Marine biofouling on ship hulls poses a dual challenge to the global shipping industry, leading to significant penalties in hydrodynamic performance and increasing the risk of invasive aquatic species (IAS) transfer. Traditional biofouling management relies heavily on fixed-interval maintenance or reactive cleaning based on visible speed loss, which lacks precision and often fails to address the dynamic nature of biological growth. This study proposes a novel, data-driven framework for assessing biofouling risk by integrating high-frequency Automatic Identification System (AIS) kinematic data with spatiotemporal environmental exposure parameters. The model quantifies risk through a multi-factor index that accounts for vessel downtime, sea surface temperature, and traversal of ecologically sensitive geographic zones. A case study involving a coastal bulk carrier and a global ocean-going vessel was conducted to validate the framework. Results demonstrate that the model can effectively distinguish between static-driven fouling risks in coastal operations (dominated by 94% slow-flow events) and metabolic-driven risks in global operations (dominated by 44% high-temperature exposure). The system achieved a classification accuracy of approximately 87% against a validation dataset, with a 100% detection rate for entries into known high-risk estuarine areas. By transforming abstract biological pressures into a quantifiable engineering metric, this research provides ship operators with a proactive decision-support tool to optimize hull cleaning schedules, thereby enhancing fuel efficiency and ensuring compliance with emerging environmental regulations such as the IMO’s Carbon Intensity Indicator (CII).
References
[1]
United Nations Conference on Trade and Development (2023) Review of Maritime Transport 2023. https://unctad.org/system/files/official-document/rmt2023_en.pdf
[2]
Valchev, I., Coraddu, A., Kalikatzarakis, M., Geertsma, R. and Oneto, L. (2022) Numerical Methods for Monitoring and Evaluating the Biofouling State and Effects on Vessels’ Hull and Propeller Performance: A Review. Ocean Engineering, 251, Article ID: 110883. https://doi.org/10.1016/j.oceaneng.2022.110883
[3]
International Maritime Organization (IMO) (2018) Initial IMO Strategy on Reduction of GHG Emissions from Ships. Marine Environment Protection Committee (MEPC). https://www.imo.org/en/ourwork/environment/pages/imo-strategy-on-reduction-of-ghg-em
[4]
Farkas, A., Song, S., Degiuli, N., Martić, I. and Demirel, Y.K. (2020) Impact of Biofilm on the Ship Propulsion Characteristics and the Speed Reduction. Ocean Engineering, 199, Article ID: 107033. https://doi.org/10.1016/j.oceaneng.2020.107033
[5]
Liu, S., Kee, Y.H., Shang, B. and Papanikolaou, A. (2023) Assessment of the Economic, Environmental and Safety Impact of Biofouling on a Ship’s Hull and Propeller. Ocean Engineering, 285, Article ID: 115481. https://doi.org/10.1016/j.oceaneng.2023.115481
[6]
Schultz, M.P. (2007) Effects of Coating Roughness and Biofouling on Ship Resistance and Powering. Biofouling, 23, 331-341. https://doi.org/10.1080/08927010701461974
[7]
Chan, F.T., MacIsaac, H.J. and Bailey, S.A. (2015) Relative Importance of Vessel Hull Fouling and Ballast Water as Transport Vectors of Nonindigenous Species to the Canadian Arctic. Canadian Journal of Fisheries and Aquatic Sciences, 72, 1230-1242. https://doi.org/10.1139/cjfas-2014-0473
[8]
Xavier, F.C., Araujo, F.C.B., Batista, D., Messano, L.V.R.d., Mizrah, D., Calado, L., et al. (2025) Managing the Risk of Marine Bioinvasion via Biofouling: Trends in Methods of Assessment, Policy, and Legislation. Ocean and Coastal Research, 73, e25021. https://doi.org/10.1590/2675-2824073.24092
[9]
Kim, D., Alayande, A.B., Lee, J., Jang, J., Jo, S., Jae, M., et al. (2024) Emerging Marine Environmental Pollution and Ecosystem Disturbance in Ship Hull Cleaning for Biofouling Removal. Science of the Total Environment, 906, Article ID: 167459. https://doi.org/10.1016/j.scitotenv.2023.167459
[10]
Scianni, C. and Georgiades, E. (2019) Vessel In-Water Cleaning or Treatment: Identification of Environmental Risks and Science Needs for Evidence-Based Decision Making. Frontiers in Marine Science, 6, Article 467. https://doi.org/10.3389/fmars.2019.00467
[11]
Coraddu, A., Oneto, L., Baldi, F., Cipollini, F., Atlar, M. and Savio, S. (2019) Data-driven Ship Digital Twin for Estimating the Speed Loss Caused by the Marine Fouling. Ocean Engineering, 186, Article ID: 106063. https://doi.org/10.1016/j.oceaneng.2019.05.045
[12]
Luoma, E., Laurila-Pant, M., Altarriba, E., Nevalainen, L., Helle, I., Granhag, L., et al. (2022) A Multi-Criteria Decision Analysis Model for Ship Biofouling Management in the Baltic Sea. Science of the total Environment, 852, Article ID: 158316. https://doi.org/10.1016/j.scitotenv.2022.158316
[13]
Uzun, D., Demirel, Y.K., Coraddu, A. and Turan, O. (2019) Time-dependent Biofouling Growth Model for Predicting the Effects of Biofouling on Ship Resistance and Powering. Ocean Engineering, 191, Article ID: 106432. https://doi.org/10.1016/j.oceaneng.2019.106432
[14]
Demirel, Y.K., Uzun, D., Zhang, Y., Fang, H., Day, A.H. and Turan, O. (2017) Effect of Barnacle Fouling on Ship Resistance and Powering. Biofouling, 33, 819-834. https://doi.org/10.1080/08927014.2017.1373279
[15]
Song, S., Demirel, Y.K. and Atlar, M. (2020) Penalty of Hull and Propeller Fouling on Ship Self-Propulsion Performance. Applied Ocean Research, 94, Article ID: 102006. https://doi.org/10.1016/j.apor.2019.102006
[16]
Laurie, A., Anderlini, E., Dietz, J. and Thomas, G. (2021) Machine Learning for Shaft Power Prediction and Analysis of Fouling Related Performance Deterioration. Ocean Engineering, 234, Article ID: 108886. https://doi.org/10.1016/j.oceaneng.2021.108886
[17]
Kacimi, A., Bouda, A., Sievers, M., Bensari, B., Houma, F., Nacef, L., et al. (2021) Modeling the Risk of Introducing Non-Indigenous Species through Ship Hull Biofouling: Case Study of Arzew Port (Algeria). Management of Biological Invasions, 12, 1012-1036. https://doi.org/10.3391/mbi.2021.12.4.14
[18]
Mannix, E.J., Wei, S., A. Woodham, B., Wilkinson, P. and Robinson, A.P. (2021) Automating the Assessment of Biofouling in Images Using Expert Agreement as a Gold Standard. Scientific Reports, 11, Article No. 2739. https://doi.org/10.1038/s41598-021-81011-2
[19]
Coutts, A.D.M. and Taylor, M.D. (2004) A Preliminary Investigation of Biosecurity Risks Associated with Biofouling on Merchant Vessels in New Zealand. New Zealand Journal of Marine and Freshwater Research, 38, 215-229. https://doi.org/10.1080/00288330.2004.9517232
