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

Author

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  • 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
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    References listed on IDEAS

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    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).

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