Abstract
Increased CO2 emissions from urban energy consumption pose a significant challenge to regional carbon mitigation policies. In this paper, we integrated two nighttime light (NTL) data: the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) composite data to estimate the energy carbon emissions from 2000 to 2019. Then the spatiotemporal dynamics of carbon footprint and deficit in the Yellow River Basin were analyzed at the provincial, municipal, and county scales combined with NPP data. The study shows that (1) the total amount of energy consumption CO2 emissions in the Yellow River Basin had increased from 1332 Mt in 2000 to 6469 Mt in 2019, but the average annual growth rate slowed down after 2010 from 11.5 to 5.61%. (2) From 2000 to 2018, the provinces with the highest carbon footprint and carbon deficit were concentrated in Inner Mongolia and Shanxi. In 2018, Inner Mongolia’s carbon footprint was 1366.91 × 104 km2, accounting for 22.8% of the total. Cities with high carbon footprint were mainly economic centers and energy-intensive areas of various provinces. High-carbon deficit counties were mainly distributed in the western region. In 2018, 954 counties exhibited carbon deficits. (3) The carbon footprint in the Yellow River Basin at the municipal and county scales have a significant spatial correlation. The H–H clusters of the carbon footprint on the municipal scale were distributed in the middle reaches of the Yellow River Basin. At the county scale, the L-L clusters were mainly in Sichuan and eastern Henan regions. Through the analysis of the spatial and temporal evolution of carbon footprint and carbon deficit in the Yellow River Basin, it is significant to measure the degree of comprehensive coordination of carbon sources and sinks in the basin, to grasp the differences in the level of regional carbon emissions, and to promote synergistic regional governance, assist in the formulation of more precise carbon emission reduction policies, and to promote green and high-quality development.
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Funding
The financial support of this work is funded by the National Natural Science Foundation of China (NSFC) under Grant No. 41801173, National Innovation and Entrepreneurship Training Project for University (China) under Grant No. 202210430045, and University-Industry Collaborative Education Program under Grant No. S2022315).
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Jinhua Liu: methodology; conceptualization; formal analysis. Kehao Diao: writing—review and editing; software; formal analysis; data curation. Minmin Tian: conceptualization; software. PengXu: methodology; supervision.
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Liu, J., Diao, K., Tian, M. et al. Multiscale spatial–temporal evolution of energy carbon footprint in the Yellow River Basin of China based on DMSP/OLS and NPP/VIIRS integrated data. Environ Sci Pollut Res 31, 312–330 (2024). https://doi.org/10.1007/s11356-023-30826-9
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DOI: https://doi.org/10.1007/s11356-023-30826-9