Carbon emission prediction control coefficient analysis for public institutions towards carbon neutrality by 2060: A case study of Tianjin

Abstract

Accurate carbon emissions prediction and development of mitigation pathways are critical but challenging for achieving carbon neutrality in the public building sector. This study systematically analysed the energy consumption and emissions of over 7000 public institution buildings in Tianjin, China, using data from 2016 to 2024. The Grey model (1,1) and Grey–Markov models were employed to analyse historical trends and forecast future carbon emissions. Comparative results showed the Grey–Markov model performed better and was validated by external data, with actual values falling within the corresponding uncertainty intervals. Projections indicated that total carbon emissions and emission intensity for Tianjin's public buildings are to decline, reaching approximately 3.4290 million tCO₂ and 66.87 kgCO₂/m² by 2035. However, scenario analysis revealed that the current annual emission control coefficient proposed by the government (k = 0.98) is insufficient to achieve carbon neutrality by 2060. To limit residual emissions to 5% of the 2023 baseline by 2060 requires strengthening annual control to k ≤ 0.92; achieving 1% residual requires k ≤ 0.87. Achieving these pathways demands accelerated and coordinated efforts in building retrofits, deep energy system decarbonization, robust policy, and financial frameworks. This study provides a scientifically grounded methodology for emission prediction and targeted mitigation strategy formulation.