Mitigating persistent organic pollutants from marine plastics through enhanced recycling: A review

Lightweight deep learning model for underwater waste segmentation based on sonar images

In recent years, the rapid accumulation of marine waste not only endangers the ecological environment but also causes seawater pollution. Traditional manual salvage methods often have low efficiency and pose safety risks to human operators, making automatic underwater waste recycling a mainstream approach. In this paper, we propose a lightweight multi-scale cross-level network for underwater waste segmentation based on sonar images that provides pixel-level location information and waste categories for autonomous underwater robots. In particular, we introduce hybrid perception and multi-scale attention modules to capture multi-scale contextual features and enhance high-level critical information, respectively. At the same time, we use sampling attention modules and cross-level interaction modules to achieve feature down-sampling and fuse detailed features and semantic features, respectively. Relevant experimental results indicate that our method outperforms other semantic segmentation models and achieves 74.66 % mIoU with only 0.68 M parameters. In particular, compared with the representative PIDNet Small model based on the convolutional neural network architecture, our method can improve the mIoU metric by 1.15 percentage points and can reduce model parameters by approximately 91 %. Compared with the representative SeaFormer T model based on the transformer architecture, our approach can improve the mIoU metric by 2.07 percentage points and can reduce model parameters by approximately 59 %. Our approach maintains a satisfactory balance between model parameters and segmentation performance. Our solution provides new insights into intelligent underwater waste recycling, which helps in promoting sustainable marine development.

Innovative application of Nile Red (NR)-based dye for direct detection of micro and nanoplastics (MNPs) in diverse aquatic environments

This paper presents the results of a research aimed at establishing a novel method for the detection of primary and secondary micro- and nanoplastics (MNPs), by using the fluorescence properties of the dye Nile Red-n-heptane (NR-H). The method has been applied to the detection of laboratory degraded polymers (Polystyrene, PS and Polyethylene Terephthalate, PET) as well as traceable latex microspheres in aqueous environments, showing a remarkable detection capacity and avoiding the prior extraction or processing of MNPs in natural samples, with significant time savings compared to conventional methods. The study has been carried out on various types of water, including samples from wastewater treatment plants, boreholes, seawater and synthesized seawater. The effectiveness of the staining process was evaluated by scanning electron microscopy (SEM), dynamic light scattering (DLS) and optical microscopy. As a result, a novel standardizable protocol for the rapid detection of MNPs has been established, with the potential to improve environmental protection through fast in-situ detection and identification of plastic contaminants. The limitations of the protocol in the quantification of MNPs have also been identified and further studies are proposed to overcome these limitations.

Innovative remediation strategies for persistent organic pollutants in soil and water: A comprehensive review

Persistent organic pollutants (POPs) provide a serious threat to human health and the environment in soil and water ecosystems. This thorough analysis explores creative remediation techniques meant to address POP pollution. Persistent organic pollutants are harmful substances that may withstand natural degradation processes and remain in the environment for long periods of time. Examples of these pollutants include dioxins, insecticides, and polychlorinated biphenyls (PCBs). Because of their extensive existence, cutting-edge and environmentally friendly eradication strategies must be investigated. The most recent advancements in POP clean-up technology for soil and water are evaluated critically in this article. It encompasses a wide range of techniques, such as nanotechnology, phytoremediation, enhanced oxidation processes, and bioremediation. The effectiveness, cost-effectiveness, and environmental sustainability of each method are assessed. Case studies from different parts of the world show the difficulties and effective uses of these novel techniques. The study also addresses new developments in POP regulation and monitoring, highlighting the need of all-encompassing approaches that include risk assessment and management. In order to combat POP pollution, the integration of diverse remediation strategies, hybrid approaches, and the function of natural attenuation are also examined. Researchers, legislators, and environmental professionals tackling the urgent problem of persistent organic pollutants (POPs) in soil and water should benefit greatly from this study, which offers a complete overview of the many approaches available for remediating POPs in soil and water.