Plastic pollution, particularly in marine environments, is a major global concern. Annual ocean plastic waste is estimated at 8.8 million tons. Erosion and fragmentation of plastic debris lead to the formation of secondary micro- and nanoplastics, while primary microplastics are directly introduced via sources such as cosmetics. The size range terminology is still evolving, but generally, microplastics encompass particles from 1 µm to 5 mm, with nanoplastics typically defined as particles smaller than a few micrometers (this study considers 100 nm particles as nanoplastics and ≥1 µm as microplastics). Nanoplastics are particularly problematic due to their small size (difficult to capture, cellular penetration), large surface area (toxin binding), and colloidal nature (limited quantification and qualification methods). Studies have documented the presence of nanoplastics in aquatic animals and even human placentas. While extensive data exists on microplastic abundance, there's a significant gap in nanoplastic analytics for particles between 1 nm and 1 µm, primarily due to challenges in their capture, separation, and analysis. Existing methods, such as filtration, elutriation, density flotation, and velocity-based techniques, are only suitable for larger microplastics (>50 µm). This leaves a critical gap in the recovery, quantification, and characterization of submicron colloidal plastic particles. Plant-derived cellulose nanofibrils (CNF) present a promising alternative. These nanomaterials, with dimensions of 3-10 nm laterally and lengths up to micrometers, are water-responsive, self-assemble, and exhibit unique properties including the ability to recover gold ions from wastewater and interact with various nanoparticles. Their hygroscopic nature, coupled with high surface area, differentiates them from other nanomaterials. This study explores the potential of nanocellulose networks to capture and quantify colloidal plastics.

The existing literature highlights the significant environmental and health implications of microplastic and nanoplastic pollution. Studies have shown microplastics accumulate in various aquatic organisms, leading to health issues and entering the human food chain. The absence of effective techniques for the capture and quantification of the most challenging colloidal fraction of nanoplastics has been a major hurdle in understanding their environmental impact. Previous research on microplastic remediation has primarily focused on larger particles using methods like filtration, density separation, and elutriation. These techniques are not effective for the smaller nanoplastic particles. The use of nanocellulose, particularly its hygroscopic nature and high surface area, offers a novel approach to address this challenge. Studies on the interaction of nanocellulose with other nanoparticles show promise for its potential as a remediation material.

This study employed model polystyrene (PS) particles (1 µm and 100 nm diameter) with anionic and cationic surface charges and well-defined size distributions. Larger polyethylene (PE) particles with a broader size distribution were also utilized to assess the versatility of the nanocellulose-based capture process. Two main experimental setups were used: 1. **Microfluidic analysis:** Fluorescently labeled PS nano- and microplastics were introduced into a microfluidic device containing native CNF hydrogels. Fluorescence intensity was monitored in real-time to assess particle capture. 2. **Self-standing film experiments:** Self-standing films of native CNF and TEMPO-oxidized CNF (TEMPO-CNF), along with regenerated cellulose (RC) and polystyrene (PS) films as controls, were immersed in aqueous dispersions containing PS nano- and microplastics and PE microplastics. Fluorescence spectroscopy was used to quantify captured particles. The effects of environmental parameters were examined by varying pH and NaCl concentrations in the nanoplastic dispersions. Surface-sensitive methods were employed to understand binding mechanisms. Specifically, Quartz Crystal Microbalance with Dissipation Monitoring (QCM-D) was used to investigate the adsorption of PS nanoparticles on ultrathin films of different materials. SEM and image analysis were used to quantitatively assess particle uptake and to determine the extent of surface coverage. Finally, the random sequential adsorption (RSA) model was employed to interpret the particle adsorption data, providing insights into the adsorption kinetics and surface coverage. The RSA model treats particles as geometrically restricted and fixed circular objects, enabling the calculation of the theoretical maximum coverage (θc = 0.547), and provides a framework for interpreting the dynamic interactions between nanoplastic particles and nanocellulose surfaces.

The key findings of the study include: 1. **Effective Nanoparticle Capture:** Native CNF hydrogels effectively captured both nano- and microplastic particles in real-time microfluidic experiments, with significantly higher capture efficiency for positively charged nanoplastics compared to their microplastic counterparts. This is attributed to the hydrogel’s hygroscopic nature and high surface area, facilitating particle transport and entrapment. 2. **TEMPO-CNF Superiority:** Self-standing TEMPO-CNF films demonstrated superior performance in capturing both nano- and microplastics compared to native CNF, RC, and PS films. TEMPO-CNF's high hygroscopicity and anionic charge played a crucial role in capturing particles, with a notably high efficiency for anionic nanoplastics. The results indicate that the capture mechanism isn't solely based on electrostatic interactions but is strongly influenced by the hygroscopic nature of the nanocellulose network which allows for capillary-driven transport of the particles into the film. 3. **Versatility of Nanocellulose:** Nanocellulose films efficiently captured PE microplastics, demonstrating the method's versatility across different plastic types. The smaller area of TEMPO-CNF film required to completely remove anionic polystyrene nanoplastics compared to the native CNF highlights the enhanced efficiency of TEMPO-CNF. 4. **Interfacial Interactions:** QCM-D measurements revealed that electrostatic repulsion prevents direct binding of anionic PS nanoparticles to highly anionic TEMPO-CNF. Adsorption of PS nanoparticles increased with higher ionic strength, suggesting that electrostatic repulsion is screened, enhancing nanoparticle binding to both CNF and TEMPO-CNF surfaces. The absence of adsorption of colloidal PE particles (PE(<450nm)) on cellulosic surfaces suggests the importance of surface chemistry and particle stability. 5. **Quantitative Nanoparticle Detection:** By combining QCM-D data, image analysis, and the RSA model, the study developed a novel quantitative method for detecting and quantifying nanoplastic particles. This approach enabled the determination of adsorption rates, surface coverage, and the amount of water associated with the adsorbed nanoplastic particles. The results showed that regenerated cellulose exhibited the highest affinity for PS nanoparticles, while native CNF and polystyrene showed lower adsorption. The amount of bound water was found to be a significant factor affecting the surface coverage.

This study addresses the critical need for effective methods to capture and quantify colloidal nano- and microplastics. The findings demonstrate the potential of nanocellulose networks as a universal and versatile solution for collecting plastic particles regardless of their size, surface chemistry, or type. The synergistic effect of high hygroscopicity and high surface area enables efficient particle capture through capillary-driven transport and entrapment within the porous nanocellulose network. The quantitative method developed provides a significant advancement in nanoplastic detection and quantification. The results underscore the importance of considering both hygroscopicity and surface interactions in designing materials for effective nanoplastic removal. The use of renewable, non-toxic, and readily modifiable nanocellulose offers a sustainable approach to addressing this pressing environmental challenge.

This research introduces a novel, highly effective method for capturing colloidal nano- and microplastics using plant-based nanocellulose networks. The method's versatility, effectiveness, and sustainability make it a promising solution for addressing plastic pollution. Future research could focus on optimizing nanocellulose materials for different environmental conditions and exploring large-scale applications for on-site collection and remediation of nano- and microplastics.

The study primarily utilized model polystyrene and polyethylene particles, which might not fully represent the complex diversity of plastics found in real-world environmental samples. The use of fluorescently labeled particles may introduce artifacts in some measurements. Future studies should investigate a broader range of plastic types and sizes and explore the applicability of this technique to complex environmental matrices.