefore, this paper constructed a tourism ecological security evaluation indicator system suitable for geoparks by using the “Driving-Pressure-State-Impact-Response” (DPSIR) model. The spatial autocorrelation and obstacle degree model are used to analyze the spatio-temporal characteristics and influencing factors of the tourism ecological security index (TESI) of Huanggang Dabieshan UGGp in 2000, 2005, 2010, 2015 and 2018, respectively. The results indicate that the TESI of the study area has gradually improved from 2000 to 2018. Spatially, the level of TESI presents a gradient distribution from the townships where the main scenic spots are located to the surrounding townships. The main obstacle factors affecting TESI include: per capita tourism income, proportion of comprehensive tourism revenue in GDP, per capita net income of rural residents, proportion of tertiary industry in GDP, coverage of nature reserves, planning integrity of geopark, informatization of geopark, growth rate of tourists, comprehensive utilization rate of solid waste, etc. The influencing factors of TESI varied from time to time. Balancing the conflict between local tourism activities and environmental protection, encouraging the participation of local communities, and strengthening science popularization for the local public will effectively improve the tourism ecological security of geoparks.

To mitigate climate change, reducing carbon dioxide (CO₂) emissions is of paramount importance. China, the largest global CO₂ emitter, proposes to peak carbon emissions by 2030 and become carbon neutral by 2060; transforming the energy structure represents one of the primary means of addressing carbon emissions; thus, it is essential to investigate the impacts of alternate energy sources throughout the country. Based on energy consumption and carbon emissions data from 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Taiwan, and Macau, due to the lack of data), the study here investigated the shares of coal, petroleum, natural gas, and non-fossil energy sources (i.e., hydropower, nuclear power, wind power, solar power, and biomass power), as they relate to total, per capita, and per unit GDP CO₂ emissions via spatial regression. The results showed that: (1) The epicenters of coal and carbon emissions have shifted from the east to the central and western regions; (2) There is a significant correlation between energy structure and carbon emissions: coal has a positive effect, petroleum’s effects are positive at first, and negative subsequently; while both natural gas and non-fossil energy sources have a negative impact; (3) Provincial-level carbon emissions are affected by energy structure, carbon emissions in neighboring regions, and other factors.