IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v360y2024ics0306261924002691.html
   My bibliography  Save this article

Ship energy consumption analysis and carbon emission exploitation via spatial-temporal maritime data

Author

Listed:
  • Chen, Xinqiang
  • Lv, Siying
  • Shang, Wen-long
  • Wu, Huafeng
  • Xian, Jiangfeng
  • Song, Chengcheng

Abstract

Global greenhouse gas emission attracts significant attentions across varied communities, and carbon emission (CE) reduction has become hot topic in the maritime field considering that appropriately 3% CE come from the field. The prerequisite for fulfilling the task is to accurately quantify the ship CE. To achieve the aim, the study utilizes indicators, such as carbon dioxide (CO2) emission, CO2 index, fuel consumption, energy efficiency operational indicator (EEOI), fleet energy efficiency management index (FEEMI), to analyze ship energy consumption. We employ ship voyage data from container, oil tanker, bulk carrier and liquefied natural gas (LNG) carrier to evaluate ship energy consumption. We have testified EEOI variation tendency under different ship cargo loading volume states (i.e., full/partial load) and speed deceleration scenario. Moreover, the FEEMI indicator is used to determine energy efficiency for different ship fleets (container ship fleet, oil tanker fleet, bulk carrier fleet, LNG fleet). Experimental results suggest that EEOI is proportional to ship energy consumption when the sailing distance and cargo volume are constant. The ship EEOI indicator calculated in full-loaded status is obviously smaller than the counterpart under partial-load status. The fleet energy consumption efficiency shows a slight increase (at least 1%) due to release of ship energy efficiency management plan. The research findings can help maritime policy-makers provide more reasonable regulations for the purpose of ship energy consumption enhancement.

Suggested Citation

  • Chen, Xinqiang & Lv, Siying & Shang, Wen-long & Wu, Huafeng & Xian, Jiangfeng & Song, Chengcheng, 2024. "Ship energy consumption analysis and carbon emission exploitation via spatial-temporal maritime data," Applied Energy, Elsevier, vol. 360(C).
    • Handle: RePEc:eee:appene:v:360:y:2024:i:c:s0306261924002691
    DOI: 10.1016/j.apenergy.2024.122886
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924002691
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.122886?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Qingchen & Li, Hongchang & Shang, Wen-long & Wang, Kun, 2022. "Spatio-temporal distribution of Chinese cities’ air quality and the impact of high-speed rail," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    2. Shang, Wen-Long & Zhang, Mengxiao & Wu, Guoyuan & Yang, Lan & Fang, Shan & Ochieng, Washington, 2023. "Estimation of traffic energy consumption based on macro-micro modelling with sparse data from Connected and Automated Vehicles," Applied Energy, Elsevier, vol. 351(C).
    3. Vujović, Tanja & Petković, Zdravka & Pavlović, Miloš & Jović, Srdjan, 2018. "Economic growth based in carbon dioxide emission intensity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 179-185.
    4. Katarzyna Prill & Cezary Behrendt & Marcin Szczepanek & Iwona Michalska-Pożoga, 2020. "A New Method of Determining Energy Efficiency Operational Indicator for Specialized Ships," Energies, MDPI, vol. 13(5), pages 1-17, March.
    5. César O. Peralta P. & Giovani T. T. Vieira & Simon Meunier & Rodrigo J. Vale & Mauricio B. C. Salles & Bruno S. Carmo, 2019. "Evaluation of the CO 2 Emissions Reduction Potential of Li-ion Batteries in Ship Power Systems," Energies, MDPI, vol. 12(3), pages 1-19, January.
    6. Gao, Ruobin & Li, Ruilin & Hu, Minghui & Suganthan, Ponnuthurai Nagaratnam & Yuen, Kum Fai, 2023. "Dynamic ensemble deep echo state network for significant wave height forecasting," Applied Energy, Elsevier, vol. 329(C).
    7. Shang, Wen-Long & Chen, Yishui & Yu, Qing & Song, Xuewang & Chen, Yanyan & Ma, Xiaolei & Chen, Xiqun & Tan, Zhijia & Huang, Jianling & Ochieng, Washington, 2023. "Spatio-temporal analysis of carbon footprints for urban public transport systems based on smart card data," Applied Energy, Elsevier, vol. 352(C).
    8. Lixian Fan & Yuhan Xu & Meifeng Luo & Jingbo Yin, 2022. "Modeling the interactions among green shipping policies," Maritime Policy & Management, Taylor & Francis Journals, vol. 49(1), pages 62-77, January.
    9. Yujiro Wada & Tatsumi Yamamura & Kunihiro Hamada & Shinnosuke Wanaka, 2021. "Evaluation of GHG Emission Measures Based on Shipping and Shipbuilding Market Forecasting," Sustainability, MDPI, vol. 13(5), pages 1-22, March.
    10. Chungen Yin & Christian Kjaer Rosenvinge & Marcus Pless Sandland & Anders Ehlers & Keun Woo Shin, 2023. "Improve Ship Propeller Efficiency via Optimum Design of Propeller Boss Cap Fins," Energies, MDPI, vol. 16(3), pages 1-17, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Zhijun & Fei, Jiangang & Du, Yuquan & Ong, Kok-Leong & Arisian, Sobhan, 2024. "A near real-time carbon accounting framework for the decarbonization of maritime transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
    2. Han, Peixiu & Liu, Zhongbo & Li, Chi & Sun, Zhuo & Yan, Chunxin, 2024. "A novel federated learning-based two-stage approach for ship energy consumption optimization considering both shipping data security and statistical heterogeneity," Energy, Elsevier, vol. 309(C).
    3. Tomasz Cepowski & Paweł Kacprzak, 2024. "Reducing CO 2 Emissions through the Strategic Optimization of a Bulk Carrier Fleet for Loading and Transporting Polymetallic Nodules from the Clarion-Clipperton Zone," Energies, MDPI, vol. 17(14), pages 1-30, July.
    4. Tan, Zhijia & Shao, Shuai & Zhang, Di & Shang, Wen-Long & Ochieng, Washington & Han, Yi, 2024. "Decarbonizing the inland container fleet with carbon cap-and-trade scheme," Applied Energy, Elsevier, vol. 376(PB).

    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. Tian, Shirun & Yan, Fei & Shang, Wen-Long & Majumdar, Arnab & Chen, Haibo & Chen, Mingyang & Zeinab, Mohammed & Tian, Yuchen, 2025. "Energy consumption analysis of trains based on multi-mode virtual coupling operation control strategies," Applied Energy, Elsevier, vol. 377(PD).
    2. Nestor Goicoechea & Luis María Abadie, 2021. "Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System," Energies, MDPI, vol. 14(22), pages 1-25, November.
    3. Daniela Nicoleta Sahlian & Adriana Florina Popa & Raluca Florentina Creţu, 2021. "Does the Increase in Renewable Energy Influence GDP Growth? An EU-28 Analysis," Energies, MDPI, vol. 14(16), pages 1-16, August.
    4. Giovani T. T. Vieira & Derick Furquim Pereira & Seyed Iman Taheri & Khalid S. Khan & Mauricio B. C. Salles & Josep M. Guerrero & Bruno S. Carmo, 2022. "Optimized Configuration of Diesel Engine-Fuel Cell-Battery Hybrid Power Systems in a Platform Supply Vessel to Reduce CO 2 Emissions," Energies, MDPI, vol. 15(6), pages 1-34, March.
    5. Pan, Junyu & Du, Lizhao & Wu, Haitao & Liu, Xiaoqian, 2024. "Does environmental law enforcement supervision improve corporate carbon reduction performance? Evidence from environmental protection interview," Energy Economics, Elsevier, vol. 132(C).
    6. Hu, Wenfa & He, Xinhua, 2024. "The role of fiscal policies in supporting a transition to a low-carbon economy: Evidence from the Chinese shipping industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    7. Renjie Li & Yanyan Qin, 2024. "Car-Following Strategy Involving Stabilizing Traffic Flow with Connected Automated Vehicles to Reduce Particulate Matter (PM) Emissions in Rainy Weather," Sustainability, MDPI, vol. 16(5), pages 1-23, February.
    8. Zheng, Zihao & Ali, Mumtaz & Jamei, Mehdi & Xiang, Yong & Abdulla, Shahab & Yaseen, Zaher Mundher & Farooque, Aitazaz A., 2023. "Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    9. Tan, Zhijia & Shao, Shuai & Zhang, Di & Shang, Wen-Long & Ochieng, Washington & Han, Yi, 2024. "Decarbonizing the inland container fleet with carbon cap-and-trade scheme," Applied Energy, Elsevier, vol. 376(PB).
    10. Dong, Haoxuan & Shi, Junzhe & Zhuang, Weichao & Li, Zhaojian & Song, Ziyou, 2025. "Analyzing the impact of mixed vehicle platoon formations on vehicle energy and traffic efficiencies," Applied Energy, Elsevier, vol. 377(PA).
    11. Konur, Olgun & Yuksel, Onur & Aykut Korkmaz, S. & Ozgur Colpan, C. & Saatcioglu, Omur Y. & Koseoglu, Burak, 2023. "Operation-dependent exergetic sustainability assessment and environmental analysis on a large tanker ship utilizing Organic Rankine cycle system," Energy, Elsevier, vol. 262(PA).
    12. Wu, Han & Gao, Xiao-Zhi & Heng, Jia-Ni, 2024. "Bio-multisensory-inspired gate-attention coordination model for forecasting short-term significant wave height," Energy, Elsevier, vol. 294(C).
    13. Bagherabadi, Kamyar Maleki & Skjong, Stian & Bruinsma, Jogchum & Pedersen, Eilif, 2023. "Investigation of hybrid power plant configurations for an offshore vessel with co-simulation approach," Applied Energy, Elsevier, vol. 343(C).
    14. Aziz, Ghazala & Sarwar, Suleman & Waheed, Rida & Khan, Mohd Saeed, 2023. "Significance of hydrogen energy to control the environmental gasses in light of COP26: A case of European Countries," Resources Policy, Elsevier, vol. 80(C).
    15. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    16. Mahdavi-Meymand, Amin & Sulisz, Wojciech, 2023. "Application of nested artificial neural network for the prediction of significant wave height," Renewable Energy, Elsevier, vol. 209(C), pages 157-168.
    17. Huang, Kai & Zhou, Peng & Liu, Zhiyuan & Tang, Tianli & Zhang, Honggang & Jiang, Wei, 2024. "The calculation and distribution of CAV carbon emissions on urban transportation systems: A comparative analysis of renewable and non-renewable energy sources," Renewable Energy, Elsevier, vol. 230(C).
    18. Zhao, Lingxiao & Li, Zhiyang & Pei, Yuguo & Qu, Leilei, 2024. "Disentangled Seasonal-Trend representation of improved CEEMD-GRU joint model with entropy-driven reconstruction to forecast significant wave height," Renewable Energy, Elsevier, vol. 226(C).
    19. Pang, Junheng & Dong, Sheng, 2023. "A novel multivariable hybrid model to improve short and long-term significant wave height prediction," Applied Energy, Elsevier, vol. 351(C).
    20. Liang, Zeyu & Qian, Tao & Korkali, Mert & Glatt, Ruben & Hu, Qinran, 2024. "A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement," Applied Energy, Elsevier, vol. 376(PA).

    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:eee:appene:v:360:y:2024:i:c:s0306261924002691. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.