We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Distribution and Characteristics of Microplastic Deposits on Sandy Beaches: Integrating Gnss Positioning, Μ-Raman Spectroscopy, and Unsupervised Models
No summary available — this paper's abstract is not included in the open metadata provided by the publisher. Learn why →
More Papers Like This
Microplastic deposits prediction on Urban Sandy Beaches: Integrating Remote Sensing, GNSS Positioning, µ-Raman Spectroscopy, and Machine Learning Models
AI summary Read the abstract
Researchers integrated remote sensing, GNSS altimetric surveys, micro-Raman spectroscopy, and machine learning models to predict microplastic deposition patterns on urban sandy beaches along the central Sao Paulo coastline, finding MP concentrations ranging from 6 to 35 MPs/m2.
Raman Spectroscopy Based Approaches for Microplastics Investigations
AI summary Read the abstract
Researchers reviewed Raman spectroscopy-based approaches — including confocal Raman microscopy, surface-enhanced Raman scattering, and automated imaging — for identifying and characterizing microplastics in environmental samples, highlighting their superior chemical specificity compared to FTIR for sub-10-μm particles. Accurate chemical identification of microplastics at the nanoscale is foundational for both environmental monitoring and toxicological research, as particle composition (polymer type and additives) strongly influences biological harm.
Toward a Method of Assessing Microplastic Accumulation in Beach Sand Deposits
AI summary Read the abstract
Researchers tested four saline density separation solutions to develop a low-cost method for extracting and quantifying microplastics from beach sand, achieving recovery rates of 61–78% for coarse particles across six plastic types. Standardizing affordable extraction methods is a critical step toward generating comparable microplastic concentration data across global beach environments.
Microplastics Characterization by Raman Microscopy
AI summary Read the abstract
Raman microscopy enables reliable identification and quantification of microplastics in environmental samples, with smaller particles posing greater ecological risk due to their higher numbers and broader species exposure. Standardizing this analytical technique is essential for producing comparable data across studies and informing effective pollution monitoring.
Microplastics Characterization by Raman Microscopy
AI summary Read the abstract
Raman microscopy has emerged as a powerful tool for identifying and characterizing microplastics at small particle sizes that are difficult to analyze with other methods, enabling more accurate quantification in environmental samples. Improving characterization techniques is critical because smaller microplastic particles are more numerous and more likely to be ingested by a wider range of organisms, including humans.
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.