As awareness on the impact of anthropogenic underwater noise on marine life grows, underwater noise measurement programs are needed to determine the current status of marine areas and monitor long-term trends. The Joint Monitoring Programme for Ambient Noise in the North Sea (JOMOPANS) collaborative project was funded by the EU Interreg to collect a unique dataset of underwater noise levels at 19 sites across the North Sea, spanning many different countries and covering the period from 2019 to 2020. The ambient noise from this dataset has been characterised and compared - setting a benchmark for future measurements in the North Sea area. By identifying clusters with similar sound characteristics in three broadband frequency bands (25–160 Hz, 0.2–1.6 kHz, and 2–10 kHz), geographical areas that are similarly affected by sound have been identified. The measured underwater sound levels show a persistent and spatially uniform correlation with wind speed at high frequencies (above 1 kHz) and a correlation with the distance from ships at mid and high frequencies (between 40 Hz and 4 kHz). Correlation with ocean current velocity at low frequencies (up to 200 Hz), which are susceptible to nonacoustic contamination by flow noise, was also evaluated. These correlations were evaluated and simplified linear scaling laws for wind and current speeds were derived. The presented dataset provides a baseline for underwater noise measurements in the North Sea and shows that spatial variability of the dominant sound sources must be considered to predict the impact of noise reduction measures. | publishedVersion

The intensification of agriculture has promoted the simplification and specialization of agroecosystems, resulting in negative impacts such as decreasing landscape heterogeneity and increasing use of plant protection products (PPP), with the acceleration of PPP transfers to environmental compartments and loss in biodiversity. In this context, the present work reviews the various levers for action promoting the prevention and management of these transfers in the environment and the available modelling tools. Two main categories of levers were identified: (1) better control of the application, including the reduction of doses and of PPP dispersion during application thanks to appropriate equipment and settings, PPP formulations and consideration of meteorological conditions; (2) reduction of post-application transfers at plot scales (soil cover, low tillage, organic matter management, remediation etc. and at landscape scales using either dry (grassed strips, forest, hedgerows and ditches) or wet (ponds, mangroves and stormwater basins) buffer zones. The management of PPP residues leftover in the spray tanks (biobeds) also represents a lever for limiting point-source PPP pollution. Numerous models have been developed to simulate the transfers of PPPs at plot scales. They are scarce for landscape scales. A few are used for regulatory risk assessment. These models could still be improved, for example, if current agricultural practices (e.g. agro-ecological practices and biopesticides), and their effect on PPP transfers were better described. If operated alone, none of the levers guarantee a zero risk of PPP transfer. However, if levers are applied in a combined manner, PPP transfers could be more easily limited (agricultural practices, landscape organization etc.).

Seagrass meadows are one of the world's most diverse ecosystems offering habitats for an extensive array of species, as well as serving as protectors of coral reefs and vital carbon sinks. Furthermore, they modify hydrodynamics by diminishing water flow velocities and enhancing sediment deposition, indicating the potential for microplastic accumulation in their sediments. The build-up of microplastics could potentially have ecological impacts threatening to ecosystems, however little is known about microplastic abundance and controlling factors in seagrass sediments. Here we investigated microplastic characteristics and abundances within sediments underlying four seagrass meadow sites on the Turneffe Atoll, Belize. Sediment cores were collected and sub-sampled to include a range of replicate surface sediments (0–4 cm) and depth cores (sediment depths 0–2, 2–5, 5–10, 10–20 and 20–30 cm). These were analysed using 25 μm resolution μFTIR, with spectral maps processed using siMPle software. Microplastics were prevalent across the sites with an abundance range (limit of detection (LOD) blank-corrected) of < LOD to 17137 microplastics kg−1 dw found on the east side of the atoll. However, their abundances varied greatly between the replicate samples. Polyethylene and polypropylene were the most commonly detected polymers overall, although the dominant polymer type varied between sites. There were no differences in the abundance of microplastics between sites, nor could abundance distributions be explained by seagrass cover. However, abundances of microplastics were highest in sediments with lower proportions of fine grained particles (clay, <4 μm) suggesting that hydrodynamics override seagrass effects. Additionally, no patterns were seen between microplastic abundance and depth of sediment. This suggests that microplastic abundance and distribution in seagrass meadows may vary significantly depending on the specific geographical locations within those meadows, and that more complex hydrodynamic factors influence spatial variability at a localised scale. | publishedVersion

Marine vibrators are a new technology being developed for seismic surveys. These devices can transmit continuous instead of impulsive sound and operate over a narrower frequency band and at lower peak pressure than airguns, which is assumed to reduce their environmental impacts. We exposed spawning Atlantic cod (Gadus morhua) to sound produced by a prototype, but full-scale, marine vibrator, and monitored behavioural responses of tagged cod using acoustic telemetry. Fish were exposed to 10 × 3 h continuous sound treatments over a 4-day period using a randomised-block design. Sound exposure levels were comparable to airgun exposure experiments conducted previously with the same set-up ranging from ∼115 to 145 dB re 1 μPa2s during exposure. Telemetry data were used to assess 1) whether marine vibrator exposure displaced cod from the spawning ground, through estimation of residence and survival probabilities, and 2) fine-scale behavioural responses within the test site, namely swimming depth, activity levels, displacement, and home ranges. Forty-two spawning cod were tagged prior to the exposure, with 22 present during the exposure. All 22 tags were equipped with pressure sensors and ten of these additionally with accelerometers. While no premature departure from the spawning site was observed, cod reacted to the exposure by decreasing their activity levels (by up to 50%, SE = 7%) and increasing their swimming depth (by up to 2.5 m, SE = 1.0 m) within the test site during the exposure period. These behavioural responses varied by sex and time of day. Cod reactions to a marine vibrator may be more pronounced than reactions to airguns, possibly because continuous sound is more disturbing to fish than intermittent sound at the same exposure levels. However, given sample size limitations of the present study, further studies with continuous sound are necessary to fully understand its impact and biological significance. | publishedVersion

Per- and polyfluoroalkyl substances (PFAS) were analysed in a high number of terrestrial samples of soil, earthworm, bird eggs and liver from red fox and brown rat in an urban area in Norway from 2013 to 2020. PFOS and the long chain PFCAs were the most dominating compounds in all samples, proving their ubiquitous distribution. Other less studied compounds such as 6:2 FTS were first and foremost detected in earthworm. 8:2 FTS was found in many samples of fieldfare egg, sparrowhawk egg and earthworm, where the eggs had highest concentrations. Highest concentrations for both 6:2 FTS and 8:2 FTS were detected at present and former industry areas. FOSA was detected in many samples of the species with highest concentrations in red fox liver and brown rat liver of 3.3 and 5.5 ng/g ww. PFAS concentrations from the urban area were significantly higher than from background areas indicating that some of the species can be suitable as markers for PFAS emissions in an urban environment. Fieldfare eggs had surprisingly high concentrations of PFOS and PFCA concentrations from areas known to be or have been influenced by industry. Biota-soil-accumulation factor and magnification calculations indicate accumulation and magnification potential for several PFAS. Earthworm and fieldfare egg had average concentrations above the Canadian and European thresholds in diet for avian wildlife and predators. For earthworms, 18 % of the samples exceeded the European threshold (33 ng/g ww) of PFOS in prey for predators, and for fieldfare eggs, 35 % of the samples were above the same threshold. None of the soil samples exceeded a proposed PNEC of PFOS for soil living organisms of 373 ng/g dw. | publishedVersion

Pharmaceuticals, stimulants, and biocides enter the environment via wastewater from urban, domestic, and industrial areas, in addition to sewage, aquaculture and agriculture runoff. While some of these compounds are easily degradable in environmental conditions, others are more persistent, meaning they are less easily degraded and can stay in the environment for long periods of time. By exploring the adsorptive properties of a wide range of pharmaceuticals, stimulants, and biocides onto particles relevant for marine conditions, we can better understand their environmental behaviour and transport potential. Here, the sorption of 27 such compounds to inorganic (kaolin) and biotic (the microalgae Cryptomonas baltica) marine particles was investigated. Only two compounds sorbed to microalgae, while 23 sorbed to kaolin. The sorption mechanisms between select pharmaceuticals and stimulants and kaolin was assessed through exploring adsorption kinetics (caffeine, ciprofloxacin, citalopram, fluoxetine, and oxolinic acid) and isotherms (ciprofloxacin, citalopram, and fluoxetine). Temperature was shown to have a significant impact on partitioning, and the impact was more pronounced closer to maximum sorption capacity for the individual compounds. | publishedVersion

The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms have emerged as powerful tools for predicting sediment yield. However, their use by decision-makers can be attributed to concerns regarding their consistency with the involved physical processes. In light of this issue, this study aims to develop a physics-informed ML approach for predicting sediment yield. To achieve this objective, Gaussian, Center, Regular, and Direct Copulas were employed to generate virtual combinations of physical of the sub-basins and hydrological datasets. These datasets were then utilized to train deep neural network (DNN), conventional neural network (CNN), Extra Tree, and XGBoost (XGB) models. The performance of these models was compared with the modified universal soil loss equation (MUSLE), which serves as a process-based model. The results demonstrated that the ML models outperformed the MUSLE model, exhibiting improvements in Nash–Sutcliffe efficiency (NSE) of approximately 10%, 18%, 32%, and 41% for the DNN, CNN, Extra Tree, and XGB models, respectively. Furthermore, through Sobol sensitivity and Shapley additive explanation–based interpretability analyses, it was revealed that the Extra Tree model displayed greater consistency with the physical processes underlying sediment transport as modeled by MUSLE. The proposed framework provides new insights into enhancing the accuracy and applicability of ML models in forecasting sediment yield while maintaining consistency with natural processes. Consequently, it can prove valuable in simulating process-related strategies aimed at mitigating sediment transport at watershed scales, such as the implementation of best management practices.

This paper presents a novel method to select the optimal combination of grid resolution and number of Lagrangian elements (LEs) required in numerical modelling of oil concentrations at sea. A sensitivity analysis in terms of grid resolution and the number of LEs, was carried out to understand the uncertainty that these userdependent parameters introduce in the numerical results. A dataset of 211,200 simulations performed under 400 metocean patterns, 6 initial volumes, 11 grid resolutions, and different numbers of LEs (100 to 500,000), was used to analyze the sensitivity of the model along different Thresholds of Concern. Results show the importance of a correct selection of the number of LEs and the grid resolution in Lagrangian modelling of surface oil concentrations. The method proposed will allow selecting the optimal combination of these parameters to find an optimal balance between the accuracy and the computational cost of the simulation. | This work was partly carried out in the framework of the project PID2020-117267RB-I00 (COIL) funded by MCIN/AEI/10.13039/501100011033// and the project PDC2021-120892-I00 (BLOWHAZARD) funded by MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR.