[Prediction of Long-term Decarbonization Trends in Cities Under Carbon Emission Constraints].

Abstract

With climate change posing an increasingly serious threat to the environment, economic development, and human health, global attention is gradually focusing on CO₂. As the main source of carbon emissions from global energy activities, cities have become a key battlefield for reducing carbon emissions. To accurately predict the long-term carbon emission trend of cities, this study first constructed a carbon emission constraint policy indicator system according to the logic of "policy objectives policy system policy execution market mechanism." Subsequently, using the BP neural network model, a long-term carbon emission trend prediction model for cities was constructed by combining GDP, industrial structure, population size, energy structure, and energy intensity, and long-term carbon emissions forecasts were made for Beijing, Tianjin, Shanghai, and Chongqing from 2021 to 2060. The results showed that： ① The total carbon emissions of Scope 1, Scope 2, and Scope 3 of Beijing, Shanghai, and Chongqing all showed a significant downward trend, whereas Tianjin showed a trend of first increasing and then decreasing, reaching a peak of 619 million tons in 2025； ② under the overall downward trend, there was a plateau period between Beijing and Shanghai, in which carbon emissions remained relatively stable during a specific time without a significant decrease； ③ an overly complex policy system may have suppressed the efficiency of carbon reduction and a reasonable intensity of policy implementation is the key to ensuring a sustained decrease in carbon emissions； and ④ slowing down the expansion of carbon market coverage appropriately had a positive effect on promoting further reduction of carbon emissions.