Maritime-Accident-Induced Environmental Pollution and Economic Loss Analysis Using an Interpretable Data-Driven Method

Zeguo Zhang, Qinyou Hu and Jianchuan Yin ()
Additional contact information
Zeguo Zhang: Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China
Qinyou Hu: Key Laboratory of Transport Industry of Marine Technology and Control Engineering, Shanghai Maritime University, Shanghai 200210, China
Jianchuan Yin: Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China

Sustainability, 2025, vol. 17, issue 7, 1-27

Abstract: In this study, we developed an interpretable machine learning (ML) framework to predict marine pollution and economic losses from accident risk factors. A triple-feature selection process identified key predictors, followed by a comparative analysis of eight ML models. Random forest outperformed other models in forecasting environmental and property damage. The interpretable model was established based on the SHAP value framework, which revealed that onboard personnel count, vessel dimensions (length), and accident/ship types account for the risk factors with the most severe consequences, with environmental conditions like wind speed and air temperature contributing secondary effects. The methodology enables two critical applications: (1) environmental agencies can proactively assess accident impact through the identified risk triggers, optimizing emergency response planning, and (2) insurance providers gain data-driven risk evaluation metrics to refine premium calculations. By quantifying how human/technical factors, including crew members and vessel specifications, dominate over natural variables in accident effects, this data-driven approach provides actionable insights for maritime safety management and financial risk mitigation, achieving high prediction accuracy while maintaining model transparency through Shapley value explanations.

Keywords: maritime safety; risk factor; interpretable machine learning; environmental and economic-loss analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/7/3023/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/7/3023/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:7:p:3023-:d:1623013

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().