The Chinese government has committed to reaching its carbon emissions peak by 2030, which is a major undertaking. However, traditional carbon allocation processes may face a suite of difficulties, including the dynamics of the allocation principle, the independence of the allocation entities and
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The Chinese government has committed to reaching its carbon emissions peak by 2030, which is a major undertaking. However, traditional carbon allocation processes may face a suite of difficulties, including the dynamics of the allocation principle, the independence of the allocation entities and data availability. Considering these difficulties, in this study, we developed a multi-level carbon allocation model that integrates five sectors and 30 provinces in China. Based on the clustering of the sectoral carbon emission of major countries (or regions), the model simulates and analyzes carbon allocation at the provincial level in China under the peak commitment. The results of this study are as follows: First, in contrast to allocating national carbon allocations (NCAs) to provinces, the grandfather principle is the only option for allocating NCAs to sectors. In the future, China’s carbon emissions pattern will be dominated by the contribution from electricity and heat production sectors. This carbon emission pattern can be further divided into three categories: Pattern M, where the manufacturing and construction sectors significantly contribute to total emissions; Pattern R, where the residential buildings and commercial and public services sectors have a significant contribution to total emissions; and Pattern T, where the contribution of the transport sector to total emissions is substantial. Second, emission patterns affect the allocation of sectoral carbon allocations at the national level (SCANs). Although the preferences vary from sector to sector, they are consistent between the national and provincial levels. Third, compared with sectoral preferences, provincial preferences are more complex. Sixteen provinces, including Hebei, Shanxi and Inner Mongolia, prefer Pattern T. There are nine provinces, for example, Guangdong, Shandong and Jiangsu, whose preferred pattern is M; and five provinces, represented by Beijing, Shanghai and Tianjin, have a preference for Pattern R. Last, but not least, to achieve China’s peak commitment, different provinces face alternative peak pressures. It is worth mentioning that, in patterns R and T, provinces with a high proportion of manufacturing and construction sector emissions, such as Guangdong, Shandong, Jiangsu and Zhejiang, may have to increase the share of carbon emissions from the transport sector or from residential buildings and commercial and public services sectors to postpone their peak year.