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Abstract Assessing microplastics risk to aquatic ecosystems has been limited by lack of holistic exposure data and poor understanding of biological response thresholds. Here we take advantage of two recent advances, a toxicological meta-analysis that produced biotic response thresholds and a method to quantitatively correct exposure data for sampling methodology biases, to assess microplastic exposure risk in San Francisco Bay, California, USA. Using compartment-specific particle size abundance data, we rescaled empirical surface water monitoring data obtained from manta trawls (> 333 μm) to a broader size (1 to 5000 μm) range, corrected for biases in fiber undercounting and spectroscopic subsampling, and assessed the introduced uncertainty using probabilistic methods. We then compared these rescaled concentrations to four risk thresholds developed to inform risk management for California for each of two effect categories/mechanisms - tissue translocation-mediated effects and food dilution - each aligned to ecologically relevant dose metrics of surface area and volume, respectively. More than three-quarters of samples exceeded the most conservative food dilution threshold, which rose to 85% when considering just the Central Bay. Within the Central Bay, 38% of the samples exceeded a higher threshold associated with management planning, which was statistically significant at the 95% confidence interval. For tissue translocation-mediated effects, no samples exceeded any threshold with statistical significance. The risk associated with food dilution is higher than that found in other systems, which likely reflects this study having been conducted for an enclosed water body. A sensitivity analysis indicated that the largest contributor to assessment variability was associated with estimation of ambient concentration exposure due to correcting for fiber undercounting. Even after compensating for biases associated with fibers and other small particles, concentrations from the trawl samples were still significantly lower than the 1-L grab samples taken at the same time, suggesting our SFB risk estimates are an underestimate. We chose to rely on the trawl data because the 1-L grab sample volume was too small to provide accurate spatial representation, but future risk characterization studies would be improved by using in-line filtration pumps that sample larger volumes while capturing a fuller range of particle size than a towed net.

Most marine litter pollution is assumed to originate from land-based sources, entering the marine environment through rivers. To better understand and quantify the risk that plastic pollution poses on aquatic ecosystems, and to develop effective prevention and mitigation methods, a better understanding of riverine plastic transport is needed. To achieve this, quantification of riverine plastic transport is crucial. Here, we demonstrate how established methods can be combined to provide a rapid and cost-effective characterization and quantification of floating macroplastic transport in the River Rhine. We combine visual observations with passive sampling to arrive at a first-order estimate of macroplastic transport, both in number (10–75 items per hour) and mass per unit of time (1.3–9.7 kg per day). Additionally, our assessment gives insight in the most abundant macroplastic polymer types the downstream reach of the River Rhine. Furthermore, we explore the spatial and temporal variation of plastic transport within the river, and discuss the benefits and drawbacks of current sampling methods. Finally, we present an outlook for future monitoring of major rivers, including several suggestions on how to expand the rapid assessment presented in this paper.

Understanding the global mass inventory is one of the main challenges in present research on plastic marine debris. Especially the fragmentation and vertical transport processes of oceanic plastic are poorly understood. However, whereas fragmentation rates are unknown, information on plastic emissions, concentrations of plastics in the ocean surface layer (OSL) and fragmentation mechanisms is available. Here, we apply a systems engineering analytical approach and propose a tentative ‘whole ocean’ mass balance model that combines emission data, surface area-normalized plastic fragmentation rates, estimated concentrations in the OSL, and removal from the OSL by sinking. We simulate known plastic abundances in the OSL and calculate an average whole ocean apparent surface area-normalized plastic fragmentation rate constant, given representative radii for macroplastic and microplastic. Simulations show that 99.8% of the plastic that had entered the ocean since 1950 had settled below the OSL by 2016, with an additional 9.4 million tons settling per year. In 2016, the model predicts that of the 0.309 million tons in the OSL, an estimated 83.7% was macroplastic, 13.8% microplastic, and 2.5% was