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        Degassing in Inland Shipping - An Exploratory Study on Identifying Degassing Patterns and Hotspots on Dutch Inland Waterways Based on AIS and IVS data

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        Publication date
        2025
        Author
        Pas, Bram van der
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        Summary
        Vessels transporting liquid gasses still contain some vapour after discharging their cargo. These vessels need to degas their cargo tanks of this vapour in order to not contaminate their next cargo. Most of the vessels release these vapours unprocessed into the atmosphere. This uncontrolled degassing of vapours, especially volatile organic compounds (VOCs), from inland tanker vessels can pose a serious risk for the environment and human health. To combat the uncontrolled degassing of vessels, the Convention on the collection, Deposit, and reception of waste generated during Navigation on the Rhine and other Inland waterways (CDNI), which is also ratified by the Netherlands, introduced a phased ban on the uncontrolled degassing of multiple substances on 1 October 2024. However, the enforcement of this ban proved to be a challenge due to the lack of effective detection methods. This study explores the potential of using Automatic Identification System (AIS) and Informatie en volgsysteem Scheepvaart (IVS) data to identify degassing patterns and hotspots on Dutch inland waterways. A methodology is developed to detect deviations in tanker vessel movement by comparing the actual taken routes with the optimal route between the start and destination point. After filtering out explainable deviating behaviour, a density estimation technique is applied on the data to identify potential degassing hotspots and an emission volume analysis is conducted to estimate the emission created by degassing. The results indicate that locations with certain characteristics are preferred for degassing activities. However, this methodology relies on multiple assumptions, and the current validation using a confusion matrix indicate a precision of 63.8% (based on 160 predicted classifications) and a recall of only 42.1% (based on 242 actual cases). The accuracy of the methodology is indicated on 98.2%, but this is heavily skewed by the large amount of true-negative results (10.583) . Despite the many limitations that emerged during the research, the process provides valuable insights on the strengths and constraints of AIS and IVS data for detecting degassing activity. The findings can support the Inspectie Leefomgeving en Transport (ILT) and Rijkswaterstaat in further refining detection methods and enforcement strategies and showed the potential of the current proposed method. Future work should focus on applying the method on bigger datasets, increasing the accuracy of the method and a better validation of the results.
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        https://studenttheses.uu.nl/handle/20.500.12932/48913
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