Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155594
Title: Abatement of atmospheric pollutant emissions with autonomous shipping in maritime transportation using Bayesian probabilistic forecasting
Authors: Liu, Jiahui
Law, Adrian Wing-Keung
Duru, Okan
Keywords: Engineering::Civil engineering
Issue Date: 2021
Source: Liu, J., Law, A. W. & Duru, O. (2021). Abatement of atmospheric pollutant emissions with autonomous shipping in maritime transportation using Bayesian probabilistic forecasting. Atmospheric Environment, 261, 118593-. https://dx.doi.org/10.1016/j.atmosenv.2021.118593
Journal: Atmospheric Environment 
Abstract: This study examines the potential abatement of environmental pollutant emissions with the adoption of autonomous vessels in future maritime transportation using Bayesian probabilistic forecasting algorithm. The emission reductions can be attributed to the related technological advancement, including particularly the improvements in navigational performance and berthing in port, which can achieve better efficiencies and lower fluctuations in sailing speeds. The scenario modeling approach is first established based on the foreseeable development of energy policies and usage as well as ship operations. Subsequently, assessment is performed in five major ports worldwide, namely Shanghai, Singapore, Long Beach, Hamburg, Tokyo from Year 2020 to 2050. The results are compared to the corresponding projections with manned shipping to determine the probabilistic emission abatements with the gradual adoption of autonomous ships into the fleet. Overall, the results provide a better understanding of the future environmental benefits with autonomous shipping to the policymakers, shipowners, and shipping industry.
URI: https://hdl.handle.net/10356/155594
ISSN: 1352-2310
DOI: 10.1016/j.atmosenv.2021.118593
Schools: School of Civil and Environmental Engineering 
Rights: © 2021 Elsevier Ltd. All rights reserved. This paper was published in Atmospheric Environment and is made available with permission of Elsevier Ltd.
Fulltext Permission: embargo_20230922
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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