Smart estimation of pollutant emissions from marine transport

• Autorzy: Uriasz Janusz , Wolak Aleksander

Identyfikatory

DOI

10.36163/aon-2021-0002

• Języki publikacji: EN

Abstrakty

EN

The production and analysis of transport statistics is part of the process of maritime transport management and monitoring. As there is strong need to protect the environment through the reduction of greenhouse gas emissions by the transport sector, CO2 in particular, it is necessary to assess the emissions of pollutants emitted by sea-going ships. The article presents an intelligent method of estimating pollution volumes based on harmonised sets of data on vessel traffic obtained from the monitoring of the Automatic Identification System and developed artificial intelligence models. The created methods allow estimating emissions of pollutants from individual sea vessels, aggregate pollutant amounts in a selected geographical area, or on a selected route and in port. The data obtained can be visualized for conducting statistical analyses. The work was performed under the TranStat project executed jointly with the Central Statistical Office. "The project financed by the National Centre of Research and Development as part of the program Gospostrateg, Agreement Gospostrateg1/383385/12/NCBR/2018”.

Słowa kluczowe

EN

emission of pollutants; artificial intelligence; harmonized datasets; maritime transport; statistics; AIS

• Wydawca: Polskie Forum Nawigacyjne
• Czasopismo: Annual of Navigation
• Rocznik: 2021
• Tom: No. 27
• Strony: 17--27
• Opis fizyczny: Bibliogr. 5 poz., rys., wykr.

Twórcy

autor

Uriasz Janusz

• Department of Electronics and Telecommunications Maritime University of Szczecin Szczecin, Poland

autor

Wolak Aleksander

• Department of Electronics and Telecommunications Maritime University of Szczecin Szczecin, Poland

Bibliografia

• 1. European Commission, Communication on 'Fit for 55': delivering the EU's 2030 climate target on the way to climate neutrality, COM(2021)550 final.
• 2. European Commission, Entec, Quantification of emissions from ships associated with ship movements between ports in the European Community, 2005.
• 3. EEA, 2013. EMEP/EEA air pollutant emission inventory guidebook 2013: technical guidance to prepare national emission inventories. EEA Tech. Rep. 23 http://dx.doi.org/10.2800/92722.
• 4. Cepowski T., Determination of design formulas for container ships at the preliminary design stage using artificial neural network and multiple nonlinear regression, Ocean Engineering 238(1), 2021.
• 5. Cepowski T., Chorab P., The Use of Artificial Neural Networks to Determine the Engine Power and Fuel Consumption of Modern Bulk Carriers, Tankers and Container Ships, Energies 14(16):4827, 2021.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).