Evaluation of environmental impact and GHG emission with energy system modeling combined with LCA in building sector: A review

Abstract

Entering the 21st century, building energy consumption ranks first in total energy consumption, environmental pollution is increasing, and the construction sector has become the main energy source. The ability to reduce greenhouse gas emissions by replacing fossil fuels such as oil, gas and coal with fuels from renewable sources is a key factor in the development of net zero energy buildings. Therefore, it is important to analyze and organize previous and current research in this area to get an overview of the importance of built environmental assessment and net zero energy buildings. This review therefore summarizes the literature of previous life cycle assessment (LCA) and energy modeling studies conducted for environmental assessment of construction and construction-related industry sectors, considering construction products and entire building systems, buildings and civil structures. Bibliographic methods and scientometric analyzes have been adopted and proposed to tentatively explore research themes in this field. This observation indicates that BIM-LCA (Building Information Management Life Cycle Assessment) optimization is currently an important and inevitable research focus in the building-related energy field. Finally, there was a qualitative discussion on the achievement of key goals. We provided an up-to-date literature review on LCA construction, used energy system models to assess environmental impacts, and discussed key challenges in LCA construction, ongoing research, and possible solutions to solve the identified problems. The results also provide a comprehensive knowledge framework linking previous and current research areas with future research trends. The results provide researchers with an interdisciplinary focus on insights and solid engineering knowledge from the latest research on BIM-LCA.

Advanced Energy Performance Modelling: Case Study of an Engineering and Technology Precinct

“…This data should be meticulously integrated with sophisticated predictive models to facilitate precise prognostications of future energy requirements. Only through this rigorous integration can one implement energy management initiatives that are effective and optimize energy utilization sustainably [16].…”