Dynamic integrated simulation of carbon emission reduction potential in China's building sector

IF 10.5 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Qiang Du , Zilang Wan , Mengqi Yang , Xiaoyan Wang , Libiao Bai
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Abstract

The building sector has received increasing attention due to its significant contribution to carbon emissions and great reduction potential. With continuous technology implementation, it is critical to identify the trajectories of emissions and potential reduction for China's building sector to achieve carbon peak and carbon neutrality targets. This study develops an integrated model by combining the system dynamics (SD) model and the long-range energy alternatives planning (LEAP) model to estimate energy consumption and carbon emissions of different types of buildings. The LEAP model is constructed based on the predictions from the SD model, which identifies the critical activity level parameters including number of households and building stocks by type. Coupled with scenario analysis, the model is applied to simulate the building emissions reduction potential and the contribution of five mitigation technologies across four scenarios. The results indicate that carbon emissions will peak at 2.80 Billion tons (Bt) in 2032 under the business as usual scenario (BAS). By 2060, reductions of 28.55 %, 59.03 %, and 76.53 % will be achieved under the advanced technology scenario (ATS), intersectoral synergistic scenario (ISS), and continuous improvement scenario (CIS), respectively. Among the five technologies, electrification and efficient end-use device technologies contribute the greatest reductions of 0.16 Bt and 0.23 Bt, respectively. Under the CIS, carbon emissions will advance toward 2024 with a peak of 2.47 Bt. This study not only provides a theoretical tool for energy and emissions analysis but also formulates targeted technology roadmaps for building sector emission mitigation.
中国建筑行业碳减排潜力的动态综合模拟
建筑行业因其对碳排放的重要贡献和巨大的减排潜力而受到越来越多的关注。随着技术的不断实施,确定中国建筑行业的排放轨迹和减排潜力对于实现碳峰值和碳中和目标至关重要。本研究结合系统动力学(SD)模型和远期能源替代规划(LEAP)模型,建立了一个综合模型,用于估算不同类型建筑的能耗和碳排放。LEAP 模型是根据 SD 模型的预测建立的,该模型确定了关键的活动水平参数,包括家庭数量和不同类型的建筑存量。结合情景分析,该模型用于模拟四种情景下的建筑减排潜力和五种减排技术的贡献。结果表明,在 "一切照旧 "情景(BAS)下,碳排放量将在 2032 年达到峰值 28.0 亿吨(Bt)。到 2060 年,在先进技术情景(ATS)、部门间协同情景(ISS)和持续改进情景(CIS)下,将分别实现 28.55%、59.03% 和 76.53% 的减排。在这五种技术中,电气化和高效终端设备技术的减排量最大,分别为 0.16 Bt 和 0.23 Bt。在 CIS 条件下,碳排放量将在 2024 年达到峰值 24.7 Bt。这项研究不仅为能源和排放分析提供了理论工具,还为建筑行业减排制定了有针对性的技术路线图。
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来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
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