Pathways to Carbon Peak: Scenario-Based Forecasting for the Middle Yangtze River Urban Agglomeration Using Gaussian Process Regression

As a pivotal region within the Yangtze River Economic Belt, the Middle Yangtze River Urban Agglomeration is characterized not only by dense economic activity and population concentration but also as a significant source of carbon emissions. This study investigates the carbon emission characteristics of the region and forecasts future emission trajectories to support the achievement of China’s 2030 carbon peak target. A Gaussian Process Regression (GPR) model was employed, utilizing data from 31 prefecture-level cities spanning from 2000 to 2021, with rigorous accuracy validation. Comparative analyses against Artificial Neural Networks (ANN), Least Squares Support Vector Machines (LSSVM), and ARIMA models demonstrate the superior predictive performance of the proposed GPR approach. The results indicate that the timing of carbon peaking varies across different economic growth and energy consumption scenarios. Under low-growth conditions with either slow or rapid energy reduction, the region is projected to peak be-tween 2025 and 2028. Conversely, under high-growth scenarios with slow or rapid energy reduction, achieving the 2030 carbon peak target appears unlikely. To effectively advance emission reduction, policy strategies should be tailored to local contexts, focusing on industrial restructuring, energy system optimization, and technological innovation, while avoiding undue compromise of economic development. Through such measures, the Middle Yangtze River Urban Agglomeration can pursue carbon peaking alongside sustainable economic growth.