The Development Path and Carbon-Reduction Method of Low-Carbon Pilot Urban Areas in China - Lining Zhou; Qingqin Wang; Haizhu Zhou; Yiqiang Jiang; Rongxin Yin; Tong Lu (Buildings)
Urban carbon emissions account for 75% of the total social emissions and are a key area for achieving the country’s “dual carbon” goals. This study takes the Sino-Singapore Tianjin Eco-City as a case, constructs a multi-dimensional carbon emission accounting model, integrates six systems, including buildings, transportation, water systems, solid waste, renewable energy, and carbon sinks, and proposes a comprehensive research method that takes into account both long-term prediction and a short-term dynamic analysis. The long-term emission trends under different scenarios are simulated through the KAYA model. It is found that under the enhanced low-carbon scenario, the Eco-City will reach its peak in 2043 (2.253 million tons of CO2) and drop to 2.182 million tons of CO2 in 2050. At the same time, after comparing models, such as random forest and support vector machine, the XGBoost algorithm is adopted for short-term prediction (R2 = 0.984, MAE = 0.195). The results show that it is significantly superior to traditional methods and can effectively capture the dynamic changes in fields, such as buildings and transportation. Based on the prediction results, the study proposes six types of collaborative emission-reduction paths: improving building energy efficiency (annual emission reduction of 93800 tons), promoting green travel (58,900 tons), increasing the utilization rate of non-conventional water resources (3700 tons), reducing per capita solid waste generation (14,400 tons), expanding the application of renewable energy (288,200 tons), and increasing green space carbon sinks (135,000 tons). The total annual emission-reduction potential amounts to 594,000 tons. This study provides a valuable reference for developing carbon reduction strategies in urban areas.