Jörg Feldmann, a professor at the University of Graz, spoke about his team’s research using non-target analysis to analyze per- and polyfluorinated substances (PFAS).
Non-target analysis is quickly becoming a more popular method for analyzing per- and polyfluorinated substances (PFAS) in the environment. The technique allows analytical scientists to analyze all the compounds in a single sample, said Jörg Feldmann, a professor at the University of Graz, speaking at the Winter Conference on Plasma Spectrochemistry on Jan. 16.
Mass balance approaches using inductively coupled plasma–mass spectrometry (ICP-MS) and combustion ion chromatography (CIC), Feldmann said, can make an analytical workflow for non-target analysis possible. ICP-MS can also help with identification of unknown PFAS and help to quantify PFAS for which no standards are available. Feldmann’s team of researchers have been using ICP-MS to test for PFAS in wastewater and Alpine soil.
Major PFAS chemicals of environmental concern include perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluorobutanesulfonic acid (PFBS), as well as others.
“The idea is basically to get an idea of the whole exposome,” Feldmann said. “When we looked in the database, we realized more than half of these compounds have elements that can be detected by ICP-MS.”
Typically, scientists use high performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC-ESI–MS/MS) to analyze pollutants in surface water. However, using this technique, only 30-40 compounds can be analyzed. There are many remaining PFAS and organofluorines that remain undetected.
There are some common problems with non-target screening in natural water samples, Feldmann said. These include the identification of chemicals of emerging concern (CEC) without standards, quantification without analytical standards, and the assessment of compound coverage for one element in the workflow.
ICP-MS could prove a viable alternative to identifying remaining PFAS and organofluorines in water samples. Using the technique, the team is working to identify unknown PFAS compounds in the wastewater samples. One researcher, Feldmann said, found traces of antidepressants and other drugs that contain PFAS.
“ICP-MS can actually help very nicely because we have elemental specific detection, which is in parallel to the molecule,” he said.
In the second experiment, the team looked at PFAS in Alpine soil. This soil was particularly interesting, Feldmann said, because it was sampled from high up in the Alps, where there is generally less human pollution.
“We wanted to measure PFAS in pristine Alpine soils,” he said. “There’s no sewage sludge dumped on these soils but let’s see if we can find some PFAS.”
The team did find PFAS in the soil. This originates from a specific type of ski wax, Feldmann said. Fluoro wax, which is now banned for use, contains traces of polar mobile PFAS. However, more than 99.99% are F-polymers and non-polar fluorocarbon. Non-polar PFAS and F-polymers retained in Alpine soil may be a source for mobile PFAS for centuries, he said, even though the use of fluoro wax is no longer used.
Future studies, Feldmann said, may look at the bioavailability of PFAS in Alpine soil, using single-particle–inductively coupled plasma–time-of-flight mass spectrometry (spICP-TOF-MS)for F-NPS in soil, and quantitative methods for F-polymers in the environment.
Reviewing the Impact of 2D-COS on Analyzing Microplastic Impact on the Environment
January 20th 2025A recent review article highlighted how two-dimensional correlation spectroscopy (2D-COS) is advancing microplastics research and uncovering their aging processes and interactions with environmental substances.
Advancing Soil Carbon Analysis Post-Wildfire with Spectroscopy and Machine Learning
January 14th 2025Researchers from the University of Oviedo used diffuse reflectance spectroscopy (DRS) and machine learning (ML) to analyze post-wildfire soil organic carbon fractions, identifying key spectral regions and algorithms for advancing remote sensing applications.
Trending on Spectroscopy: The Top Content of 2024
December 30th 2024In 2024, we launched multiple content series, covered major conferences, presented two awards, and continued our monthly Analytically Speaking episodes. Below, you'll find a selection of the most popular content from Spectroscopy over the past year.