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Biosensors for the Marine Environment: Introduction -- Microgravity Changes Membrane Properties and Triggers Bioluminescence in Pyrocystis noctiluca as an Approach for New Biosensor Concepts -- Addressing Ciguatera Risk Using Biosensors for the Detection of Gambierdiscus and Ciguatoxins -- Antibody, Aptamer and Affimer-Based Affinity Tools for Marine Toxin Biosensing -- Environmental DNA as a Tool for Single Species Detection -- Paper-Based Devices for Virus Detection in Water -- Electrochemical MIP Sensors for Environmental Analysis -- Whole-Cell Biosensors and Phagocytosis with Cryo-Conserved Cells in Coastal Areas and in Orbit (ISS) Under Microgravity -- Marine Whole-Cell Biosensing for "Real-Time" Determination of the Ballast Water Treatment Efficiency -- Sensors for Monitoring Faecal Indicator Bacteria in Bathing Waters -- Electrochemical (Bio)sensors for Toxins Control in the Marine Environment. .

AbstractThis paper evaluates for the first time the spatial distribution of a wide group of organic (phthalates, nitro, aliphatic, halogen, aromatic, phenol and amino compounds) and inorganic pollutants along the Liffey river in Dublin city. The work takes into account the effect of short-term weather conditions on the occurrence of these contaminants. The results showed that rainfall conditions affect the levels of pollutants along the river in the days following a rainfall event. In addition, the tributaries entering the river Liffey were not found to impact its water quality. In relation to organic pollutants, 2,4,6-trichlorophenol, 2-nitrophenol and phthalate compounds were found in many water samples between concentrations of 0.21 and 2.17 μg L−1. On the other hand, dimethyl phthalate was present in certain samples at levels around 100 μg L−1. The levels of these contaminants in the river were lower than the toxicity values reported in the literature. Regarding inorganic pollutants, nitrates were detected from 0.59 to 6.81 mg L−1increasing from upstream to downstream. Based on the chemical nature and applications of detected pollutants, the river contamination can be mainly related to agricultural, industrial activities as well as diffuse urban contributions. These vary with location within a short distance and have the potential to impact aquatic biodiversity as the chemical composition changes with rainfall events.

Demands from various scientific and management communities along with legislative requirements at national and international levels have led to a need for innovative research into large-scale, low-cost, reliable monitoring of our marine and freshwater environments. In this paper we demonstrate the benefits of a multi-modal approach to monitoring and how an in-situ sensor network can be enhanced with the use of contextual image data. We provide an outline of the deployment of a visual sensing system at a busy port and the need for monitoring shipping traffic at the port. Subsequently we present an approach for detecting ships in a challenging image data set and discuss how this can help to create an intelligent marine monitoring network.

Continual measurement is key to understanding sudden and gradual changes in chemical and biological quality of water, and for taking reactive remedial action in the case of contamination. Monitoring of water bodies will increase in future within Europe to comply with legislative requirements such as the Water Framework Directive and globally owing to pressure from climate change. Establishing high quality long-term monitoring programs is regarded as essential if the implementation of pertinent legislation is to be successful. However, conventional discrete sampling programs and laboratory-based analysis techniques can be costly, and are unlikely to provide timely and reliable estimates of true ranges of deterministic physicochemical variability in a water body with marked temporal or spatial variability. Only continual or near continual measurements have the capacity to detect ephemeral or sporadic events, thus providing the potential for on-line event detection and classification. The aim of this work is to demonstrate the potential role of continuous data acquisition in decision support as part of a smart city project. In this work, a multi-modal smart sensor network system framework for large scale estuarine and marine water quality monitoring is proposed. The application of a number of evolving techniques that allow automated detection and clustering of events from data generated by in situ sensors within environmental time series datasets is described. We provide examples of how change in the range of variables such as turbidity and salinity might be detected and clustered to provide the end user with greater ability to detect the onset of environmentally significant events. Finally, we discuss the acquisition of data from in situ water quality sensors and its utility within the framework a smart city-smart bay integrated project.

AbstractIntegrative passive samplers, such as DGT (Diffusive Gradients in Thin-films), are identified in European Technical Guidance Documents as promising tools to improve the quality of the assessment, in the context of the WFD (EU Water Framework Directive). However, DGT results cannot yet be used directly in a regulatory framework to assess the chemical status of water bodies, as DGT labile concentrations cannot be directly compared to the metal AA-EQSmarine water (Annual Average Environmental Quality Standard) established by the WFD, which are defined in the dissolved concentration. Therefore, prior to using DGT results in a regulatory context, for cadmium, nickel and lead, an adaptation of existing AA-EQSmarine water for DGTs should be pursued, ensuring at least the same level of protection. In this sense, in the framework of the MONITOOL project, a robust database of dissolved and labile metal concentrations in transitional and coastal waters, for adapting the existing AA-EQSmarine water for DGT technique, was obtained. Building on these results, this study proposes a methodology and provides values and equations for using DGT results for the chemical status assessment of marine waters, by adapting the EQSmarine water to adapted EQSDGT or predicting dissolved concentrations from DGT results. Based on available dataset, a first simulation of "chemical status" assessment per MONITOOL sampling site using DGT measured labile concentrations was carried out and the results were compared to an assessment based on dissolved concentration to check their compliance. These results demonstrate that the use of DGT passive samplers is appropriate for the metal concentrations level encountered in the marine environment. Further work is recommended to test the effectiveness of the methodology proposed in this study under WFD conditions on more sites and to establish common strategy guidelines for the use of DGT passive samplers in monitoring.