We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
A reliable method to determine airborne microplastics using quantum cascade laser infrared spectrometry
AI summary Read the abstract
Researchers developed a faster and more reliable method for measuring airborne microplastics using a quantum cascade laser infrared spectrometer. They tested different passive sampling devices and sample digestion approaches, then optimized the automated instrument to distinguish fibers from particles with over 90% accuracy. Standardizing how airborne microplastics are measured is critical because air is a significant but poorly characterized route of human microplastic exposure.
The number of studies dealing with airborne microplastics (MPs) is increasing but sampling and sample treatment are not standardized, yet. Here, a fast and reliable method to characterize MPs is presented. It involves the study of two passive sampling devices to collect atmospheric bulk deposition (wet and dry deposition) and three digestion methods (two alkaline-oxidative and an oxidative) to treat the samples. The alkaline-oxidative method based on KOH and NaClO was selected for a mild organic matrix digestion. In addition, some operational parameters of a high-throughput quantum cascade laser-based infrared device (LDIR) were optimized: an effective automatic tiered approach to differentiate fibres from particles (>90 % success in validation) and a criterion to establish positive matches when comparing an unknown spectrum against the spectral database (proposed match index > 0.85). The procedural analytical recoveries were very good for particles (82-90 %) and slightly lower for fibres (62-73 %). Finally, the amount and type of MPs deposited at a sub-urban area NW Spain were evaluated. Most common polymers were Polyethylene (PE), Polypropylene (PP) and Polyethylene terephthalate (PET). The deposition rates ranged 98-1220 MP/m/day, ca. 1.7 % of the total collected particles. More than 50 % of the total MPs deposited were in the 20-50 μm size range, whereas fibres were mostly in the 50-500 μm size range.
More Papers Like This
Reviewing the fundamentals and best practices to characterize microplastics using state–of–the-art quantum-cascade laser reflectance-absorbance spectroscopy
AI summary Read the abstract
Researchers reviewed best practices for using quantum cascade laser infrared imaging (a high-speed scanning technology) to reliably identify microplastic particles, addressing technical pitfalls like particle-size effects on spectral readings. Standardizing this method is important for generating consistent, comparable data as governments push for official microplastic monitoring programs.
Rapid Identification and Quantification of Microplastics in the Environment by Quantum Cascade Laser-Based Hyperspectral Infrared Chemical Imaging
AI summary Read the abstract
Quantum cascade laser infrared microscopy was evaluated as a rapid method for identifying and quantifying microplastics in environmental samples. The technique showed potential for faster polymer identification compared to conventional FTIR mapping, offering advantages for high-throughput microplastic monitoring.
High-throughput environmental microplastic identification and quantification using a wide-field QCL-IR based microscope
AI summary Read the abstract
Researchers developed a wide-field quantum cascade laser infrared microscope capable of identifying and quantifying microplastics at significantly higher throughput than conventional FTIR methods. The system can process large environmental sample areas rapidly, addressing the bottleneck of slow manual analysis that limits large-scale microplastic monitoring.
Improved method for rapid characterization of microplastics in environmental samples with QCL-IR based microscopy and micro spectroscopy (Conference Presentation)
AI summary Read the abstract
Researchers presented a quantum cascade laser infrared (QCL-IR) microscopy method for rapidly characterizing microplastics in environmental samples. The approach combines spatial imaging with chemical identification to classify particles by size, shape, and polymer type faster than conventional FTIR microscopy. Improved throughput in microplastic characterization helps researchers process the large sample volumes needed for environmental monitoring studies.
Discrete frequency infrared-guided image for microplastic analysis: Performance and limitations
AI summary Read the abstract
Researchers evaluated the performance and limitations of a discrete frequency infrared imaging approach using a quantum cascade laser for microplastic analysis, finding that over 90% of fluorescently labelled polyethylene particles larger than 20 micrometers were correctly identified, with throughput-accuracy tradeoffs at high-throughput settings.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.