Abstract
The analysis of household consumption carbon emissions (HCCEs), a significant source of CO2 emissions, is essential to achieving China’s carbon peak before 2030 and carbon neutrality before 2060. Based on the calculation of urban and rural HCCEs during 2005–2019, the differences between urban and rural areas, spatial–temporal pattern and agglomeration characteristics of HCCEs were analyzed, and the panel quantile STIRPAT model was constructed to empirically test the influence of socioeconomic factors on urban and rural HCCEs at different quantile levels. The results indicate that, first, China’s HCCEs are generally growing, indirect HCCEs are more than direct HCCEs, urban HCCEs are far more than rural, and the gap has a growing trend. Second, the urban and rural HCCEs have significant disequilibrium and agglomeration characteristics in space, and high-high and low-low agglomerations dominated the local region. Third, household size and the number of patent application authorizations increase the urban and rural HCCEs, while the consumption capacity and consumption structure inhibit the urban and rural HCCEs. In addition, the level of education also has an inhibitory effect on the rural HCCEs, while the aging degree of the population has a significant positive impact on the rural HCCEs when it is only at the 90th percentile. Finally, it is suggested to formulate differentiated emission reduction policies.
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This research was supported by the National Natural Science Foundation of China (No. 72002029) and Philosophy and Social Science Foundation of Heilongjiang Province (No. 21JYB152).
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Y.L.: responsible for data collection and draft writing. X.L.: responsible for the revision of the first draft. H.L.: responsible for the typesetting of the paper. Y.N.: responsible for drawing the pictures in the paper. J.Z.: Responsible for correct paper references.
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Lian, Y., Lin, X., Luo, H. et al. Empirical research on household consumption carbon emissions and key impact factors in urban and rural China. Environ Sci Pollut Res 30, 62423–62439 (2023). https://doi.org/10.1007/s11356-023-26292-y
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DOI: https://doi.org/10.1007/s11356-023-26292-y