Curated Feature Articles

MICROPLASTICS & NANOPLASTICS

FT-IR Spectroscopy for Microplastic Classification

WILL WETZEL

Reports on a review examining FT-IR’s role in identifying and quantifying environmental microplastics.

Tracking Microplastics in the Environment via FT-IR Microscopy

SPECTROSCOPY STAFF

A technique overview demonstrating how FT-IR microscopy is applied to detect and identify environmental microplastics (20–1000 μm).

ATR FT-IR and NIR Spectroscopy Reveal the Sources of Microplastics in Biosolids

JEROME WORKMAN, JR, SPECTROSCOPY STAFF

Reports on a study comparing ATR FT-IR and NIR spectroscopy for identifying polymer types in microplastics from biosolid samples at six NYC water resources recovery facilities. ATR FT-IR was more effective for smaller particles (10–100 μm); NIR was more effective for larger particles (100–500 μm) and better identified PP and PET. Recommends combined use for comprehensive biosolid microplastic analysis.

Tracking Microplastics Across Air, Water, and Soil: What Spectroscopy Reveals About Global Pollution

JEROME WORKMAN, JR.

Reports on a multi-institutional study presenting a comprehensive view of microplastic contamination across aquatic, terrestrial, and atmospheric compartments. Central to the research is application of FT-IR and Raman spectroscopy to classify polymer types and assess degradation states.

Identifying Microplastics Using ATR-FT-IR Spectroscopy and Raman Spectroscopy

SPECTROSCOPY STAFF

Reports on a study combining attenuated total reflectance Fourier transform infrared (ATR-FTIR) and Raman spectroscopy with a 1D convolutional neural network for improved microplastic classification. The team characterized eight common microplastics, building combined IR/Raman spectral databases and training the model on the combined data, achieving near-perfect classification accuracy across diverse environmental samples.

SOIL ANALYSIS: CONTAMINANTS, ORGANIC MATTER, & ENVIRONMENTAL MONITORING

Near-Infrared Spectroscopy Enables High-Throughput Monitoring of Soil Elements

SPECTROSCOPY STAFF

Reports on a study demonstrating NIR reflectance spectroscopy (1100–2500 nm) combined with chemometric modeling (PLSR, PRM) for high-throughput soil element monitoring, predicting Cd, Cu, Pb, Ni, Cr, Zn, Mn, and Fe concentrations across 234 soil samples.

Using NIR Spectroscopy in Low-Level Petroleum Hydrocarbon Detection

WILL WETZEL

Reports on a spectral subtraction workflow enhancing NIR reflectance sensitivity for low-level petroleum hydrocarbon pollution in soils (178–1,716 mg/kg).

Monitoring Soil Quality Using MIR and NIR Spectral Models: An Interview with Felipe Bachion de Santana

FELIPE BACHION DE SANTANA, WILL WETZEL

An interview discussing a comparative study of MIR and NIR spectral models for predicting soil physical and chemical parameters (total carbon, nitrogen, bulk density, clay, sand, silt, pH, exchangeable Mg and K) using ball-milled and sieved soil.

Conducting Soil Analysis Using Vis-NIR Spectroscopy

WILL WETZEL

Reports on a review evaluating in-field vis-NIR spectroscopy (350–2500 nm) as a fast, reliable alternative to laboratory soil testing. Covers sensor range/type comparisons, carrier platforms, cross-calibration potential, and commonly analyzed properties (carbon content, texture, nitrogen, pH, cation exchange capacity), while identifying persistent gaps in field-deployment reliability.

Non-Linear Memory-Based Learning Advances Soil Property Prediction Using Vis-NIR Spectral Data

JEROME WORKMAN, JR.

Reports on a non-linear memory-based learning (N-MBL) model for vis-NIR soil property prediction that outperformed traditional machine learning and local modeling methods, particularly for soil organic matter and total nitrogen.

A Look at Vis-NIR and NIR Spectroscopy in Characterizing Soil Fertility

WILL WETZEL

Discusses a study evaluating vis-NIR spectroscopy for in situ soil fertility assessment as a cost-effective alternative to laboratory testing.