The Ligurian Sea is a deep basin in the northernmost sector of the western Mediterranean which shows peculiar hydrodynamic and meteo-oceanographic features. The coasts of the Ligurian Sea are among the most urbanised and industrialised along the Italian coastline: the main causes of disturbance being littoral urban development and harbour activities, the building of littoral rail- and highways, and the presence of several polluted discharges. This review, by evaluating the huge scientific output published in the last three decades, describes and discusses the most important geological, hydrological and biological characteristics of the Ligurian Sea. We show that this regional sea has largely been investigated in terms of its geological and structural evolution, as well as in terms of the sedimentation dynamics of the littoral and deep bottoms, with particular attention to the sedimentation balance of the beaches and their erosive processes. We report that the prevalent hydrodynamic and meteo-oceanographic conditions favour a continuous exchange of coastal water masses, and that the seasonal and interannual dynamics of water masses can effects the local climate, with direct and indirect consequences on fish and benthic communities documented in the last decade. We stress that although recent studies offer good knowledge of the distribution of coastal benthic communities, only scant information is available for the whole continental shelf, the submarine canyons and the rocky bathyal bottoms. Our meta-analysis reveals that significant fishing activities are monitored, but also that certain sectors of the biological resource are suffering, and suggests the set up of appropriate management measures. The Ligurian Sea hosts a number of Marine Protected Areas (MPAs) of high relevance, while the institution of the Whale Sanctuary completes the protection policy of the Regione Liguria. Our meta-analysis points out the need for long-term studies, based primarily on the analysis of those areas of the Ligurian Sea that have been little investigated to date. Finally, only properly addressed studies, using experimental approaches and along appropriate spatial and temporal scales, might allow us to understand the functioning of the Ligurian marine ecosystems, evaluate their health conditions and the dynamics of the main variables that affect the distribution of the single species (including species of high economic value) and benthic communities.

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools.

In this paper, we present two novel experimental setups specifically designed to perform in situ long-term monitoring of the aging behaviour of commercial plastic granules (HDPE, PP, PLA and PBAT). The results of the first six months of a three year monitoring campaign are presented. The two experimental setups consist of: (i) special cages positioned close to the sea floor at a depth of about 10 m, and (ii) a box containing sand exposed to atmospheric agents to simulate the surface of a beach. Starting from March 2020, plastic granules were put into the cages and plunged in seawater and in a sandboxe. Chemical spectroscopic and thermal analyses (GPC, SEM, FTIR-ATR, DSC, TGA) were performed on the granules before and after exposure to natural elements for six months, in order to identify the physical-chemical modifications occurring in marine environmental conditions (both in seawater and in sandy coastal conditions). Changes in colour, surface morphology, chemical composition, thermal properties, molecular weight and polydispersity, showed the different influences of the environmental conditions. Photooxidative reaction pathways were prevalent in the sandbox. Abrasive phenomena acted specially in the sea environment. PLA and PBAT did not show significant degradation after six months, making the possible reduction of marine pollution due to this process negligible.

It is well established that most of the plastic pollution found in the oceans is transported via rivers. Unfortunately, the main processes contributing to plastic and debris displacement through riparian systems is still poorly understood. The Marine Litter Drifter project from the Arno River aims at using modern consumer software and hardware technologies to track the movements of real anthropogenic marine debris (AMD) from rivers. The innovative “Marine Litter Trackers” (MLT) were utilized as they are reliable, robust, self-powered and they present almost no maintenance costs. Furthermore, they can be built not only by those trained in the field but also by those with no specific expertise, including high school students, simply by following the instructions. Five dispersion experiments were successfully conducted from April 2021 to December 2021, using different types of trackers in different seasons and weather conditions. The maximum distance tracked was 2845 km for a period of 94 days. The activity at sea was integrated by use of Lagrangian numerical models that also assisted in planning the deployments and the recovery of drifters. The observed tracking data in turn were used for calibration and validation, recursively improving their quality. The dynamics of marine litter (ML) dispersion in the Tyrrhenian Sea is also discussed, along with the potential for open-source approaches including the “citizen science” perspective for both improving big data collection and educating/awareness-raising on AMD issues.