IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i23p16388-d1289875.html
   My bibliography  Save this article

Optimization of Preventive Maintenance Timing of Highway Bridges Considering China’s “Dual Carbon” Target

Author

Listed:
  • Lunyou Pei

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Bing Wang

    (School of Civil & Environmental Engineering and Geography Science, Ningbo University, Ningbo 315211, China)

  • Ying Liu

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Xiaoling Liu

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

Abstract

The dual carbon target is a two-stage carbon reduction goal proposed by China, while the bridge maintenance strategy does not consider the need for sustainable development. Therefore, this article studies the optimization of bridge maintenance timing under China’s dual carbon goals. Firstly, this paper aims to minimize the total cost of maintenance and carbon emissions, considering the continuous effects of carbon pricing and emissions in the context of the dual carbon goals. The CHINAGEM-E model is employed to predict carbon prices, and a preventive maintenance decision-making method for highway bridges is established. Secondly, based on the theory of material residual strength, a degradation model for the technical condition of highway bridges is constructed. Finally, an in-depth case analysis of an in-service highway bridge is conducted to derive optimal maintenance solutions under three scenarios. In comparison to scenarios considering only maintenance costs or those based on benchmark carbon prices, the comprehensive maintenance cost under the dual carbon targets is the highest. In the total maintenance cost, carbon emission costs constitute over 50%, emphasizing the need for increased attention to carbon emission cost studies in future maintenance research. The methodology proposed in this paper is the first to connect carbon prices with the timing of preventive maintenance for bridges, providing a more scientific and sustainable basis for future highway bridge maintenance decisions.

Suggested Citation

  • Lunyou Pei & Bing Wang & Ying Liu & Xiaoling Liu, 2023. "Optimization of Preventive Maintenance Timing of Highway Bridges Considering China’s “Dual Carbon” Target," Sustainability, MDPI, vol. 15(23), pages 1-15, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16388-:d:1289875
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/23/16388/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/23/16388/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shenghao Feng & Xiujian Peng & Philip Adams, 2021. "Energy and Economic Implications of Carbon Neutrality in China -- A Dynamic General Equilibrium Analysis," Centre of Policy Studies/IMPACT Centre Working Papers g-318, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Sun, Wei & Zhang, Chongchong, 2018. "Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm," Applied Energy, Elsevier, vol. 231(C), pages 1354-1371.
    3. Huimin Bi & Hao Xiao & Kejuan Sun, 2019. "The Impact of Carbon Market and Carbon Tax on Green Growth Pathway in China: A Dynamic CGE Model Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(6), pages 1312-1325, May.
    4. Ignacio J. Navarro & Víctor Yepes & José V. Martí, 2018. "Life Cycle Cost Assessment of Preventive Strategies Applied to Prestressed Concrete Bridges Exposed to Chlorides," Sustainability, MDPI, vol. 10(3), pages 1-16, March.
    5. A. Indermühle & T. F. Stocker & F. Joos & H. Fischer & H. J. Smith & M. Wahlen & B. Deck & D. Mastroianni & J. Tschumi & T. Blunier & R. Meyer & B. Stauffer, 1999. "Holocene carbon-cycle dynamics based on CO2 trapped in ice at Taylor Dome, Antarctica," Nature, Nature, vol. 398(6723), pages 121-126, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qi, Shaozhou & Cheng, Shihan & Tan, Xiujie & Feng, Shenghao & Zhou, Qi, 2022. "Predicting China's carbon price based on a multi-scale integrated model," Applied Energy, Elsevier, vol. 324(C).
    2. Chong Zhang & Zhiying Feng, 2024. "Carbon emissions trading price forecasts by multi-perspective fusion," Economic Analysis Letters, Anser Press, vol. 3(2), pages 13-25, June.
    3. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(C).
    4. Yunting Feng & Yong Geng & Ge Zhao & Mengya Li, 2022. "Carbon Emission Constraint Policy in an OEM and Outsourcing Remanufacturer Supply Chain with Consumer Preferences," IJERPH, MDPI, vol. 19(8), pages 1-16, April.
    5. Liao, Haolan & Wu, Di & Wang, Yuhan & Lyu, Zeyu & Sun, Hongmei & Nie, Yongyou & He, He, 2022. "Impacts of carbon trading mechanism on closed-loop supply chain: A case study of stringer pallet remanufacturing," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    6. Zhang, Jinzhu & Liu, Yu & Zhou, Meifang & Chen, Boyang & Liu, Yawen & Cheng, Baodong & Xue, Jinjun & Zhang, Wei, 2022. "Regulatory effect of improving environmental information disclosure under environmental tax in China: From the perspectives of temporal and industrial heterogeneity," Energy Policy, Elsevier, vol. 164(C).
    7. Shenghao Feng & Keyu Zhang & Xiujian Peng, 2021. "Elasticity of Substitution Between Electricity and Non-Electric Energy in the Context of Carbon Neutrality in China," Centre of Policy Studies/IMPACT Centre Working Papers g-323, Victoria University, Centre of Policy Studies/IMPACT Centre.
    8. Wu, Qunli & Ma, Zhe & Meng, Fanxing, 2022. "Long-term impacts of carbon allowance allocation in China: An IC-DCGE model optimized by the hypothesis of imperfectly competitive market," Energy, Elsevier, vol. 241(C).
    9. Aman Kumar & Harish Chandra Arora & Krishna Kumar & Mazin Abed Mohammed & Arnab Majumdar & Achara Khamaksorn & Orawit Thinnukool, 2022. "Prediction of FRCM–Concrete Bond Strength with Machine Learning Approach," Sustainability, MDPI, vol. 14(2), pages 1-25, January.
    10. Sun, Wei & Zhang, Junjian, 2022. "A novel carbon price prediction model based on optimized least square support vector machine combining characteristic-scale decomposition and phase space reconstruction," Energy, Elsevier, vol. 253(C).
    11. Chun-Yao Lee & Guang-Lin Zhuo, 2021. "A Hybrid Whale Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 9(13), pages 1-19, June.
    12. Zhang, Meng & Kang, Guoqing & Wu, Lifeng & Guan, Yong, 2022. "A method for capacity prediction of lithium-ion batteries under small sample conditions," Energy, Elsevier, vol. 238(PC).
    13. Li, Jingmiao & Liu, Dehong, 2023. "Carbon price forecasting based on secondary decomposition and feature screening," Energy, Elsevier, vol. 278(PA).
    14. Sreedhar, I. & Vaidhiswaran, R. & Kamani, Bansi. M. & Venugopal, A., 2017. "Process and engineering trends in membrane based carbon capture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 659-684.
    15. Tang, Ling & Wang, Haohan & Li, Ling & Yang, Kaitong & Mi, Zhifu, 2020. "Quantitative models in emission trading system research: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    16. Cao, Jing & Dai, Hancheng & Li, Shantong & Guo, Chaoyi & Ho, Mun & Cai, Wenjia & He, Jianwu & Huang, Hai & Li, Jifeng & Liu, Yu & Qian, Haoqi & Wang, Can & Wu, Libo & Zhang, Xiliang, 2021. "The general equilibrium impacts of carbon tax policy in China: A multi-model comparison," Energy Economics, Elsevier, vol. 99(C).
    17. Zhang, Tingting & Tang, Zhenpeng & Wu, Junchuan & Du, Xiaoxu & Chen, Kaijie, 2021. "Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization algorithm," Energy, Elsevier, vol. 229(C).
    18. Ullah, Atta & Ullah, Saif & Pinglu, Chen & Khan, Saba, 2023. "Impact of FinTech, governance and environmental taxes on energy transition: Pre-post COVID-19 analysis of belt and road initiative countries," Resources Policy, Elsevier, vol. 85(PA).
    19. Li, Guohui & Ning, Zhiyuan & Yang, Hong & Gao, Lipeng, 2022. "A new carbon price prediction model," Energy, Elsevier, vol. 239(PD).
    20. Jianguo Zhou & Xuejing Huo & Xiaolei Xu & Yushuo Li, 2019. "Forecasting the Carbon Price Using Extreme-Point Symmetric Mode Decomposition and Extreme Learning Machine Optimized by the Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 12(5), pages 1-22, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16388-:d:1289875. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.