Giannis Spiliopoulos, Dimitris Zissis, Julio de La Cueva, Ioannis Kontopoulos
Global Oceans 2020: Singapore – U.S. Gulf Coast, 2020
In this paper we present a complete framework for modelling and estimating vessel GHG emissions and related air pollutants (i.e. CO2 and SOx, NOx and PM) in ports, based on data collected from the Automatic Identification System (AIS). Our approach adopts a modified lambda architecture approach, which consists of a knowledge extraction batch processing step and a real time emissions calculation step. The approach makes it possible to automatically identify the berths or ports where emissions are high in a consistent and uniform way across the globe.
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