Reducing pollution levels generated by short sea shipping : use of Bayesian networks to analyse the utilization of liquefied natural gas as an alternative fuel
Reducing pollution levels generated by short sea shipping : use of Bayesian networks to analyse the utilization of liquefied natural gas as an alternative fuel
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.
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