Analysis of the LCA-Emergy and Carbon Emissions Sustainability Assessment of a Building System with Coupled Energy Storage Modules

被引:0
|
作者
Zhang, Junxue [1 ]
Pan, Zhihong [1 ]
Li, Yingnan [2 ,3 ]
机构
[1] Jiangsu Univ Sci & Technol, Sch Civil Engn & Architecture, Zhenjiang 212100, Peoples R China
[2] Korea Univ, OJeong Resilience Inst, Seoul 02841, South Korea
[3] Jiangsu Univ, Dept Environm Design, Zhenjiang 212013, Peoples R China
基金
中国博士后科学基金;
关键词
sustainable analysis; LCA-emergy and carbon emission; neural network method; energy storage module; NEURAL-NETWORKS; CONSUMPTION;
D O I
10.3390/buildings15020151
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper uses a perspective of life cycle ecological emergy and carbon footprint to quantitatively verify the sustainable status of building systems; it also employs a neural network model to predict and analyze their long-term ecological and carbon footprint effects. The research results show that the stages of building material production and building operation play a major role in the emergy and carbon emissions of the entire building system, and their changes show an inverse trend. As the building system operates, the greater the system loss and consumption, the environmental load rate (ELR) will gradually increase, and the sustainability parameter (ESI) will also gradually decrease. The integration of energy storage modules significantly improves the sustainability of the building system. When calculated over five time periods (5 years, 10 years, 20 years, 30 years, and 50 years), the overall carbon emission reduction rates after adding the energy storage module are 39.4%, 33.6%, 39.2%, 42.5%, and 38.8% respectively, demonstrating that the energy storage module has a significant positive effect on the sustainability of the building system. This study reveals the energy efficiency and environmental impact of the building system throughout its entire life cycle, providing a scientific basis for optimizing building design.
引用
收藏
页数:23
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