Modelling the spatial and seasonal distribution, fate and transport of floating plastics in tropical coastal waters

Model-based estimation of seasonal transport of macro-plastics in a marine protected area

Management of plastic litter in Marine Protected Areas (MPAs) is expensive but crucial to avoid harms to critical environments. In the present work, an open-source numerical modelling chain is proposed to estimate the seasonal pathways and fates of macro-plastics, and hence support the effective planning and implementation of sea and beach cleaning operations. The proposed approach is applied to the nearshore region that includes the MPA of Capo Milazzo (Italy). A sensitivity analysis on the influence of tides, wind, waves and river floods over the year indicates that seasonality only slightly affects the location and extension of the macro-plastic accumulation zones, and that beach cleaning operations should be performed in autumn. Instead, the influence of rivers on plastic litter distribution is crucial for the optimal planning of cleaning interventions in the coastal area.

Assessing the Settling Velocity of Biofilm-Encrusted Microplastics: Accounting for Biofilms as an Equivalent to Surface Roughness

While it is well established that a biofilm contributes to the sinking of plastics, the underlying mechanisms of how it influences the vertical transport of plastics have not been well explained. In this context, our study dives into the intricate effects of biofouling on the settling velocity (Ws) of microplastics (MPs) within the fluid. We adopt the perspective that the biofilm is a form of surface roughness impacting the drag coefficient (Cd) and vertical settling of MPs. By advancing the biofouling process model, we simulate the temporal variations of density and biofilm thickness of biofouled floating MPs, accounting for realistic parameters and assuming a layer-by-layer growth of biofilm on plastisphere surfaces. MPs of polyethylene (PE) exhibit a quicker initiation of descent compared to their polypropylene (PP) counterparts. Furthermore, leveraging computational fluid dynamics (CFD) simulation, the method to predict the Cd of spherical MPs with surface roughness is established. By treating the thickness of the biofilm as roughness height, an explicit method to predict the Ws of biofouled MPs is derived. The settling experiments for biofouled MPs conducted not only support the combination of the biofouling model and the explicit method to predict the Ws of biofouled MPs but also enhance the prediction accuracy by introducing a ratio parameter Co to better relate the equivalent surface roughness height (k) to the biofilm thickness (σ), i.e., k = Co·σ, where the recommended value of Co for spherical PP and PE MPs is between 0.5 to 0.8. This study, thus, provides new insights into the dynamics of biofouled MPs in hydraulic ecosystems.

An integrated modelling framework for multiple pollution source identification in surface water

Pollution source identification is vital in water safety management. An integrated simulation-optimization modelling framework comprising a process-based hydrodynamic water quality model, artificial neural network surrogate model and particle swarm optimization (PSO) was proposed to achieve rapid, accurate and reliable pollution source identification. In this study, the hydrodynamics and water quality processes in a straight lab-based flume were simulated to test pollution source identification under steady flow conditions. Additionally, the pollution source identification in the unsteady flow conditions was examined using a real-life estuary, specifically the Yangtze River estuary. First, we developed two process-based models to simulate hydrodynamics and water quality in the flume and estuary. Then, the data generated from the process-based models were used to develop surrogate models. Three typical artificial neural networks (ANNs) algorithms: backpropagation (BP), radial basis function (RBF) and general regression neural networks (GRNN) were selected to develop surrogates for process-based models (PBMs), and they were coupled with PSO algorithm to achieve the hybrid modelling framework for pollution source identification. Our results showed that hybrid PBM-ANNs-PSO models could be applied to identify the pollution source and quantify release intensity in spatial distribution when the discharge type was assumed as the point source with a continuous release. Multiple-performance criteria metrics, in terms of the coefficient of determination, root-mean-square error, mean absolute error, evaluated the model performance as "Excellent prediction". The BP-PSO models consistently appear to be the top-performing source identification model within the developed models, with most cases of relative error (RE) values lower than 5%. The new insights from the hybrid modelling framework would provide useful information for the local government agency to make reasonable decisions regarding pollution source identification issues.

Litter traps: A comparison of four marine habitats as sinks for anthropogenic marine macro-litter in Singapore

The potential for marine litter being trapped in biodiverse marine habitats such as mangrove forests, seagrass meadows and coral reefs is poorly understood. This study presents the first comprehensive investigation on the status of macro-litter across four marine habitats in Singapore during the two monsoonal seasons. Overall, litter density did not vary considerably between the southwest and the northeast monsoon. The litter density in terms of count was generally lower in seagrass meadows and coral reefs compared to mangroves and beaches. Plastic was the major type of litter found across most habitat types. Notably, many fishing-related items were found on coral reefs, while drinking straws were abundant at the mangrove strandlines during the southwest monsoon. Foam fragments and cigarette butts were common at the beach strandlines. These results suggest that mangroves among other habitats examined here should be prioritised for clean-up efforts in order to restore these critical coastal habitats.

Microplastics transport in a low-inflow estuary at the entrance of the Gulf of California

Microplastics (MPs) are recognized as a global emergent pollution impact, which can affect all food chains. Estimating MPs transport pathways in coastal ecosystems is needed to assess their likely effects. Here, we studied MPs accumulation and transport pathways in the Estero de Urias lagoon system (low-inflow estuary) using field data and a 3D particle model. Field results showed that the MPs present similar abundances throughout the study area during the dry and rainy seasons. Model simulations indicated that i) morphology and tidal currents caused the MPs discharged in the lagoon to remain inside, and ii) wind-induced currents caused the MPs in the coastal area to be transported to the southwest. These transport processes may be responsible for homogenizing MPs concentrations through the studied area. In addition, model simulations suggested that EUL-dense waters can export MPs from the coastal area to the sea bottom.

Anthropogenic marine litter: An approach to environmental quality for India's southeastern Arabian Sea coast

Anthropogenic marine litter (AML), mainly plastic, is a global concern that is persistent and widespread. To prevent and mitigate this threat, we need to understand the magnitude and source of AML. There is limited knowledge about AML pollution on the Indian Coast. In this context, the present study examined the distribution, abundance, typology, and beach quality based on AML along 22 beaches on the southeastern coast of the Arabian Sea. A total of 4911 AML items were classified into 9 categories, weighing 16.79 kg, and retrieved from a total area of 8000 m². The mean abundance and weight of AML in the current study were 0.45 ± 0.34 items/m² and 1.53 ± 0.92 g/m², respectively. Thottapally showed the most abundant AML among the studied beaches with 0.96 items/m², followed by Azheekkal with 0.73 items/m². Plastic, being the most common item, accounts for 77.6 % of all items and has a mean density of 0.35 items/m² comprising hard plastic (22 %), thermocol (13 %), food wrappers (7 %), cigarette butts (7 %), plastic rope (6 %), and plastic cutlery (6 %). Hazardous anthropogenic litter (HAL) was maximum at Thottapally (17.71 %; 85 out of 480 items collected). Based on the cleanliness of beaches, they are graded "moderately clean" (63 %) by the General Index (GI), "clean" (54 %), and "moderately clean" (40 %) as calculated by the Clean Coast Index (CCI). Hazardous Anthropogenic Beach Litter Index (HABLI) classifies 72 % of beaches as "moderately safe", while the Environmental Status Index (ESI) rates 68 % of beaches as "mediocre". Besides, model simulations demonstrated the pathways of AML propagation, which correlate to the littoral and coastal current flow patterns over the region. Land-based activities were the crucial factors influencing AML distribution. The study highlighted the need for effective regional litter management strategies, policy instruments for the litter impact pathways, economic, regulatory, and behavioural management tools, which were also discussed.

Occurrence of antibiotic resistance genes carried by plastic waste from mangrove wetlands of the South China Sea

Plastic waste can carry organisms such as bacterial pathogens and antibiotic resistance genes (ARGs) over long distances. However, only few studies have been conducted on the occurrence of ARGs in plastic waste from mangrove wetlands. This study evaluated the distribution characteristics and ecological risks of plastic waste from mangroves in the coastal areas of the South China Sea. The correlation between anthropogenic activity levels and abundance of ARGs in mangroves was evaluated. Transparent and white were the common colors of plastic waste in mangroves. The main shapes of plastic waste were foam and film. The predominant types of plastic waste order were as follows: polyethylene (30.18 %) > polypropylene (27.51 %) > polystyrene (23.59 %). The living area (LA) mangroves had the highest polymer hazard and pollution load indices of 329.09 and 10.03, respectively. The abundance of ARGs (5.08 × 10⁸ copies/g) on the plastic surface in LA mangroves was significantly higher than that of the other mangrove areas. Furthermore, there was a significant correlation between ARGs and intI1 on the plastic surface in mangroves. Correlation analysis between the ARGs and intI1 showed that most of the ARGs were correlated with intI1 except for msbA. In LA mangroves, sociometric and environmental factors showed significant correlations with the absolute abundances of the four ARGs and intI1, indicating that anthropogenic activities may lead to changes in the amount of ARGs on plastic surfaces. Furthermore, the ARG storage of plastic waste from different mangroves was as follows: protected areas (3.12 × 10¹⁷ copies) > living areas (2.99 × 10¹⁷ copies) > aquaculture pond areas (2.88 × 10¹⁷ copies). The higher ARG storage of LA mangroves, with the smallest area, greatly increased its ecological risk. The results of this study can provide basic data for processes that influence the distribution of plastic waste and ARGs in mangroves.

Transport of degradable/nondegradable and aged microplastics in porous media: Effects of physicochemical factors

The degradable properties of degradable plastics allow them to form microplastics (MPs) faster. Therefore, degradable MPs may easily be transported in the underground environment. Research on degradable MPs transport in porous media is necessary and urgent. In this study, polylactic acid (PLA) and polyvinyl chloride (PVC) were selected to compare the transport differences between degradable and nondegradable MPs under different factors (flow rates, ionic strengths (ISs), pH, and coexisting cations) through column experiments, and UV irradiation was used to further simulate the effect of aging on different types of MPs. Fourier transform infrared (FT-IR) and X-ray photoelectron spectroscopy (XPS) were used to characterize functional groups and to determine the surface elements of MPs, respectively. The results showed that MPs were more mobile at higher flow rate, lower IS, higher pH, and monovalent cations. The order of transport capacity of MPs was PVC < aged PVC < PLA < aged PLA. This result was mainly attributed to the more negative Zeta potential and higher dispersion stability of aged PLA and PLA, which were caused by abundant O-functional groups. Compared with PVC, the O/C ratio of PLA increased significantly after aging, indicating that PLA was more prone to aging. The advection-dispersion-equation (ADE) fitted the transport data of MPs well. The interaction energy of MPs and quartz sand was accurately predicted by the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. This work contributes to a comprehensive understanding of the transport of degradable MPs in the environment.

A high-precision prediction for spatiotemporal distribution and risk assessment of antibiotics in an urban watershed using a hydrodynamic model

A methodology for the high-precision prediction and risk assessment of antibiotics at the watershed scale was established. Antibiotic emission inventory and attenuation processes were integrated into the MIKE 11 model to predict the spatiotemporal distribution of norfloxacin, ofloxacin, enrofloxacin, erythromycin, roxithromycin, and sulfamethoxazole in the Nanfei River watershed, China. Considering the variations in antibiotic removal in sewage treatment plants, manure composting, and lagoon systems, the high, medium, and low removal efficiencies of selected antibiotics across China were obtained and used as the best, expected, and worst scenarios, respectively, to evaluate the uncertainty of antibiotic emissions. The predicted concentrations were comparable to antibiotic measurements after flow calibration. The prediction results showed that the highest concentration exposures were mainly concentrated in urban areas with a dense population. Flow variations controlled the temporal distribution characteristics of antibiotics via the dilution effect, and the concentrations of antibiotics in the dry season were 3.1 times higher than those in the wet season. The median concentrations of norfloxacin and erythromycin ranged from 111.36 ng/L to 592.33 ng/L and 106.63 ng/L to 563.01 ng/L, respectively, which both posed a high risk to cyanobacteria and a medium risk to spreading antibiotic resistance. Scenario analysis further demonstrated that high removal efficiencies of these antibiotics can considerably reduce the potential ecotoxicity risks and bacterial resistance selection. The developed methodology for predicting the distribution and risk of antibiotics was suitable for the risk assessment and control strategy of human- and livestock-sourced pollutants.

Identifying marine debris source position using adjoint marginal sensitivity method and stranded beach litter data in Singapore

Movement of marine debris is transboundary and complex, travelling vast distances and accumulating on shorelines. These marine debris wash ashore as stranded beach litter. The objective of this work is to identify release sources of marine debris accumulated along the Singapore coastlines collected by applying a time-backward adjoint marginal sensitivity method and citizen science data of stranded beach litter by a voluntary beach clean-up group. A popular tourist hotspot on the opposite shore was estimated as a possible release source contributing to the marine debris accumulation. This analytical result was validated by population density, industry types, rainfall, and inference from product packaging labels. The use of the citizen science data also illustrated potential as a data source for baseline monitoring and long-term cross-border research that influence policymaking. Future research can be conducted in an expanded domain, considering monsoon effects and instantaneous release events.

Microplastic pollution in fragile coastal ecosystems with special reference to the X-Press Pearl maritime disaster, southeast coast of India

Microplastics (MPs) are a global environmental concern and pose a serious threat to marine ecosystems. This study aimed to determine the abundance and distribution of MPs in beach sediments (12 beaches), marine biota (6 beaches) and the influence of microbes on MPs degradation in eco-sensitive Palk Bay and Gulf of Mannar coast. The mean MP abundance 65.4 ± 39.8 particles/m² in beach sediments; 0.19 ± 1.3 particles/individual fish and 0.22 ± 0.11 particles g^-1 wet weight in barnacles. Polyethylene fragments (33.4%) and fibres (48%) were the most abundant MPs identified in sediments and finfish, respectively. Histopathological examination of fish has revealed health consequences such as respiratory system damage, epithelial degradation and enterocyte vacuolization. In addition, eight bacterial and seventeen fungal strains were isolated from the beached MPs. The results also indicated weathering of MPs due to microbial interactions. Model simulations helped in tracking the fate and transboundary landfall of spilled MPs across the Indian Ocean coastline after the X-Press Pearl disaster. Due to regional circulations induced by the monsoonal wind fields, a potential dispersal of pellets has occurred along the coast of Sri Lanka, but no landfall and ecological damage are predicted along the coast of India.

Source, fate, transport and modelling of selected emerging contaminants in the aquatic environment: Current status and future perspectives

The occurrence of emerging contaminants (ECs), such as pharmaceuticals and personal care products (PPCPs), perfluoroalkyl and polyfluoroalkyl substances (PFASs) and endocrine-disrupting chemicals (EDCs) in aquatic environments represent a major threat to water resources due to their potential risks to the ecosystem and humans even at trace levels. Mathematical modelling can be a useful tool as a comprehensive approach to study their fate and transport in natural waters. However, modelling studies of the occurrence, fate and transport of ECs in aquatic environments have generally received far less attention than the more widespread field and laboratory studies. In this study, we reviewed the current status of modelling ECs based on selected representative ECs, including their sources, fate and various mechanisms as well as their interactions with the surrounding environments in aquatic ecosystems, and explore future development and perspectives in this area. Most importantly, the principles, mathematical derivations, ongoing development and applications of various ECs models in different geographical regions are critically reviewed and discussed. The recommendations for improving data quality, monitoring planning, model development and applications were also suggested. The outcomes of this review can lay down a future framework in developing a comprehensive ECs modelling approach to help researchers and policymakers effectively manage water resources impacted by rising levels of ECs.

Advancing prediction of emerging contaminants in a tropical reservoir with general water quality indicators based on a hybrid process and data-driven approach

Monitoring and predicting the occurrence and dynamic distributions of emerging contaminants (ECs) in the aquatic environment has always been a great challenge. This study aims to explore the potential of fully utilizing the advantages of combining traditional process-based models (PBMs) and data-driven models (DDMs) with general water quality indicators in terms of improving the accuracy and efficiency of predicting ECs in aquatic ecosystems. Two representative ECs, namely Bisphenol A (BPA) and N, N-diethyltoluamide (DEET), in a tropical reservoir were chosen for this study. A total of 36 DDMs based on different input datasets using Artificial Neural Networks (ANN) and Random Forests (RF) were examined in three case studies. The models were applied in prognosis validation based on easily accessible data on water quality indicators. Our results revealed that all the models yielded good fits when compared to the observed data. These new insights into the advantages using the combination of traditional PBMs and DDMs with general water quality datasets help to overcome the constraints in terms of model accuracy and efficiency as well as technical and budget limitations due to monitoring surveys and laboratory experiments in the study of fate and transport of ECs in aquatic environments.

Microplastics in equatorial coasts: Pollution hotspots and spatiotemporal variations associated with tropical monsoons

Microplastics (MP < 5 mm) are eroding oceanic health and coastal development at a planetary scale. Coastlines in Southeast Asia (SEA) are plagued with plastic litters, but how MP are dispersed within SEA region is poorly understood, which can vary dramatically under the tropical climate. We systematically quantified MP in equatorial Singapore, to assess how prevailing Monsoons and other factors impact MP distributions in beaches and mangroves. Data highlighted spatial preponderance differed broadly by seasons (p < 0.05) and were strongly modulated by wind speediness (p < 0.05; r = 0.6-0.7) and promoted transboundary migrations of MP. Conversely, an inverse relationship existed between sediment MP and rainfall (r = -0.54) possibly due to re-entrainment of surficial MP. Elevated concentrations in mangrove's compartments (p < 0.05) suggest effective repository hotspots. Coastal MP consisted assorted morphologies and commonest polymers including 34% polypropylene (PP), 26% polyethelene (PE), and 23% Low Density PE. Further comparisons revealed coastal MP in Singapore accelerated by two orders of magnitude since 2014, implying cumulative pollution which is not reversible. We synthesized the first seasonal coastal MP report in SEA which is useful for source apportionment, prediction study, and mitigation planning under tropical circumstances.

Do microplastic biofilms promote the evolution and co-selection of antibiotic and metal resistance genes and their associations with bacterial communities under antibiotic and metal pressures?

Microplastic (MP) biofilms with heterogeneous bacterial compositions and structure have become a hotspot of antibiotic resistance genes (ARGs) in aquatic environments. The evolutionary features of ARGs and their related factors including class 1 integron (intI1), metal resistance genes (MRGs), and bacterial communities in MP biofilms under exogenous pressures and how they compared with natural substrates (NS) are unclear. The individual and combined pressures of sulfamethoxazole, tetracycline, and zinc were used to drive the dynamic evolution of ARGs, intI1, MRGs, and bacterial communities in the MP and NS biofilms. The exogenous pressures from the combined selection of sulfamethoxazole, tetracycline, and zinc and their increasing concentrations both significantly enhanced the abundances of ARGs on the MP compared to the NS. Meanwhile, the selective pressures resulted in obvious dissimilarities between the MP and NS bacterial communities. The core bacterial taxa and the co-occurrence patterns of ARGs and bacterial genera in the biofilms of MP and NS were obviously different, and more potential ARG host bacteria selectively colonized the MP. Metal pressure also enhanced the enrichment of ARGs in the MP biofilms by promoting the spread of intI1 via the co-selection mechanism.

Size-dependent adsorption of waterborne Benzophenone-3 on microplastics and its desorption under simulated gastrointestinal conditions

Microplastics (MPs) are global pollutants with heightened environmental and health concerns in recent years because of their worldwide distribution across aquatic environments, ability to load chemical contaminants and the potential for ingestion by animals, including human. In this study, three commonly used and environmentally detected plastics, i.e. polystyrene, polyethylene, polypropylene with sizes of 550, 250 and 75 μm, plus two submicron-sized polystyrene microplastics (5 and 0.5 μm) were assessed as solid adsorbents for a prevalent UV filter, benzophenone-3 (BP-3). The affinity and process of adsorption exhibited differentials among different sizes and types of MPs. Apparent desorption of BP-3 from MPs under simulated gastrointestinal conditions was not significantly enhanced, which might be due to the presence of the enzyme proteins, indicating potential risk of the contaminants carried by MPs. The desorption of BP-3 from MPs was affected by the size, type of MPs and the components of the gastrointestinal fluid.

Microplastics in aquatic environment: Challenges and perspectives

The occurrence of microplastics in the aquatic environment has become a growing concern globally. Microplastics pose a hazard to the ecological system, and their presence, particularly in the water, has an adverse impact on human health and the ecosystem. Microplastics are released into the environment directly from everyday used plastic items, degradation of plastics, industries, and wastewater treatment plants. Once these contaminants enter the water, aquatic life feeds on them, and microplastics enter the food chain and cause severe health hazards. An assessment of microplastics' ecological risks is essential; however, it is challenging in the present scenario due to limited information available. To fill these knowledge gaps, this paper comprehensively reviews the sources and transport of microplastics in the water environment and their environmental and health effects, global policy frameworks, analytical techniques for microplastic detection, and control strategies to prevent microplastics release in the aquatic environment.

A comprehensive modelling approach to understanding the fate, transport and potential risks of emerging contaminants in a tropical reservoir

We developed a comprehensive integrated water quality modeling approach towards a better understanding of the fate and transport of emerging contaminants and comprehensive assessment of their potential risks in a tropical reservoir. Two representative emerging contaminants, namely Bisphenol A (BPA) and N, N-diethyltoluamide (DEET), were selected for this study. Unlike the traditional water quality modeling approach, the target emerging contaminants were modelled in four multi-compartments and coupled to a 3D-dimensional eutrophication model to investigate their interactions with other water quality state variables. First, the integrated model was calibrated and validated in four multi-compartments against an observed dataset in 2014. Subsequently, the correlation analysis between emerging contaminants and general water quality parameters were conducted. The potential ecological risks in this reservoir were also assessed via the trophic state index (TSI) and coupled to a species sensitivity distribution (SSD)-Risk Quotient (RQ) method. Finally, the model was applied to describe the dynamics of the two emerging contaminants and examine the direct and indirect influences of other environmental factors on their multi-compartment distributions in the aquatic environment. The comprehensive approach provides new insights into dynamic modeling of the fate and transport of emerging contaminants, their interactions with other state variables as well as an assessment of their potential risks in aquatic ecosystems.