Analysing Ship Nox Emissions with Hadoop A Case Study for the Port of Rotterdam
Abstract
Atmospheric emissions such as NOx from ship engines have a drastic impact on the environment. Controlling them is crucial for maintaining a sustainable growth for any logistics company. The Port of Rotterdam (The Netherlands) is using big data analytics to gain actionable insights into these emissions. Our case study deals with the implementation of the emission calculations and reporting implemented in Hadoop. In the analytical setup we introduce the method for estimating emissions based on recorded ship position data and information about its engines. We present a flexible approach that stores intermediate results allowing different levels of aggregation. These levels of aggregations are per geographical area, per grid or for a whole journey attributed to each visited berth. The results are visualized in a Geographical Information System (GIS). The estimated atmospheric emissions also serves as input for the deposition model. We present some selected results of emissions per grid as well as for pre-defined areas. These results are used by the port to make strategic decision. For future work we recommend to also implement the deposition model in Hadoop as this model is also calculative intensive and therefore it currently only accepts aggregated emissions as input, whereby its accuracy is most likely reduced.
Copyright & License
All Research Plus Journals (RPJ) publish open access articles under the terms of the Creative Commons Attribution (CC BY-SA 4.0) https://creativecommons.org/licenses/by-sa/4.0/ License which permits use, distribution and reproduction in any medium, provided the original work is properly cited & ShareAlike terms followed.
Copyright on any research article in a journal published by a RPJ is retained by the author(s). Authors grant RPJ a license to publish the article and identify itself as the original publisher. Upon author(s) by giving permission to RPJ either via RPJ journal portal or other channel to publish their research work in RPJ agrees to all the terms and conditions of https://creativecommons.org/licenses/by-sa/4.0/ License and terms & condition set by RPJ.
3rd party copyright
It is the responsibility of author(s) to secure all necessary copyright permissions for the use of 3rd-party materials in their manuscript.
Disclaimer
Research Plus Journals Open Access articles posted to repositories or websites are without warranty from RPJ of any kind, either express or implied, including, but not limited to, warranties of merchantability, fitness for a particular purpose, or non-infringement. To the fullest extent permitted by law RPJ disclaims all liability for any loss or damage arising out of, or in connection, with the use of or inability to use the content.
