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Exploring Optimisation Pathways for Underground Space Quality Under the Synergy of Multidimensional Perception and Environmental Parameters

  • Tianning Yao
  • , Liang Sun*
  • , Lin Geng
  • , Yao Xu*
  • , Ziqi Xu
  • , Kuntao Hu
  • , Xing Chen
  • , Pan Liao
  • , Jin Wang
  • *Corresponding author for this work
  • China University of Mining and Technology
  • Harbin institute of technology
  • Southwest Jiaotong University
  • Yancheng Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

With the acceleration of urbanisation and the increased utilisation of underground space, providing a comfortable and healthy environment in public underground areas has emerged as a significant research topic. This study constructs a comprehensive decision-making framework for underground space environments by integrating human perception evaluations with physical environmental parameters. Using Shanghai Wujiaochang as a case study, field data collection and questionnaire surveys were conducted to evaluate key factors such as temperature (22.63 °C–26.39 °C), wind speed (0.26 m/s–0.67 m/s), and sound levels (59.68 dB–61.21 dB) for commercial-oriented spaces, and 63.15 dB–75.45 dB for transport-oriented spaces) to users’ perceived experiences. The appropriate ranges for key parameters were identified through single-indicator fitted regression analysis and the XGBoost machine-learning model, revealing the relationship between environmental parameters and human perception. The results indicated significant differences in user needs across various functional spaces, with commercial-oriented areas emphasising environmental attractiveness and comfort, while transport-oriented spaces prioritised access efficiency and safety. This study provided quantitative design benchmarks for underground spaces’ dynamic regulation and sustainable management, proposing a precise and adaptive environmental decision-making framework that combines physical parameters with user-perception feedback.

Original languageEnglish
Article number204
JournalBuildings
Volume15
Issue number2
DOIs
StatePublished - Jan 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • environmental regulation
  • machine learning
  • multidimensional perception
  • suitability parameters
  • underground space

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