0
Article Tier 2 Environmental Sources Marine & Wildlife Policy & Risk Sign in to save

A Real-time Product to Help Ocean Cleanup Operations

AI summary Read the abstract

A real-time operational product was developed to simulate the drift of ocean plastic debris using ocean current models derived from satellite and drifter data, aimed at improving the efficiency of ocean cleanup operations. The tool helps predict where old, weathered plastic debris accumulates to guide search and recovery efforts.

Study Type Environmental

Growing awareness of plastic pollution in the ocean results in increasing numbers of projects and ideas of the open ocean cleanup. The efficiency of such operations is severely limited by the absence of an observing system capable of detecting individual items of their dense groups. To help coordinate the search of debris, we simulate patterns of old, low-windage debris. In these numerical experiments, model tracer is advected by the SCUD (Surface CUrrents from Diagnostic) model, derived from a synthesis of drifter and satellite data. A standard drifter is drogued at 15 meters depth that corresponds well to the vertical extent of such debris as derelict fishing nets or depth of mixing of microplastics. The model starts from 1993 (when satellite altimetry became available) and is run under continuous uniform source from all shorelines. Calculations are looped until the solution reaches saturation. This way we eliminate sensitivity to (usually unknown) distribution of debris sources and focus on the tracer patterns that are determined by the ocean dynamics. Panel A exemplifies the model tracer pattern that was tested and approved in several collaborative debris search operations. One lesson from that experience was that wind plays a critical role in the success of the operation: wind ways block the view and mix debris down, removing it from the surface and making observations difficult. Even if debris is detected, it’s retrieval in the rough sea may be also difficult. To account for the effect of the wind we use 10-day NOAA WFS output (B) and introduce functions (C), describing wind effects on visibility and operations. These functions are then used to mask tracer simulations (A). The final product, presented on panel D, visualizes a compromise between areas of high debris concentration and regions of acceptable forecasted sea state. The North Pacific product is public and is currently being tested in operations. Figure Caption. Real-time model tracer concentration (A), 10-day mean speed from the NOAA WFS (B), function describing effects of the wind on visibility of debris and feasibility of operations (C), and combined product quantifying success of the search & retrieval operation (D). Units are m/s in B and conventional elsewhere.

More Papers Like This

Article Tier 2

A Real-time Product to Help Ocean Cleanup Operations

AI summary Read the abstract

Researchers developed a real-time oceanographic product to support open-ocean plastic cleanup operations, integrating current, wind, and wave data to generate operational forecasts of plastic debris drift and accumulation that can guide the routing of cleanup vessels.

Article Tier 2

Drift Field Net: Learning Ocean Lagrangian advection fields from in-situ and satellite observations

AI summary Read the abstract

Scientists built an AI tool that predicts ocean currents more accurately than current forecasting systems, helping track where floating plastic debris drifts in the Pacific. Better predictions mean cleanup crews can target garbage patches more effectively, which matters because ocean microplastics eventually make their way into seafood and drinking water.

Article Tier 2

Predicting Drift in the North Pacific Garbage Patch: A Benchmark of Data-Driven and Physics-Based Models

AI summary Read the abstract

Researchers compared computer models that predict how floating ocean debris drifts in the North Pacific Garbage Patch, testing both physics-based methods and data-driven approaches trained on ocean current data. They checked these predictions against real GPS tracking data from drifting buoys and tagged debris. Data-driven models performed better than physics-based ones for short-term forecasts of up to 72 hours.

Article Tier 2

Modeling the convergence of buoyant debris in the Indian Ocean: Insights from surface drifter trajectories and Lagrangian simulations

AI summary Read the abstract

Researchers used six surface drifter trajectories in the Southern Indian Ocean, combined with Lagrangian particle simulations that incorporate Stokes drift, to map a plastic convergence zone in the western basin fed by the Agulhas Return Current and South Equatorial Current—filling a major gap in understanding where buoyant debris accumulates in this under-monitored ocean.

Article Tier 2

Comparing models and observations of the surface accumulation zone of floating plastic in the North Atlantic subtropical gyre

AI summary Read the abstract

This study compared ocean circulation models to observational data on where floating plastic accumulates in the North Atlantic subtropical gyre. Improving model accuracy is important for predicting plastic concentration zones and designing effective ocean cleanup strategies.

Research digests by email

When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.

Email me about

Share this paper