Current riverine plastic monitoring best practices mainly consider surface observations, thus neglecting the underlying distribution of plastics in the water column. Bias on plastic budgets estimations hinders advances on modelling and prediction of plastics fate. Here, we experimentally disclose the structure of plastics transport in surface water flows by investigating how thousands of samples of plastics commonly found in fluvial environments travel in turbulent river flows. We show for the first time that surface tension plays a key role in the transport of plastics since its effects can be of the same magnitude as buoyancy and turbulence, therefore holding a part of the dispersed buoyant plastics captive by the water surface. We investigate two types of transport; surfaced plastics (surface tension-turbulence-buoyancy dominated), in contact with the free surface, and suspended plastics (turbulence-buoyancy dominated). We prove that this duality in transport modes is a major source of error in the estimation of plastic budgets, which can be underestimated by 90 % following current, well-established monitoring protocols if sampling is conducted solely in the water surface. Based on our empirical findings, we optimize physics-driven monitoring strategies for plastic fluxes in rivers, thereby achieving over a ten-fold reduction of the bias and uncertainty of riverine plastic pollution estimates.

Gas–liquid flows occur in many natural environments such as breaking waves, river rapids and human-made systems, including nuclear reactors and water treatment or conveyance infrastructure. Such two-phase flows are commonly investigated using phase-detection intrusive probes, yielding velocities that are considered to be directly representative of bubble velocities. Using different state-of-the-art instruments and analysis algorithms, we show that bubble–probe interactions lead to an underestimation of the real bubble velocity due to surface tension. To overcome this velocity bias, a correction method is formulated based on a force balance on the bubble. The proposed methodology allows to assess the bubble–probe interaction bias for various types of gas-liquid flows and to recover the undisturbed real bubble velocity. We show that the velocity bias is strong in laboratory scale investigations and therefore may affect the extrapolation of results to full scale. The correction method increases the accuracy of bubble velocity estimations, thereby enabling a deeper understanding of fundamental gas-liquid flow processes.