Spatiotemporal dynamics of CO2 emissions using nighttime light data: a comparative analysis between the Yellow and Yangtze River Basins in China
Wei Wei,
Haibo Du (),
Libang Ma,
Chunfang Liu and
Junju Zhou
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Wei Wei: Northwest Normal University
Haibo Du: Nanjing Normal University
Libang Ma: Northwest Normal University
Chunfang Liu: Northwest Normal University
Junju Zhou: Northwest Normal University
Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 1, No 44, 1102 pages
Abstract:
Abstract Scientific estimation and dynamic monitoring of CO2 emission trends are an important basis for formulating regional differentiated carbon reduction strategies. Using the integrated nighttime light data, this study estimated CO2 emissions in the Yellow River Basin (YRB) and Yangtze River Basin (YZRB) and discussed the similarities and differences of the spatial distribution of CO2 emissions for the two river basins. The results showed that: (1) The CO2 emissions in the two basins continued to rise, but the growth rate decreased from 2000 to 2018, showing an overall convergence trend, but have not yet reached carbon peak. (2) The high emission and high agglomeration areas were located in Shandong Province in the downstream of the YRB, Shanxi, Shaanxi and Inner Mongolia in the midstream and upstream, and the Yangtze River Delta (YRD). (3) Compared with the YRB, the growth rate of CO2 emissions in the YZRB is slower, and the growth rate declines greatly. In the YRB, it had higher CO2 emissions amount, wider area of high carbon emissions and more obvious spatial agglomeration than that in the YZRB. (4) According to CO2 emissions and economic development level, 220 cities of the two river basins were classified three types: low CO2–low development, high CO2–low development and high CO2–high development.
Keywords: CO2 emissions; Nighttime light data; Spatiotemporal dynamics; Regional differentiation; Yellow River Basin; Yangtze River Basin (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-022-02750-4
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