General characteristics of relative dispersion in the ocean

Linear alkylbenzene sulfonate pollution investigation along the Capibaribe River Estuarine System (Northeast Brazil) using a digital imaging-based methodology

The Capibaribe Estuarine System (CES), in Recife-Brazil, is threatened by pollution from domestic effluents, including linear alkylbenzene sulfonate (LAS), a widely used and potentially toxic surfactant. This study uses an innovative in situ methodology: digital image-based (DIB) captured by smartphone, focused on environmental issues and analysis of LAS contamination in CES, assessing pollution sources and tidal influence. Triplicate water samples were collected over 4 consecutive weeks at 6 stations along the CES. The DIB method quantified LAS through color intensity by reaction with methylene blue. LAS concentrations ranged from 0.06 to 1.43 mg L-1, exceeding the limits allowed by CONAMA (National Environmental Council from Brazil) and USEPA (United States Environmental Protection Agency) (0.2 mg L-1). The highest concentrations were observed at the confluence of polluted rivers, and at stations close to the discharge of treated or irregularly discharged effluents, characterizing these locals as the main input sources of LAS for the CES. Higher concentrations were observed especially at ebb flow during spring tides, with lower contaminant dispersion, while areas with stronger marine influence had lower concentrations. The results showed critical levels of LAS in the CES, highlighting potential impacts on local biodiversity and human health, since several people use its water for various activities, including fishing. The DIB methodology has proven to be accurate, fast, cost-effective, and sustainable, making it a promising tool for environmental monitoring and/or improving effluent management.

Lagrangian flow networks for passive dispersal: Tracers versus finite-size particles

The transport and distribution of organisms such as larvae, seeds, or litter in the ocean as well as particles in industrial flows is often approximated by a transport of tracer particles. We present a theoretical investigation to check the accuracy of this approximation by studying the transport of inertial particles between different islands embedded in an open hydrodynamic flow aiming at the construction of a Lagrangian flow network reflecting the connectivity between the islands. To this end, we formulate a two-dimensional kinematic flow field which allows the placement of an arbitrary number of islands at arbitrary locations in a flow of prescribed direction. To account for the mixing in the flow, we include a von Kármán vortex street in the wake of each island. We demonstrate that the transport probabilities of inertial particles making up the links of the Lagrangian flow network essentially depend on the properties of the particles, i.e., their Stokes number, the properties of the flow, and the geometry of the setup of the islands. We find a strong segregation between aerosols and bubbles. Upon comparing the mobility of inertial particles to that of tracers or neutrally buoyant particles, it becomes apparent that the tracer approximation may not always accurately predict the probability of movement. This can lead to inconsistent forecasts regarding the fate of marine organisms, seeds, litter, or particles in industrial flows.

A Lagrangian model for drifting ecosystems reveals heterogeneity-driven enhancement of marine plankton blooms

Marine plankton play a crucial role in carbon storage, global climate, and ecosystem function. Planktonic ecosystems are embedded in patches of water that are continuously moving, stretching, and diluting. These processes drive inhomegeneities on a range of scales, with implications for the integrated ecosystem properties, but are hard to characterize. We present a theoretical framework that accounts for all these aspects; tracking the water patch hosting a drifting ecosystem along with its physical, environmental, and biochemical features. The theory resolves patch dilution and internal physical mixing as a function of oceanic strain and diffusion. Ecological dynamics are parameterized by an idealized nutrient and phytoplankton population and we specifically capture the time evolution of the biochemical spatial variances to represent within-patch heterogeneity. We find that, depending only on the physical processes to which the water patch is subjected, the plankton biomass response to a resource perturbation can vary in size up to six times. This work indicates that we must account for these processes when interpreting and modeling marine ecosystems and provides a framework with which to do so.

Timing and probability of arrival for sea lice dispersing between salmon farms

Sea lice are a threat to the health of both wild and farmed salmon and an economic burden for salmon farms. With a free-living larval stage, sea lice can disperse tens of kilometres in the ocean between salmon farms, leading to connected sea louse populations that are difficult to control in isolation. In this paper, we develop a simple analytical model for the dispersal of sea lice (Lepeophtheirus salmonis) between two salmon farms. From the model, we calculate the arrival time distribution of sea lice dispersing between farms, as well as the level of cross-infection of sea lice. We also use numerical flows from a hydrodynamic model, coupled with a particle tracking model, to directly calculate the arrival time of sea lice dispersing between two farms in the Broughton Archipelago, British Columbia, in order to fit our analytical model and find realistic parameter estimates. Using the parametrized analytical model, we show that there is often an intermediate interfarm spacing that maximizes the level of cross-infection between farms, and that increased temperatures will lead to increased levels of cross-infection.

Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach

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.

Numerical and experimental analysis of Lagrangian dispersion in two-dimensional chaotic flows

We present a review and a new assessment of the Lagrangian dispersion properties of a 2D model of chaotic advection and diffusion in a regular lattice of non stationary kinematic eddies. This model represents an ideal case for which it is possible to analyze the same system from three different perspectives: theory, modelling and experiments. At this regard, we examine absolute and relative Lagrangian dispersion for a kinematic flow, a hydrodynamic model (Delft3D), and a laboratory experiment, in terms of established dynamical system techniques, such as the measure of (Lagrangian) finite-scale Lyapunov exponents (FSLE). The new main results concern: (i) an experimental verification of the scale-dependent dispersion properties of the chaotic advection and diffusion model here considered; (ii) a qualitative and quantitative assessment of the hydro-dynamical Lagrangian simulations. The latter, even though obtained for an idealized open flow configuration, contributes to the overall validation of the computational features of the Delft3D model.

The Finite Size Lyapunov Exponent and the Finite Amplitude Growth Rate

The finite size Lyapunov exponent (FSLE) has been used extensively since the late 1990s to diagnose turbulent regimes from Lagrangian experiments and to detect Lagrangian coherent structures in geophysical flows and two-dimensional turbulence. Historically, the FSLE was defined in terms of its computational method rather than via a mathematical formulation, and the behavior of the FSLE in the turbulent inertial ranges is based primarily on scaling arguments. Here, we propose an exact definition of the FSLE based on conditional averaging of the finite amplitude growth rate (FAGR) of the particle pair separation. With this new definition, we show that the FSLE is a close proxy for the inverse structural time, a concept introduced a decade before the FSLE. The (in)dependence of the FSLE on initial conditions is also discussed, as well as the links between the FAGR and other relevant Lagrangian metrics, such as the finite time Lyapunov exponent and the second-order velocity structure function.

Spreading of Lagrangian Particles in the Black Sea: A Comparison between Drifters and a High-Resolution Ocean Model

The Lagrangian dispersion statistics of the Black Sea are estimated using satellite-tracked drifters, satellite altimeter data and a high-resolution ocean model. Comparison between the in-situ measurements and the model reveals good agreement in terms of the surface dispersion. The mean sub-basin coherent structures and currents of the Black Sea are well reproduced by the model. Seasonal variability of the dispersion in the upper (15 m), intermediate (150 m) and deep (750 m) layers are discussed with a special focus of the role of sub-basin scale structures and currents on the turbulent dispersion regimes. In terms of the surface relative dispersion, the results show the presence of the three known turbulent exponential, Richardson and diffusive-like regimes. The non-local exponential regime is only detected by the model for scales <10 km, while the local Richardson regime occurs between 10 and 100 km in all cases due to the presence of an inverse energy cascade range, and the diffusive-like regime is well detected for the largest distance by drifters (100–300 km) in winter/spring. Regarding the surface absolute dispersion, it reflects the occurrence of both quasi-ballistic and random-walk regimes at small and large times, respectively, while the two anomalous hyperbolic (5/4) and elliptic (5/3) regimes, which are related to the topology of the Black Sea, are detected at intermediate times. At depth, the signatures of the relative and absolute dispersion regimes shown in the surface layer are still valid in most cases. The absolute dispersion is anisotropic; the zonal component grows faster than the meridional component in any scenario.

Search strategy in a complex and dynamic environment: the MH370 case

Search and detection of objects on the ocean surface is a challenging task due to the complexity of the drift dynamics and lack of known optimal solutions for the path of the search agents. This challenge was highlighted by the unsuccessful search for Malaysian Flight 370 (MH370) which disappeared on March 8, 2014. In this paper, we propose an improvement of a search algorithm rooted in the ergodic theory of dynamical systems which can accommodate complex geometries and uncertainties of the drifting search areas on the ocean surface. We illustrate the effectiveness of this algorithm in a computational replication of the conducted search for MH370. We compare the algorithms using many realizations with random initial positions, and analyze the influence of the stochastic drift on the search success. In comparison to conventional search methods, the proposed algorithm leads to an order of magnitude improvement in success rate over the time period of the actual search operation. Simulations of the proposed search control also indicate that the initial success rate of finding debris increases in the event of delayed search commencement. This is due to the existence of convergence zones in the search area which leads to local aggregation of debris in those zones and hence reduction of the effective size of the area to be searched.

Eddy Detection in HF Radar-Derived Surface Currents in the Gulf of Naples

Submesoscale eddies play an important role in the energy transfer from the mesoscale down to the dissipative range, as well as in tracer transport. They carry inorganic matter, nutrients and biomass; in addition, they may act as pollutant conveyors. However, synoptic observations of these features need high resolution sampling, in both time and space, making their identification challenging. Therefore, HF coastal radar were and are successfully used to accurately identify, track and describe them. In this paper we tested two already existing algorithms for the automated detection of submesoscale eddies. We applied these algorithms to HF radar velocity fields measured by a network of three radar systems operating in the Gulf of Naples. Both methods showed shortcomings, due to the high non-geostrophy of the observed currents. For this reason we developed a third, novel algorithm that proved to be able to detect highly asymmetrical eddies, often not properly identified by the previous ones. We used the results of the application of this algorithm to estimate the eddy boundary profiles and the eddy spatial distribution.

A Synergetic Approach for the Space-Based Sea Surface Currents Retrieval in the Mediterranean Sea

We present a method for the remote retrieval of the sea surface currents in the Mediterranean Sea. Combining the altimeter-derived currents with sea-surface temperature information, we created daily, gap-free high resolution maps of sea surface currents for the period 2012–2016. The quality of the new multi-sensor currents has been assessed through comparisons to other surface-currents estimates, as the ones obtained from drifting buoys trajectories (at the basin scale), or HF-Radar platforms and ocean numerical model outputs in the Malta–Sicily Channel. The study yielded that our synergetic approach can improve the present-day derivation of the surface currents in the Mediterranean area up to 30% locally, with better performances for the the meridional component of the motion and in the western section of the basin. The proposed reconstruction method also showed satisfying performances in the retrieval of the ageostrophic circulation in the Sicily Channel. In this area, assuming the High Frequency Radar-derived currents as reference, the merged multi-sensor currents exhibited improvements with respect to the altimeter estimates and numerical model outputs, mainly due to their enhanced spatial and temporal resolution.

Markov-chain-inspired search for MH370

Markov-chain models are constructed for the probabilistic description of the drift of marine debris from Malaysian Airlines flight MH370. En route from Kuala Lumpur to Beijing, MH370 mysteriously disappeared in the southeastern Indian Ocean on 8 March 2014, somewhere along the arc of the 7th ping ring around the Inmarsat-3F1 satellite position when the airplane lost contact. The models are obtained by discretizing the motion of undrogued satellite-tracked surface drifting buoys from the global historical data bank. A spectral analysis, Bayesian estimation, and the computation of most probable paths between the Inmarsat arc and confirmed airplane debris beaching sites are shown to constrain the crash site, near 25^°S on the Inmarsat arc.

Effect of small scale transport processes on phytoplankton distribution in coastal seas

Coastal ocean ecosystems are major contributors to the global biogeochemical cycles and biological productivity. Physical factors induced by the turbulent flow play a crucial role in regulating marine ecosystems. However, while large-scale open-ocean dynamics is well described by geostrophy, the role of multiscale transport processes in coastal regions is still poorly understood due to the lack of continuous high-resolution observations. Here, the influence of small-scale dynamics (O(3.5–25) km, i.e. spanning upper submesoscale and mesoscale processes) on surface phytoplankton derived from satellite chlorophyll-a (Chl-a) is studied using Lagrangian metrics computed from High-Frequency Radar currents. The combination of complementary Lagrangian diagnostics, including the Lagrangian divergence along fluid trajectories, provides an improved description of the 3D flow geometry which facilitates the interpretation of two non-exclusive physical mechanisms affecting phytoplankton dynamics and patchiness. Attracting small-scale fronts, unveiled by backwards Lagrangian Coherent Structures, are associated to negative divergence where particles and Chl-a standing stocks cluster. Filaments of positive divergence, representing large accumulated upward vertical velocities and suggesting accrued injection of subsurface nutrients, match areas with large Chl-a concentrations. Our findings demonstrate that an accurate characterization of small-scale transport processes is necessary to comprehend bio-physical interactions in coastal seas.

Numerical-ecotoxicological approach to assess potential risk associated with oilfield production chemicals discharged into the sea

Several different chemical products are used on oil platforms to aid oil-water separation during the production process. These chemicals may enter into the sea by means of production water (PW), the main discharge derived from oil and gas offshore platforms. Consequently, toxic effects may occur in the marine environment, causing reductions in wildlife numbers, degrading ecosystem functions and threatening human health. For most of these chemicals, environmental toxicity and safety thresholds in marine ecosystems have not been fully investigated as yet. In this work, a numerical-ecotoxicological approach is proposed to assess the potential environmental risk associated with the discharge of five oilfield production chemicals (deoiler, scale inhibitor, corrosion inhibitor, catalyst, dehydrating agent) from a platform in the southern Adriatic Sea (Mediterranean Sea). Their concentrations in the seawater are numerically predicted, under different seasonal conditions, starting from the real concentrations used during the production process. The predicted concentrations are then evaluated in terms of possible toxic effects in order to assess the potential risk of oilfield production chemicals discharged into the sea.