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A novel scheme for shore power data to enhance containership-at-berth emission estimation

A novel scheme for shore power data to enhance containership-at-berth emission estimation
A novel scheme for shore power data to enhance containership-at-berth emission estimation
Ship-at-berth emissions significantly affect air quality and health of human beings in a port and its neighbourhood. However, it is challenging to estimate these emissions precisely due to stringent data requirements. Shore Power (SP) data, including its actual energy consumption and duration, offers useful insights to refine these estimates, but has yet to be fully explored. This study proposes a novel scheme incorporating SP data to improve the accuracy of containership-at-berth emission estimates and evaluate emission reduction measures. The findings reveal substantial differences among existing emission estimates from identical case studies, highlighting the importance of SP data. Additionally, it demonstrates significant emissions from low-load main engines and confirms the efficacy of SP in emission reduction. These findings provide valuable insights into emission estimation methods and their potential applications in estimating emission reduction measures, underlining the importance of policy support in facilitating the SP implementation.
1361-9209
Wang, Jinggai
7493da50-d358-4766-9827-c491b7491150
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d
Ge, Ying-En
ff8f8bad-b12e-45d6-9d70-7534dea7801b
Wang, Jinggai
7493da50-d358-4766-9827-c491b7491150
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d
Ge, Ying-En
ff8f8bad-b12e-45d6-9d70-7534dea7801b

Wang, Jinggai, Li, Huanhuan, Yang, Zaili and Ge, Ying-En (2024) A novel scheme for shore power data to enhance containership-at-berth emission estimation. Transportation Research Part D: Transport and Environment, 134, [104353]. (doi:10.1016/j.trd.2024.104353).

Record type: Article

Abstract

Ship-at-berth emissions significantly affect air quality and health of human beings in a port and its neighbourhood. However, it is challenging to estimate these emissions precisely due to stringent data requirements. Shore Power (SP) data, including its actual energy consumption and duration, offers useful insights to refine these estimates, but has yet to be fully explored. This study proposes a novel scheme incorporating SP data to improve the accuracy of containership-at-berth emission estimates and evaluate emission reduction measures. The findings reveal substantial differences among existing emission estimates from identical case studies, highlighting the importance of SP data. Additionally, it demonstrates significant emissions from low-load main engines and confirms the efficacy of SP in emission reduction. These findings provide valuable insights into emission estimation methods and their potential applications in estimating emission reduction measures, underlining the importance of policy support in facilitating the SP implementation.

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Accepted/In Press date: 31 July 2024
e-pub ahead of print date: 8 August 2024
Published date: 8 August 2024

Identifiers

Local EPrints ID: 503660
URI: http://eprints.soton.ac.uk/id/eprint/503660
ISSN: 1361-9209
PURE UUID: 2c057228-ec91-4ec1-9403-2f700d9c6f13
ORCID for Huanhuan Li: ORCID iD orcid.org/0000-0002-4293-4763

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Date deposited: 08 Aug 2025 16:34
Last modified: 22 Aug 2025 02:49

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Contributors

Author: Jinggai Wang
Author: Huanhuan Li ORCID iD
Author: Zaili Yang
Author: Ying-En Ge

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