Equilibrating the supply and demand for ecosystem services (ESs) is essential for sustainable development. Nonetheless, elements like policy modifications, land utilization, and climate change are profoundly transforming the dynamics of ecosystem service supply and demand (ESSD). As a result, there is an imperative necessity to methodically evaluate and predict these alterations by including both social and environmental elements. This study utilized the Henan region of the Yellow River Basin (HYRB) as a case study to forecast alterations in the supply and demand for three ESs—water production (WY), carbon storage (CS), and food production (FP)—under three scenarios for 2030 and 2050, grounded in the SSP-RCP framework. We further evaluated the supply–demand equilibrium at both grid and county degrees. The results indicate the following key findings: (1) From 2020 to 2050, there are significant spatial differences in the supply and demand of these services. While the supply of CS and FP exceeds demand, the supply of WY falls short. (2) The supply–demand ratios for WY and CS are projected to decline under all scenarios, whereas FP is expected to continue growing. Surplus areas for WY and CS are aggregated in the northwest, southwest, and central areas, while FP surpluses are found in the eastern and northern plains. Deficits for all three services are primarily located in urban areas. (3) The dominant spatial patterns of supply–demand matching also vary. WY and CS exhibit high–low agglomeration patterns, particularly in the northwest and southwest mountain regions, while FP shows low–low agglomeration, mainly in the southwest and northwest mountain areas. These findings enhance comprehension of the dynamics of ESSD, serving as a foundation for environmental preservation and sustainable advancement in the Yellow River Basin, China.

As global climate change accelerates, the urban heat island (UHI) phenomenon has become increasingly pronounced, posing significant challenges to urban energy balance, atmospheric processes, and public health. This study used the Weather Research and Forecasting (WRF) model to dynamically downscale two CMIP6 scenarios—moderate forcing (SSP245) and high forcing (SSP585)—focusing on Zhengzhou, a rapidly urbanizing city in central China. High-resolution simulations captured fine-scale intra-urban temperature patterns and analyze the spatial and seasonal variations in UHI intensity in 2030 and 2060. The results demonstrated significant seasonal variations in UHI effects in Zhengzhou for both 2030 and 2060 under SSP245 and SSP585 scenarios, with the most pronounced warming in summer. Notably, under the SSP245 scenario, elevated autumn temperatures in suburban areas reduced the urban–rural temperature gradient, while intensified rural cooling during winter enhanced the UHI effect. These findings underscore the importance of integrating high-resolution climate modeling into urban planning and developing targeted adaptation strategies based on future UHI patterns to address climate challenges.