Carbon Emissions Peak Prediction and the Reduction Pathway in Buildings during Operation in Jilin Province Based on LEAP

• Main Authors: Haiyan Duan, Shipei Zhang, Siying Duan, Weicheng Zhang, Zhiyuan Duan, Shuo Wang, Junnian Song, Xian’en Wang
• Format: Article
• Language: English
• Published: MDPI AG 2019-08-01
• Series: Sustainability
• Subjects: building; cold region; reducing carbon emission; long-energy alternatives planning (LEAP) system; terminal energy use; Jilin Province
• Online Access: https://www.mdpi.com/2071-1050/11/17/4540

The building sector has gradually become a major contributor of carbon emissions in recent years. Its carbon emissions, which result from the long heating period and considerable consumption of coal in residential buildings during operation, must be reduced. To this end, the long-range energy alternatives planning system was adopted for the forecasting of carbon emissions in baseline scenarios, energy-saving, energy-saving−low-carbon, and low-carbon. On the basis of these predictions, the contributions of heating, cooling, cooking, illumination, washing, and other activities to carbon emissions were analyzed. The influencing factors in the reduction of carbon emissions from residential buildings in a cold region were identified. The results showed that energy-saving−low-carbon was the optimal scenario to reduce carbon emissions. Meanwhile, carbon emissions will peak in 2030, with a value of 42.06 Mt under the same scenario. As the top three influencing factors, heating, cooling, and cooking contribute 55.74%, 18.86%, and 17.29% of carbon emissions, respectively. Sensitivity results showed the differential effects of 32 factors on the reduction of carbon emissions in residential buildings. Carbon emissions could be reduced by 17.41%, 35.51%, 31.10%, and 14.10% by controlling the building scale, heating, cooling, and cooking, respectively. To this end, seven factors, including the rationing of central heating, were identified. Then, pathways to reducing carbon emissions were proposed under different scenarios. The present research fills the gap between reality and the predicted pathway, considering the heterogeneity of the climate.