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OpenDrift plastic waste in Thanh Hoa

Table 2. Observational data on the types, quantities, composition, size, and density of plastic waste present
in the Ma, Lach Bang, and Len rivers

Waste type Lach Bang Len Ma
Quantity (pieces) Mass (kg) Quantity (pieces) Mass (kg) Quantity (pieces) Mass (kg)
Plastic bags 186 4.50 588 11.76 1,259 45.79
Strings 45 0.97 118 2.03 387 2.28
Food bags 91 1.23 402 6.72 431 0.74
Single-use 72 0.87 187 0.98 236 0.97
plastics
Hard plastics 88 1.84 170 3.84 158 2.59
Styrofoam 132 0.40 185 0.46 506 0.93
Pineapple sacks 16 1.77 26 3.55 114 8.91
Raincoats 11 0.73 12 2.05 65 5.86
Fishing-tackle 41 0.50 133 2.13 353 3.73

A B

Figure 5. Average river flow in April, July, September,
and December for the Ma River at Cam Thuy station Figure 6. Comparison of marine plastic debris
accumulation trends between OpenDrift model
patterns. Combined with hydrodynamic forcing, the setup results and unmanned aerial vehicle (UAV)-derived
enables accurate simulation of plastic waste trajectories observations in the Nghi Son bay area. (A) Simulation
and accumulation zones in the OpenDrift framework. results for September 2024 from the OpenDrift
model. (B) UAV-derived observations from imagery
4. Results and discussion captured in September 2024.

4.1. Model simulation and accuracy assessment The results indicate that the modeled trend of
In this study, simulation results from the OpenDrift plastic accumulation aligns reasonably well with
model, run from June 2024 and forecasted through observations from remote sensing data. The general
September 2024, were compared with plastic debris pattern shows higher concentrations of plastic debris
detection data extracted from unmanned aerial vehicle in enclosed coastal areas, gradually decreasing toward
(UAV) imagery captured in late September 2024 (project offshore regions. This suggests that the OpenDrift
code: ĐTĐL.CN.55/20). The comparison is illustrated model provides a reasonably accurate simulation of the
in Figure 6, where Figure 6A shows the simulated plastic transport, dispersion, and accumulation of plastic debris
debris density under the September 2024 scenario, and in the Thanh Hoa marine area.
Figure 6B presents plastic debris density derived from Based on these simulation results, the model was
UAV-based calculations. These datasets were overlaid subsequently applied to the remaining scenarios
to evaluate the accuracy of the model in capturing to develop risk zoning maps for plastic debris
plastic waste dispersion and accumulation patterns. accumulation.

Volume 22 Issue 4 (2025) 83 doi: 10.36922/AJWEP025170129