Spatiotemporal analysis of carbon emission efficiency across economic development stages and synergistic emission reduction in the Beijing-Tianjin-Hebei region.

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Tác giả: Peipei Chen, Bin Niu, Qing Wei, Lianqing Xue, Ju Yang, Huijin Zhang

Ngôn ngữ: eng

Ký hiệu phân loại: 583.5 *Caryophyllidae

Thông tin xuất bản: England : Journal of environmental management , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 552388

Exploring regional carbon emission efficiency and its patterns is crucial for promoting a sustainable economy. This study investigated the spatiotemporal variations of carbon emissions and emission efficiency in the Beijing-Tianjin-Hebei region. Night light data was used to estimate carbon emissions, and the Super-EBM model was employed to calculate carbon emission efficiency. The migration patterns and directional changes of the emission efficiency's coordinate of center were explored using standard deviation ellipses. The Theil index was applied to analyze regional disparities in carbon emission efficiency, while both global and local Moran's indices were used to assess spatial autocorrelation. The Malmquist-Luenberger index was used to analyze the driving forces behind emission efficiency changes. The results show that total carbon emissions increased until peaking in 2013, followed by a decline. Night light data exhibited a high correlation with carbon emissions, with significant regional variations. Beijing and Tianjin saw a decrease in their carbon emissions proportions, while high-emission zones were concentrated in economically developed cities. Emission efficiency in the region increased from 0.624 in 2000 to 0.834 in 2020, with northern areas seeing more significant improvements. The spatial pattern of emission efficiency shifted from southwest to northeast, with its coordinate of center moving 13.19 km westward between 2000 and 2020. Synergistic carbon reduction strategies were proposed based on the coordination of carbon emissions and efficiency across cities. This study offers valuable insights and provides a scalable framework for regional carbon reduction strategies.
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