Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports
This study examines the impact of monitoring, reporting, and verification (MRV) system indicators on the costs associated with the emissions trading system (ETS) of the maritime sector in the European Union. Since maritime transport has recently been incorporated into the ETS, it becomes essential t...
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| Format: | Article |
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MDPI AG
2025-03-01
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| Series: | Inventions |
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| Online Access: | https://www.mdpi.com/2411-5134/10/2/28 |
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| author | Javier Vaca-Cabrero Nicoletta González-Cancelas Alberto Camarero-Orive Jorge Quijada-Alarcón |
| author_facet | Javier Vaca-Cabrero Nicoletta González-Cancelas Alberto Camarero-Orive Jorge Quijada-Alarcón |
| author_sort | Javier Vaca-Cabrero |
| collection | DOAJ |
| description | This study examines the impact of monitoring, reporting, and verification (MRV) system indicators on the costs associated with the emissions trading system (ETS) of the maritime sector in the European Union. Since maritime transport has recently been incorporated into the ETS, it becomes essential to understand how different operational and environmental factors affect the economic burden of shipping companies and port competitiveness. To this end, a model based on Bayesian networks is used to analyse the interdependencies between key variables, facilitating the identification of the most influential factors in the determination of the costs of the ETS. The results show that fuel efficiency and CO<sub>2</sub> emissions in port are decisive in the configuration of costs. In particular, it was identified that emissions during the stay in port have a greater weight than expected, which suggests that strategies such as the use of electrical connections in port (cold ironing) may be key to mitigating costs. Likewise, navigation patterns and traffic regionalisation show a strong correlation with ETS exposure, which could lead to adjustments in maritime routes. This probabilistic model offers a valuable tool for strategic decision-making in the maritime sector, benefiting shipping companies, port operators, and policymakers. However, future research could integrate new technologies and regulatory scenarios to improve the accuracy of the analysis and anticipate changes in the ETS cost structure. |
| format | Article |
| id | doaj-art-68d71710641f46dcaa28a1c88d96f05a |
| institution | DOAJ |
| issn | 2411-5134 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Inventions |
| spelling | doaj-art-68d71710641f46dcaa28a1c88d96f05a2025-08-20T03:13:49ZengMDPI AGInventions2411-51342025-03-011022810.3390/inventions10020028Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European PortsJavier Vaca-Cabrero0Nicoletta González-Cancelas1Alberto Camarero-Orive2Jorge Quijada-Alarcón3Department of Transport, Territorial and Urban Planning Engineering, Universidad Politécnica de Madrid, 28040 Madrid, SpainDepartment of Transport, Territorial and Urban Planning Engineering, Universidad Politécnica de Madrid, 28040 Madrid, SpainDepartment of Transport, Territorial and Urban Planning Engineering, Universidad Politécnica de Madrid, 28040 Madrid, SpainFaculty of Civil Engineering, Technological University of Panama, Panama City 0819-07289, PanamaThis study examines the impact of monitoring, reporting, and verification (MRV) system indicators on the costs associated with the emissions trading system (ETS) of the maritime sector in the European Union. Since maritime transport has recently been incorporated into the ETS, it becomes essential to understand how different operational and environmental factors affect the economic burden of shipping companies and port competitiveness. To this end, a model based on Bayesian networks is used to analyse the interdependencies between key variables, facilitating the identification of the most influential factors in the determination of the costs of the ETS. The results show that fuel efficiency and CO<sub>2</sub> emissions in port are decisive in the configuration of costs. In particular, it was identified that emissions during the stay in port have a greater weight than expected, which suggests that strategies such as the use of electrical connections in port (cold ironing) may be key to mitigating costs. Likewise, navigation patterns and traffic regionalisation show a strong correlation with ETS exposure, which could lead to adjustments in maritime routes. This probabilistic model offers a valuable tool for strategic decision-making in the maritime sector, benefiting shipping companies, port operators, and policymakers. However, future research could integrate new technologies and regulatory scenarios to improve the accuracy of the analysis and anticipate changes in the ETS cost structure.https://www.mdpi.com/2411-5134/10/2/28maritime emissions trading system (ETS)monitoring reporting and verification (MRV)Bayesian networksport competitivenessdigitalisationdecision-making |
| spellingShingle | Javier Vaca-Cabrero Nicoletta González-Cancelas Alberto Camarero-Orive Jorge Quijada-Alarcón Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports Inventions maritime emissions trading system (ETS) monitoring reporting and verification (MRV) Bayesian networks port competitiveness digitalisation decision-making |
| title | Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports |
| title_full | Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports |
| title_fullStr | Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports |
| title_full_unstemmed | Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports |
| title_short | Bayesian Networks Applied to the Maritime Emissions Trading System: A Tool for Decision-Making in European Ports |
| title_sort | bayesian networks applied to the maritime emissions trading system a tool for decision making in european ports |
| topic | maritime emissions trading system (ETS) monitoring reporting and verification (MRV) Bayesian networks port competitiveness digitalisation decision-making |
| url | https://www.mdpi.com/2411-5134/10/2/28 |
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