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Reduction Strategies for Greenhouse Gas Emissions from High-Speed Railway Station Buildings in a Cold Climate Zone of China

Author

Listed:
  • Nan Wang

    (School of Architecture, Tianjin University, No. 92 Weijin Street, Nankai District, Tianjin 300072, China)

  • Daniel Satola

    (Research Centre of Zero Emission Neighbourhoods in Smart Cities (FME-ZEN), Department of Architecture and Technology, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

  • Aoife Houlihan Wiberg

    (Belfast School of Architecture and the Built Environment, Faculty of Computing, Engineering and the Built Environment, Ulster University, Belfast BT15 1ED, UK)

  • Conghong Liu

    (School of Architecture, Tianjin University, No. 92 Weijin Street, Nankai District, Tianjin 300072, China)

  • Arild Gustavsen

    (Research Centre of Zero Emission Neighbourhoods in Smart Cities (FME-ZEN), Department of Architecture and Technology, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

Abstract

Implementing China’s emission reduction regulations requires a design approach that integrates specific architectural and functional properties of railway stations with low greenhouse gas (GHG) emission. This article analyzes life cycle GHG emissions related to materials production, replacement and operational energy use to identify design drivers and reduction strategies implemented in high-speed railway station (HSRS) buildings. A typical middle-sized HSRS building in a cold climate zone in China is studied. A detailed methodology was proposed for the development and assessment of emission reduction strategies through life cycle assessment (LCA), combined with a building information model (BIM). The results reveal that operational emissions contribute the most to total GHG emissions, constituting approximately 81% while embodied material emissions constitute 19%, with 94 kgCO 2eq /m 2 ·a and 22 kgCO 2eq /m 2 ·a respectively. Optimizing space can reduce operational GHG emissions and service life extension of insulation materials contributes to a 15% reduction in embodied GHG emissions. In all three scenarios, the reduction potentials of space, envelope, and material type optimization were 28.2%, 13.1%, and 3.5% and that measures for reduced life cycle emissions should focus on space in the early stage of building design. This study addresses the research gap by investigating the life cycle GHG emissions from HSRS buildings and reduction strategies to help influence the design decisions of similar projects and large space public buildings which are critical for emission reduction on a larger scale.

Suggested Citation

  • Nan Wang & Daniel Satola & Aoife Houlihan Wiberg & Conghong Liu & Arild Gustavsen, 2020. "Reduction Strategies for Greenhouse Gas Emissions from High-Speed Railway Station Buildings in a Cold Climate Zone of China," Sustainability, MDPI, vol. 12(5), pages 1-22, February.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:1704-:d:324760
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    References listed on IDEAS

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    1. Antonio Ángel Rodríguez Serrano & Santiago Porras Álvarez, 2016. "Life Cycle Assessment in Building: A Case Study on the Energy and Emissions Impact Related to the Choice of Housing Typologies and Construction Process in Spain," Sustainability, MDPI, vol. 8(3), pages 1-29, March.
    2. Christofer Skaar & Nathalie Labonnote & Klodian Gradeci, 2018. "From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA," Sustainability, MDPI, vol. 10(7), pages 1-19, July.
    3. Babak Raji & Martin J. Tenpierik & Andy Van den Dobbelsteen, 2017. "Early-Stage Design Considerations for the Energy-Efficiency of High-Rise Office Buildings," Sustainability, MDPI, vol. 9(4), pages 1-28, April.
    4. Mechri, Houcem Eddine & Capozzoli, Alfonso & Corrado, Vincenzo, 2010. "USE of the ANOVA approach for sensitive building energy design," Applied Energy, Elsevier, vol. 87(10), pages 3073-3083, October.
    5. A.M. Fogheri, 2015. "Energy Efficiency in Public Buildings," Rivista economica del Mezzogiorno, Società editrice il Mulino, issue 3-4, pages 763-784.
    6. Baoquan Cheng & Jingwei Li & Vivian W. Y. Tam & Ming Yang & Dong Chen, 2020. "A BIM-LCA Approach for Estimating the Greenhouse Gas Emissions of Large-Scale Public Buildings: A Case Study," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    7. Asian Development Bank (ADB) & Asian Development Bank (ADB) & Asian Development Bank (ADB) & Asian Development Bank (ADB), 2015. "Improving Energy Efficiency and Reducing Emissions through Intelligent Railway Station Buildings," ADB Reports RPT157604, Asian Development Bank (ADB).
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    Cited by:

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    2. Zhen Liu & Peixuan Li & Fenghong Wang & Mohamed Osmani & Peter Demian, 2022. "Building Information Modeling (BIM) Driven Carbon Emission Reduction Research: A 14-Year Bibliometric Analysis," IJERPH, MDPI, vol. 19(19), pages 1-26, October.
    3. Wanbei Jiang & Weidong Liu, 2020. "Provincial-Level CO 2 Emissions Intensity Inequality in China: Regional Source and Explanatory Factors of Interregional and Intraregional Inequalities," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    4. A. H. S. Garmabaki & Adithya Thaduri & Stephen Famurewa & Uday Kumar, 2021. "Adapting Railway Maintenance to Climate Change," Sustainability, MDPI, vol. 13(24), pages 1-27, December.
    5. Fang, Zigeng & Yan, Jiayi & Lu, Qiuchen & Chen, Long & Yang, Pu & Tang, Junqing & Jiang, Feng & Broyd, Tim & Hong, Jingke, 2023. "A systematic literature review of carbon footprint decision-making approaches for infrastructure and building projects," Applied Energy, Elsevier, vol. 335(C).
    6. Ahmad Jrade & Farnaz Jalaei & Jieying Jane Zhang & Saeed Jalilzadeh Eirdmousa & Farzad Jalaei, 2023. "Potential Integration of Bridge Information Modeling and Life Cycle Assessment/Life Cycle Costing Tools for Infrastructure Projects within Construction 4.0: A Review," Sustainability, MDPI, vol. 15(20), pages 1-25, October.

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