Carbon Emission Control in Civil Engineering Management: Optimization and Future Trends Based on Whole Life Cycle Management

DOI

10.2991/978-94-6463-688-8_48How to use a DOI?

Keywords

Civil engineering management; carbon emission control; ARIMA model; life cycle management; BIM technology

Abstract

Carbon mission control in civil engineering management is crucial for climate change response. Based on life-cycle management, optimizing carbon emissions has become a key topic and future trend. This paper analyzes carbon emissions in material production, supply, and construction stages, predicts energy-related emissions using ARIMA models, and proposes LCM strategies. By examining building material selection, construction processes, and emission sources, targeted optimization measures are proposed. BIM and LCA technologies are innovatively applied to enhance carbon data accuracy and managerial control. As global climate policies evolve and technology innovates, professional training in low-carbon management is essential. The widespread application of intelligent technology and low-carbon materials in civil engineering management holds significant promise.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ziyi Bao
AU  - Zhiguo Li
PY  - 2025
DA  - 2025/04/30
TI  - Carbon Emission Control in Civil Engineering Management: Optimization and Future Trends Based on Whole Life Cycle Management
BT  - Proceedings of the 2024 6th International Conference on Civil Architecture and Urban Engineering (ICCAUE 2024)
PB  - Atlantis Press
SP  - 474
EP  - 480
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-688-8_48
DO  - 10.2991/978-94-6463-688-8_48
ID  - Bao2025
ER  -