five

None -

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/None_-/29536708
下载链接
链接失效反馈
官方服务:
资源简介:
Green renovation of building (GRB) is usually full of challenges and limited by multiple factors, including environment, technology, materials, and region. It is necessary to lower the impact on residents’ lives and reasonably address construction waste during the renovation process. In this study, a system dynamics model was constructed according to the whole lifecycle theory and green development theory to evaluate the comprehensive benefits of GRB. This model was adopted to analyze the constraints during the renovation process. In addition, the key indicators, were simulated, including pollution, greenness, and resident satisfaction. The system dynamics model simulation results indicated that during the decision-making and project phases, the simulated greenness value of GRB reached 1.623, with a variation value of 1.515. This finding substantiated the substantial influence of this phase on greenness transformation. During the engineering warranty and post-evaluation phase, the greenness change value was the highest of 6.173. Therefore, long-term maintenance and continuous improvement are crucial for greenness. Meanwhile, the proportion of green energy usage gradually increased during the GRB process, while other energy consumption and pollution indicators decreased. This demonstrated the potential of GRB in promoting sustainable development. The study has validated the efficacy of the simulation and analysis of GRB projects through the system dynamics method while providing theoretical foundations for the planning and implementation of GRB projects. By comprehensively considering technological, economic, policy, and social factors, system dynamics model can assist decision-makers in optimizing GRB strategies, achieving a dual improvement in environmental and economic benefits.
创建时间:
2025-07-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作