Exploring Material Selection and Applications for Embedded Carbon Reduction in the Built Environment

Authors

  • Jingwen He Samfox School of Architecture, Washington University in St. Louis, California, United States of America
  • Qian Meng School of Architecture and Design, University of Technology Sydney, Sydney, Australia
  • Haoran Xu Graduate School of Architecture, Planning and Preservation, Columbia University, New York, United States of America

DOI:

https://doi.org/10.5281/zenodo.14242407

Keywords:

embodied carbon, material selection, sustainable construction, life cycle assessment, net-zero emissions

Abstract

The building and construction industry is a significant contributor to global greenhouse gas emissions, with 37% of total emissions attributed to this sector. While efforts have primarily targeted operational carbon emissions, which stem from building operations like heating and cooling, the urgent need to address embodied carbon—associated with the materials used and their life cycle—has gained attention. This paper explores the critical role of material selection and innovative practices in reducing embedded carbon in the built environment. It highlights collaborative models and international cooperation essential for decarbonizing building materials to achieve net-zero emissions by mid-century. The findings underscore that embodied carbon currently represents a growing proportion of a building's overall carbon footprint, necessitating proactive measures in the design and construction phases. By integrating life cycle assessments and prioritizing sustainable material choices, stakeholders can significantly diminish carbon emissions and align with global climate goals. Through case studies and best practices, this research advocates for a comprehensive approach to carbon reduction that encompasses both operational and embodied emissions in the built environment.

Downloads

Download data is not yet available.

References

Zou, J., Zhao, H., & Li, N. (2024). Operational efficiency through machine learning and optimization in supply chain management. Academic Journal of Science and Technology, 12(1).

Zhao, S., Zhang, T., & Li, N. (2024). Machine learning analysis of key features in household financial decision-making. Academic Journal of Science and Technology, 12(2), 1-6.

Zhang, X., Xu, L., Li, N., & Zou, J. (2024). Research on credit risk assessment optimization based on machine learning.

Yao, T. (2024, August). Research on the local head loss coefficient in short-tube hydraulic testing. in 3rd International Conference on Applied Mechanics and Engineering Structures (AMES 2024), pp. 89-97. Atlantis Press.

Xiangyu, G., Yao, T., Gao, F., Chen, Y., Jian, X., & Ma, H. (2024). A new granule extrusion-based for 3D printing of POE: studying the effect of printing parameters on mechanical properties with “response surface methodology. Iranian Polymer Journal, 1-12.

Wang, H., Li, Z., & Li, J. (2024). Road car image target detection and recognition based on YOLOv8 deep learning algorithm.

Wang, H., & Tong, X. Layer-wise asynchronous training of neural network with synthetic gradient on distributed system.

Wang, H., Li, J., & Li, Z. (2024). AI-generated text detection and classification based on bert deep learning algorithm. arXiv preprint arXiv:2405.16422.

Salman, U., Belaish, S., Ji, Z., Huang, D., Zheng, N., & Xu, B. (2022). Comparing the economic value of lithium-ion battery technologies in the nine wholesale electricity markets in North America. iEnergy, 1(3), 363-373.

Shimin LE, Ke XU, Huang Y, Xinye SH. An Xgboost based system for financial fraud detection. in E3S Web of Conferences, 214, pp. 02042. EDP Sciences.

Xu, W., Chen, J., & Xiao, J. (2024). A hybrid price forecasting model for the stock trading market based on AI technique. Authorea Preprints.

Liu, H., Shen, F., Qin, H., & Gao, F. (2024). Research on flight accidents prediction based back propagation neural network. arXiv preprint arXiv:2406.13954.

Li, N., Xu, L., Zhang, X., & Zou, J. (2024). Research on financial fraud detection based on deep graph neural network.

Li, N., Xu, L., Zhang, X., & Zou, J. (2024). Research on Financial Fraud detection based on deep graph neural network.

Lai, S., Feng, N., Sui, H., Ma, Z., Wang, H., Song, Z., ... & Yue, Y. (2024). FTS: A framework to find a faithful TimeSieve. arXiv preprint arXiv:2405.19647.

Huang, S., Diao, S., & Wan, Y. (2024, September). Application of machine learning methods in predicting functional recovery in ischemic stroke patients. in The 1st International Scientific and Practical Conference “Innovative Scientific Research: Theory, Methodology, Practice”, Boston, USA. International Science Group, 289, pp. pp. 240.

Xiao, J., Deng, T., & Bi, S. (2024). Comparative analysis of LSTM, GRU, and transformer models for stock price prediction. arXiv preprint arXiv:2411.05790.

Huang, D., Liu, Z., & Li, Y. (2024). Research on tumors segmentation based on image enhancement method. arXiv preprint arXiv:2406.05170.

Fu, Y., & Yao, T. (2024). Investigation of O phase spheroidization behavior in Ti2AlNb alloy using high-throughput experiments. Journal of Materials Engineering and Performance, 1-11.

Ding, Y., Li, J., Wang, H., Liu, Z., & Wang, A. (2025). Attention-enhanced multimodal feature fusion network for clothes-changing person re-identification. Complex & Intelligent Systems, 11(1), 1-15.

Sun, Y., & Ortiz, J. (2024). GenAI-Driven Cyberattack detection in V2X networks for enhanced road safety and autonomous vehicle defense. International Journal of Advance in Applied Science Research, 3, 67-75.

Diao, S., Wei, C., Wang, J., & Li, Y. (2024). Ventilator pressure prediction using recurrent neural network. arXiv preprint arXiv:2410.06552.

Wang, C., Chen, J., Xie, Z., & Zou, J. (2024, July). Research on education big data for student's academic performance analysis based on machine learning. in Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Education Digitalization and Computer Science, pp. 223-227.

Wang, C., Chen, J., Xie, Z., & Zou, J. (2024, July). Research on education big data for student's academic performance analysis based on machine learning. in Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Education Digitalization and Computer Science, pp. 223-227.

Wang, C., Chen, J., Xie, Z., & Zou, J. (2024). Research on personalized teaching strategies selection based on deep learning.

Liu, H., Xie, R., Qin, H., & Li, Y. (2024). Research on dangerous flight weather prediction based on machine learning. arXiv preprint arXiv:2406.12298.

Shui, H., Sha, X., Chen, B., & Wu, J. (2024, May). Stock weighted average price prediction based on feature engineering and Lightgbm model. in Proceedings of the 2024 International Conference on Digital Society and Artificial Intelligence, pp. 336-340.

Li, B., Zhang, K., Sun, Y., & Zou, J. (2024). Research on travel route planning optimization based on large language model.

Huang, D., Xu, L., Tao, W., & Li, Y. (2024). Research on genome data recognition and analysis based on louvain algorithm.

Diao, S., Huang, S., & Wan, Y. (2024, September). Early detection of cervical adenocarcinoma using immunohistochemical staining patterns analyzed through computer vision technology. in The 1st International Scientific and Practical Conference “Innovative Scientific Research: Theory, Methodology, Practice”, Boston, USA. International Science Group, 289, pp. p. 256.

Chen, Y., Yan, S., Liu, S., Li, Y., & Xiao, Y. (2024, August). EmotionQueen: A benchmark for evaluating empathy of large language models. Findings of the Association for Computational Linguistics, pp. 2149-2176.

Wang, Y., He, Z., Zou, J., Xie, H., & Bao, J. (2024). Energy transition for sustainable economy: What is the role of government governance and public concern?. Finance Research Letters, 106087.

Wang, D. (Ed.). (2016). Information Science and Electronic Engineering: Proceedings of the 3rd International Conference of Electronic Engineering and Information Science (ICEEIS 2016), January 4-5, Harbin, China. CRC Press.

Qu, M. (2024). High precision measurement technology of geometric parameters based on binocular stereo vision application and development prospect of the system in metrology and detection. Journal of Computer Technology and Applied Mathematics, 1(3), 23-29.

Diao, S., Huang, D., & Jiang, G. (2024). The role of artificial intelligence in personalized medicine through advanced imaging.

Huang, D., Ma, H., Wang, J., Du, Y., & Li, R. (2024). Mof-mediated paper-based (bio) sensors for detecting of food and environmental pollutants: Preparation strategies and emerging applications. Microchemical Journal, 111692.

Li, B., Jiang, G., Li, N., & Song, C. (2024, August). Research on large-scale structured and unstructured data processing based on large language model. in Proceedings of the International Conference on Machine Learning, Pattern Recognition and Automation Engineering, pp. 111-116.

Feng, Z., Ge, M., Meng, Q., & Chen, Y. (2024). Research on old building renovation strategies by using green building technologies.

Ge, M., Feng, Z., & Meng, Q. (2024). Urban planning and green building technologies based on artificial intelligence: Principles, applications, and global case study analysis. Applied Science and Engineering Journal for Advanced Research, 3(5), 18-27.

Feng, Z., Ge, M., & Meng, Q. (2024). Enhancing energy efficiency in green buildings through artificial intelligence. Applied Science and Engineering Journal for Advanced Research, 3(5), 10-17.

Diao, S., Wei, C., Wang, J., & Li, Y. (2024). Ventilator pressure prediction using recurrent neural network. arXiv preprint arXiv:2410.06552.

Jin, W., Liu, H., & Shen, F. (2024). Artificial intelligence in flight safety: Fatigue monitoring and risk mitigation technologies. Applied Science and Engineering Journal for Advanced Research, 3(5), 1-9.

Li, B., Jiang, G., Li, N., & Song, C. (2024). Research on large-scale structured and unstructured data processing based on large language model.

Jin, W., Liu, H., & Shen, F. (2024). AI-assisted pilot fatigue risk assessment: Integrating facial recognition and physiological signal analysis.

Jiang, G., Zhao, S., Yang, H., & Zhang, K. (2024). Research on finance risk management based on combination optimization and reinforcement learning.

Li, B., Zhang, K., Sun, Y., & Zou, J. (2024). Research on travel route planning optimization based on large language model.

Diao, S., Wan, Y., Huang, S., & Ma, H. (2024, July). Research on cancer prediction and identification based on multimodal medical image fusion. in Proceedings of the 3rd International Symposium on Robotics, Artificial Intelligence and Information Engineering, pp. 120-124.

Meng, Q., Ge, M., & Feng, Z. (2024). The integration of artificial intelligence in architectural visualization enhances augmented realism and interactivity.

Peng, Z. H. A. N. G., Bin-MeiZi, Z. H. A. N. G., Jian-Ke, Z. O. U., & Xiang-Beng, L. I. U. (2018). The methods, effects and mechanism of priming attachment security towards social behaviors. Journal of Psychological Science, (3), 615.

Wang, C., Chen, J., Xie, Z., & Zou, J. (2024). Research on personalized teaching strategies selection based on deep learning.

Chen, J. (2024). School reforms for low-income students under conflict theory. Journal of Advanced Research in Education, 3(3), 36-44.

Wang, C., Chen, J., Xie, Z., & Zou, J. (2024). Research on education big data for students academic performance analysis based on machine learning. arXiv preprint arXiv:2407.16907.

Downloads

Published

2024-11-29

How to Cite

He, J., Meng, Q., & Xu, H. (2024). Exploring Material Selection and Applications for Embedded Carbon Reduction in the Built Environment. Applied Science and Engineering Journal for Advanced Research, 3(6), 51–59. https://doi.org/10.5281/zenodo.14242407