Emerging marine environmental pollution and ecosystem disturbance in ship hull cleaning for biofouling removal

Numerous marine sessile organisms adhere to ship hulls and increase the sailing resistance. Antibiofouling paints are employed to maintain the ship performance. However, the chemicals employed for antifouling purposes are becoming increasingly diverse, lacking clear toxicological information. Particularly, the imperfect antibiofouling efficacies of these chemicals necessitate periodic hull cleaning to dislodge attached marine organisms. This hull cleaning process inadvertently releases a plethora of hazardous substances, including antibiofouling chemicals, heavy metals, and cleaning agents, alongside exotic microorganisms. This results in profound marine pollution and ecosystem disruption. Specifically, these exotic microorganisms pose a novel ecological threat in coastal waters. However, despite the gravity of ship hull cleaning-related issues, comprehensive investigations have been lacking, and international regulatory measures are gaining attention recently. Aiming to provide solutions to the emerging challenges associated with hull cleaning, this review endeavors to comprehensively address the biofouling organisms and their mechanisms, potential antifouling paint hazards, and effective hull cleaning methodologies.

Adhesion Behavior in Fish: From Structures to Applications

In nature, some fish can adhere tightly to the surface of stones, aquatic plants, and even other fish bodies. This adhesion behavior allows these fish to fix, eat, hide, and migrate in complex and variable aquatic environments. The adhesion function is realized by the special mouth and sucker tissue of fish. Inspired by adhesion fish, extensive research has recently been carried out. Therefore, this paper presents a brief overview to better explore underwater adhesion mechanisms and provide bionic applications. Firstly, the adhesion organs and structures of biological prototypes (e.g., clingfish, remora, Garra, suckermouth catfish, hill stream loach, and goby) are presented separately, and the underwater adhesion mechanisms are analyzed. Then, based on bionics, it is explained that the adhesion structures and components are designed and created for applications (e.g., flexible gripping adhesive discs and adhesive motion devices). Furthermore, we offer our perspectives on the limitations and future directions.

Metals and suspended solids in the effluents from in-water hull cleaning by remotely operated vehicle (ROV): Concentrations and release rates into the marine environment

An increase in the use of ROVs for in-water hull cleaning (IWC) has led to the need to understand the risks to the marine environment posed by the release of IWC effluents. The primary objective of this research is to investigate the characteristics of wastewater generated during IWC, specifically concerning suspended solids (SS) and metal concentrations, and their release rates and total load to the environment. The IWC effluents contain substantial amounts of SS and metals, with Cu and Zn being the most prevalent. These metals are predominantly associated with fine antifouling paint particles, posing a potential risk of secondary pollution upon release into the marine environment. While the treatment systems demonstrated effectiveness in reducing SS and particulate metals, achieving complete removal of dissolved and particulate metals below ambient levels proved to be challenging. To mitigate environmental risks, this study proposes, based on the particle size analysis, the implementation of multistage filtration systems with an optimal filtration pore size for the effluent treatment. In conclusion, we highlight the potential environmental risks of IWC activities. As most metals have a strong affinity towards particles in wastewater, effective removal of particles is essential to alleviate environmental stress at IWC sites.

Effect of wastewater from the in-water cleaning of ship hulls on attached and unattached microalgae

Environmental spills of in-water hull cleaning wastewater (HCW) containing heavy metals and biocides is inevitable, and the effects of HCW on microalgae are unknown. To investigate this, we conducted microcosm experiments by adding HCW to natural seawater. HCW samples were obtained from two different cleaning methods (soft: sponge, hard: brush), and 5 % or 10 % were added to natural seawater as treatments. Dissolved Cu concentrations were 5 to 10 times higher in the treatments than those in the control. There were significant differences in growth of unattached microalgae depending on HCW dose (chlorophyll a: 34.1 ± 0.8 μg L-1 in control vs. 12.6 ± 4.3 μg L-1 in treatments). Conversely, the biomass of attached microalgae increased with HCW dose, which was associated with most of the nutrient reduction later in the experiment, rather than unattached microalgae. Our findings suggest that HCW can significantly impact microalgal community, especially depending on spill volume.

Investigating the Impacts of UVC Radiation on Natural and Cultured Biofilms: An assessment of Cell Viability

Biofilms are conglomerates of cells, water, and extracellular polymeric substances which can lead to various functional and financial setbacks. As a result, there has been a drive towards more environmentally friendly antifouling methods, such as the use of ultraviolet C (UVC) radiation. When applying UVC radiation, it is important to understand how frequency, and thus dose, can influence an established biofilm. This study compares the impacts of varying doses of UVC radiation on both a monocultured biofilm consisting of Navicula incerta and field-developed biofilms. Both biofilms were exposed to doses of UVC radiation ranging from 1626.2 mJ/cm2 to 9757.2 mJ/cm2 and then treated with a live/dead assay. When exposed to UVC radiation, the N. incerta biofilms demonstrated a significant reduction in cell viability compared to the non-exposed samples, but all doses had similar viability results. The field biofilms were highly diverse, containing not only benthic diatoms but also planktonic species which may have led to inconsistencies. Although they are different from each other, these results provide beneficial data. Cultured biofilms provide insight into how diatom cells react to varying doses of UVC radiation, whereas the real-world heterogeneity of field biofilms is useful for determining the dosage needed to effectively prevent a biofilm. Both concepts are important when developing UVC radiation management plans that target established biofilms.

Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models

In this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-known convolutional neural network models was used. Using the transfer learning technique, the images of the hull surfaces were used to retrain the six models. The proposed method exhibited an accuracy of 98.13%, a precision of 98.73%, a recall of 97.50%, and an F₁-score of 98.11% for the classification of the test set. Furthermore, the time taken for the classification of one image was verified to be approximately 56.25 ms, which is applicable to ROUVs that require real-time inspection.

A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

To tackle the problem of aquatic environment pollution, a vision-based autonomous underwater garbage cleaning robot has been developed in our laboratory. We propose a garbage detection method based on a modified YOLOv4, allowing high-speed and high-precision object detection. Specifically, the YOLOv4 algorithm is chosen as a basic neural network framework to perform object detection. With the purpose of further improvement on the detection accuracy, YOLOv4 is transformed into a four-scale detection method. To improve the detection speed, model pruning is applied to the new model. By virtue of the improved detection methods, the robot can collect garbage autonomously. The detection speed is up to 66.67 frames/s with a mean average precision (mAP) of 95.099%, and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

Seawater contamination associated with in-water cleaning of ship hulls and the potential risk to the marine environment

In-water cleaning can clear-off foulants from ship hulls to prevent transportation of non-indigenous species and reduce hull friction and consequent fuel use. However, during cleaning, antifouling paint residues containing toxic substances can be released into the environment. To understand the potential risks of in-water hull cleaning, cleaning effluents were collected and analyzed for total suspended solid (TSS), particle size distribution, and metal concentrations. TSS concentrations were 97.3-249 mg/L, corresponding to release rates of 12.9-37.5 g/m² from the hull surface. Particles with sizes of ≥8 μm contributed 75-94% of the TSS. Average Cu and Zn concentrations in the effluents were 209 μg/L and 1510 μg/L, respectively, which were used for risk assessment in two port scenarios. Although the risks vary with the scale of the hull cleaning and the ports, in-water cleaning poses clear risks to marine environments, unless the effluents are recovered or treated before being released.

Review of Underwater Ship Hull Cleaning Technologies

This paper presents a comprehensive review and analysis of ship hull cleaning technologies. Various cleaning methods and devices applied to dry-dock cleaning and underwater cleaning are introduced in detail, including rotary brushes, high-pressure and cavitation water jet technology, ultrasonic technology, and laser cleaning technology. The application of underwater robot technology in ship cleaning not only frees divers from engaging in heavy work but also creates safe and efficient industrial products. Damage to the underlying coating of the ship caused by the underwater cleaning operation can be minimized by optimizing the working process of the underwater cleaning robot. With regard to the adhesion technology mainly used in underwater robots, an overview of recent developments in permanent magnet and electromagnetic adhesion, negative pressure force adhesion, thrust force adhesion, and biologically inspired adhesion is provided. Through the analysis and comparison of current underwater robot products, this paper predicts that major changes in the application of artificial intelligence and multirobot cooperation, as well as optimization and combination of various technologies in underwater cleaning robots, could be expected to further lead to breakthroughs in developing next-generation robots for underwater cleaning.

Testing of novel net cleaning technologies for finfish aquaculture

To avoid the negative impacts caused by biofouling development, aquaculture nets around the world are periodically cleaned using high-pressure washers. Net cleaning is labour-intense and costly, can damage antifouling coatings on the nets, and pose contamination as well as fish health and welfare risks. To support the environmental sustainability of the growing aquaculture sector, novel net cleaning methods are needed. This study examined low-pressure-, cavitation-, and suction-based cleaning technologies as alternatives to conventional high-pressure cleaning. Using field experiments, cleaning efficacy, cleaning waste generation, and the impact of cleaning on coating integrity and net strength were evaluated. Cavitation and high-pressure cleaning achieved considerably higher cleaning efficacy than low-pressure and suction cleaning. However, a single high-pressure treatment caused up to 53% coating degradation, compared to 2% for cavitation. All technologies produced similar cleaning waste and neither reduced net strength significantly. This study identifies cavitation cleaning as promising technology for biofouling control on aquaculture nets.

A Rule-Based Reasoner for Underwater Robots Using OWL and SWRL

Web Ontology Language (OWL) is designed to represent varied knowledge about things and the relationships of things. It is widely used to express complex models and address information heterogeneity of specific domains, such as underwater environments and robots. With the help of OWL, heterogeneous underwater robots are able to cooperate with each other by exchanging information with the same meaning and robot operators can organize the coordination easier. However, OWL has expressivity limitations on representing general rules, especially the statement “If … Then … Else …”. Fortunately, the Semantic Web Rule Language (SWRL) has strong rule representation capabilities. In this paper, we propose a rule-based reasoner for inferring and providing query services based on OWL and SWRL. SWRL rules are directly inserted into the ontologies by several steps of model transformations instead of using a specific editor. In the verification experiments, the SWRL rules were successfully and efficiently inserted into the OWL-based ontologies, obtaining completely correct query results. This rule-based reasoner is a promising approach to increase the inference capability of ontology-based models and it achieves significant contributions when semantic queries are done.

SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots

In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.