Abstract

Supported by the coordinated development strategy, the Beijing–Tianjin–Hebei (BTH) region has achieved rapid development but also faces severe energy consumption and environmental pollution problems. As the main responsibility of emission reduction, the coordinated and orderly implementation of carbon emission reduction in Beijing, Tianjin, and Hebei is of great significance to the realization of the carbon neutrality target. Based on this, this study comprehensively uses the expanded STIRPAT model, optimized extreme learning machine (ELM) network, entropy method, and zero-sum gains DEA (ZSG-DEA) model to explore the carbon emission drivers, long-term emission reduction pathway, and carbon quota allocation in the BTH region. The results of the driving factor analysis indicate that the proportion of non-fossil energy consumption is a significant driving factor for Beijing’s carbon emissions, and the improvement of the electrification level can inhibit the carbon emissions. The total energy consumption has the greatest impact on the carbon emissions of Tianjin and Hebei. The simulation results reveal that under the constraint of the carbon neutrality target, Beijing, Tianjin, and Hebei should formulate more stringent emission reduction measures to ensure that the overall carbon emission will reach its peak in 2030. The cumulative emission reduction rate should exceed 60% in 2060, and negative carbon technology should be used to offset carbon emissions of not less than 360 million tons (Mt) per year by 2060. Furthermore, the allocation results show that Beijing will receive a greater carbon quota than Hebei. The final allocation scheme will greatly promote and encourage carbon emission reduction in Hebei Province, which is conducive to achieving the goal of carbon neutrality.

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