Advancing power sector decarbonization represents one of the most direct and effective measures in carbon emissions reductions and climate change mitigation. Replacing to-be-retired coal fired power generation with nuclear ones, also known as coal-to-nuclear conversion (C2N), has been recently discussed as an economical technology pathway in this regard. The provincial development potential of C2N in China, which may vary by natural conditions and the establishment of future standards, remains to be determined. This study analyzed this potential using a multistep process. This study newly established a comprehensive database of China's coal-fired power plants and designed an evaluation system for C2N with constraints from dimensions including earthquake geology, population density, and water availability. This is followed by a multi-scenario analysis of the potential, based on China's actual conditions and different C2N approaches. The results show that: C2N is a feasible pathway in China's low-carbon transition, with population density being the primary influencing factor on the total potential available. Under the considered constraints, the site potentials for conversion into Large Reactors (LRs) and Small Modular Reactors (SMRs) is approximately 56 and 979 GW, respectively, if China could expand inland nuclear deployment. With the continuation of current policy and inland nuclear development constrained, there would be no potential remaining for LRs, while potentials for SMRs would reduce by 94% to 55 GW, illustrating the decisive impact of inland nuclear policy on China's prospects of C2N. Further, under the two conversion approaches of complete replacement and partial replacement, the potential sites for LRs would be 6 and 10 GW, respectively, while the potential sites for SMRs would be 502 and 244 GW, respectively, suggesting major development potential of SMRs in China if C2N is allowed. This study is valuable for the early quantification of the provincial C2N development potential in China.
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Open Access
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Advances in Climate Change Research 2026, 17(2): 421-430
Published: 13 January 2026
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