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China has become the world's largest carbon emitter, and its commitment to peak carbon emissions by 2030 is important for global development. The construction industry is one of China's biggest carbon emitters, and its peak has a direct impact on China's carbon commitment. Due to the regional heterogeneity of different provinces, the carbon emission of construction industry (CECI) at provincial level is of unique significance. To accurately predict the peak of provincial CECI, a prediction model was established by system dynamics, including direct CECI, indirect CECI and operational CECI. Taking Jiangsu province as an example, the single and multiple scenario settings with increasing R&D investment, promoting energy-saving buildings and implementing carbon trading from 2016 to 2030 was carried out, indicating that: 1) Without any carbon emission reduction measures, the CECI would maintain an annual growth rate of 5.58% to reach 530.61 million tons by 2030, and the indirect and operational CECI account for the majority of total with an average annual growth rate of 8.02% and 2.79% respectively. 2) All three measures had good carbon reduction effects, which would reduce the total CECI by 26.46% 21.68% and 10.68% respectively by 2030, but only when implemented simultaneously can CECI peak before 2030, 308.77 million tons at 2029. In the end, three policy implications was put forward. The framework presented in this paper provided a basis for the prediction of peak CECI in a province or state, which can help policy makers plan a more reasonable low-carbon development roadmap. [Display omitted] • The total carbon emissions of provincial construction industry are predicted. • Direct, indirect and operational carbon emissions are predicted respectively. • The total carbon emissions will not peak before 2030 under the basic scenario. • Carbon emissions will peak at 308.77 million tons in 2029 under multiple scenario. • Encouraging R&D investment, energy-saving buildings and carbon trading are crucial. [ABSTRACT FROM AUTHOR]