Nanoplastics in Water: Artificial Intelligence-Assisted 4D Physicochemical Characterization and Rapid In Situ Detection.

For the first time, we present a much-needed technology for the in situ and real-time detection of nanoplastics in aquatic systems. We show an artificial intelligence-assisted nanodigital in-line holographic microscopy (AI-assisted nano-DIHM) that automatically classifies nano- and microplastics simultaneously from nonplastic particles within milliseconds in stationary and dynamic natural waters, without sample preparation. AI-assisted nano-DIHM identifies 2 and 1% of waterborne particles as nano/microplastics in Lake Ontario and the Saint Lawrence River, respectively. Nano-DIHM provides physicochemical properties of single particles or clusters of nano/microplastics, including size, shape, optical phase, perimeter, surface area, roughness, and edge gradient. It distinguishes nano/microplastics from mixtures of organics, inorganics, biological particles, and coated heterogeneous clusters. This technology allows 4D tracking and 3D structural and spatial study of waterborne nano/microplastics. Independent transmission electron microscopy, mass spectrometry, and nanoparticle tracking analysis validates nano-DIHM data. Complementary modeling demonstrates nano- and microplastics have significantly distinct distribution patterns in water, which affect their transport and fate, rendering nano-DIHM a powerful tool for accurate nano/microplastic life-cycle analysis and hotspot remediation.

In-situ and real-time nano/microplastic coatings and dynamics in water using nano-DIHM: A novel capability for the plastic life cycle research.

A novel nano-digital inline holographic microscope (nano-DIHM) was used to advance in-situ and real-time nano/microplastic physicochemical research, such as particle coatings and dynamic processes in water. Nano-DIHM data provided evidence of distinct coating patterns on nano/microplastic particles by oleic acid, magnetite, and phytoplankton, representing organic, inorganic, and biological coatings widely present in the natural surroundings. A high-resolution scanning transmission electron microscopy confirmed nano-DIHM data, demonstrating its nano/microplastic research capabilities. The sedimentation of two plastic size categories was examined: (a) ∼10 to 700 µm, and (b) ∼ 1 to 5 mm. Particle size was the primary factor affecting the sedimentation for studied (a) microplastics and (b) pellets. Two types of silicone rubbers exhibited different sedimentation processes. We also demonstrated that inorganic ions in seawater and oleic acid organic coatings altered the sedimentation velocity of studied plastics by 9 - 13% and 5 - 9%, respectively. Semi-empirical probability functions were developed and incorporated into a numerical model (CaMPSim-3D) to simulate the transport of studied microplastics and pellets in the Saint John River estuary. Water dynamics was the driving force of plastic transport, yet the accumulation of plastics was selectively dependant on particle physicochemical properties such as size and density by ∼ 7%. The usage of nano-DIHM for targeted identification of nano/microplastic hotspots and aquatic plastic wastes remediation were discussed.

A numerical framework for modeling fate and transport of microplastics in inland and coastal waters.

Proliferation of microplastics in rivers, lakes, estuaries, coastal waters and oceans is a major global challenge and threat to the environment, livelihoods and human health. Reliable predictive tools can play an essential role in developing an improved understanding of microplastics behaviour, exposure and risk in water bodies, and facilitate identification of sources and accumulation hot spots, thereby enabling informed decision-making for targeted prevention and clean-up activities. This study presents a new numerical framework (CaMPSim-3D) for predicting microplastics fate and transport in different aquatic settings, which consists of a Lagrangian, three-dimensional (3D) particle-tracking model (PTM) coupled with an Eulerian-based hydrodynamic modeling system (TELEMAC). The 3D PTM has several innovative features that enable accurate simulation and efficient coupling with TELEMAC, which utilizes an unstructured computational mesh. The PTM is capable of considering spatio-temporally varying diffusivity, and uses an innovative algorithm to locate particles within the Eulerian mesh. Model accuracy associated with different advection schemes was verified by comparing numerical predictions to known analytical solutions for several test cases. The implications of choosing different advection schemes for modeling microplastics transport was then investigated by applying the PTM to simulate particle transport in the lower Saint John River Estuary in eastern Canada. The sensitivity of the PTM predictions to the advection scheme was investigated using six numerical schemes with different levels of complexity. Predicted particle distributions and residence times based on the fourth-order Runge-Kutta (RK4) scheme differed significantly (residence times by up to 100 %) from those computed using the traditional first-order (Euler) method. The Third Order Total Variation Diminishing (TVD3) Runge-Kutta method was found to be optimal, providing the closest results to RK4 with approximately 27 % lower computational cost.

Fate and transport of coastal driftwood: A critical review.

Driftwood originating from natural and anthropogenic sources is abundant in coastal regions and plays an important role in ecosystems, providing habitat, structure, nutrients, and carbon storage. Conversely, large accumulations of driftwood can litter coastal zones, negatively impact coastal ecosystems and pose hazards to navigation, infrastructure and communities. Knowledge of the processes underlying the fate and transport of coastal driftwood is therefore needed to inform sustainable management practices. The present state of understanding is limited, and predominantly founded on studies of rivers and tsunamis, where the spatio-temporal scales and driving processes are significantly different from typical climatic or storm conditions in coastal waters. The authors critically review research on fate and transport of driftwood in coastal waters, and identify research needs and opportunities. Key knowledge gaps relate to: interactions between driftwood, littoral zone hydrodynamics and geomorphology; mechanisms of driftwood rafting and accumulation; and influence of weathering and degradation on mobility.