Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel
Abstract Pollution adjacent to the continent's shores has increased in the last decades, so it has been necessary to establish an energy policy to improve environmental conditions. One of the proposed solution was the search of alternative fuels to the commonly used in Short Sea Shipping to red...
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2019
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Online Access: | http://dx.doi.org/10.2478/kones-2019-0018 https://content.sciendo.com/view/journals/kones/26/1/article-p147.xml https://www.sciendo.com/pdf/10.2478/kones-2019-0018 |
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crdegruyter:10.2478/kones-2019-0018 2023-05-15T16:51:35+02:00 Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel Serrano, Beatriz Molina González Cancelas, Nicoleta Soler Flores, Francisco 2019 http://dx.doi.org/10.2478/kones-2019-0018 https://content.sciendo.com/view/journals/kones/26/1/article-p147.xml https://www.sciendo.com/pdf/10.2478/kones-2019-0018 en eng Walter de Gruyter GmbH http://creativecommons.org/licenses/by-nc-nd/3.0 CC-BY-NC-ND Journal of KONES volume 26, issue 1, page 147-158 ISSN 2354-0133 journal-article 2019 crdegruyter https://doi.org/10.2478/kones-2019-0018 2022-05-11T14:46:42Z Abstract Pollution adjacent to the continent's shores has increased in the last decades, so it has been necessary to establish an energy policy to improve environmental conditions. One of the proposed solution was the search of alternative fuels to the commonly used in Short Sea Shipping to reduce pollution levels in Europe. Studies and researches show that liquefied natural gas could meet the European Union environmental requirements. Even environmental benefits are important; currently there is not significant number of vessels using it as fuel. Moreover, main target of this article is exposing result of a research in which a methodology to establish the most relevant variables in the decision to implement liquefied natural gas in Short Sea Shipping has been development using data mining. A Bayesian network was constructed because this kind of network allows to get graphically the relationships between variables and to determine posteriori values that quantify their contributions to decision-making. Bayesian model has been done using data from some European countries (European Union, Norway and Iceland) and database was generated by 35 variables classified in 5 categories. Main obtained conclusion in this analysis is that variables of transport and international trade and economy and finance are the most relevant in the decision-making process when implementing liquefied natural gas. Even more, it can be stablish that capacity of liquefied natural gas regasification terminals under construction and modal distribution of water cargo transportation continental as the most decisive variables because they are the root nodes in the obtained network. Article in Journal/Newspaper Iceland De Gruyter (via Crossref) Norway Journal of KONES 26 1 147 158 |
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English |
description |
Abstract Pollution adjacent to the continent's shores has increased in the last decades, so it has been necessary to establish an energy policy to improve environmental conditions. One of the proposed solution was the search of alternative fuels to the commonly used in Short Sea Shipping to reduce pollution levels in Europe. Studies and researches show that liquefied natural gas could meet the European Union environmental requirements. Even environmental benefits are important; currently there is not significant number of vessels using it as fuel. Moreover, main target of this article is exposing result of a research in which a methodology to establish the most relevant variables in the decision to implement liquefied natural gas in Short Sea Shipping has been development using data mining. A Bayesian network was constructed because this kind of network allows to get graphically the relationships between variables and to determine posteriori values that quantify their contributions to decision-making. Bayesian model has been done using data from some European countries (European Union, Norway and Iceland) and database was generated by 35 variables classified in 5 categories. Main obtained conclusion in this analysis is that variables of transport and international trade and economy and finance are the most relevant in the decision-making process when implementing liquefied natural gas. Even more, it can be stablish that capacity of liquefied natural gas regasification terminals under construction and modal distribution of water cargo transportation continental as the most decisive variables because they are the root nodes in the obtained network. |
format |
Article in Journal/Newspaper |
author |
Serrano, Beatriz Molina González Cancelas, Nicoleta Soler Flores, Francisco |
spellingShingle |
Serrano, Beatriz Molina González Cancelas, Nicoleta Soler Flores, Francisco Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
author_facet |
Serrano, Beatriz Molina González Cancelas, Nicoleta Soler Flores, Francisco |
author_sort |
Serrano, Beatriz Molina |
title |
Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
title_short |
Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
title_full |
Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
title_fullStr |
Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
title_full_unstemmed |
Reducing Pollution Levels Generated by Short Sea Shipping. Use of Bayesian Networks to Analyse the Utilization of Liquefied Natural Gas as an Alternative Fuel |
title_sort |
reducing pollution levels generated by short sea shipping. use of bayesian networks to analyse the utilization of liquefied natural gas as an alternative fuel |
publisher |
Walter de Gruyter GmbH |
publishDate |
2019 |
url |
http://dx.doi.org/10.2478/kones-2019-0018 https://content.sciendo.com/view/journals/kones/26/1/article-p147.xml https://www.sciendo.com/pdf/10.2478/kones-2019-0018 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Journal of KONES volume 26, issue 1, page 147-158 ISSN 2354-0133 |
op_rights |
http://creativecommons.org/licenses/by-nc-nd/3.0 |
op_rightsnorm |
CC-BY-NC-ND |
op_doi |
https://doi.org/10.2478/kones-2019-0018 |
container_title |
Journal of KONES |
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26 |
container_issue |
1 |
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147 |
op_container_end_page |
158 |
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1766041701327044608 |