Review and prediction: Carbon emissions from the materialization of residential buildings in China

IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Sustainable Cities and Society Pub Date : 2025-03-01 Epub Date: 2025-02-10 DOI:10.1016/j.scs.2025.106211
Xing Xiong , Xiaojun Li , Shaobo Chen , Dian Chen , Jinchen Lin
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Abstract

Previous studies on carbon emissions from the materialization of residential buildings differ significantly in their case sources, methods, and research findings. Consequently, it is essential to investigate the general characteristics and driving factors of carbon emissions in this context. A systematic review was carried out with research papers on carbon emissions of the materialization stage of residential buildings in China. Analysis of the carbon emission results reveals an average carbon emission intensity (CEI) of 409.04 kgCO2e/m². Through standardized coefficients and significance tests, the effects of 20 driving factors were quantified. Four explanatory models were developed using enter regression to interpret the results of existing multi-family building samples. Additionally, four predictive models were created through backward elimination to assist designers in predicting CEI during the conceptual design phase. The findings indicate that minimizing new construction areas is the most effective strategy for reducing total carbon emissions, and adopting prefabricated construction methods significantly decreases CEI. Conversely, enhancements in building performance may inadvertently increase CEI. Other key impact factors on CEI include building age, climate zone, and calculating object. It is important to recognize that the driving factors for the three sub-stages of production, transportation, and construction vary considerably, and thus should be studied separately whenever feasible. This research contributes to promoting carbon reduction in the building industry by advancing research on the calculation of carbon emissions.
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回顾与预测:中国住宅建筑实体化带来的碳排放
以往关于住宅建筑实体化碳排放的研究在案例来源、方法和研究结果上存在很大差异。因此,有必要在此背景下研究碳排放的一般特征和驱动因素。对中国住宅建筑实体化阶段的碳排放研究论文进行了系统的综述。碳排放分析结果显示,平均碳排放强度(CEI)为409.04 kgCO2e/m²。通过标准化系数和显著性检验,量化了20个驱动因素的影响。利用进入回归建立了四个解释模型来解释现有多户建筑样本的结果。此外,通过逆向消去法建立了四个预测模型,以帮助设计者在概念设计阶段预测CEI。研究结果表明,减少新建筑面积是减少总碳排放的最有效策略,采用装配式建筑方式显著降低了CEI。相反,构建性能的增强可能会无意中增加CEI。其他影响CEI的关键因素包括建筑年龄、气候带和计算对象。重要的是要认识到,生产、运输和建设三个子阶段的驱动因素差异很大,因此应该在可行的情况下单独研究。本研究通过推进碳排放计算的研究,有助于促进建筑行业的碳减排。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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