The rapid development of urbanization and population growth in China has posed a major threat to the green sustainable development of the ecological environment. However, the impact of urbanization on the eco-environmental quality (EEQ) in China remains to be developed. Understanding their interactive coupling mechanism is of great significance to achieve the urban sustainable development goals. By using multi-source remote sensing data and the coupling coordination degree model (CCDM), we intended to answer the question “What are the temporal and spatial characteristics of urbanization and EEQ in China on the pixel scale during 2000–2013, and what is the coupling mechanism between the urbanization and the EEQ?”. To answer these questions, we explored the coupling mechanism between urbanization and the EEQ in China with a combined mathematical and graphics model. The results show that the urbanization and the coupling coordination degree (CCD) of the whole region continually increased from 2000 to 2013, especially in the three major urban agglomerations, with a spatial distribution pattern that was “high in the east and low in the west”. Most importantly, from 2000 to 2013, the CCD type of cities in China gradually evolved from uncoordinated cities to coordinated cities. Additionally, the decisive factor affecting the CCD from 2000 to 2013 was the development of urbanization, and the degree at which urbanization had an impact on CCD was about 8.4 times larger than that of the EEQ. At the same time, the rapid urbanization that has occurred in some areas has led to a significant decline in the EEQ, thus indicating that China needs to increase its protection of the ecological environment while pursuing social and economic development in the future. This study makes up for the deficiencies in the existing literature and investigates the long-term coupling of the EEQ and urbanization in China, thereby providing a new research perspective for the sustainable development of China and even the world in the future.

Since the beginning of the new century, there has been a notable enhancement in China’s ecological environment quality (EEQ), a development occurring in tandem with climate change and the extensive ecological restoration projects (ERPs) undertaken in the country. However, comprehensive insights into the spatial and temporal characteristics of China’s EEQ, and its responses to both climate change and human activities over the past two decades, have remained largely elusive. In this study, we harnessed a combination of multi-source remote-sensing data and reanalysis data. We employed Theil–Sen median trend analysis, multivariate regression residual analysis, and the Hurst index to examine the impacts and changing patterns of climatic factors and human activities on China’s EEQ during the past two decades. Furthermore, we endeavored to forecast the future trajectory of EEQ. Our findings underscore a significant improvement in EEQ across most regions of China between 2002 and 2019, with the most pronounced enhancements observed in the Loess Plateau, Northeast China, and South China. This transformation can be attributed to the combined influence of climatic factors and human activities, which jointly accounted for alterations in EEQ across 78.25% of China’s geographical expanse. Human activities (HA) contributed 3.93% to these changes, while climatic factors (CC) contributed 17.79%. Additionally, our projections indicate that EEQ is poised to continue improving in 56.70% of China’s territory in the foreseeable future. However, the Loess Plateau, Tarim Basin, and Inner Mongolia Plateau are anticipated to experience a declining trend. Consequently, within the context of global climate change, the judicious management of human activities emerges as a critical imperative for maintaining EEQ in China. This study, bridging existing gaps in the literature, furnishes a scientific foundation for comprehending the evolving dynamics of EEQ in China and informs the optimization of management policies in this domain.

The pressing need to address climate change and advance global sustainable development has heightened the emphasis on ecosystem services, especially carbon sequestration. This research assesses the supply and demand dynamics of carbon sequestration services on Hainan Island, China, highlighting its significant contributions to global biodiversity conservation and carbon balance. The analysis considers the spatial distribution and interrelation of these services in light of recent land use and ecological policy changes. The methodology incorporates land use and land cover data, the Normalized Difference Vegetation Index (NDVI), meteorological data, and soil data. A gravity model is employed to elucidate the supply–demand relationship for carbon sequestration services, examining the flow across different regions and identifying spatial connections and their intensities. The results indicate a notable increase in carbon sequestration supply in Hainan from 2000 to 2020, particularly in the central mountainous areas. Conversely, the demand for these services has risen, especially in the northern plains’ urban areas and southern coastal towns. The gravity model reveals a strong spatial interdependence between the central mountainous supply zones and the high-demand urban locales. This study underscores the disparities in carbon sequestration supply and demand on Hainan, emphasizing the need for the strategic management of these elements. It provides critical data for ecological compensation policies and offers insights into the roles of regional ecosystems in climate change mitigation. The research highlights the necessity of incorporating ecosystem services into land-use planning and decision-making to foster sustainable development and strengthen climate resilience.

Rising temperatures, extreme precipitation events such as excessive or insufficient rainfall, increasing levels of carbon dioxide, and associated climatic factors will persistently impact crop growth and agricultural production. The warming temperatures have reduced the agricultural crop yields. Rice (Oryza sativa L.) is the major food crop, which is particularly susceptible to the effects of climate change. It is very important to accurately evaluate the impacts of climate change on rice growth and rice yield. In this study, the rice growth during 1981–2018 (baseline period) and 2041–2100 (future period) were separately simulated and compared within the CERES-Rice model (v4.6) using high-quality weather data, soil, and field experimental data at six agro-meteorological stations in Hainan Province. For the climate data of the future period, the SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios were applied, with carbon dioxide (CO₂) fertilization effects considered. The adaptation strategies such as adjusting planting dates and switching rice cultivars were also assessed. The simulation results indicated that the early rice yields in the 2050s, 2070s, and 2090s were projected to decrease by 6.2%, 11.8%, and 20.0% when the CO₂ fertilization effect was not considered, compared with the results of the baseline period, respectively, while late rice yields would decline by 9.9%, 23.4%, and 36.3% correspondingly. When accounting for the CO₂ fertilization effect, the yields of early rice and late rice in the 2090s increased 16.9% and 6.2%, respectively. Regarding adaptation measures, adjusting planting dates and switching rice cultivars could increase early rice yields by 22.7% and 43.3%, respectively, while increasing late rice yields by 20.2% and 34.2% correspondingly. This study holds substantial scientific importance for elucidating the mechanistic pathways through which climate change influences rice productivity in tropical agro-ecosystems, and provides a critical foundation for formulating evidence-based adaptation strategies to mitigate climate-related risks in a timely manner. Cultivar substitution and temporal shifts in planting dates constituted two adaptation strategies for attenuating the adverse impacts of anthropogenic climate change on rice.

Tropical–subtropical monsoon Asia faces pronounced hydroclimatic change under future warming, yet the regional patterns and emission scenario dependence of drought risk remain unclear. Using a 14-member CMIP6 multi-model ensemble from the NEX-GDDP-CMIP6 dataset, we assessed drought evolution under SSP1-2.6 and SSP5-8.5 (2015–2100). Combining the 3-month Standardized Precipitation Evapotranspiration Index (SPEI-3) with event-based run theory and Mann–Kendall trend analysis, we evaluated four complementary drought dimensions: annual mean SPEI, frequency, intensity, and duration. Regional drought area was used as a spatial diagnostic of extent. A persistent west-to-east moisture gradient characterizes present-day conditions: chronic deficits prevail in southwestern China, southern Myanmar, and Thailand, whereas southeastern China and the equatorial belt maintain relative surpluses. This contrast intensifies through the century, with negative SPEI anomalies deepening by 0.2–0.4 units and chronic drought zones expanding into previously marginal areas. Under SSP1-2.6, no metric shows statistically significant trends. By contrast, SSP5-8.5 produces robust drying, with 8.0% of the area showing significant SPEI declines and up to 30.9% exhibiting significant intensification. Scenario-driven increments affect 89–99.7% of the area across all indicators, confirming that higher emissions systematically elevate drought frequency, persistence, and severity. Scenario uncertainty surpasses model structural uncertainty first for intensity (2067), then area (2078), duration (2079), and frequency (2090), reflecting earlier model convergence on the forced thermodynamic shift than on threshold-dependent frequency counts. Stringent mitigation consistent with the Paris Agreement can largely stabilize regional moisture regimes, whereas continued high emissions will drive pervasive drought intensification across one of the world’s most populous and biodiverse forest regions.

Hainan Province is the only tropical province in China and is an important tropical rice-producing region, playing a critical role in regional food security. Rising temperatures associated with climate change may adversely affect rice growth and yield in tropical and subtropical regions, increasing production risks. This study integrated meteorological data from six national agro-meteorological stations in Hainan Province with long-term observations of rice phenology and yield to assess future climate impacts using a multi-climate model and multi-crop model ensemble framework. The CERES-Rice, ORYZA2000, and WOFOST models were separately calibrated and validated using historical observations. Subsequently, CMIP6 projections from five GCMs under SSP1-2.6, SSP3-7.0, and SSP5-8.5 were used to simulate rice phenology and yield during the 2050s, 2070s, and 2090s. A multi-model ensemble mean was further used to integrate inter-model differences across scenarios and future periods. All three crop models showed satisfactory performance in simulating rice phenology and yield. Future warming generally advanced flowering and maturity dates of early rice, whereas late rice exhibited greater spatial and inter-model variability. Yield losses became more pronounced under SSP3-7.0 and SSP5-8.5, with late rice showing greater reductions than early rice. Sowing date adjustment partially offset climate-induced yield losses, although the optimal strategy differed between rice seasons and climate scenarios. Overall, the multi-model framework provided a robust basis for climate risk assessment and adaptation planning for tropical double-rice production in Hainan Province.