This study utilizes emerging hotspot analysis to explore the spatio-temporal trends of vegetation optical depth (VOD) observed in Ku, X, and C microwave bands over China from 2002 to 2017. Furthermore, it analyzes the impacts of anthropogenic activities, represented by land use change, on the spatial and temporal changes in VOD, and employs Partial Least Squares Structural Equation Model to quantitatively assess the climatic effects on VOD changes. Overall, VOD exhibits a southeast-to-northwest gradient over China, with central and southern regions identified as VOD hotspots, while Xinjiang and the central Inner Mongolia Plateau are identified as VOD cold spots. Regions with consistent emerging hotspot analysis results across the three bands demonstrate a "greening" phenomenon in sparsely-vegetated regions nationwide. Additionally, the association between land use change and emerging hotspots reveals strong impacts of human activities on VOD variations. Specifically, persistent and intensified VOD hotspots predominantly correspond to scenarios where grassland is converted to forest. Attribution of VOD changes using Partial Least Squares Structural Equation Modeling indicates that, in the humid zone, where hydrothermal conditions are favorable and soil moisture is abundant, further increases in temperature and precipitation may inhibit vegetation growth. In contrast, in the arid zone, the inhibitory effect of temperature is less prominent. In the Tibetan Plateau, increases in both temperature and precipitation will promote vegetation growth. The insights from this study are expected to provide scientific support for monitoring ecosystem changes, uncovering their driving forces, and assessing the effectiveness of ecological measures.

Economic globalization and regional integration have pushed international borders from closure to opening-up, making them a hot spot for studying human-environment relations. The promotion of African integration has lasted for decades and has also affected cross-border landscape and land use. Since the signing of the African Continental Free Trade Area Agreement, the processes of forest loss and gain and other land cover change within international borders of continental Africa and its main influencing factors (e.g., active fire) as well as their contribution remain understudied. With the Sentinel-2 10-m land use/land cover products, Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) active fires, LandScan population density, and armed conflict records during 2017-2022, we first examined the inter-annual dynamics and cross-transformations between forest (trees), rangeland (grass and shrub), and bare ground within a total of 146 international borders of the African continent, covering 49 countries. We then determined the major influencing factors and quantified their contribution using Random Forest Regression and correlation analysis. The results show that: (1) the international borders of continental Africa are characterized by a general distribution pattern of forest, rangeland, and bare ground in a sequential order in both the northern and southern parts, divided by the equator. The three land cover types account for nearly 90% of all borders, and dominate (>80%) the change in land cover at the borders with an average annual rate of 2%. Forest loss due to the transformation into rangeland remains a major trend albeit short-term forest gain in 2020. (2) Active fire and population density are the primary and secondary respectively causes of forest cover change along national borders in Africa. The relationship between forest changes and the frequency of active fire or population density is initially weak and then strong during the study period. (3) Nearly 90% of interannual forest loss is strongly and positively correlated with the occurrence of active fires along the international borders of continental Africa, showing a gradual increase on both the northern and southern sides of the equator due to the seasonal dynamics of active fires. (4) Active fires have a more pronounced impact on forest decline within African borders during dry seasons. This study contributes to providing a methodological reference for exploring the causal factors of tropical forest change and the extent to which land-use change at the borders responds to regional integration.

Analyzing the evolution of spatial patterns and driving forces of carbon transfer is essential for the equitable allocation of carbon emission responsibilities, accurate identification of regional carbon emission sources, and improvement in carbon reduction efficiency. Existing research on carbon transfer in China has primarily focused on inter-country and inter-provincial connections at single points in time, lacking an analysis of the long-term dynamic evolution and driving factors behind both domestic and international carbon transfers at the provincial scale. This study addresses this research gap. Using a multi-scale input-output model, this study quantified the carbon transfers associated with domestic and international trade for 31 Chinese provinces (excluding Hong Kong, Macau, and Taiwan) from 1997 to 2017. It further analyzed the evolution characteristics of spatial patterns and their driving forces. The findings indicate: (1) Carbon transfers in both domestic and international trade increased significantly across all provinces. Spatial differentiation intensified along a north-south axis for domestic trade and an east-central-west axis for international trade. (2) Growth in net carbon transfers in domestic trade was primarily driven by carbon-intensive industries, whereas growth in international trade transfers was primarily driven by manufacturing industries. (3) The intensification of spatial differentiation in domestic carbon transfers was mainly driven by the expansion of inter-regional trade in carbon-intensive industries. Similarly, intensified spatial differentiation in international carbon transfers was mainly driven by increased exports of manufactured products. Conversely, reductions in carbon emission intensity and adjustments in input-output structures had mitigating effects on these trends. This study provides scientific support for optimizing provincial carbon reduction strategies and developing coordinated inter-provincial carbon reduction policies in China.

Advancing the transfer and application of clean energy technologies is a pivotal strategy for addressing energy-related environmental and climate challenges. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a major economic and innovation hub in China, possesses substantial potential in facilitating clean energy technology transfer and reducing carbon emissions. This study examines the spatial dynamics of local, interregional, and international clean energy technology transfers within the GBA, based on patent transfer data from 2010 to 2022. Furthermore, the study employs the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model to assess the impact of these transfers on the region's emission reduction targets. This study reveals the following findings: (1) The scale of local clean energy technology transfers within the GBA exhibits a fluctuating upward trend, predominantly following an "intra-city hub-and-spoke" model. The transfer network has evolved from a single-core to a dual-core and, eventually, to a multi-center configuration. (2) Interregional clean energy technology transfers are increasingly active, narrowing the gap with local transfers. The transfer model has shifted from concentration to diffusion, with external demand transitioning from the Yangtze River Delta to the Beijing-Tianjin-Hebei region. The spatial pattern of outward diffusion has expanded from innovation-intensive cities in the eastern and central regions to western cities such as Haixi, Urumqi, and Karamay. (3) The scale of international clean energy technology transfers remains relatively small, but its activity is gradually increasing, with the Hong Kong-Shenzhen core network engaging with a more diverse array of partners. (4) Clean energy technology transfer has had a significant inhibitory effect on carbon emissions in the GBA, particularly through local and interregional intercity transfers, while the emission reduction effect of international transfers is not yet significant. This study sheds light on the spatial pathways, characteristics, and emission reduction impacts of clean energy technology transfers in the GBA, providing valuable insights for formulating regional low-carbon policies and promoting technological innovation cooperation.