Detection of microplastics based on spatial heterodyne Raman spectroscopy

Artificial intelligence in microplastic detection and pollution control

The rising prevalence of microplastics (MPs) in various ecosystems has increased the demand for advanced detection and mitigation strategies. This review examines the integration of artificial intelligence (AI) with environmental science to improve microplastic detection. Focusing on image processing, Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, and hyperspectral imaging (HSI), the review highlights how AI enhances the efficiency and accuracy of these techniques. AI-driven image processing automates the identification and quantification of MPs, significantly reducing the need for manual analysis. FTIR and Raman spectroscopy accurately distinguish MP types by analyzing their unique spectral features, while HSI captures extensive spatial and spectral data, facilitating detection in complex environmental matrices. Furthermore, AI algorithms integrate data from these methods, enabling real-time monitoring, traceability prediction, and pollution hotspot identification. The synergy between AI and spectral imaging technologies represents a transformative approach to environmental monitoring and emphasizes the need to adopt innovative tools for protecting ecosystem health.

In-situ detection of microplastics in the aquatic environment: A systematic literature review

Microplastics are ubiquitous in the aquatic environment and have emerged as a significant environmental issue due to their potential impacts on human health and the ecosystem. Current laboratory-based microplastic detection methods suffer from various drawbacks, including a lack of standardisation, limited spatial and temporal coverage, high costs, and time-consuming procedures. Consequently, there is a need for the development of in-situ techniques to detect and monitor microplastics to effectively identify and understand their sources, pathways, and behaviours. Herein, we adopt a systematic literature review method to assess the development and application of experimental and field technologies designed for the in-situ detection and monitoring of aquatic microplastics, without the need for sample preparation. Four scientific databases were searched in March 2023, resulting in a review of 62 relevant studies. These studies were classified into seven sensor categories and their working principles were discussed. The sensor classes include optical devices, digital holography, Raman spectroscopy, other spectroscopy, hyperspectral imaging, remote sensing, and other methods. We also looked at how data from these technologies are integrated with machine learning models to develop classifiers capable of accurately characterising the physical and chemical properties of microplastics and discriminating them from other particles. This review concluded that in-situ detection of microplastics in aquatic environments is feasible and can be achieved with high accuracy, even though the methods are still in the early stages of development. Nonetheless, further research is still needed to enhance the in-situ detection of microplastics. This includes exploring the possibility of combining various detection methods and developing robust machine-learning classifiers. Additionally, there is a recommendation for in-situ implementation of the reviewed methods to assess their effectiveness in detecting microplastics and identify their limitations.

Detection of microplastics via a confocal-microscope spatial-heterodyne Raman spectrometer with echelle gratings

Microplastic pollution has become a global environmental problem that cannot be ignored. Raman spectroscopy has been widely used for microplastics detection because it can be performed in real-time and is non-destructive. Conventional detection techniques have had weak signals and low signal-to-noise ratios (SNR). Here, an efficient and reliable detection method is demonstrated. Specifically, a confocal microscope combined with an echelle-grating spatial-heterodyne Raman spectrometer (CM-ESHRS) was constructed. The confocal microscopy and the characteristics of the echelle grating enabled high optical throughput, high SNR, high spectral resolution, and a wide spectral detection band. After spectral calibration, the resolution approached 0.67 cm-1, moreover, the spectral detection range for a single order was 1372.16 cm-1. We detected and analyzed nineteen kinds of microplastics, such as polyamide, polypropylene, and polymethylmethacrylate, and the main vibrational spectral bands were categorized. Compared with commercial dispersive spectrometers, CM-ESHRS has a higher optical throughput. In addition, we examined microplastics with various particle sizes, microplastics mixed in flour, and microplastic particles of different materials under mixed conditions, all of which yielded complete spectral information. Overall, CM-ESHRS exhibits good potential applications for the detection of microplastics.

Silver nanostars arrayed on GO/MWCNT composite membranes for enrichment and SERS detection of polystyrene nanoplastics in water

Nanoplastic water contamination has become a critical environmental issue, highlighting the need for rapid and sensitive detection of nanoplastics. In this study, we aimed to prepare a graphene oxide (GO)/multiwalled carbon nanotube (MWCNT)-silver nanostar (AgNS) multifunctional membrane using a simple vacuum filtration method for the enrichment and surface-enhanced Raman spectroscopy (SERS) detection of polystyrene (PS) nanoplastics in water. AgNSs, selected for the size and shape of nanoplastics, have numerous exposed Raman hotspots on their surface, which exert a strong electromagnetic enhancement effect. AgNSs were filter-arrayed on GO/MWCNT composite membranes with excellent enrichment ability and chemical enhancement effects, resulting in the high sensitivity of GO/MWCNT-AgNS membranes. When the water samples flowed through the portable filtration device with GO/MWCNT-AgNS membranes, PS nanoplastics could be effectively enriched, and the retention rate for 50 nm PS nanoplastics was 97.1 %. Utilizing the strong SERS effect of the GO/MWCNT-AgNS membrane, we successfully detected PS nanoparticles with particle size in the range of 50-1000 nm and a minimum detection concentration of 5 × 10-5 mg/mL. In addition, we detected 50, 100, and 200 nm PS nanoplastics at concentrations as low as 5 × 10-5 mg/mL in real water samples using spiking experiments. These results indicate that the GO/MWCNT-AgNS membranes paired with a portable filtration device and Raman spectrometer can effectively enrich and rapidly detect PS nanoplastics in water, which has great potential for on-site sensitive water quality safety evaluation.

Distribution patterns and environmental risk assessments of microplastics in the lake waters and sediments from eight typical wetland parks in Changsha city, China

The quality of water in urban parks is closely related to people's daily lives, but the pollution caused by microplastics in park water and sediments has not been comprehensively studied. Therefore, eight typical parks in the urban area of Changsha, China, were selected, and Raman spectroscopy was used to explore the spatial distributions and compositions of the microplastics in the water and sediments, analyze their influencing factors, and evaluate their environmental risks. The results showed that the abundances of surface water microplastics in all parks ranged from 150 to 525 n L-1, and the abundances of sediment microplastics ranged from 120 to 585 n kg-1. The microplastics in the surface water included polyethylene terephthalate (PET), chlorinated polyethylene (CPE), and fluororubber (FLU), while those in the sediments included polyvinyl chloride (PVC), wp-acrylate copolymer (ACR), and CPE. Regression analyses revealed significant positive correlations between human activities and the abundances of microplastics in the parks. Among them, the correlations of population, industrial discharge and domestic wastewater discharge with the abundance of microplastics in park water were the strongest. However, the correlations of car flow and tourists with the abundance of microplastics in park water were the weakest. Based on the potential ecological risk indices (PERI) classification assessment method, the levels of microplastics in the waters and sediments of the eight parks were all within the II-level risk zone (53-8,549), among which the risk indices for Meixi Lake and Yudai Lake were within the IV risk zone (1,365-8,549), which may have been caused by the high population density near the park. This study provides new insights into the characteristics of microplastics in urban park water and sediment.

Innovative overview of the occurrence, aging characteristics, and ecological toxicity of microplastics in environmental media

Microplastics (MPs), pollutants detected at high frequency in the environment, can be served as carriers of many kinds of pollutants and have typical characteristics of environmental persistence and bioaccumulation. The potential risks of MPs ecological environment and health have been widely concerned by scholars and engineering practitioners. Previous reviews mostly focused on the pollution characteristics and ecological toxicity of MPs, but there were few reviews on MPs analysis methods, aging mechanisms and removal strategies. To address this issue, this review first summarizes the contamination characteristics of MPs in different environmental media, and then focuses on analyzing the detection methods and analyzing the aging mechanisms of MPs, which include physical aging and chemical aging. Further, the ecotoxicity of MPs to different organisms and the associated enhanced removal strategies are outlined. Finally, some unresolved research questions related to MPs are prospected. This review focuses on the ageing and ecotoxic behaviour of MPs and provides some theoretical references for the potential environmental risks of MPs and their deep control.