Carbon Emission Accounting and Emission Reduction Path of Container Terminal Under Low-Carbon Perspective
Accurate carbon emission estimation across all operational stages of container terminals is essential for advancing low-carbon development in the transportation sector and designing effective emission reduction pathways. This study develops a two-layer carbon accounting framework that integrates vessel berthing–waiting and terminal operations, tailored to the operational characteristics of Shanghai Port container terminals. The Ship Traffic Emission Assessment Model (STEAM) is applied to estimate emissions during berthing, while a bottom-up method is employed for mobile-mode container handling operations. Targeted mitigation strategies—such as shore power adoption, operational optimization, and “oil-to-electricity” or “oil-to-gas” transitions—are evaluated through comparative analysis. Results show that vessels generate substantial emissions during erthing, which can be significantly reduced (by over 60%) through shore power usage. In terminal operations, internal transport trucks have the highest emissions, followed by straddle carriers, container tractors, and forklifts; in stacking, tire cranes dominate emissions. Comprehensive comparisons indicate that “oil-to-electricity” can reduce total emissions by approximately 39%, while “oil-to-gas” can achieve reductions of about 73%. These findings provide technical and policy insights for supporting the green transformation of container terminals under the national dual-carbon strategy.
Institutions
- University of Science and Technology of China (CN)
- Chinese Academy of Sciences (CN)
- Hefei Institutes of Physical Science (CN)
- Institute of Intelligent Machines (CN)
- State Key Laboratory of Transducer Technology (CN)
- Beijing Municipal Ecological and Environmental Monitoring Center (CN)
- Chinese Research Academy of Environmental Sciences (CN)
Publication Details
- Journal
- Atmosphere
- Published
- 2025-10-03
- DOI
- https://doi.org/10.3390/atmos16101158
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00