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Wang, J, Li, H, Yang, Z and Ge, YE (2024) A novel scheme for shore power data to enhance containership-at-berth emission estimation. Transportation Research Part D: Transport and Environment, 134. ISSN 1361-9209
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A novel scheme for shore power data to enhance containership-at-berth emission estimation.pdf - Published Version Available under License Creative Commons Attribution. Download (4MB) | Preview |
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Shore power; Ship-at-berth emissions; Comparative analysis; Influence factor; Emission reduction measures; 0502 Environmental Science and Management; 1205 Urban and Regional Planning; 1507 Transportation and Freight Services; Logistics & Transportation |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering |
| Divisions: | Engineering |
| Publisher: | Elsevier |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 09 Oct 2024 13:29 |
| Last Modified: | 09 Oct 2024 13:30 |
| DOI or ID number: | 10.1016/j.trd.2024.104353 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/24480 |
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