王韶华, 赵暘春, 张伟, 刘晔. 京津冀碳排放的影响因素分析及达峰情景预测基于供给侧改革视角[J]. 北京理工大学学报(社会科学版), 2022, 24(6): 54-66. DOI: 10.15918/j.jbitss1009-3370.2022.0626
    引用本文: 王韶华, 赵暘春, 张伟, 刘晔. 京津冀碳排放的影响因素分析及达峰情景预测基于供给侧改革视角[J]. 北京理工大学学报(社会科学版), 2022, 24(6): 54-66. DOI: 10.15918/j.jbitss1009-3370.2022.0626
    WANG Shaohua, ZHAO Yangchun, ZHANG Wei, LIU Ye. Analysis on Influencing Factors of Carbon Emission and Scenario Forecast of Carbon Peak in Beijing-Tianjin-HebeiA Perspective of Supply-side Reform[J]. Journal of Beijing Institute of Technology (Social Sciences Edition), 2022, 24(6): 54-66. DOI: 10.15918/j.jbitss1009-3370.2022.0626
    Citation: WANG Shaohua, ZHAO Yangchun, ZHANG Wei, LIU Ye. Analysis on Influencing Factors of Carbon Emission and Scenario Forecast of Carbon Peak in Beijing-Tianjin-HebeiA Perspective of Supply-side Reform[J]. Journal of Beijing Institute of Technology (Social Sciences Edition), 2022, 24(6): 54-66. DOI: 10.15918/j.jbitss1009-3370.2022.0626

    京津冀碳排放的影响因素分析及达峰情景预测基于供给侧改革视角

    Analysis on Influencing Factors of Carbon Emission and Scenario Forecast of Carbon Peak in Beijing-Tianjin-HebeiA Perspective of Supply-side Reform

    • 摘要: 京津冀经济增长与碳排放尚未完全脱钩,难以协同调控发展与减排。为缓解此类结构性矛盾,基于STIRPAT拓展模型,在供给侧改革视角下运用通径分析揭示要素流动、产业协同、制度干预等因素对京津冀碳排放的影响机理,从人力、资本、技术等要素层面设计调控情景进行达峰预测。研究发现:(1)转变河北的高碳排放模式是有效促进京津冀低碳转型的重要基础;(2)劳动生产率、政府干预、经济增长均促进京津冀碳排放,能源强度、产业结构升级协同均抑制京津冀碳排放。资本效率促进北京碳排放,而抑制天津、河北碳排放。此外,劳动生产率、经济增长是重要中介因素;(3)均衡调控情景下,京津冀整体、天津、河北均如期达峰。资本调控情景下,京津冀协同调控水平最高,河北达峰时间提前5年;人力调控情景下,京津冀协同调控水平最低,整体达峰时间推迟5年。

       

      Abstract: The economic growth of Beijing, Tianjin and Hebei has not yet been decoupled from carbon emissions, and it is difficult to coordinate their economic development and carbon emission reduction. In order to alleviate such structural contradictions, based on the STIRPAT expansion model, path analysis is used to reveal the impact mechanism of factors such as factor circulation, industrial collaboration, and institutional intervention on carbon emissions in Beijing, Tianjin and Hebei from the perspective of supply side reform, and peak prediction is made by designing adjustment scenarios from the perspective of human, capital, technology and other factors. the results show that: (1) Changing the high carbon emission model of Hebei is an important foundation for effectively promoting the low carbon transformation of Beijing-Tianjin-Hebei; (2) Labor productivity, government intervention and economic growth all promote the carbon emission of Beijing-Tianjin-Hebei, while energy intensity and industrial structure upgrading and coordination all restrain its carbon emission. Capital efficiency promotes carbon emissions in Beijing, while curbs carbon emissions in Tianjin and Hebei. In addition, labor productivity and economic growth are important intermediary factors. (3)Under the balanced regulation scenario, the Beijing-Tianjin-Hebei, Tianjin and Hebei reached the peak on schedule. Under the capital regulation scenario, the coordinated regulation level of Beijing-Tianjin-Hebei is the highest, and the peak time of Hebei is 5 years ahead of schedule; Under the human resource regulation scenario, the coordinated regulation level of Beijing Tianjin Hebei is the lowest, and the overall peak time is delayed by 5 years.

       

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