Coastal habitats are being rapidly altered by ‘ocean sprawl’, the replacement of natural, soft-sediment coastline with hard artificial structures of stone and concrete, potentially facilitating range expansions of rocky shore species. On the coasts of Britain and Ireland, climatic warming of coastal waters has coincided with range expansions of the intertidal gastropod Phorcus lineatus at four separate range edges, allowing a replicated analysis of range edge population genetics. Genomic analysis of single nucleotide polymorphism (SNP) markers in range edge populations provides no consistent evidence of local adaptation or genetic bottlenecks associated with these range expansions, suggesting that they have occurred primarily through dispersal of large numbers of larvae over short distances. Combined analysis of data from a high-resolution three-dimensional hydrodynamic model, surveys of British and Irish coasts, and neutral SNP markers indicates that ocean currents, deepwater channels and large expanses of unsuitable soft sediment habitat may limit expansion beyond current range edges. Construction of artificial rocky substrate such as coastal defences and offshore energy schemes at range edges does not yet appear to have enabled further range expansion, nor increased genetic connectivity across natural habitat gaps. This suggests that these artificial habitats are suboptimal or that expansion is restricted by climatic thresholds and/or oceanographic features rather than habitat availability. Ecological approaches to coastal engineering may change this situation if widely adopted, allowing artificial shores to act as habitat corridors and hence improving the climate resilience of rocky shore species

Coastal dunes are prone to morphological change during storm events, with implications for coastal flood risk, erosion and ecosystem function. Here, we consider the morphological impacts of a range of compound storm-driven events on the Ynyslas beach and dune system in mid-Wales (UK). Hydrodynamic and sediment transport processes were investigated by applying a multi-model framework, including a spectral wave model (Swan), a morphodynamic model (XBeach), and an aeolian sediment transport model (Duna). Simulations were forced with spring tides interacting with different combinations of extreme (100-year return period) storm surge, wave height, wind stress, and sea-level rise conditions. The worst-case simulation -- combining the above stressors -- predicted coastal water levels of 4.8 m above Highest Astronomical Tide and caused alongshore currents of speed up to 1.5 m/s. Waves caused severe erosion of the dune face, with an averaged horizontal recession of 20 m and 2.5 m of vertical erosion, producing a net volume erosion of approximately 50 m^3/m. Storm winds caused erosion of the dune crest and leeward slope of up to 85 m^3/m. This level of erosion represents maximal morphological change following a single compound storm event. Simulations with various combinations of the above drivers revealed that the extreme wave action is the most important factor to raise water level and increase nearshore currents, while sea-level rise will accelerate beach erosion at a faster rate compared to storm surges. The results have implications for climate change: projected sea-level rise and increased wave heights and winds speed in the future will likely accelerate dune erosion and change the morphology of the beach and the adjoining estuary ecosystem. The methodology is transferable to other beach and dune systems worldwide.

Estuarine compound flooding is a major concern for many communities worldwide. Terrestrial and space observations can provide high-resolution data to assess the accuracy of flood models by capturing the temporal and spatial scales of hazards. In this study, we applied in situ measurements and Sentinel-1 SAR data to calibrate and validate the LISFLOOD-FP hydrodynamic model in simulating compound flood events. The model parameterization of bottom roughness was calibrated using a land cover map, with in-estuary water levels during two flooding events compared to observations from moored pressure sensors. Furthermore, a raw Sentinel-1 SAR image that captured the flooding extent was pre-processed to remove noise and correct distortions. Image classification techniques were applied to isolate surface water from dry land in the SAR image, with the un-supervised classifier showing better results than the supervised. The processed image was compared with the modelled flood extent using eight comparative scenarios, using overlapping indices. Matching was good in the upper estuary, where compound flooding was strongest, but less accurate in other locations, likely due to unresolved drainage channels on the digital elevation model (DEM). The study has shown that processed SAR images combined with traditional in situ measurements can provide robust spatiotemporal validation for flood inundation models.

Microplastics (MPs) in wastewater are increasingly recognised as potential vectors for pathogens and antimicrobial resistance (AMR), yet their role across treatment remains poorly understood. This study tracked viral, bacterial, and AMR associations with MPs from hospital wastewater through to coastal receiving waters, including simulated combined sewer overflow (CSO) events, using quantitative real-time PCR, and shotgun metagenomics. MP concentrations found naturally in the wastewater matrix, declined from 467 to 33 particles L⁻¹ during WWTP passage, achieving 93% removal. Norovirus (GI and GII) and bacteria colonised beads and wet wipes throughout, with wet wipes retaining higher viral and AMR loads than plastic beads, likely due to structural complexity. Sequential sampling across treatment stages showed a reduction in norovirus and bacterial loads by ∼1 log, yet pathogens remained detectable on beads and wet wipes in final effluent. NoV GI predominated, while NoV GII concentrations and the class I integron-integrase (intI1) gene varied by treatment stage and sample type. Metagenomics showed enrichment of potentially pathogenic genera (Aeromonas, Pseudomonas, Flavobacterium) in bead and wet wipe biofilms, and network analysis identified associations between Aeromonas and clinically relevant beta-lactam resistance genes (OXA, CTX). Shifts at the activated sludge stage indicated bead and wet wipe associated communities in effluent reflect treatment microbiota rather than influent sources. Environmental MP concentrations are below those required to deliver an infectious viral dose, suggesting MP-mediated transmission is unlikely under normal conditions. However, during CSO events, beads and wet wipes retained high viral loads and may act as pathogen transport vectors. These findings highlight CSO management as a priority for reducing MP-associated pathogen risks in receiving waters.

Accurate prediction of suspended sediment concentration (SSC) is critically important for water quality assessments in marine and terrestrial aquatic environments. However, there is uncertainty associated with traditional predictive algorithms due to the non-stationarity of the SSC data; hence, studies to improve predictions are required. A Variational Mode Decomposition-Long Short-Term Memory-Self Attention-ensemble (VMD-LSTM-SA-ensemble) model is proposed for SSC prediction in this paper. The SSC data from the Rio Grande River, U.S., and the Belgian coastal zone were used to compare the performance of several models. It is found that the accuracy of the LSTM model is higher than the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) models. The integration of the LSTM model with a SA mechanism enhances prediction accuracy. Additionally, by applying VMD, the non-stationarity of the SSC data is effectively reduced. Thus, both the VMD-LSTM-SA-add and VMD-LSTM-SA-ensemble models perform better than the LSTM-SA model. The VMD-LSTM-SA-ensemble model effectively mitigates the accumulation of errors common in other models. Consequently, the VMD-LSTM-SA-ensemble model exhibits better performance in both single-step and multi-step predictions. These findings demonstrate the VMD-LSTM-SA-ensemble model exhibits superiority in predicting the SSC.

Microplastics (MPs) enter rivers and estuaries directly from urban water discharges, yet their type, distribution, residence, and role as potential vectors for harmful microbial communities remain poorly understood. This study characterises the presence of different MP types and identifies the potential associated microbial communities originating from a wastewater treatment plant (WWTP) and wider catchment sources in the Conwy estuary, UK, over a 15-month sampling period. Advanced laser direct infrared (LDIR) spectroscopy was used to classify MPs by size, shape, and polymer type, while molecular techniques identified microbial communities in associated water samples. MPs were present consistently in both the effluent and the river, with concentrations highest at the WWTP effluent, where daily loads peaked at nearly 1 kg. Across the campaign, 9,199 MPs were detected at the effluent pipe and 2,008 downstream, spanning 14 polymer types—polyurethane being the most abundant. Seasonal variations in MP abundance overall appeared not to be driven directly by changes in river flow rates, water level, nor rainfall. Microbial analysis of the water samples revealed diverse communities, including human pathogens (Moraxellaceae spp.) and antibiotic resistance genes (ARG). Potential markers of sewage contamination, such as Zoogloea and Prevotella, were also identified. This study highlights the challenges in effectively removing MPs during wastewater treatment and discharge into aquatic environments. It emphasises the need for standardised methods to quantify MPs accurately. The research provides valuable insights into MP contamination, environmental fate, and the potential for MPs to harbour harmful microbial communities. These findings are essential for developing strategies to mitigate the impacts of MPs on aquatic ecosystems and public health.

Understanding the flocculation dynamics of suspended particulate matter is essential for a comprehensive understanding of sediment transport in estuarine and coastal ecosystems. Field observations were conducted during both spring and neap tidal cycles at two contrasting sites, the highly turbulent, low-salinity Xuliujing site of the Yangtze River estuary, and the weakly turbulent, high-salinity Belgian coastal station MOW1. The two sites exhibited different flocculation dynamics and floc size distributions (FSDs). At Xuliujing, strong river discharge and pronounced ebb dominance intensified turbulent shear, making the fragmentation of flocs the governing process. This resulted in multimodal FSDs with high proportions of microflocs (similar to 13 mu m) and macroflocs (similar to 55 mu m). In contrast, at MOW1, high salinity and relatively weak, symmetric tidal currents favored salt-enhanced aggregation, resulting in larger, more stable flocs and more uniform FSDs. These contrasts indicate that in freshwater environments, turbulence controls both aggregation and breakup, whereas in saline waters, salinity governs aggregation and turbulence primarily limits the maximum size of flocs. Furthermore, a one-dimensional vertical hydrodynamic model coupled with a population balance flocculation model demonstrated satisfactory accuracy in simulating current velocities, suspended particulate matter concentrations, and FSDs at both sites, showing its capability to capture flocculation dynamics under different environmental conditions.

Exploring the intricate relationships between land and marine processes is essential for a comprehensive understanding of climate dynamics. While contemporary coupled climate models have made significant progress in capturing various interactions, the explicit resolution of estuarine and intertidal processes remains a challenge. Building upon the foundation laid by the UKC3 UK national climate model, we present a novel perspective by incorporating a high-resolution (

Flood protection authorities are not prepared for compound flood risk in estuaries-now and in the face of climate change. Climate projections are rarely downscaled appropriately to assess future changes in storm surge and concurrent river discharge extremes, and their interactions to exacerbate flooding. This is the first time that hourly and fine spatial resolution (7/2.2 km sea level/precipitation), physically consistent, climate projections are used to assess changes in storm surge and river discharge-driven compound events. The analysis, applied to the Dyfi estuary, western UK, uses 12 downscaled perturbed parameter ensembles for the high-emissions "RCP8.5" scenario from a global climate model (HadGEM3-GC3.0). Residual surge and river discharge projections are assessed independently to identify changes in magnitudes and return periods-then combined to identify changing patterns of dependence and timing of compound events. Under RCP8.5 scenario to 2080, river discharge is expected to increase by 28%-29% for 1/20 and 1/50-year events. Extreme (95th percentile) discharge events are more likely to occur concurrently with extreme surges, and compound events will occur more often, and with a shorter time lag between peak surge and peak discharge-potentially compounding flooding further. The analysis provided forcing conditions representative of future 1 in 20-year and 1 in 50-year events used to simulate a potential increased flood footprint in the estuary. The research raises the question of the wider pattern of future compound events throughout the UK, and worldwide, highlighting the critical need for downscaled, coastal and fluvial projections to futureproof flood management strategies.

ABSTRACTMany sharks, rays and skates are highly threatened and vulnerable to overexploitation, as such reliable monitoring of elasmobranchs is key to effective management and conservation. The mobile and elusive nature of these species makes monitoring challenging, particularly in temperate waters with low visibility. Environmental DNA (eDNA) methods present an opportunity to study these species in the absence of visual identification or invasive techniques. However, eDNA data alone can be difficult to interpret for species monitoring, particularly in a marine setting where its distribution can be influenced by water currents. In this study, we investigated the spatial and temporal distribution of elasmobranch species in two Special Areas for Conservation (SAC) off the coast of Wales. We took monthly eDNA samples for 1 year (starting September 2020 and March 2022 for the northern and southern SACs, respectively), and used metabarcoding to reveal the presence of elasmobranch species. We combined these data with hydrodynamic modelling and particle tracking methods to simulate the potential origins of the detected eDNA. We detected 11 elasmobranch species, including the critically endangered angelshark (Squatina squatina) and tope (Galeorhinus galeus). Most detections were in the spring and the fewest in the autumn. The particle tracking simulations predicted that eDNA was shed, on average, approximately 7 km and 15 km (in the northern and southern SACs, respectively) from the sampling stations at which it was detected. These results show that the two SACs represent important areas for elasmobranchs in the United Kingdom and demonstrate that eDNA methods combined with particle tracking simulations can represent a new frontier for monitoring marine species.

Transparent exopolymer particles (TEPs) are crucial for enhancing the flocculation of microplastics (MPs). However, quantitatively evaluating the influence of TEP on the flocculation process and addressing these effects in a flocculation model are challenging. In this study, three freshwater microalgae ( Scenedesmus sp., Aulacoseira granulata , and Melosira varians ) with various levels of TEP production were incubated to investigate the biologically mediated flocculation process with MPs in a mixing chamber. The results revealed that the three microalgal species significantly increased flocculation, with floc size increasing notably (one‐way analysis of variance, p value < 0.001) at later incubation periods (12, 16, 20, 24, and 30 days), compared with the early incubation periods (after 6 and 9 days), when TEP production was lower. A critical TEP concentration (0.42 mg/L) was observed, beyond which further increases in TEP production had minimal effects on the flocculation process. Among the selected microalgae, the Scenedesmus sp.‐MPs mixture presented a faster floc growth rate than Aulacoseira granulata and Melosira varians . Furthermore, a modified population balance equation model was proposed to incorporate the ratio of the TEP concentration to the microplastic concentration into the aggregation and maximum specific growth rate parameters. The modified model revealed that the floc growth rate and equilibrium mean size are dependent on the TEP concentration when the MP concentration is fixed, which is in good agreement with the experimental data. The modified model illustrates the potential to simulate exopolymer‐driven interactions between microalgae and MPs and provides insights into the mechanisms of bio‐mediated flocculation.

Urban wastewater contains a diverse array of human pathogenic viruses, often in high concentrations, presenting a significant challenge for water quality management. Sewage spills into natural water systems therefore pose a significant public health risk due to the potential to cause viral infections, yet the behaviour of viruses under dynamic environmental conditions remains poorly understood. This study investigates the decay of sewage-associated viruses (Adenovirus, Enterovirus, Hepatitis A Virus, Influenza A Virus, Norovirus GII, and Respiratory Syncytial Virus) in river, estuary, and marine water, with and without simulated sunlight. Using both qPCR and capsid integrity qPCR (CI-qPCR) methods, we found that in the absence of sunlight, time was the most significant factor influencing viral decay across all water types. The time required for a 90 % reduction in viral gene copies (T90) was observed within 0.3-24.3 days. Simulated sunlight accelerated viral decay, with significant reductions in gene copies l-1 observed within 1-3 days for all viruses studied, and T90 values ranging from 7 to 62.8 h. The effect of salinity on viral decay varied among viruses and water types. These results highlight the complex interplay between environmental water properties and viral persistence, emphasizing the critical role of solar radiation in viral inactivation. The study also demonstrates the value of using both qPCR and CI-qPCR methods to assess total and potentially infectious viral loads, respectively. These results have important implications for water quality management and public health risk assessment in diverse aquatic environments, particularly in the context of the increased frequency of sewage spills occurring in response to climate change and increasing urbanization. The data will support improvements in water quality modelling and associated risk management, contributing to more effective measures for protecting public health in coastal and inland water systems.

Tidal stream energy conversion is an attractive renewable energy option due to the predictability of tides and high energy density. Yet, before sites can be exploited to their full potential, detailed resource characterization is required to optimize device selection and array configuration, and to minimize environmental impacts. This study focuses on the Morlais tidal energy site in North Wales, where developers have been awarded 38 MW of tidal stream generation capacity by the UK Government. The study analyses sea bed and water column data collected across the site over the past decade, including multibeam echosounder data, multiple acoustic Doppler current profiler (ADCP) time series, meteorological and wave data. Additionally, high-resolution tidal and wave models are applied to further characterize the spatio-temporal variability. The undisturbed power density exceeds 10 kW/m2 at Morlais, with the most energetic locations closest to the shore - facilitating power export to the grid. There is significant interaction of waves and currents across the site. However, this mainly influences wave properties, which could affect maintenance of moorings or devices (due to increased wave steepness), rather than directly influencing the tidal energy resource. There are variations in flood/ebb asymmetry between ADCP moorings, and this is relatively strong at some locations.

Sea birds in the Irish Sea are known to target tidal mixing fronts (the interfaces between seasonally stratified and mixed waters) as foraging grounds as these tend to be areas high in nutrients and primary productivity and thus, prey availability. However, little is known about the inter- and intraannual variability of the areas selected as foraging grounds by the sea birds. Here, using foraging locations derived from GPS tags on Manx shearwaters (Puffinus puffinus) and reanalysis oceanographic data and observational data collected from cruises, we evaluate which oceanographic features are targeted by the shearwaters on their foraging trips into the Irish Sea and how the characteristics of these frontal areas vary seasonally and interannually. Comparing a range of different physical measures to describe front locations, we show that the birds generally select interannually persistent marginally stratified (as defined by the potential energy anomaly) areas. Furthermore, we demonstrate that the features which are selected by the birds as foraging grounds vary over the course of summer months. Next, we use projections of future changes in shelf sea oceanography to highlight and discuss the consequences changing shelf sea stratification and physical features in the Irish Sea.

Estuaries are crucial for freshwater and nutrient cycling throughout shelf seas that drives the biodiversity and ecology of coastal and marine wildlife, and provide ecosystem services that sustain the livelihoods and wellbeing of coastal communities. These ecosystems are, however, potential pollution corridors and sinks carrying sewage and other loads containing harmful pathogens and contaminants – a serious health issue that is worsening with littoralisation and population growth. Being at the interface between oceanographic and fluvial processes, estuaries are the most dynamic coastal system, where water quality processes and habitat dynamics are shaped by complex geo-physical, chemical, and biological interactions that change over small spatio-temporal scales and are unique to each estuary. It is essential that these systems maintain safe water quality standards and that we are prepared for future changes in water quality that will affect their ecological status and public health risk. This research aims to characterise variability and potential change in indicators of estuary health across the UK, using a robust analysis and modelling strategy, that can be built upon to evaluate a range of water quality degradation processes and used to inform future management strategies. We will present the first analysis of both riverine and marine climate projections for the 21st Century (UKCP18 RCP8.5 perturbed parameter ensemble), downscaled to hourly- and sub-meso-scales, and applied to all estuaries in England. In particular, characterising projected changes in hydrology, temperature, salinity, sea level, and coincident conditions. Additionally, we have developed fine-scale estuary hydrodynamic models (Delft3D) of all estuaries and present potential changes in simulated estuary residence times as a result of projected sea-level rise and changing hydrology. The analyses and simulations highlight estuaries and estuary types that are vulnerable to changes in the physical stressors of coastal water quality – where coastal management efforts and hazard response should be focused the coming decades.

Sustainability of bivalve shellfish farming relies on clean coastal waters, however, high levels of faecal indicator organisms (FIOs, e.g. Escherichia coli) in shellfish results in temporary closure of shellfish harvesting beds to protect human health, but with economic consequences for the shellfish industry. Active Management Systems which can predict FIO contamination may help reduce shellfishery closures. This study evaluated predictors of E. coli concentrations in two shellfish species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas), at different spatial and temporal scales, within 12 estuaries in England and Wales. We aimed to: (i) identify consistent catchment-scale or within-estuary predictors of elevated E. coli levels in shellfish, (ii) evaluate whether high river flows associated with rainfall events were a significant predictor of shellfish E. coli concentrations, and the time lag between these events and E. coli accumulation, and (iii) whether operation of Combined Sewer Overflows (CSO) is associated with higher E. coli concentrations in shellfish. A cross-catchment analysis gave a good predictive model for contamination management (R2 = 0.514), with positive relationships between E. coli concentrations and river flow (p=0.001), turbidity (p=0.002) and nitrate (p=0.042). No effect was observed for catchment area, the number of point source discharges, or agricultural land use type. 64% of all shellfish beds showed a significant relationship between E. coli and river flow, with typical lag-times of 1-3 days. Detailed analysis of the Conwy estuary indicated that E. coli counts were consistently higher when the CSO had been active the previous week. In conclusion, we demonstrate that real-time river flow and water quality data may be used to predict potential risk of E. coli contamination in shellfish at the catchment level, however, further refinement (coupling to fine-scale hydrodynamic models) is needed to make accurate predictions for individual shellfish beds within estuaries.

Treated and untreated wastewater enters estuaries via point source discharges, after which complex estuarine hydrodynamics can retain high concentrations of pathogens in these systems for days to weeks, posing a serious risk to public health. Through comprehensive fine scale three-dimensional numerical modelling, this research aims to study drivers of pathogen dispersal in estuaries and pathways of pathogen distribution. An interdisciplinary approach, combining knowledge from numerical modelling with laboratory derived data on pathogen behaviour and interactions with sediments, has been taken to improve the reliability of the model: 1) key fine-scale estuarine processes, i.e. current (including density current), turbulent mixing, and sediment transport have been studied using a process-based numerical model; 2) decay curves of target pathogens obtained through laboratory experiments for different water temperature, salinity, UV radiation have been implemented in the model; 3) the model also aims to incorporate pathogen attachment to sediments, their deposition, resuspension and subsequently altered decay rates.The Conwy estuary in North Wales, UK, has been used as our case study. The estuary holds considerable historical and contemporary significance in terms of shellfishery and tourism. With a catchment area of 678 km2 supporting a population of ~80,000 and large pastures, the estuary is susceptible to a range of pathogens, posing a public health risk via ingestion of bathing waters and indirectly via sea food. The transport of pathogens from point sources, including wastewater discharge and sewage overflow, into the coastal environment has been studied under both current and future climate conditions such as sea level rise, warmer coastal waters, stronger river flow and population growth drawn from climate projections. As a further aspect of this research, conceptual estuarine systems will also be used to study fate and transport of pathogens under common estuarine dynamics and under representative climate scenarios. This integration will allow for a more holistic approach that widens the applicability of the findings.This research will provide improved understanding of pathogen dispersal in coastal waters and the impact of climate change on pathogen distribution and potential exposure to humans. It will also provide insights for the development of adaptation strategies to protect public health under changing environmental conditions.

Estuarine flooding is driven by extreme sea-levels and river discharge, either occurring independently or at the same time, or in close succession to exacerbate the hazard, known as compound events. Estuaries have their own dynamics, and different behavior means flooding will occur under different conditions. Recent UK storms, including Storm Desmond (2015) and Ciara (2020), have highlighted the vulnerability of mountainous Atlantic-facing catchments to the impacts of compound flooding including risk to life and short- and long-term socioeconomic damages. There is a need to identify site-specific thresholds for flooding in estuaries, which represent the magnitude of key drivers over which flooding occurs, to improve prediction and early-warning of compound flooding. In this study, observational data and numerical modelling were used to reconstruct the historic flood record of an estuary particularly vulnerable to compound flooding (Conwy, North Wales). The record was used to develop a method for identifying combined sea level and river discharge thresholds for flooding using idealised simulations and joint-probability analyses. Only 6 records of known flooding are identified in the official record. The key limitation of using historic records of flooding is that not all flooding events have been documented, and there are gaps in the record. Therefore, this research also identified the top 50 extreme sea-level and river discharge events in the historic gauge measurements in the estuary, and cross-checked these against online sources using web scraping to establish if these additional 100 extreme events also led to flooding. A more comprehensive historic record of flooding allows more accurate thresholds for flooding to set in each estuary. Caesar-LISFLOOD, a hydrodynamic flow and morphological evolution model, is used in a sensitivity test to simulate inundation under different idealized sea-level and river discharge conditions to further isolate accurate thresholds. The variation in flooded area from a baseline scenario is used to capture flood magnitude associated with each scenario. The results show how flooding extent responds to increasing total water level and river discharge, with notable amplification in flood extent due to the compounding drivers in some circumstances, and sensitivity due to a 3-hour time-lag between the drivers. Joint probability analysis is important for establishing compound flood risk behaviour. Elsewhere in the estuary, either sea state (lower-estuary) or river flow (upper-estuary) dominated the hazard, and single value probability analysis is sufficient. These methods can be applied to estuaries worldwide to identify site-specific thresholds for flooding to support emergency response and long-term coastal management plans.

Many countries that are substantial contributors to global plastic pollution are also prone to tropical cyclones. Yet, the capacity for tropical cyclones to redistribute plastic waste has not been characterised. To address this, we simulate plastic transport from coasts in the Philippines archipelago during seven tropical cyclones, with a focus on the 2021 Super Typhoon Rai. To simulate plastic dispersal, a Lagrangian particle tracking model (OpenDrift) is forced with extreme typhoon wind conditions (parametric cyclone model) combined with ocean surface currents (comprising tidal currents, density-driven and wind-driven circulation, and Stokes drift). Compared to baseline simulations with quiescent wind conditions, we simulated plastics to be transported four times faster during Super Typhoon Rai (up to ∼ 40 km/day). Due to strong onshore typhoon winds, plastics were 10% more likely to become beached. Tropical cyclones create predictable patterns of plastic dispersal, exposing targeted regions to elevated plastic accumulation.