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<p>As a pivotal component of the Yangtze River Economic Belt, the Middle Yangtze River Urban Agglomeration (MYRUA) experiences continuously growing carbon emissions, making its peaking pathway crucial for achieving China’s national “2030 peak” target. <i>Existing studies often rely on linear models, which inadequately capture the nonlinearity and uncertainty inherent in emission dynamics. Moreover, few have integrated Gaussian Process Regression (GPR) with spatiotemporal analysis at the urban agglomeration scale for forecasting</i>. To address these gaps, this study develops an integrated analytical framework combining spatial analysis and GPR. Utilizing panel data from 31 prefecture-level cities within the MYRUA from 2000 to 2021, we diagnose the spatiotemporal evolution of carbon emissions and conduct scenario-based forecasting. The key findings are: (1) Carbon emissions exhibit a distinct “core-periphery” spatial pattern, forming high-emission clusters centered around Wuhan, Changsha, and Nanchang. (2) The GPR model demonstrates superior predictive accuracy and provides essential uncertainty quantification compared to benchmark models including Artificial Neural Networks, Least Squares Support Vector Machines, and Autoregressive Integrated Moving Average. (3) Scenario forecasts reveal a divergence in peaking pathways among major Chinese urban agglomerations. Developed agglomerations like the Yangtze River Delta and Beijing-Tianjin-Hebei are projected to peak before 2030. In contrast, the MYRUA, along with the Chengdu-Chongqing and Central Plains agglomerations, may peak between 2025 and 2028 under low-growth scenarios but face significant challenges under high-growth scenarios. (4) Assessment using a composite Carbon Peaking Pressure Index identifies the MYRUA as under the highest pressure, attributed to its heavy industrial structure and strong growth inertia. This research provides methodological support and empirical evidence for formulating differentiated carbon peaking strategies for urban agglomerations. We recommend promoting industrial restructuring, energy system decarbonization, and coordinated regional governance to facilitate the emission reduction process.</p>

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Pathways to Carbon Peak in the Middle Yangtze River Urban Agglomeration: Scenario Forecasting and Pressure Assessment Using Gaussian Process Regression

  • 期刊论文

  • 发表日期：

    2026年1月29日

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  • Xinbao Chen,
  • Junqi Lei,
  • Xinyi Zhang

摘要

As a pivotal component of the Yangtze River Economic Belt, the Middle Yangtze River Urban Agglomeration (MYRUA) experiences continuously growing carbon emissions, making its peaking pathway crucial for achieving China’s national “2030 peak” target. Existing studies often rely on linear models, which inadequately capture the nonlinearity and uncertainty inherent in emission dynamics. Moreover, few have integrated Gaussian Process Regression (GPR) with spatiotemporal analysis at the urban agglomeration scale for forecasting. To address these gaps, this study develops an integrated analytical framework combining spatial analysis and GPR. Utilizing panel data from 31 prefecture-level cities within the MYRUA from 2000 to 2021, we diagnose the spatiotemporal evolution of carbon emissions and conduct scenario-based forecasting. The key findings are: (1) Carbon emissions exhibit a distinct “core-periphery” spatial pattern, forming high-emission clusters centered around Wuhan, Changsha, and Nanchang. (2) The GPR model demonstrates superior predictive accuracy and provides essential uncertainty quantification compared to benchmark models including Artificial Neural Networks, Least Squares Support Vector Machines, and Autoregressive Integrated Moving Average. (3) Scenario forecasts reveal a divergence in peaking pathways among major Chinese urban agglomerations. Developed agglomerations like the Yangtze River Delta and Beijing-Tianjin-Hebei are projected to peak before 2030. In contrast, the MYRUA, along with the Chengdu-Chongqing and Central Plains agglomerations, may peak between 2025 and 2028 under low-growth scenarios but face significant challenges under high-growth scenarios. (4) Assessment using a composite Carbon Peaking Pressure Index identifies the MYRUA as under the highest pressure, attributed to its heavy industrial structure and strong growth inertia. This research provides methodological support and empirical evidence for formulating differentiated carbon peaking strategies for urban agglomerations. We recommend promoting industrial restructuring, energy system decarbonization, and coordinated regional governance to facilitate the emission reduction process.