Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data
This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identifi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/12/2/320 |
| _version_ | 1797297808909271040 |
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| author | João N. Ribeiro da Silva Tiago A. Santos Angelo P. Teixeira |
| author_facet | João N. Ribeiro da Silva Tiago A. Santos Angelo P. Teixeira |
| author_sort | João N. Ribeiro da Silva |
| collection | DOAJ |
| description | This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identification based on the visited port terminal is described. The methodology is implemented in a computational tool, SEA (Ship Emission Assessment). First, the accuracy of the method for ship type identification is assessed and then the methodology is validated by comparing its predictions with those of two other methodologies. The tool is applied to three case studies using AIS data of maritime traffic along the Portuguese coast and in the port of Lisbon for one month. The first case study compares the estimated emissions of a ferry and a cruise ship, with the ferry emitting much less than the cruise ship. The second case study estimates the geographical distribution of emissions in the port of Lisbon, with terminals corresponding to areas with a heavier concentration of exhaust emissions. The third case study focuses on the emissions from a container ship sailing along the continental coast of Portugal, differing considerably from port traffic since it operates exclusively in cruising mode. |
| first_indexed | 2024-03-07T22:25:45Z |
| format | Article |
| id | doaj.art-727f73beb6704d3387313aa60dde1af9 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-07T22:25:45Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-727f73beb6704d3387313aa60dde1af92024-02-23T15:23:17ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-02-0112232010.3390/jmse12020320Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System DataJoão N. Ribeiro da Silva0Tiago A. Santos1Angelo P. Teixeira2Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico (IST), Universidade de Lisboa (UL), 1049-001 Lisbon, PortugalCentre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico (IST), Universidade de Lisboa (UL), 1049-001 Lisbon, PortugalCentre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico (IST), Universidade de Lisboa (UL), 1049-001 Lisbon, PortugalThis paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identification based on the visited port terminal is described. The methodology is implemented in a computational tool, SEA (Ship Emission Assessment). First, the accuracy of the method for ship type identification is assessed and then the methodology is validated by comparing its predictions with those of two other methodologies. The tool is applied to three case studies using AIS data of maritime traffic along the Portuguese coast and in the port of Lisbon for one month. The first case study compares the estimated emissions of a ferry and a cruise ship, with the ferry emitting much less than the cruise ship. The second case study estimates the geographical distribution of emissions in the port of Lisbon, with terminals corresponding to areas with a heavier concentration of exhaust emissions. The third case study focuses on the emissions from a container ship sailing along the continental coast of Portugal, differing considerably from port traffic since it operates exclusively in cruising mode.https://www.mdpi.com/2077-1312/12/2/320Automatic Identification Systemport and coastal maritime trafficship emissionsports |
| spellingShingle | João N. Ribeiro da Silva Tiago A. Santos Angelo P. Teixeira Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data Journal of Marine Science and Engineering Automatic Identification System port and coastal maritime traffic ship emissions ports |
| title | Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data |
| title_full | Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data |
| title_fullStr | Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data |
| title_full_unstemmed | Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data |
| title_short | Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data |
| title_sort | methodology for predicting maritime traffic ship emissions using automatic identification system data |
| topic | Automatic Identification System port and coastal maritime traffic ship emissions ports |
| url | https://www.mdpi.com/2077-1312/12/2/320 |
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