Advanced Gas Chromatography Methods for Detecting PFAS Contamination in Soil

Per- and polyfluoroalkyl substances (PFAS), often called “forever chemicals,” are widely used in products such as waterproof clothing, food packaging, cosmetics, and non-stick cookware because of their strong chemical stability and resistance to heat, water, and oil. However, these same properties allow PFAS to persist in the environment, spread through soil and water, and potentially enter the food chain, raising growing concerns about their effects on human health and ecosystems. Detecting PFAS in soil is particularly difficult because they exist in very low concentrations and include thousands of chemically different compounds. To address these challenges, modern chromatographic techniques, especially gas chromatography coupled with mass spectrometry (GC-MS), are becoming increasingly important for sensitive and reliable PFAS analysis. Research conducted at the University of Ferrara (Italy) presents a new analytical method that combines dynamic headspace extraction and thermal desorption with advanced gas chromatography systems to improve the detection of volatile and semi-volatile PFAS in soil samples. In addition to measuring specific PFAS compounds, the method also allows broader screening for other environmental contaminants, providing a faster, more sensitive, and environmentally friendly approach for monitoring pollution in soils.

LCGC International spoke to Flavio A. Franchina (FAF) and Maria Chiara Corviseri (MCC) of the University of Ferrara, corresponding and lead authors, respectively, of a paper presenting this method.¹

Given the amphiphilic nature and low boiling points of (semi-)volatile PFAS, how do these physicochemical properties influence the choice between liquid chromatography and gas chromatography for their analysis?

FAF: PFASs comprise a highly heterogeneous group of chemicals, so it is important to select the proper separation mechanism depending on the specific needs. In general, molecular volatility is the key factor enabling the GC separation. Larger molecules and ionic species tend to exhibit stronger intermolecular interactions, leading to poor volatility, making these compounds more suitable for LC separations. In contrast, smaller, neutral molecules typically have weaker intermolecular interactions, making them more volatile and thus better candidates for GC analysis.

For PFAS, however, this distinction is less immediate. The perfluorinated chain has unique physicochemical properties, making the molecule poorly polarizable and characterized by weak Van der Waals interactions. As a result, fluorinated compounds often exhibit higher volatility than their hydrocarbon analogues. This feature makes certain PFAS amenable for GC analysis, even when their molecular weight might suggest otherwise. On the other hand, PFAS contain polar functional groups, such as carboxylic or sulfonic acids. These groups introduce strong intermolecular interactions, which significantly reduce volatility. In such cases, the polar head counterbalances the weak interactions of the fluorinated tail, making these compounds more suitable for LC, often in their ionized form.

In summary, while the fluorinated chain tends to increase volatility by reducing intermolecular interactions, the presence of polar functional groups can dominate the overall behavior. Therefore, the choice between GC and LC for PFAS analysis depends on the balance between the non-polar fluorinated tail and the polar head.

What are the key advantages of coupling dynamic headspace extraction (DHS) with thermal desorption (TD) compared to conventional extraction techniques such as SPE or LLE for PFAS analysis in soil matrices?

MCC: Dynamic headspace extraction coupled with thermal desorption is a technique that enables the analyte enrichment into a trap. By applying a continuous purge flow, it allows sampling of varying headspace volumes in a dynamic condition, facilitating the depletion of volatile analytes from the sample. In the context of PFAS analysis, where these compounds are ubiquitous, minimizing sample handling is very important and techniques such as solid-phase extraction or solvent extraction can increase the risk of contamination due to the multiple steps required before final injection. Additionally, because soil is a complex matrix, headspace extraction offers a key advantage, confining by nature most of the matrix interferences. Unlike solvent-based extraction methods, which may co-extract unwanted compounds, headspace techniques selectively isolate volatile analytes, resulting in cleaner extracts for analysis. In our study, among other variables, we also tested three different conditions for headspace extraction; by evaluating just soil, soil added with water, and soil added with a mixture 1:1 of water and methanol (total volume 5mL). The latter because the use of a co-solvent behaves as interface to help extracting the analyte from the matrix first. Among the conditions tested, the mixture of water and methanol provided the best recovery and reproducibility for the target analytes, and it was chosen to validate the final method.

Can you explain how background contamination from laboratory materials affects PFAS analysis and what chromatographic or instrumental strategies can be implemented to mitigate these issues?

MCC: Because of their exceptional resistance to heat, chemical degradation, and surface activity, PFAS are widely used in the manufacture of laboratory materials such as tubing, vials, caps, seals, and coatings. Fluoropolymers, such as polytetrafluoroethylene (PTFE) are commonly used due to their inertness and stability. However, this widespread use makes PFAS contamination in analytical workflows a significant concern. Although PFAS-free labware is increasingly available, eliminating PTFE and other fluorinated materials from the analytical setup is often impractical. As a result, there is a persistent risk of background contamination originating from labware, instrument components (e.g., tubing, seals), solvents, and even laboratory air or dust. To minimize the risk of false positives and ensure data reliability, it is essential to implement rigorous blank control strategies.

In our routine, for example, we include different controls, including tube blanks, vial blanks, extraction system blanks, instrument blanks and matrix blanks. Considering these blank controls together with samples helps identify both the presence and the source of contamination. Additional good practices include avoiding fluoropolymer-containing materials where possible (e.g., replacing PTFE with polypropylene), using high-purity reagents, pre-cleaning labware, and regularly monitoring background levels. Together, these measures are critical for accurate PFAS determination, especially at trace concentration levels.

Why was GC-TOFMS selected as the primary detection technique, and how does time-of-flight mass spectrometry enhance sensitivity and compound identification compared to quadrupole-based MS systems?

FAF: GC separation was selected because of the (semi-)volatile nature of the initially targeted PFAS, and we confirmed it to be a reliable analytical technique for their detection. Time-of-flight mass spectrometry (TOFMS) especially adds that layer of selectivity for the characterization of these compounds, in addition to higher sensitivity. In my opinion, the other key advantage of TOF analyzers is their ability to acquire full-spectrum data by recording all ions generated in the ion source over a wide mass range simultaneously which boost sensitivity. Being not blind to what’s known pushes research laboratories to another level, which is indispensable in discovery and novel development studies, where additional molecules belonging to the same chemical class or other relevant pollutants can be present in the sample. Of course, training and awareness are important to fully exploit and transform the data into information.

Finally, the combination with multidimensional comprehensive GC fully satisfies the capability of a TOF analyzer, providing the most versatile and powerful analytical platform for chemical analysis at the single molecule level, with maximum sensitivity, resolution, and identification capabilities.

In the context of complex soil matrices, how does comprehensive two-dimensional gas chromatography (GC×GC) improve separation capacity and peak resolution for both targeted and non-targeted PFAS analysis?

MCC: Aspects like sample complexity and analyte concentration make very challenging the determination of pollutants in environmental samples such as soil. Even with a tailored sample extraction and purification, some interferences often remain and might cause troubles in identification and quantification of target analytes. Also, with powerful detection capabilities we experience isobaric compounds which cause false positive identification or overestimation in the sample. Having an additional separation dimension like in GC×GC helps to better identify and resolve these faults.

In the context of non-targeted analysis instead, I can say that any additional resolution is surely beneficial for the discovery of new pollutants.

The other very important benefit from GC×GC in trace analysis, especially when using in space band focusing modulators, is the increased detectability.

What challenges arise when validating a quantitative GC-based method for PFAS at ppt-level concentrations, and how are parameters such as LOQ, precision, and matrix effects addressed?

MCC: Achieving concentration at the ppt level represents a significant analytical challenge, as PFAS can be present at trace levels. Moreover, PFAS include a wide variety of compounds with different physicochemical properties that make it difficult to develop a single extraction and analytical method, with the same parameters being suitable for all sub-classes to detect such low concentrations. One of the challenges we faced was related to the extraction volume: although higher extraction volumes resulted in improved recovery for less volatile compounds, the associated standard deviation prevented their use.

During method validation, several key performance parameters must be assessed. First, we started at higher concentration levels to evaluate and set key experimental parameters (such as solvent vent, split flow, and temperature ramp program), followed by the construction of the calibration curve and the estimation of the limits of detection (LOD) and quantification (LOQ), that are required to be experimentally verified afterwards.

Precision and accuracy are important indicators of method reliability and reproducibility. This was addressed performing different replicates for each point of the calibration, to check the repeatability of the analysis, and it is typically expressed as relative standard deviation. We evaluated it particularly at the lowest calibration level, where variability is generally higher. Accuracy, which expresses how much the experimental concentration is near to the theoretical value, can be determined by analyzing samples spiked with known concentrations and expressing the results in terms of recovery (%) or deviation (bias) from the true value. Matrix effect represents another important aspect, and it should be tested since co-eluting matrix components can lead to ion suppression or enhancement. In our case we built a matrix-matched calibration curve, so we had already the presence of other components, but if it is not employed, it can significantly alter the analytical response of target compounds.

How does the use of sorption tubes in DHS influence analyte recovery and reproducibility, particularly for PFAS with varying volatility and functional groups?

MCC: Trap tubes are packed with adsorbent materials of varying chemical nature. When analyzing PFAS, it is important to consider that these compounds exhibit different physicochemical behaviors and volatilities depending on their molecular structure and functional groups. As a result, their interactions with the sorbent materials can differ significantly, and multiple processes may influence their recovery, including competitive adsorption among coexisting compounds. When we tested different extraction volumes, for example, we noticed that, increasing the extraction volume, we achieved higher recovery for the less volatile compounds, but also a decrease of the most volatile compounds’ response, suggesting a phenomenon of breakthrough and displacement. From a reproducibility point of view, we observed that increasing the sampled volume can also lead to higher variability, as reflected by an increase in the standard deviation. In light of these considerations, we chose to use the lowest extraction volume that we tested, as a compromise between recovery and standard deviation, even if we had to sacrifices heaviest compounds’ trapping.

For non-targeted screening, how does GC×GC-TOFMS enable the detection of unknown or emerging PFAS, and what role do accurate mass spectra and deconvolution algorithms play in compound identification?

FAF: The GC×GC and TOFMS binomial fulfill each other in terms of performance and the boost in selectivity and sensitivity from combining them facilitates the detection of emerging and unknown pollutants.

Generally, the computational complexity of deconvolution algorithms is proportional to the density of interference reaching the MS. Instead, the unbiased physical separation from other matrix components allows cleaner mass spectra for molecular information, and cleaner mass spectra helps any deconvolution algorithm.

The use of accurate mass measurements helps reduce false positives, since some fragment ions may be shared with other compounds. Furthermore, when molecular ions are visible, also the identification becomes more confident. This is valid for both putative annotations, relying on MS libraries, and unknown analytes.

Playing with ionization modes adds another layer of information, and it can also improve the detection of molecular ions for accurate identifications. This is especially true for the heterogeneous nature of PFAS, with some classes ionizing better than others with different ionization mechanisms than EI.

Considering the shift from long-chain to short-chain and (semi-)volatile PFAS, what new analytical challenges does this pose for chromatographic separation and mass spectrometric detection?

FAF: Long-chain PFAS have historically been the most extensively studied, and as a result, several validated analytical methods are available for their extraction, separation, and quantification. However, the ongoing shift toward short-chain PFAS presents significant and novel analytical challenges. These compounds remain relatively understudied and poorly characterized, making their analysis an active area of research.

These short-chain and (semi-)volatile PFAS pose challenges in all the steps involved in the analytical process, not only separation and detection.

The first limitation affecting PFAS monitoring strategies, especially those (semi-)volatile of more recent attention, is the lack of available analytical standards. This significantly hinders method development, validation, and accurate quantification. A recent 2025 report from the European Chemicals Agency estimated that, out of approximately 10,000 overall PFAS currently recognized, authentic analytical standards are available for only about 6% of these compounds.

Besides the attention for their ubiquitous nature and risks of cross-contamination, a critical challenge arises when performing the sample preparation. Due to their nature, these compounds are prone to analyte loss during sample preparation due to their volatility or surface adsorption. This can lead to systematic underestimation or false negative detection.

From a chromatographic perspective, short-chain PFAS are generally volatile, resulting in early elution with potential co-elution with the extraction solvents (if any), in addition to other matrix components. On the detection side, if using EI MS, most (semi-)volatile PFAS subclasses that we are studying tend to produce few and less distinctive fragment ions. If this can be seen as a limitation, it could be used for subclass screening and grouping.

How does the integration of green analytical chemistry principles—such as solvent minimization through TD—impact method robustness, reproducibility, and scalability for routine environmental monitoring?

FAF: Most validated methods currently used for environmental monitoring rely on solvent extraction or SPE, both of which require the use of organic solvents. In contrast, the principles of green chemistry promote the reduction of hazardous substances while encouraging more sustainable analytical practices. Consequently, there is a growing demand to pursue greener alternatives, which must still undergo rigorous validation and be accepted by international regulatory agencies before implementation in routine monitoring. We are experiencing the presence of many greener approaches and among them, the combined use of dynamic headspace with thermal desorption (TD) represents a valid solution.

However, the approach we published introduces experimental variables and additional operational parameters to be aware of. For example, sample humidity and breakthrough during sampling can drastically affect the results and must be properly verified and tuned with the trapping material. During the thermal desorption, purge and desorption flow rates are very important, and they must be carefully controlled and optimized to ensure total column transfer; often, the use of a cryotrap is essential to further reduce injection band broadening. Although the fine-tuning of these parameters is inevitably time-intensive, it is crucial for establishing methodological robustness, and it ultimately yields long-term benefits for routine use.

Last point, and still relevant for my teaching role, is the pedagogical experience for graduate students (and not only!) that optimizing such parameters provides to understand the injection process in GC.

References

1. Corviseri, M. C.; Dos Santos Polidoro, A.; Stevanin, C.; Pasti, L.; Franchina, F.A.Development and Optimization of PFAS Extraction in Soil's Headspace Followed by Multidimensional Gas Chromatography and Mass Spectrometry. Anal Bioanal Chem. 2025.DOI: 10.1007/s00216-025-06266-4