# Measuring aliphatic hydrocarbons in sediments by direct thermal desorption-gas chromatography-mass spectrometry: Matrix effects and quantification challenges

Florence Portet-Koltalo, Kévin Humbert, Julie Cosme, Maxime Debret, Christophe Morin, Steeven Le Gohlisse

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Florence Portet-Koltalo, Kévin Humbert, Julie Cosme, Maxime Debret, Christophe Morin, et al. Measuring aliphatic hydrocarbons in sediments by direct thermal desorption-gas chromatography-mass spectrometry: Matrix effects and quantification challenges. Journal of Chromatography A, 2024, 1722, 10.1016/j.chroma.2024.464895. hal-05060955

HAL Id: hal-05060955

https://hal.science/hal-05060955v1

Submitted on 9 May 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>

# Measuring aliphatic hydrocarbons in sediments by direct thermal desorption-gas chromatography-mass spectrometry: Matrix effects and quantification challenges

Florence Portet-Koltalo<sup>a,*</sup>, Kévin Humbert<sup>a,b</sup>, Julie Cosme<sup>a</sup>, Maxime Debret<sup>b</sup>, Christophe Morin<sup>a</sup>, Steeven Le Gohlisse<sup>a</sup>

<figure><img src="image_4.png" /></figure>

## ARTICLE INFO

**Keywords:**

Paraffinic alkanes

Thermodesorption GC-MS

Sediments

Experimental designs

Matrix effects

## ABSTRACT

Direct sample introduction thermal desorption (TD) coupled to GC-MS was investigated for the analysis of paraffinic hydrocarbons (HCs) from polluted sediments. TD-GC-MS is sometimes used for analysing paraffinic HCs from atmospheric particles but rarely for their direct desorption from sediments. So, the new TD methodology, applied to sediments, required development, optimization and validation. A definitive screening experimental design was performed to discriminate the critical factors on TD efficiency, from model sediments containing various organic matter (OM) amounts. Low molecular weight HCs had extraction behaviours markedly different from high molecular ones (HMW-HCs), but a compromise was found using very few sediment amount (5 mg), high temperature rate (55 °C min⁻¹) and final temperature (350 °C). Linear HCs (n-C10 to n-C40) could be quantified using the matrix-matched calibration method, with very low detection limits (3.8–13.4 ng). The amount of the overall paraffinic alkanes was also determined as a sum of unresolved components between predefined equivalent carbon ranges. The developed solventless methodology was compared to an optimized solvent microwave assisted extraction (MAE). Matrix effects could be higher for TD compared to MAE but it depended on sediment matrix. When matrix effect was strong, particularly on HMW-HCs signal depletion, a dilution with pure non-porous sand was favourable for accurate quantification. The sum of resolved and unresolved HCs gave comparable results between MAE and TD extractions, with an exception of alkanes greater than C30 which were less quantitatively extracted via TD. However, TD-GC-MS was more sensitive than MAE-GC-MS. So TD-GC-MS is useful for analyzing sediments containing a great range of paraffinic HCs (C9-C34) and it has the advantages of being fully automated, with few sample preparation and operator intervention, using very low amounts of solvent, and generating few wastes.

## 1. Introduction

Hydrocarbons (HCs) represent a complex family of thousands of organic compounds containing carbon and hydrogen and many of them are volatile, with high vapour pressures, while longer carbon chain HCs are semi- or not volatile. Non-gaseous alkanes are the family of saturated bituminous HCs that are soluble in non- or low-polar organic solvents. Intermediate volatile organic compounds are defined as having a vapour pressure between 0.013 and 13.3 Pa at 25 °C, from dodecane (C12) to octadecane (C18) *n*-alkanes [1]. So longer-chain hydrocarbons, from

C19 to C40, are considered non-volatile. HCs can be released in the environment from petrogenic or pyrogenic anthropogenic sources (i.e. oil spills or incomplete combustion of fossil fuels) but also from natural petroleum seeps, biomass combustion, vegetation biosynthesis or diagenetic transformations in soils, sediments or oceans [2]. With the increased consumption of petroleum fuels for decades, HCs have attracted researches in various areas such as the current or historical monitoring of their contamination in soils or sediments, or in the context of soil remediation projects [3]. Indeed petroleum-contaminated soils or sediments pose a severe risk to the environment and living organisms

<footnote><sup>a</sup> COBRA Laboratory UMR CNRS 6014, Normandie University, UNIROUEN, 55 rue Saint Germain, Evreux 27000, France</footnote>

<footnote><sup>b</sup> M2C Laboratory UMR 6143, Normandie University, UNIROUEN, FR CNRS 3730 SCALE, Bâtiment Blondel, Place Emile Blondel, Mont Saint Aignan CEDEX 76821, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: florence.koltalo@univ-rouen.fr (F. Portet-Koltalo).</footnote>
inhabiting the polluted areas.

Analytical chemistry offers a wide range of methods for investigating intermediate or non-volatile bituminous HCs in soils or sediments [4]. A standard gravimetric procedure consists in extracting total petroleum hydrocarbons (TPHs) from soils or sediments using *n*-hexane, then to eliminate some polar interfering compounds through a purification step and to weight the evaporated residue [5]. The result, given in mg TPHs per kg of soil is nonspecific and has a high limit of detection (LOD). Another common method is to use IR spectroscopy after extraction but this analytical tool is not selective and can be biased by the response of the extracting solvent [6]. To be more specific, separation methodologies, mainly gas chromatography (GC), are performed with previous steps of solvent extraction to measure TPHs [7]. Although aliphatic and aromatic compounds can be fractionated on silica gel columns using different solvent mixtures, the paraffinic fraction can contain yet hundreds of different compounds and neither one-dimensional GC nor comprehensive GC × GC can fully resolve such mixtures [8]. But GC can yield aliphatic fractions with predefined equivalent carbon (EC) ranges. For example, a reference method for the Canada-Wide Standard for Petroleum Hydrocarbons in soils defined different fractions, based on carbon numbers of normal (linear and not-branched) *n*-alkanes, including C10 to C16, C16 to C34 and C34 to C50 *n*-alkane fractions [9]. GC is generally coupled to a flame ionization detector (FID) to measure C10-C36 TPHs in soils or sediments, giving a fingerprint of the major components in a petroleum product, providing information about the pollution source [10]. But measuring TPHs from hexane extraction followed by GC-FID does not allow distinguishing aliphatic from aromatic HCs. A purification/fractionation step can be added, using aluminium oxide or silica gel columns, or using thin layer chromatography (TLC) [11]. Thus, methods for determining extractable petroleum hydrocarbons (EPH) (from methylene chloride) use fractionation and allow determining aliphatic (C9-C36) from aromatic fractions. However, despite the fractionation step, other classes of organic interfering compounds, particularly those containing halogens (PCBs, organochlorine pesticides...) or phenols or phthalate esters are unfortunately present in the fraction containing the aliphatic HCs, biasing GC-FID results. Coupling GC or TLC to a high-resolution mass spectrometer (MS) allows obtaining a higher specificity and a very high resolution in the detection of all HCs from petroleum products. However, GC hyphenated to low-resolution MS is much frequently used to analyse and quantify paraffinic HC pollutants from soils or sediments [12,13].

A fact is that the majority of aliphatic HC analyses are performed after solvent extraction from soils or sediments, using different procedures, the most traditional being mechanical shake, Soxhlet or ultrasonic bath extractions. These procedures use large volumes of organic solvents and are time-consuming [14,15]. Other techniques, such as supercritical fluid extraction, pressurised liquid extraction or QuEChERS use far less volumes of solvents [2,16–18]. Microwave-assisted extraction (MAE) is also powerful compared to the other solvent extraction methods [19]. But obtaining quantitative HC extraction yields remain problematic due to the great diversity of physicochemical properties of HCs that directly affect their solubility into the solvents and the strength of their interaction with the soil matrix.

Thermal desorption (TD) uses elevated temperatures to desorb volatile or semi-volatile organic compounds from solid matrices and can be an attractive alternative to solvent extraction. A wide range of methodologies using TD extraction coupled to GC-MS has been developed for analysing a variety of compounds sorbed to different solid materials, such as dioxins from fly ash, transformation products of dimethylhydrazine from soils, polychlorinated biphenyls from sediments or small smelly molecules from fish [20–23]. Concerning hydrocarbons, TD is preferentially used for analysing volatile ones on-line or after a collection step of the gaseous phase on sorbent tubes [24,25]. Nevertheless, TD can also be used for measuring semi-volatile HCs from particulate solid phases. However, TD is generally used for desorbing and analysing aromatic HCs (i.e. PAHs) and more specially from airborne particulate

matter or dust [24,26–29]. TD is less commonly used for analysing paraffinic HCs from atmospheric particles [30]. Although significant cracking of HCs is not expected at the temperature limit of 300 °C [31], thermal desorption is much less used for analysing them directly from soils or sediments. Pyrolysis at higher temperatures (300 °C–650 °C) is preferred to analyse the full soil organic matter (OM), as higher molecular weight HCs (>C27) seem difficult to desorb quantitatively from soils at lower temperatures [32]. Unfortunately, bond cleavage of the carbonaceous macromolecules has been described above 300 °C, generating interfering lower molecular weight HCs and biasing quantification of native paraffinic compounds. Finally, although thermal desorption was successfully used to desorb quantitatively petroleum products from contaminated soils in remediation projects [33], it was not fully examined as an analytical tool and compared with more classical solvent extraction methodologies.

It is why the performance of a specific methodology was investigated in this study for the analysis of paraffinic HCs, via direct sediment introduction followed by thermal desorption and GC-MS quantification. A chemometric approach was performed to discriminate for the first time the critical influential factors and their interactions on the HCs extraction efficiency from model sediments containing various OM amounts. The semi- and non-volatile linear *n*-alkanes (*n*-C10 to *n*-C40) were quantitatively analysed. The amount of paraffinic alkanes was determined as the sum of resolved and unresolved components eluted from the GC column between the retention times of *n*-C10 to *n*-C40. TD-GC-MS was also compared to an optimized MAE-GC-MS solvent extraction methodology, which could be considered as a reference extraction procedure, representing a more classic extraction by solvent. Matrix effects, which are of great concern in analytical chemistry, were examined and compared between the two methodologies as they can cause quantification inaccuracies. An original solution was examined (solid/solid dilution) to reduce adverse matrix effects on quantification and an attempt was made to validate the TD-GC-MS with a standard sediment.

## 2. Materials and methods

### 2.1. Chemicals

Toluene, methylene chloride and acetone (HPLC grade) were furnished by Fisher Scientific (Illkirch, France). A standard solution of hydrocarbons (HC) (*n*-alkanes C10-C40, 50 mg L⁻¹ in heptane) was provided by Merck (St Quentin-Fallavier, France). Also provided by Merck, perdeuterated C16D and C36D *n*-alkanes were mixed together (solution E1 at 100 mg L⁻¹) and perdeuterated C12D and C30D *n*-alkanes were mixed together (solution E2 at 100 mg L⁻¹).

### 2.2. Sediments pre-treatment

Model sediments of different compositions, used for the experimental designs, were prepared by mixing dried silt (collected from surface formations covering the chalk plateau in Normandy, France) with 15 % dried sand (SIKA, Hostun, France), 8 % dried illite (IMERYS, Poigny, France) and 0.8 to 9.2 % dried organic matter (obtained from decomposition and ageing of plant detritus, VEOLIA, France). OM percentage was varying and was compensated by adjusting the percentage of silt (67.8 to 76.2 %). One of these model sediments was more particularly used for determining some method performances. It contained 8 % clay, 15 % sand, 5 % OM and 72 % silt to be close from Normandy (France) sediments formulation. All the dried model sediments were spiked with the standard mixture of C10-C40 (4 mg kg⁻¹), but also mixtures of 16 priority PAHs (2 mg kg⁻¹) and 6 indicator PCBs (0.5 mg kg⁻¹) to be representative of the multiple organic pollution in sediments from the Seine estuary, France [34]. Spiked sediments were agitated at least 2 h under a fume hood for acetone evaporation.

Two dried certified reference sediments were obtained from Merck.
CRM356 was a loamy sand sediment certified for C6-C35 TPHs and C10-C20 DRO (Diesel Range Organics). CRM372 was a sandy sediment certified for various ranges of alkanes of which C6-C35 TPHs, C10-C20 DRO, C9-C36 EPHs and C12-C16, C16-C21 and C21-C34 aliphatic HCs.

Washed Fontainebleau sand (180–500 µm particle diameter) (VWR, Rosny/Bois, France) and siliceous diatomaceous earth (10–100 µm) (Merck) were used as neutral solid substrates to dilute some sediments. To constitute homogeneous samples, 1 g sediment was mixed with 1 g sand or 1 g diatomaceous earth and blended with a magnetic stirrer.

Previous MAE or TD extractions, 2 to 10 g of dried sediments or sediment mixtures were blended with a magnetic stirrer. Each sample was finely grinded (2 × 30 s at 20 Hz) thanks to a BM500 Anton Paar ball mill (Courtaboeuf, France) and then 5.0 ± 0.1 mg aliquots could be sampled for TD-GC-MS analyses, or 2.0 ± 0.2 g aliquots for MAE-GC-MS analyses. It must be noted that fine grinding was particularly important for TD-GC-MS analyses, as well as weighing to the hundredth of a mg, allowing better quantification reproducibility.

## 2.3. Microwave assisted extraction and thermal desorption of HCs

Simultaneous extractions of HCs with PAHs and PCBs were performed using MAE (ETHOS X, Milestone, Rillieux-la-Pape, France). In the optimal conditions, six Teflon coated tubes, each containing 2 g dried and ground sediment samples, were spiked with 15 µL of the E2 solution as surrogate standards for determining extraction losses, and filled with 32 mL of toluene:acetone 1:1 (v:v). Tubes were hermetically closed and were extracted under stirring at 130 °C for 30 min (1200 W) [35]. The extracts were filtered through 0.2 µm PTFE filters (Phenomenex, le Pecq, France) and after addition of 50 µL of a solvent keeper (octanol), they were evaporated at 45 °C under 30 mbar for 2h30 with a MiVac duo concentrator (Genevac, Ipswich, UK). Then, they were reconstituted in 1.5 mL toluene, and 990 µL aliquots were mixed with 10 µL of the solution E1, as internal standards, for GC-MS quantification.

Solvent-free extractions were performed via TD coupled with GC-MS. In the optimal conditions, 5 mg dried ground samples were directly introduced into a glass liner TDU tube (Gerstel, Germany). Before use, all the TD tubes have been cleaned by using a muffle furnace (350 °C) to remove possible residual organic compounds. The apparatus was equipped with a heated desorption unit (TDU2, Gerstel), a cooled programmed temperature vaporization inlet (CIS4, Gertel) and a robotic autosampler (MPS, Gerstel). For quantification, 5 µL standard solutions containing the C10-C40, E1 and E2 solutions at the same concentration levels, were spiked onto 5 mg of the sediment matrices via the MPS system and an impregnation time of 10 min was allowed before desorption. The TDU was programmed to start at 30 °C, increased at 55 °C min⁻¹ to 350 °C (held for 15 min) with helium vent flow at 150 mL min⁻¹. During desorption, compounds were concentrated at the head of the GC column thanks to the CIS cryo trap (-35 °C). It must be noted that sediment samples must be very dry before TD extraction to avoid ice formation in the CIS and clogging. So when necessary, sediments should be freeze-dried (Alpha 2–4 LD, Christ, Deutschland) to ensure they are perfectly dry. Then, after concentration in the cooled trap, compounds were transferred to the GC column by a rapid heating of the CIS unit to 325 °C (12 °C s⁻¹). The injection to the GC column was made in splitless mode. When real sediment samples were too concentrated and generated saturated signals, sediment samples were diluted twice (w/w) with the pure Fontainebleau sand (Section 2.2). Between each sediment extraction, a blank run was performed with the injection of methylene chloride, to avoid cross-contamination.

## 2.4. GC-MS analyses and quantification

After MAE, 1-µL extract was injected (splitless mode, 285 °C) into a 6850 gas chromatographer (Agilent Technologies, USA), coupled with a 5975 mass spectrometer. The separation was performed with a DB-5MS column (60 m length × 0.25 mm i.d. × 0.25 µm film thickness) from

J&W Scientifics (Agilent). The oven program started at 60 °C (1.2 min) to 160 °C (at 40 °C min⁻¹) followed by an increase to 230 °C (at 8.5 °C min⁻¹), and finally to 305 °C (at 13 °C min⁻¹), for 44 min, under a constant carrier gas flow of 1.4 mL min⁻¹. The transfer line was set at 300 °C and the MS detection was performed via electron ionization (EI) (70 eV) in selected ion monitoring (SIM), with the chosen most abundant ion fragments *m/z* 57, 71 and 85 for HCs and 50, 66, 82 for deuterated HCs. Calibration lines were established from the C10 to C40 *n*-alkanes using 7 levels of concentrations, from 0.1 to 3 mg L⁻¹, using the internal calibration methodology, and all the determination coefficients were >0.990. Deuterated C12D and C16D were used as surrogate and internal standards, respectively, for C10-C21 *n*-alkanes and deuterated C30D and C36D were used as surrogate and internal standards, respectively, for C22-C40 *n*-alkanes. For the determination of unresolved aliphatic HCs (linear, cyclic and branched) from the [C10-C12[, [C12-C16] and]C16-C21] EC ranges, C10, C14 and C18 calibration lines were respectively used for their quantification. For the determination of HCs from the]C21-C34] and]C34-C40] EC ranges, C28 and C36 calibration lines were respectively used. It can be noted that ]Cn-Cm] means that Cn *n*-alkane and its isomers were excluded from the integrated interval. The sum of all the EC ranges gave the C10-C40 quantification. For the DRO (C10-C20 range), the C14 calibration line was chosen for quantification. Areas of the individual *n*-alkanes or the EC ranges were determined taking into account the horizontal baseline from the C10 to the C40 *n*-alkanes.

After thermal desorption, a 7890B gas chromatograph coupled with a 7000C mass spectrometer (Agilent Technologies) was used for HCs separation and detection. A DB5-5MS (J&W Scientifics) column (60 *m* × 0.25 mm i.d. × 0.25 µm) was used for separation and the carrier gas was helium (1.4 mL min⁻¹). The GC oven temperature program was the same than that described previously. MS transfer line, ion source and quadrupole temperatures were set at 310 °C, 230 °C and 150 °C, respectively. Electron ionization was performed at 70 eV and SIM mode was applied (*m/z* 57, 71, 85 for HCs and 50, 66, 82 for deuterated HCs). Using this selective detection, analytical blanks of cleaned empty TD tubes showed no interfering peaks after the solvent delay. In the case of analyses of sediments diluted with pure sand or diatomaceous earth, blanks were done from the diluting materials and were systematically subtracted from the chromatograms (Fig. S1 in supplementary materials).

Calibration lines for the matrix-matched calibration method were established using 4 to 5 added amount levels of the C10-C40 mixture, from 20 to 75 ng, and the determination coefficients were >0.980 for the linearity range. Moreover, introduction of deuterated internal standards was necessary for quantifying the unresolved paraffinic HCs: calibration line of the C12D was used to quantify the unresolved aliphatics from the [C10-C12[ and [C12-C16] EC ranges, while C16D was used for the ]C16-C21] EC range, C30D for the ]C21-C34] and C36D for ]C34-C40] EC ranges.

## 2.5. Statistical analyses

ELLISTAT software (Chavanod, France) was used for statistical calculations and modelling of HC recoveries extracted from the sediments. The significance of the models was tested comparing the coefficients of determination (R²), the adjusted coefficients of determination (R²adj) and the p-values (95 % confidence level) corresponding to the analysis of the variance (ANOVA). The most influential factors and interactions (p-values < 0.05) could be determined from these statistical tests.

# 3. Results and discussion

## 3.1. Optimization of TD extractions through a DSD+ experimental design and comparison with MAE-GC-MS

### 3.1.1. Optimization of TD-GC-MS extraction of *n*-alkanes

Experimenters usually conduct multiple step-by-step experiments to
screen the influence of many individual factors on a desirable response. It is particularly the case for optimizing an analytical process, where the response is the ability to extract quantitatively a family of contaminants from a matrix and to quantitate them. Unfortunately, this sequential methodology does not allow determining accurately the active factors that modify the response and the interactions between factors, and does not allow modelling the responses taking into account all the active factors and their interactions, simultaneously. Response surface methodologies propose experimental designs to do this with a relatively low number of runs, to possibly obtain polynomial models and to find an optimum for the responses with desirability functions. Central Composite Designs (CCD) combining a two-level factorial design with a star design and center points allow approximating the system response using non-linear models, but Definitive Screening Designs (DSD) allow studying the effects of a larger number of factors in fewer experiments. Augmented DSD+ design was used in this study to optimize the thermal desorption of HCs from a sediment matrix as lots of factors could affect paraffinic HCs extraction efficiency and as literature is very poor for discriminating the critical extraction parameters (with an exception for the extractions from airborne particles). Here, 6 factors were considered simultaneously.

Intrinsic matrix parameters were studied, such as OM content (OM factor) and sediment mass (m factor). It is well known that organic matter can be an important factor involved in HC sorption: resins or asphaltenes found in OM, or OM associated to some clay minerals can influence sorption strength [36,37]. In this study, OM was derived from the decomposition and ageing of plant detritus, as can be found in sediments. But it is not necessarily representative of the diversity of all the sediment organic materials. The attempt was to evaluate if OM content could have a significant influence on the TD desorption capacity for paraffinic HCs.

Furthermore, studying the factors involved in the desorption steps is also crucial. The first step is thermal desorption from the TD unit (TDU) and the second one is the transfer into the GC system from a cryo-focused trap (CIS unit), where desorbed analytes are concentrated. In each step, lots of factors can be more or less influential for desorbing, focusing or transferring the analytes: the TDU initial temperature, its temperature rate, the final temperature and its hold time, the temperature and purge flows to transfer the analytes to the CIS cryotrap, the CIS initial temperature, rate, final temperature and hold time could also vary. Among all the factors to consider, some of them have been demonstrated to be critical: thermal desorption parameters such as TDU temperature, rate and duration, but also vent flow to the cryo-trap [19, 38]. So these latter parameters were introduced in the experimental design study.

Table 1 shows the DSD+ experimental matrix, built with the Ellistat software, with the 6 factors investigated at two levels (-1, +1), a center point (0), and 4 supplementary runs to improve the robustness of the mathematical model. The TDU temperature started at 30 °C and the rate of the ramp (Rate factor) varied in the range 15–55 °C min⁻¹; the final temperature (T<sub>f</sub> factor) varied in the range 250–350 °C, with an hold time (Hold factor) ranging between 5 and 15 min; and the Helium vent flow (Vent factor) varied in the 50–150 mL min⁻¹ range. The CIS started at –35 °C and the ramp and final temperature were set at their maximum level (12 °C s⁻¹ to 325 °C), with a 5 min hold time.

The effects and the interactions of the factors on the thermal desorption of *n*-alkanes were estimated through the modelling software. If the studied response was the sum of *n*-alkanes areas considered together, from C10 to C40 (ΣHC), the latter could be better modelled by a linear model with three-way interactions between factors. The effects of the critical factors were analysed using the Pareto chart of effects, which allowed classifying the more to the less active factors, at a 95 % confidence level (ANOVA yielding p-values <0.05) in the order: OM × Hold × Vent > m × OM × T<sub>f</sub>. Rate was not an active factor (p-values > 0.05) even in interaction with other factors. But the overall model was not robust as it obtained a determination coefficient between the model

<table><caption>**Table 1**

DSD+ experimental design for TD optimization, with experimental values of the studied factors and their coded levels (between brackets).</caption><thead><tr><th>Run</th><th>m (mg)</th><th>OM (%)</th><th>Rate (°C min<sup>-1</sup>)</th><th>Tf (°C)</th><th>Hold (min)</th><th>Vent (mL min<sup>-1</sup>)</th></tr></thead><tbody><tr><td>1</td><td>10 (0)</td><td>1 (-1)</td><td>55 (+1)</td><td>350 (+1)</td><td>5 (-1)</td><td>150 (+1)</td></tr><tr><td>2</td><td>10 (0)</td><td>9 (+1)</td><td>15 (-1)</td><td>250 (-1)</td><td>15 (+1)</td><td>50 (-1)</td></tr><tr><td>3</td><td>5 (-1)</td><td>5 (0)</td><td>15 (-1)</td><td>350 (+1)</td><td>15 (+1)</td><td>150 (+1)</td></tr><tr><td>4</td><td>15 (+1)</td><td>5 (0)</td><td>55 (+1)</td><td>250 (-1)</td><td>5 (-1)</td><td>50 (-1)</td></tr><tr><td>5</td><td>5 (-1)</td><td>1 (-1)</td><td>35 (0)</td><td>350 (+1)</td><td>15 (+1)</td><td>50 (-1)</td></tr><tr><td>6</td><td>15 (+1)</td><td>9 (+1)</td><td>35 (0)</td><td>250 (-1)</td><td>5 (-1)</td><td>150 (+1)</td></tr><tr><td>7</td><td>15 (+1)</td><td>1 (-1)</td><td>55 (+1)</td><td>300 (0)</td><td>15 (+1)</td><td>150 (+1)</td></tr><tr><td>8</td><td>5 (-1)</td><td>9 (+1)</td><td>15 (-1)</td><td>300 (0)</td><td>5 (-1)</td><td>50 (-1)</td></tr><tr><td>9</td><td>5 (-1)</td><td>1 (-1)</td><td>55 (+1)5</td><td>250 (-1)</td><td>10 (0)</td><td>50 (-1)</td></tr><tr><td>10</td><td>15 (+1)</td><td>9 (+1)</td><td>15 (-1)</td><td>350 (+1)</td><td>10 (0)</td><td>150 (+1)</td></tr><tr><td>11</td><td>15 (+1)</td><td>1 (-1)</td><td>15 (-1)</td><td>250 (-1)</td><td>15 (+1)</td><td>100 (0)</td></tr><tr><td>12</td><td>5 (-1)</td><td>9 (+1)</td><td>55 (+1)</td><td>350 (+1)</td><td>5 (-1)</td><td>100 (0)</td></tr><tr><td>13</td><td>5 (-1)</td><td>9 (+1)</td><td>55 (+1)</td><td>250 (-1)</td><td>15 (+1)</td><td>150 (+1)</td></tr><tr><td>14</td><td>15 (+1)</td><td>1 (-1)</td><td>15 (-1)</td><td>350 (+1)</td><td>5 (-1)</td><td>50 (-1)</td></tr><tr><td>15</td><td>15 (+1)</td><td>9 (+1)</td><td>55 (+1)</td><td>350 (+1)</td><td>15 (+1)</td><td>50 (-1)</td></tr><tr><td>16</td><td>5 (-1)</td><td>1 (-1)</td><td>15 (-1)</td><td>250 (-1)</td><td>5 (-1)</td><td>150 (+1)</td></tr><tr><td>17</td><td>10 (0)</td><td>5 (0)</td><td>35 (0)</td><td>300 (0)</td><td>10 (0)</td><td>100 (0)</td></tr></tbody></table>

and the experimental values R²=60.3 % and an adjusted parameter R²<sub>adj</sub>= 47.0 %. It could be explained because low molecular weight (LMW)-HCs had markedly different from high molecular weight (HMW)-HCs. So, *n*-alkanes were examined individually to understand the influence of the factors in relation to their low (C10-C16), mid (C17-C29) and high (C30-C40) number of carbons.

The group of C10-C16 HCs could be optimized with linear models and contributions of two and/or three-way interactions between factors, R² in the range 70–85.1 % and R²<sub>adj</sub> of 60.0–76.2 %. Mass (m) and T<sub>f</sub> were the most active factors, but the Rate was also particularly influential through interactions with other factors. For this group of HCs, the best condition (corresponding to a maximal extraction) obtained a desirability of 89.9 % for a maximum sediment mass *m* = 15 mg, with a maximum OM content: the highest sediment mass and OM content helped in increasing the extractability of the more volatile LMW-HCs. A low temperature rate of 15 °C min⁻¹, a low final temperature of 250 °C and a maximum vent flow of 150 mL min⁻¹ were also favourable for their thermal desorption and transfer. The hold time was not active. As shown in Fig. 1A, a high TDU temperature was not favourable for the extraction of the LMW-HCs, because of possible carbon chain breakdown, as shown by some authors for airborne particles [28,30].

Considering the intermediate group of C17-C29 HCs, their optimization led to slightly less robust linear models, essentially with contributions of two and/or three-way interactions (R² in the range 36.0–80.7 % and R²<sub>adj</sub> of 26.8–71.9 %). Mass and OM percentage were the most active factors, and T<sub>f</sub> contributed in interaction with the Rate or the OM percentage. For this group of HCs, the best extraction condition (desirability of 85.8 %) was obtained with a minimum sediment mass *m* = 5 mg, with a maximum OM content, a high temperature rate of 55 °C min⁻¹, a final temperature of 257 °C with an Hold time of 15 min and a maximum vent flow of 150 mL min⁻¹. As shown in Fig. 1B, the influence of the sediment mass was high for these HCs and unlike LMW-HCs, high
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 1.** Three-dimensional modelling of some *n*-alkanes TD extraction (studied response: peak area) as a function of some active factors: sediment Mass (mg) and TD final temperature T~f~ (°C); A/ C12; B/ C20; C/ C36.</figcaption></figure>

sediment mass values did not allow extracting quantitatively this group of HCs. Even if the presence of high contents of OM favoured their extractability, high sample mass was not favourable, probably due to poorer mass transfer. T~f~ was not so critical than for the extraction of LMW-HCs and the higher TDU temperatures only slightly decreased their area. At last, unlike LMW-HCs, the temperature ramp (Rate) had to be the highest.

For the group of HMW-HCs from C30-C40, their optimization led to linear robust models, with contributions of two and/or three-way interactions (R² in the range 56.8–96.3 % and R²<sub>adj</sub> of 46.8–92.6 %). Vent flow and T~f~ were the most active factors, and the interactions between OM percentage and Rate or between T~f~ and the Vent flow were important. For this group of HCs, the best extraction condition (desirability of 83.7 %) was with a minimum sediment mass *m* = 5 mg, with a maximum OM content, a high temperature rate of 55 °C min⁻¹, a maximum final temperature of 350 °C with a Hold time of 9.4 min and a maximum vent flow of 150 mL min⁻¹. As shown in Fig. 1C, the influence of the sediment mass was high: HMW-PAHs were the most sensitive to mass transfer limitations and increasing the sample mass was particularly detrimental. Unlike LMW-HCs, higher values of T~f~ allowed extracting more quantitatively this group of HCs, as shown by Wang et al. for airborne particles [29].

At last, even if some factors could oppositely contribute to the extraction of this wide variety of HCs, the composite desirability function was used to calculate the optimal response for all the individual compounds. Using this tool, it appeared that whatever the OM percentage, the TDU temperature rate and hold time had to be set at their maximum level (respectively 55 °C min⁻¹ and 15 min), and the Vent flow also, to transfer a maximum of compounds from the TDU to the CIS unit. Considering the mass factor, it had to be minimal (5 mg) and the TDU final temperature had to be maximal (350 °C) although it was less favourable for LMW-HCs. It can be noted that whatever the HC class, the higher amount of OM favoured the extractability of HCs, probably because of the simultaneous extraction of other organic compounds. But it is not sure that the behaviour of such OM, resulting from the long decomposition of plants, would be the same than the one of OM containing soot or black carbon, resulting generally from anthropogenic combustion activities. Indeed, the latter can be very strong sorbents for HMW hydrocarbons.

### 3.1.2. Optimization of MAE-GC-MS extraction of *n*-alkanes

A central composite design (CCD) was used to optimize the simultaneous microwave-assisted extraction of a mixture of C10-C40 *n*-alkanes, polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) from the model sediment. The CCD combined a full factorial design with a star design to be able to model quadratic responses, generating 20 experimental runs with 6 repetitions. Three factors were more particularly screened: the volume of extracting solvent (V factor in the 10.5–37.5 mL range), the sediment mass (m factor in the 0.8–9.2 g range) and the OM percentage (OM factor in the 0.8–9.2 % range). The influence of the other factors namely acetone:toluene 50:50 (v:v) solvent mixture, extraction temperature (130 °C) and duration (30 min) was not considered in this work as these factors have been more extensively studied in the past and were adapted to extract also PAHs and PCBs [35]; however the interaction between the solid mass to extract and the chosen extraction volume had to be clarified. Indeed, Serrano and Gallego [19] mentioned that the MAE extraction efficiency of HCs could depend both on the solvent volume and on the amount of soil sample. Moreover, hydrophobic OM could be a relatively strong sorbent for apolar HCs and might be a critical factor for MAE extraction, this factor being poorly studied. The experimental design for MAE optimization is recalled in the Table S1 of the supplementary materials [35].

The CCD results fitted better with polynomial models to predict the extraction of *n*-alkanes. When the sum of all the extracted C10-C40 *n*-alkanes was considered (ΣHC), the more satisfactory model (R²=87.9 %).
$R_{adj}^2=83.6 \%)$ predicted the most active factors in the order: $V^2>V>V^3>m^2>V \times m$. Although OM was supposed to strongly sorb apolar HCs and limit their extractability, OM percentage was not identified as an active factor even through interactions. It appeared that (i) the volume of solvent was the more critical factor and (ii) the interaction between V and m was actually important to consider, and complex. In fact, there was two optimal areas: one for a minimal solvent volume (10.5 mL), the other for a volume of 33.2 mL, for sediment masses less than 4 g (Fig. S2). As mentioned by Serrano and Gallego [19], a minimal solvent volume could be favourable as there is less volatile HC losses during the evaporation step. But the higher best solvent volume of 33.2 mL was more favourable for the transfer and solubilisation of HMW-HCs. Higher volumes than 33.2 mL were detrimental because of the higher dilution of the extracted analytes. The attempt was to extract simultaneously PAHs, PCBs and HCs from sediment matrices, so a prediction profiler with the desirability function was run to find the optimal extraction conditions for the three studied families together [35]. The optimal MAE extraction recoveries were then predicted using the modelling software. They were obtained for $m = 2.5$ g sediment and $V = 32$ mL whatever the OM content. So 32 mL of toluene:acetone 1:1 (v:v) was chosen for extracting quantitatively HCs and the associated PAHs and PCBs from sediments. In these conditions, repeatability (relative standard deviation (RSD) from intra-day precision), limits of detection (LOD =3 times the standard deviation of the baseline noise) and of quantification (LOQ =10 times the standard deviation of the baseline noise) were established for the MAE extraction of the C12-C40 n-alkanes from the CRM356 standard sediment (Table 2).

## 3.2. Quantification strategies, validation with CRM372 standard sediment and matrix effects

### 3.2.1. Quantification of n-alkanes using MAE-GC-MS

Internal calibration, using deuterated C16D or C36D (Section 2.3), was used to quantify each individual *n*-alkane or the unresolved paraffinic HCs from the defined EC ranges: [C10-C12[, [C12-C16], ]C16-C21], ]C21-C34] and ]C34-C40]. Fig. S3A (supplementary materials) gives the chromatogram of CRM356 and each linear alkane or EC ranges could be easily detected thanks to the retention times of the *n*-alkanes from the C10-C40 standard solution and the specific extracted ions from deuterated *n*-alkanes. The certificate of the CRM356 gives a TPH value = 3180±846 mg kg⁻¹ and a DRO = 611±40 mg kg⁻¹ for the C10-C20 range. In our case, the C10-C40 envelope gave a value of 930±76 mg kg⁻¹ ($n = 6$) and a C10-C20 envelope = 243±15 mg kg⁻¹ ($n = 6$), which are not in agreement with the values given by the certificate. As mentioned in the introduction, the TPH and DRO values given by the certificate are unspecific and give not only the total of aliphatics, mono- and poly-aromatic HCs and asphaltenes, but also other classes of interfering compounds that are extracted with HCs. So, the values obtained via the more selective GC-MS analysis cannot be directly linked to the certificate of CRM356.

More recently, new commercial certified sediments appeared which could give more specific values. It is the case of CRM372 sediment certificate that gives not only different values for DRO, TPH, EPH but also for linear alkane ranges. Table 3 summarizes some of the CRM372 certified values in comparison with those obtained in this study. For the C12-C16, C16-C21 and C21-C34 sum of *n*-alkanes, the obtained values using MAE-GC-MS are in accordance with those of the certificate. Table 3 gives also the values obtained for the unresolved aliphatics (linear + branched + cyclic) for the different EC ranges from C10 to C40,

<caption>**Table 2**</caption>

Comparison of *n*-alkanes intra-day precision (repeatability RSD), evaluated on CRM356 (spiked or not by the C10-C40 standard mixture), limits of detection (LOD), limits of quantification (LOQ) and matrix effects, for the overall analytical processes MAE-GC-MS and TD-GC-MS.

<table><thead><tr><th rowspan="3">n-alkanes</th><th colspan="4">MAE-GC-MS</th><th colspan="4">TD-GC-MS</th></tr><tr><th colspan="2">Repeatability (n = 6)</th><th colspan="2">LOD</th><th colspan="2">Repeatability (n = 5)</th><th colspan="2">LOD</th></tr><tr><th>(%)</th><th>LOD (mg kg<sup>-1</sup>)</th><th>(ng)</th><th>LOQ (ng)</th><th>(%)</th><th>LOD (mg kg<sup>-1</sup>)</th><th>(ng)</th><th>LOQ (ng)</th><th>Matrix Effects (%)</th></tr></thead><tbody><tr><td>C12</td><td>11.5</td><td>0.398</td><td>795</td><td>2650</td><td>-66.7</td><td>16.7</td><td>0.536</td><td>13.4</td><td>44.6</td><td>19.7</td></tr><tr><td>C13</td><td>5.6</td><td>0.040</td><td>70</td><td>240</td><td>-51.7</td><td>7.7</td><td>0.486</td><td>12.2</td><td>40.5</td><td>17.9</td></tr><tr><td>C14</td><td>4.3</td><td>0.014</td><td>28</td><td>93</td><td>-37.2</td><td>8.5</td><td>0.457</td><td>11.4</td><td>38.0</td><td>16.7</td></tr><tr><td>C15</td><td>3.6</td><td>0.057</td><td>114</td><td>379</td><td>-32.8</td><td>7.8</td><td>0.400</td><td>10.0</td><td>33.3</td><td>16.7</td></tr><tr><td>C16</td><td>5.4</td><td>0.021</td><td>42</td><td>139</td><td>-34.1</td><td>8.7</td><td>0.435</td><td>10.9</td><td>36.3</td><td>25.8</td></tr><tr><td>C17</td><td>7.1</td><td>0.038</td><td>76</td><td>253</td><td>-31.7</td><td>6.7</td><td>0.413</td><td>10.3</td><td>34.4</td><td>38.4</td></tr><tr><td>C18</td><td>4.5</td><td>0.031</td><td>62</td><td>206</td><td>-32.9</td><td>6.7</td><td>0.400</td><td>10.0</td><td>33.3</td><td>22.7</td></tr><tr><td>C19</td><td>3.9</td><td>0.032</td><td>63</td><td>210</td><td>-32.4</td><td>8.0</td><td>0.341</td><td>8.5</td><td>28.4</td><td>16.5</td></tr><tr><td>C20</td><td>4.2</td><td>0.015</td><td>30</td><td>100</td><td>-31.7</td><td>7.0</td><td>0.360</td><td>9.0</td><td>30.0</td><td>27.1</td></tr><tr><td>C21</td><td>6.7</td><td>0.028</td><td>57</td><td>188</td><td>-53.0</td><td>7.8</td><td>0.362</td><td>9.1</td><td>30.2</td><td>10.4</td></tr><tr><td>C22</td><td>12.7</td><td>0.020</td><td>39</td><td>131</td><td>-53.0</td><td>9.0</td><td>0.363</td><td>9.1</td><td>30.2</td><td>-1.5</td></tr><tr><td>C23</td><td>13.1</td><td>0.043</td><td>86</td><td>288</td><td>-52.1</td><td>9.7</td><td>0.379</td><td>9.5</td><td>31.6</td><td>1.1</td></tr><tr><td>C24</td><td>20.4</td><td>0.057</td><td>114</td><td>382</td><td>-51.6</td><td>9.3</td><td>0.400</td><td>10.0</td><td>33.3</td><td>-3.6</td></tr><tr><td>C25</td><td>24.2</td><td>0.136</td><td>271</td><td>904</td><td>-50.3</td><td>7.4</td><td>0.310</td><td>7.8</td><td>25.9</td><td>-11.5</td></tr><tr><td>C26</td><td>27.2</td><td>0.187</td><td>374</td><td>1248</td><td>-51.7</td><td>9.7</td><td>0.244</td><td>6.1</td><td>20.3</td><td>-15.6</td></tr><tr><td>C27</td><td>14.4</td><td>0.063</td><td>127</td><td>423</td><td>-52.7</td><td>17.0</td><td>0.240</td><td>6.0</td><td>20.0</td><td>-15.7</td></tr><tr><td>C28</td><td>18.0</td><td>0.213</td><td>425</td><td>1418</td><td>-50.5</td><td>16.8</td><td>0.228</td><td>5.7</td><td>19.0</td><td>-35.7</td></tr><tr><td>C29</td><td>12.4</td><td>0.053</td><td>105</td><td>352</td><td>-49.5</td><td>16.3</td><td>0.250</td><td>6.3</td><td>20.8</td><td>-38.0</td></tr><tr><td>C30</td><td>n.d.</td><td>0.100</td><td>201</td><td>669</td><td>-49.1</td><td>n.d.</td><td>0.267</td><td>6.7</td><td>22.2</td><td>-49.0</td></tr><tr><td>C31</td><td>n.d.</td><td>0.113</td><td>227</td><td>756</td><td>-48.4</td><td>n.d.</td><td>0.273</td><td>6.8</td><td>22.7</td><td>-47.9</td></tr><tr><td>C32</td><td>n.d.</td><td>0.028</td><td>55</td><td>184</td><td>-45.8</td><td>n.d.</td><td>0.250</td><td>6.3</td><td>20.8</td><td>-61.0</td></tr><tr><td>C33</td><td>n.d.</td><td>0.056</td><td>113</td><td>375</td><td>-44.6</td><td>n.d.</td><td>0.300</td><td>7.5</td><td>25.0</td><td>-74.4</td></tr><tr><td>C34</td><td>n.d.</td><td>0.010</td><td>21</td><td>69</td><td>-44.2</td><td>n.d.</td><td>0.341</td><td>8.5</td><td>28.4</td><td>-47.6</td></tr><tr><td>C35</td><td>n.d.</td><td>0.021</td><td>42</td><td>141</td><td>-41.6</td><td>n.d.</td><td>0.300</td><td>7.5</td><td>25.0</td><td>-45.4</td></tr><tr><td>C36</td><td>n.d.</td><td>0.013</td><td>25</td><td>85</td><td>-40.2</td><td>n.d.</td><td>0.150</td><td>3.8</td><td>12.5</td><td>-32.5</td></tr><tr><td>C37</td><td>n.d.</td><td>0.082</td><td>164</td><td>548</td><td>-36.8</td><td>n.d.</td><td>0.185</td><td>4.6</td><td>15.4</td><td>-7.9</td></tr><tr><td>C38</td><td>n.d.</td><td>0.087</td><td>174</td><td>580</td><td>-32.8</td><td>n.d.</td><td>0.200</td><td>5.0</td><td>16.7</td><td>-9.1</td></tr><tr><td>C39</td><td>n.d.</td><td>0.072</td><td>144</td><td>481</td><td>-32.4</td><td>n.d.</td><td>0.185</td><td>4.6</td><td>15.4</td><td>-13.1</td></tr><tr><td>C40</td><td>n.d.</td><td>0.099</td><td>198</td><td>661</td><td>-35.3</td><td>n.d.</td><td>0.188</td><td>4.7</td><td>15.6</td><td>-19.5</td></tr></tbody></table>

n.d.: not detected in the non-spiked sediment.
<caption>**Table 3**</caption>

Comparison of extracted amounts with their standard deviation (SD) and the expanded uncertainty intervals (coverage factor $k = 2$) for the MAE-GC-MS and TD-GC-MS analytical processes, and values furnished by the certificate of the CRM372 sediment, with the acceptance intervals.

<table><thead><tr><th></th><th>[C12-C16]</th><th>[C16-C21]*</th><th>[C21-C34]*</th><th>[C34-C40]*</th><th>[C10-C20]<br>DRO</th><th>[C9-C36]<br>EPH</th></tr></thead><tbody><tr><td><strong>Certified values (mg kg<sup>-1</sup>)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>n-alkanes ± SD (mg kg<sup>-1</sup>)</td><td>74.7±4.7</td><td>60.9±3.9</td><td>9.8±0.6</td><td>0</td><td></td><td></td></tr><tr><td>[Acceptance interval (mg kg<sup>-1</sup>)]</td><td>[27.5-122]</td><td>[22.4-99.4]</td><td>[3.6-16.0]</td><td></td><td></td><td></td></tr><tr><td>Total HCs ± SD (mg kg<sup>-1</sup>)</td><td></td><td></td><td></td><td></td><td>457±19</td><td>336±15</td></tr><tr><td>[Acceptance interval (mg kg<sup>-1</sup>)]</td><td></td><td></td><td></td><td></td><td>[274-640]</td><td>[185-487]</td></tr><tr><td><strong>MAE-GC-MS (n=6)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>n-alkanes ± SD (mg kg<sup>-1</sup>)</td><td>53.3±1.6</td><td>49.0±2.0</td><td>9.7±0.7</td><td>0</td><td></td><td></td></tr><tr><td>[expanded uncertainty (mg kg<sup>-1</sup>)]</td><td>[50.1-56.5]</td><td>[45.0-51.0]</td><td>[8.3-11.1]</td><td></td><td></td><td></td></tr><tr><td>Total HCs ± SD (mg kg<sup>-1</sup>)</td><td>175.2±4.8</td><td>146.1±3.8</td><td>233.4±19.0</td><td>80.4±4.5</td><td>328.1±9.3</td><td>659.9±30.5</td></tr><tr><td>[expanded uncertainties (mg kg<sup>-1</sup>)]</td><td>[165.6-184.8]</td><td>[138.5-153.7]</td><td>[195.4-271.4]</td><td>[71.4-89.4]</td><td>[309.5-346.7]</td><td>[598.9-720.9]</td></tr><tr><td><strong>TD-GC-MS/MS (n=5)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>n-alkanes ± SD (mg kg<sup>-1</sup>)</td><td>70.9±9.4</td><td>42.5±3.9</td><td>8.0±1.0</td><td>0</td><td></td><td></td></tr><tr><td>[expanded uncertainty (mg kg<sup>-1</sup>)]</td><td>[52.1-89.7]</td><td>[34.7-50.3]</td><td>[6.0-10.0]</td><td></td><td></td><td></td></tr><tr><td>Total HCs ± SD (mg kg<sup>-1</sup>)</td><td>214.0±33.4</td><td>176.7±19.8</td><td>158.1±19.8</td><td>0</td><td>462.6±80.0</td><td>599.5±95.9</td></tr><tr><td>[expanded uncertainty (mg kg<sup>-1</sup>)]</td><td>[147.2-280.8]</td><td>[137.1-216.3]</td><td>[118.5-197.7]</td><td></td><td>[302.6-622.6]</td><td>[407.7-791.3]</td></tr></tbody></table>

the DRO and the total aliphatic EPHs. The value obtained for the DRO was consistent with the one proposed by the certificate, considering the acceptance interval given by the certificate and our expanded uncertainty, with a coverage factor $k = 2$. But total aliphatic EPH seemed overestimated compared to the certificate. However, there is a contradiction in the certificate that gives almost similar values for DRO and EPH, that could let us think that there are no more alkanes after C20. However, Fig. 2A shows the chromatogram of CRM372 and it can be seen that aliphatic chains longer than C20 are present in this sediment.

### 3.2.2. Quantification of n-alkanes using TD-GC-MS: validation with CRM372 standard sediment

Using TD-GC-MS, the quantification was performed via a matrix matched calibration procedure, as a previous study showed that calibration lines obtained from additions of standards on empty TD tubes did not reflect the calibration lines from additions of standards on the sediment matrix [35]. Volumes of 5 µL of the C10-C20 mixture containing the 4 deuterated n-alkanes, all from 1 to 25 mg L⁻¹ (so in the 5–125 ng range), were added to 5 mg of CRM356, and desorbed in the optimal conditions (see Section 2.3). Fig. S3B gives the chromatogram of CRM356. The linearity range was approximately from 15 to 75 ng. Below 15 ng, the signal of the added C10-C40 mixture was hidden by the high signal of CRM356 extracted HCs, LODs and LOQs were established for the TD extraction (Table 2). LODs were in the 4–13 ng range and LOQs in the 12–45 ng. It is far less than values found for MAE-GC-MS, which were respectively in the 20–795 ng (LOD) and 70–2650 ng (LOQ) ranges (Table 2). The comparison of LODs in mg per kg of extracted sediment plays in favor of MAE versus TD, as 400 times more sediment material has to be used for detecting alkanes after MAE extraction.

Repeatability (RSD intra-day precision) between the two extraction techniques was also compared. This criterion was generally in favour of MAE-GC-MS for LMW n-alkanes from C12 to C21 (RSD from 3.6 to 11.5 %) in comparison with TD-GC-MS (7.8–16.7 %), but repeatability was worse for heavier alkanes (C22-C29) extracted by MAE in comparison with TD (Table 2).

Matrix effects were also evaluated for the two methods, by comparing the ratio of the slopes of the calibration lines without/with matrix (CRM356). It appeared that the signal of the n-alkanes was systematically depleted in the presence of the matrix using MAE-GC-MS, from -31.7 to -66.7 % (mean value: -44.6 %) (Table 2). In the case of TD-GC-MS, the signal was enhanced for LMW-HCs from C12 to C21 (+10.4 to +38.4 %), but depleted for HMW-HCs (-1.5 to -74.4 %) (mean absolute value: 30.6 %). So, matrix effect could appear less using TD compared to MAE extraction. But in fact, it highly depends on the sediment matrix and for CRM372, matrix effects were more pronounced,

with a mean depletion of the signal of -68.3 % (Table 4). Signal loss was more particularly enhanced for HMW-HCs. It is possible that the percentage and nature of OM, which appears an active factor for TD, could significantly impact on matrix effects.

Finally, the validation of the TD-GC-MS method was done by using the CRM372 standard sediment, because information on linear alkanes ranges quantification is available. Fig. 2B shows the chromatogram, which differs from the one obtained after MAE extraction, more particularly after the retention time of the C26 n-alkane. It actually shows less abundance for HMW-HCs after TD extraction. Quantification trials were done but it became apparent that calibration lines were not satisfactory, showing lots of R² values <0.96 and restricted linearity zones: extracted HCs were in fact too abundant and signals of n-alkanes were rapidly saturating even at medium added levels.

It is common to dilute a liquid sample with a solvent to reduce matrix effects, particularly for LC-MS analyses where high concentrations of interfering compounds can drastically reduce MS sensitivity. With the same principle, an attempt was made to dilute CRM372 sediment using neutral solid materials composed in majority of silica (which is not very retensive for apolar HCs), such as fine diatomaceous earth or coarser pure sand (2-fold solid/solid dilution). Moreover, it could be noted in other studies that some matrices, when reduced to very fine particles, as it is the case for sediment pre-treatment before TD extraction, tend to give rise to packed masses that tend to obstruct the diffusion of compounds to extract. For this reason, some solvent-extraction processes involve the use of dispersing agents (usually sand or diatomaceous earth) in order to prevent aggregation of sample particles, favorizing compounds diffusion and extraction [39].

Diluting with the siliceous diatomaceous earth, the signal of HMW-HCs (>C30) was significantly depleted and LODs were increased which was not a benefit for their quantification. It is probable that the too fine (10–100 µm) and highly porous diatomaceous earth particles could in fact restrict HMW-HCs diffusion through the sediment matrix and so their extractability. In the case of a dilution with the coarser (180–500 µm) non-porous sand, benefits for the quantification could be demonstrated for all the HCs, and more particularly for HMW-HCs. The non-porous sand seemed to contribute to a better thermal diffusion of the HMW-HCs through the diluted matrix. Also, as can be seen in Fig. 3, the slope of the calibration line of C14 n-alkane after dilution by pure sand was quite the same than that obtained from empty tubes, demonstrating low matrix effects after dilution. Table 4 shows actually that the depletion or increase of the signal after dilution was significantly reduced, and the mean absolute value of matrix effects was more acceptable (26.9 %), particularly for HMW-HCs. Some studies discussed about the possibility that extensive fragmentation from coeluting matrix

<footnote>*$C_n-C_m$ means that $C_n$ n-alkane and its isomers are excluded from the integrated interval.</footnote>
<figure><img src="image_8.png" /><figcaption>**Fig. 2.** Chromatograms of the CRM372 certified sediment (compared to the standard solution of C10-C40 *n*-alkanes, in red) A/ extracted by MAE ; B/ extracted by thermodesorption.</figcaption></figure>

components can result in interference and significant loss of sensitivity even in the case of hard ionization techniques such as EI [40]. So HCs signal increase after dilution by non-porous coarse sand might be due to the conjunction of better HCs diffusion and extractability, and to lower negative effects from interferences during MS electron ionization.

Thus, the quantification of the linear alkanes was done from the sand diluted sediment matrix and Table 3 shows the results. The mean value of their sum (according to the considered EC ranges) was in accordance with the values given by the certificate and also with those obtained after MAE extraction. Fig. 4 shows that the certificate gives a very large acceptance interval for each EC range but that the expanded uncertainties (k = 2), in comparison, are lower after MAE or TD extractions. However, it must be noted that quantification was more reproducible using MAE extraction involving the internal calibration method, compared to TD extraction involving a matrix-matched calibration procedure.

Table 3 shows also the quantification done for the unresolved

aliphatics in each EC ranges, after MAE or TD extractions. The values obtained for low or medium molecular weight HCs were comparable with the two extraction methods, even if C12-C16 aliphatics were more quantitatively extracted with TD. So, thermal desorption gives better results than liquid extraction for the more volatile C12-C16 HCs, probably due to the lack of evaporative losses during sampling and processing [30,32]. In contrast, C21-C34 alkanes were less quantitatively extracted with TD, and the very HMW-HCs after C34 could not be detected after TD extraction while some of them could be quantified after MAE extraction. Lastly, Table 3 shows that the value of DRO obtained after TD extraction was in accordance with the certificate. But as noted previously, the value of the TD extracted aliphatics (EPH) was significantly higher than that mentioned in the certificate, but was in accordance with the value obtained after MAE extraction.
<caption>**Table 4**</caption>

Comparison of the slopes of the calibration lines from the standard C10-C40 mixture added to the certified sediments CRM356, CRM372 and CRM372 diluted 2 times by pure sand, with the C10-C40 solution added into an empty TD tube.

<table><thead><tr><th>n-alkanes</th><th>Calibration slope (empty tube)</th><th>Calibration slope (CRM356)</th><th>matrix effect (%)</th><th>Calibration slope (CRM372)</th><th>matrix effect (%)</th><th>Calibration slope (diluted CRM372)</th><th>matrix effect (%)</th></tr></thead><tbody><tr><td>C10</td><td>381,179</td><td>301,017</td><td>-21.0</td><td>288,896</td><td>-24.2</td><td>370,125</td><td>-2.9</td></tr><tr><td>C11</td><td>486,362</td><td>524,031</td><td>7.7</td><td>205,286</td><td>-57.8</td><td>521,585</td><td>7.2</td></tr><tr><td>C12</td><td>609,560</td><td>729,837</td><td>19.7</td><td>238,581</td><td>-60.9</td><td>518,739</td><td>-14.9</td></tr><tr><td>C13</td><td>634,903</td><td>748,463</td><td>17.9</td><td>331,067</td><td>-47.9</td><td>537,897</td><td>-15.3</td></tr><tr><td>C14</td><td>674,274</td><td>787,209</td><td>16.7</td><td>345,223</td><td>-48.8</td><td>764,516</td><td>13.4</td></tr><tr><td>C15</td><td>655,023</td><td>764,633</td><td>16.7</td><td>279,448</td><td>-57.3</td><td>594,615</td><td>-9.2</td></tr><tr><td>C16</td><td>650,775</td><td>818,580</td><td>25.8</td><td>430,615</td><td>-33.8</td><td>617,880</td><td>-5.1</td></tr><tr><td>C17</td><td>694,230</td><td>960,514</td><td>38.4</td><td>406,271</td><td>-41.5</td><td>642,962</td><td>-7.4</td></tr><tr><td>C18</td><td>657,521</td><td>806,465</td><td>22.7</td><td>339,162</td><td>-48.4</td><td>645,672</td><td>-1.8</td></tr><tr><td>C19</td><td>655,300</td><td>763,455</td><td>16.5</td><td>345,459</td><td>-47.3</td><td>645,979</td><td>-1.4</td></tr><tr><td>C20</td><td>657,353</td><td>835,439</td><td>27.1</td><td>360,984</td><td>-45.1</td><td>680,842</td><td>3.6</td></tr><tr><td>C21</td><td>649,853</td><td>717,415</td><td>10.4</td><td>360,247</td><td>-44.6</td><td>667,436</td><td>2.7</td></tr><tr><td>C22</td><td>648,376</td><td>638,968</td><td>-1.5</td><td>357,375</td><td>-44.9</td><td>659,352</td><td>1.7</td></tr><tr><td>C23</td><td>638,580</td><td>645,418</td><td>1.1</td><td>347,920</td><td>-45.5</td><td>673,176</td><td>5.4</td></tr><tr><td>C24</td><td>624,449</td><td>602,013</td><td>-3.6</td><td>347,051</td><td>-44.4</td><td>697,268</td><td>11.7</td></tr><tr><td>C25</td><td>585,910</td><td>518,812</td><td>-11.5</td><td>306,912</td><td>-47.6</td><td>681,718</td><td>16.4</td></tr><tr><td>C26</td><td>563,795</td><td>476,124</td><td>-15.6</td><td>266,490</td><td>-52.7</td><td>670,216</td><td>18.9</td></tr><tr><td>C27</td><td>561,562</td><td>473,141</td><td>-15.7</td><td>232,700</td><td>-58.6</td><td>670,053</td><td>19.3</td></tr><tr><td>C28</td><td>574,681</td><td>369,352</td><td>-35.7</td><td>202,070</td><td>-64.8</td><td>628,080</td><td>9.3</td></tr><tr><td>C29</td><td>588,448</td><td>364,684</td><td>-38.0</td><td>164,111</td><td>-72.1</td><td>496,352</td><td>-15.7</td></tr><tr><td>C30</td><td>610,260</td><td>311,302</td><td>-49.0</td><td>133,752</td><td>-78.1</td><td>471,621</td><td>-22.7</td></tr><tr><td>C31</td><td>602,358</td><td>314,055</td><td>-47.9</td><td>100,513</td><td>-83.3</td><td>424,587</td><td>-29.5</td></tr><tr><td>C32</td><td>601,737</td><td>234,517</td><td>-61.0</td><td>82,988</td><td>-86.2</td><td>410,700</td><td>-31.7</td></tr><tr><td>C33</td><td>560,739</td><td>143,420</td><td>-74.4</td><td>58,479</td><td>-89.6</td><td>377,946</td><td>-32.6</td></tr><tr><td>C34</td><td>542,188</td><td>284,192</td><td>-47.6</td><td>41,904</td><td>-92.3</td><td>343,196</td><td>-36.7</td></tr><tr><td>C35</td><td>521,097</td><td>284,316</td><td>-45.4</td><td>29,402</td><td>-94.4</td><td>309,101</td><td>-40.7</td></tr><tr><td>C36</td><td>518,864</td><td>349,992</td><td>-32.5</td><td>23,392</td><td>-95.5</td><td>271,492</td><td>-47.7</td></tr><tr><td>C37</td><td>462,569</td><td>425,831</td><td>-7.9</td><td>15,177</td><td>-96.7</td><td>234,430</td><td>-49.3</td></tr><tr><td>C38</td><td>438,476</td><td>398,668</td><td>-9.1</td><td>9505</td><td>-97.8</td><td>215,455</td><td>-50.9</td></tr><tr><td>C39</td><td>359,199</td><td>312,225</td><td>-13.1</td><td>5375</td><td>-98.5</td><td>162,894</td><td>-54.7</td></tr><tr><td>C40</td><td>324,807</td><td>261,504</td><td>-19.5</td><td>3411</td><td>-98.9</td><td>137,371</td><td>-57.7</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**Fig. 3.** Calibration lines obtained after addition (ng) of the C14 n-alkane on the empty TD tube, on the TD tube containing 5 mg of CRM372 or the CRM372 diluted twice with pure sand.</figcaption></figure>

## 4. Conclusions

The strategy to optimize a new TD-GC-MS method to thermally desorb and quantify paraffinic HCs from polluted sediments was to introduce directly sediments in TD tubes, without chemical pretreatment, and to discriminate the main influential factors. A DSD+ experimental design allowed discriminating some active factors and their interactions. LMW-HCs had extraction behaviours markedly different from HMW-HCs, due to their great volatility differences. The latter being difficult to extract, a compromise was found considering that HMW-HCs were more quantitatively extracted using a minimum sediment mass (for better mass transfer), a high TD temperature rate and final temperature. OM content was an active factor for TD extraction, favouring the extractability of HCs, possibly by drag-out effect. But it would be

interesting to study the influence of OM nature on the thermal desorption of paraffinic HCs, particularly those containing strong sorbents such as soot or black carbon.

In this paper, MAE was considered as a reference solvent extraction to compare the benefits of TD. This extraction technique was previously optimized via a CCD experimental design to extract quantitatively paraffinic HCs, but also PAHs and PCBs. The ratio between the solvent volume and the sediment mass was crucial to obtain quantitative results. Although matrix effects could decrease more or less the signal, MAE-GC-MS was validated for all the paraffinic HCs with the certified reference sediment CRM372 and appeared repeatable and relatively sensitive. However, it represented high volumes of organic solvent consumption.

Matrix effects from TD were examined considering different real sediments and greatly differed, probably because of the nature and the amount of the OM fraction. When matrix effect was strong, particularly on HMW-HCs signal depletion, an original solution was proposed: solid dilution of the matrix with pure non-porous sand appeared more favourable than a dilution using finest porous diatomaceous earth. The solid/solid dilution allowed a more accurate quantification through a matrix-matched calibration procedure, and the methodology could be validated thanks to the certified CRM372 sediment which gives more specific details on the analysed n-alkanes. The sum of resolved and unresolved HCs gave comparable results between MAE and TD extraction, with an exception of alkanes greater than C30 which were less quantitatively desorbed via TD. However, TD appeared more sensitive than MAE extraction.

Consequently, TD-GC-MS can be used to analyze sediments containing a great range of paraffinic HCs. This analytical approach has the advantage of being fully automated, with few sample preparation and operator intervention, using very low amounts of organic solvent and generating few wastes (sediment mass being 400 times less than that used for MAE).
<figure><img src="image_10.png" /><figcaption>**Fig. 4.** Comparison of the mean values (and their acceptance levels or expanded uncertainties, *k* = 2) of the linear alkanes extracted with TD from the certified CRM372 sediment (diluted twice with pure sand); A/[C12-C16] EC range; B/[C16-C21] EC range; C/[C21-C34] EC range.
Note: [Cn-Cm] means that Cn *n*-alkane and its isomers are excluded from the integrated interval.</figcaption></figure>

### CRediT authorship contribution statement

**Florence Portet-Koltalo:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.
**Kévin Humbert:** Validation, Methodology, Investigation, Formal analysis, Data curation.
**Julie Cosme:** Data curation.
**Maxime Debret:** Project administration, Funding acquisition.
**Christophe Morin:** Visualization, Methodology, Investigation, Formal analysis.
**Steeven Le Gohlisse:** Formal analysis, Data curation.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Data availability

The authors do not have permission to share data.

### Acknowledgments

This work has been partially supported by University of Rouen Normandy, INSA Rouen Normandy. The Centre National de la Recherche Scientifique (CNRS), European Regional Development Fund (ERDF), Labex SynOrg (ANR-11-LABX-0029), the Graduate School for Research XL-Chem (ANR-18-EURE-0020 XL CHEM), and by Region Normandie.

### Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.chroma.2024.464895.

One Table S1 and three Figs. S1–S3 are given in the supplementary materials of this paper.

### References

[1] M.H. Erickson, M. Gueneron, B.T. Jobson, Measuring long chain alkanes in diesel engine exhaust by thermal desorption PTR-MS, Atmos. Meas. Tech. 7 (2014) 225–239, https://doi.org/10.5194/amt-7-225-2014.

[2] F.D. Gallotta, J.H. Christensen, Source identification of petroleum hydrocarbons in soil and sediments from Iguaçu River Watershed. Paraná, Brazil using the CHEMSIC method (CHEMometric analysis of Selected Ion Chromatograms), J. Chromatogr. A 1235 (2012) 149–158, https://doi.org/10.1016/j.chroma.2012.02.041.

[3] A. Imam, S. Kumar Suman, D. Ghosh, P.K. Kanaujia, Analytical approaches used in monitoring the bioremediation of hydrocarbons in petroleum-contaminated soil and sludge, Trends Anal. Chem. 118 (2019) 50–64, https://doi.org/10.1016/j.trac.2019.05.023.

[4] Y.I. Pikovskii, L.A. Korotkov, M.A. Smirnova, R.G. Kovach, Laboratory analytical methods for the determination of the hydrocarbon status of soils (a review), Eurasian Soil Sci. 50 (2017) 1125–1137, https://doi.org/10.1134/S1064229317100076.

[5] Method 1664, Revision B: *n*-hexane extractable material (HEM; oil and grease) and silica gel treated *n*-Hexane Extractable Material (SGT-HEM; non-polar material) by extraction and gravimetry. United States Office of Water, Environmental Protection Agency, 4303 (2010), https://www.epa.gov/method_1664b_2010.

[6] G. Schwartz, E. Ben-Dor, G. Eshel, Quantitative analysis of Total Petroleum Hydrocarbons in soils: comparison between reflectance spectroscopy and solvent extraction by 3 certified laboratories, Appl. Environ. Soil Sci. (2012) 751956, https://doi.org/10.1155/2012/751956.

[7] Y. Sun, J. Ma, G. Yue, S. Liu, H. Liu, Q. Song, B. Wu, Comparisons of four methods for measuring Total Petroleum Hydrocarbons and short-term weathering effect in soils contaminated by crude oil and fuel oils, Water Air Soil Pollut. 232 (2021) 381, https://doi.org/10.1007/s11270-021-05341-7.

[8] H. Van De Weghe, G. Vanermen, J. Gemoets, R. Lookman, D. Bertels, Application of comprehensive two-dimensional gas chromatography for the assessment of oil contaminated soils, J. Chromatogr. A 1137 (2006) 91–100, https://doi.org/10.1016/j.chroma.2006.10.014.

[9] R. Turle, T. Nason, H. Malle, P. Fowlie, Development and implementation of the CCME reference method for the Canada-wide standard for petroleum hydrocarbons (PHC) in soil: a case study, Anal. Bioanal. Chem. 387 (2007) 957–964, https://doi.org/10.1007/s00216-006-0989-x.

[10] A. Zubair, M. Pappoe, L.A. James, K. Hawboldt, Development, optimization, validation and application of faster gas chromatography - flame ionization detector method for the analysis of total petroleum hydrocarbons in contaminated soils, J. Chromatogr. A 1425 (2015) 240–248, https://doi.org/10.1016/j.chroma.2015.10.003.

[11] S. Wang, G. Guo, Z. Yan, G. Lu, Q. Wang, F. Li, The development of a method for the qualitative and quantitative determination of petroleum hydrocarbon components using thin-layer chromatography with flame ionization detection, J. Chromatogr. A 1217 (2010) 368–374, https://doi.org/10.1016/j.chroma.2009.11.022.

[12] O. Lacroix-Andrivet, M. Hubert-Roux, A.L. Mendes Siqueira, Y. Bai, C. Afonso, Comparison of silica and cellulose stationary phases to analyze bitumen by High-Performance Thin-Layer chromatography coupled to laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry, Energy Fuels 34 (2020) 9296–9303, https://doi.org/10.1021/acs.energyfuels.0c00709.

[13] M.P. Seopela, R.I. McCrindle, S. Combrinck, W. Augustyn, Occurrence, distribution, spatio-temporal variability and source identification of *n*-alkanes and polycyclic aromatic hydrocarbons in water and sediment from Loskop dam, South Africa, Water Res. 186 (2020) 116350, https://doi.org/10.1016/jwatres.2020.116350.
[14] E. Saari, P. Perämäki, J. Jalonen, A comparative study of solvent extraction of total petroleum hydrocarbons in soil, Microchim. Acta 158 (2007) 261–268, https://doi.org/10.1007/s00604-006-0718-3.

[15] E. Saari, P. Perämäki, J. Jalonen, Evaluating the impact of extraction and cleanup parameters on the yield of total petroleum hydrocarbons in soil, Anal. Bioanal. Chem. 392 (2008) 1231–1240, https://doi.org/10.1007/s00216-008-2361-9.

[16] K. Hartonen, S. Bäwadt, H.P. Dybdahl, K. Nylund, S. Sporring, H. Lund, F. Oreld, Nordic laboratory intercomparison of supercritical fluid extraction for the determination of total petroleum hydrocarbon, polychlorinated biphenyls and polycyclic aromatic hydrocarbons in soil, J. Chromatogr. A 958 (2002) 239–248, https://doi.org/10.1016/S0021-9673(02)00401-6.

[17] J. Kronholm, J. Kettunen, K. Hartonen, M.L. Riekkola, Pressurised hot water extraction of n-alkanes and Polyaromatic Hydrocarbons in soil and sediment from the oil shale industry district in Estonia, J. Soils Sediments 4 (2004) 107–114, https://doi.org/10.1065/jss2004.03.096.

[18] A.V. Herrera-Herrera, N. Mohamed-Rodríguez, B. Socas-Rodríguez, C. Mallol, Development of a QuEChERS-based method combined with gas chromatography-mass spectrometry for the analysis of alkanes in sediments, Microchem. J. 155 (2020) 104774, https://doi.org/10.1016/j.microc.2020.104774.

[19] A. Serrano, M. Gallego, Continuous microwave-assisted extraction coupled on-line with liquid-liquid extraction: determination of aliphatic hydrocarbons in soil and sediments, J. Chromatogr. A 1104 (2006) 323–330, https://doi.org/10.1016/j.chroma.2005.12.017.

[20] P. Tsytsek, J. Czech, R. Carleer, Thermal extraction coupled with gas chromatography-mass spectrometry as a tool for analysing dioxin surrogates and precursors in fly ash, J. Chromatogr. A 1210 (2008) 212–221, https://doi.org/10.1016/j.chroma.2008.09.071.

[21] L. Corell, S. Armenta, F.A Esteve-Turrillas, Direct and fast determination of polychlorinated biphenyls in contaminated soils and sediments by thermal desorption-gas chromatography-tandem mass spectrometry, J. Chromatogr. A 1610 (2020) 460573, https://doi.org/10.1016/j.chroma.2019.460573.

[22] H. Cheng, J. Mei, J. Xie, Analysis of key volatile compounds and quality properties of tilapia (Oreochromis mossambicus) fillets during cold storage: based on thermal desorption coupled with gas chromatography-mass spectrometry (TD-GC-MS), LWT 184 (2023) 115051, https://doi.org/10.1016/j.lwt.2023.115051.

[23] M.S. Popov, N.V. Ul'yanovskii, D.S. Kosyakov, Direct quantification of 1,1-dimethylhydrazine transformation products in sandy soil by thermal desorption gas chromatography – Tandem mass spectrometry, Microchem. J. 197 (2024) 109833, https://doi.org/10.1016/j.microc.2023.109833.

[24] A. Sonnette, M. Millet, R. Ocampo, L. Alleman, P. Coddeville, Tenax-TA spiking approach of thermal desorption coupled to GC-MSMS for the quantification of PAHs in indoor air and dust, Polycycl. Aromat. Compd. 37 (2017) 170–177, https://doi.org/10.1080/10406638.2016.1253594.

[25] J. Lu, Y. Li, J. Li, S. Jing, T. An, H. Luo, C. Ma, H. Wang, Q. Fu, C. Huang, An online method for monitoring atmospheric intermediate volatile organic compounds with a thermal desorption-gas chromatography/mass spectrometry, J. Chromatogr. A 1677 (2022) 463299, https://doi.org/10.1016/j.chroma.2022.463299.

[26] M. Bates, P. Bruno, M. Caputi, M. Caselli, G. de Gennaro, M. Tutino, Analysis of polycyclic aromatic hydrocarbons (PAHs) in airborne particles by direct sample introduction thermal desorption GC/MS, Atmos. Environ. 42 (2008) 6144–6151, https://doi.org/10.1016/j.atmosenv.2008.03.050.

[27] S.S. Ho, J.Z. Yu, In-injection port thermal desorption and subsequent gas chromatography-mass spectrometric analysis of polycyclic aromatic hydrocarbons and n-alkanes in atmospheric aerosol samples, J. Chromatogr. A 1059 (2004) 121–129, https://doi.org/10.1016/j.chroma.2004.10.013.

[28] L.C. Ding, F. Ke, D.K.W. Wang, T. Dann, C.C. Austin, A new direct thermal desorption-GC/MS method: organic speciation of ambient particulate matter collected in Golden, BC, Atmos. Environ. 43 (2009) 4894–4902, https://doi.org/10.1016/j.atmosenv.2009.07.016.

[29] M. Wang, R.J. Huang, J. Cao, W. Dai, J. Zhou, C. Lin, H. Ni, J. Duan, T. Wang, Y. Chen, Y. Li, Q. Chen, I. El Haddad, T. Hoffmann, Determination of n-alkanes, polycyclic aromatic hydrocarbons and hopanes in atmospheric aerosol: evaluation and comparison of thermal desorption GC-MS and solvent extraction GC-MS approaches, Atmos. Meas. Tech. 12 (2019) 4779–4789, https://doi.org/10.5194/amt-12-4779-2019.

[30] R.M. Flores, E. Mertoglu, Optimization of a thermal desorption-gas chromatography/mass spectrometry method for characterization of semi-volatile organic compounds in high time resolved PM2.5, Atmos. Pollut. Res. 11 (2020) 619–629, https://doi.org/10.1016/j.apr.2019.12.016.

[31] R.J. Lavrich, M.D. Hays, Validation studies of thermal extraction-GC/MS applied to source emissions aerosols. 1. Semivolatile analyte-nonvolatile matrix interactions, Anal. Chem. 79 (2007) 3635–3645, https://doi.org/10.1021/ac0623282.

[32] P. Faure, P. Landais, Rapid contamination screening of river sediments by flash pyrolysis-gas chromatography-mass spectrometry (PyGC-MS) and thermodesorption GC-MS (TdGC-MS), J. Anal. Appl. Pyrolysis 57 (2000) 187–202, https://doi.org/10.1016/S0165-2370(00)00011-X.

[33] P.P. Falciglia, M.G. Giustra, F.G.A. Vagliasindi, Low-temperature thermal desorption of diesel polluted soil: influence of temperature and soil texture on contaminant removal kinetics, J. Hazard. Mater. 185 (2011) 392–400, https://doi.org/10.1016/j.jhazmat.2010.09.046.

[34] T. Gardes, F. Portet-Koltalo, M. Debret, K. Humbert, R. Levaillant, M. Simon, Y. Copard, Temporal trends, sources and relationships between sediment characteristics and polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) in sediment cores from the major Seine estuary tributary, France, Appl. Geochem. 122 (2020) 104749, https://doi.org/10.1016/j.apgeochem.2020.104749.

[35] K. Humbert, M. Debret, C. Morin, J. Cosme, F. Portet-Koltalo, Direct thermal desorption-gas chromatography-tandem mass spectrometry versus microwave assisted extraction and GC-MS for the simultaneous analysis of polyaromatic hydrocarbons (PAHs, PCBs) from sediments, Talanta 250 (2022) 123735, https://doi.org/10.1016/j.talanta.2022.123735.

[36] C. Biache, C. Lorgeoux, A. Saada, P. Faure, Behavior of PAH/mineral associations during thermodesorption: impact for the determination of mineral retention properties towards PAHs, Anal. Bioanal. Chem. 407 (2015) 3509–6516, https://doi.org/10.1007/S00216-015-8547-z.

[37] T.V. Cheshkova, V.P. Sergun, E.Y. Kovalenko, N.N. Gerasimova, T.A. Sagachenko, R.S. Min, Resins and asphaltenes of light and heavy oils: their composition and structure, Energy Fuels 33 (2019) 7971–7982, https://doi.org/10.1021/acs.energyfuels.9b00285.

[38] B.L. van Drooge, I. Nikolova, P. Pérez Ballesta, Thermal desorption gas chromatography-mass spectrometry as an enhanced method for the quantification of polycyclic aromatic hydrocarbons from ambient air particulate matter, J. Chromatogr. A 1216 (2009) 4030–4039, https://doi.org/10.1016/j.chroma.2009.02.043.

[39] L. Barp, A.M. Visnjevec, S. Moret, Pressurized Liquid Extraction: a powerful tool to implement extraction and purification of food contaminants, Foods 12 (2023) 2017–2042, https://doi.org/10.3390/foods12102017.

[40] M.L. Williams, A.A. Olomukoro, R.V. Emmons, N.H. Godage, E. Dionfriddo, Matrix effects demystified: strategies for resolving challenges in analytical separations of complex samples, J. Sep. Sci. 46 (2023) 2300571, https://doi.org/10.1002/jssc.202300571.