Trace element quantification in light fuels by total reflection X-ray fluorescence spectrometry

Trace element quantification in light fuels by total reflection X-ray fluorescence spectrometry

Journal Pre-proof Trace element quantification in light fuels by total reflection Xray fluorescence spectrometry A. Cinosi, G. Siviero, D. Monticelli...

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Journal Pre-proof Trace element quantification in light fuels by total reflection Xray fluorescence spectrometry

A. Cinosi, G. Siviero, D. Monticelli, R. Furian PII:

S0584-8547(19)30507-5

DOI:

https://doi.org/10.1016/j.sab.2019.105749

Reference:

SAB 105749

To appear in:

Spectrochimica Acta Part B: Atomic Spectroscopy

Received date:

24 October 2019

Revised date:

12 December 2019

Accepted date:

12 December 2019

Please cite this article as: A. Cinosi, G. Siviero, D. Monticelli, et al., Trace element quantification in light fuels by total reflection X-ray fluorescence spectrometry, Spectrochimica Acta Part B: Atomic Spectroscopy(2019), https://doi.org/10.1016/ j.sab.2019.105749

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© 2019 Published by Elsevier.

Journal Pre-proof Trace element quantification in light fuels by total reflection X-ray fluorescence spectrometry A. Cinosia, G. Sivieroa*, D. Monticellib, R. Furianc a

GNR s.r.l., via Torino 7, 28010 Agrate Conturbia (NO), Italy

b

22100 Como, Italy c

AmSpec Italia S.r.l, Via Ghebba 105, Oriago di Mira (VE), Italy

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*Corresponding author: [email protected] Abstract

The presence of elemental impurities in fuels is a key topic with important consequences: they may

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both adversely affect the performances of engines and contribute to the contamination of the environment, primarily air, but on the long term also waters and soils.

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Accordingly, the determination of trace elements in fuels is of the utmost importance in several

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fields, ranging from quality control to regulatory issues (e.g. control of emissions). Traditionally, atomic spectrometric techniques have been employed to this aim: these techniques typically require a pretreatment step involving either sulfate ashing, microwave digestion or dilution in

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solvents.

Here we propose a fast, direct and sensitive method for the quantification of V, Cr, Mn, Fe, Co, Ni,

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Cu, Zn, As and Pb at trace level in light and middle distillates, namely gasoline, racing and jet fuel,

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by Total Reflection X-Ray Fluorescence (TXRF). A simple sample treatment procedure, based on on-site enrichment, allowed to achieve limits of detection below 1 ng/g. The quantification method by internal standard was assessed and validated by recovery tests: its optimization and limits will be presented and discussed.

Keywords: TXRF, gasoline, jet fuel, metal traces, on-site enrichment.

1. Introduction Fuels are blends of several hydrocarbons resulting from distillation at different temperatures of crude oil: on average, about 50% in volume of a U.S. barrel was converted into gasoline and jet fuel in 2018. Considering a worldwide daily consumption of 98 million barrels, it is the most traded commodity in the world[1]. The quality of the raw material (crude oil) and of the final product is clearly of the utmost importance, and the level of trace elements is one of the quality criteria set by the petrochemical 1

Journal Pre-proof industry[2]. Trace elements in fuels may originate from several sources[3]. They may have a natural origin, i.e. the original crude oil: usually, the most abundant trace elements in petroleum are sulfur, with concentrations ranging from 0.5 mg/g to 50 mg/g, followed by vanadium and nickel, with concentration ranging from ng/g to hundreds of g/g. Contaminants may also be accidentally introduced together with additives (Pb, Mn, Al), be unintentionally present as catalyst residues (Ni, Pd, Pt) or as corrosion products during processing, storage and transport (Fe, Cu, Zn). The presence of trace elements in petrochemical raw materials, intermediate and refined products can be detrimental throughout their lifetime, from refining to combustion. V and Ni are harmful for zeolite catalysts used in catalytic cracking, the process in which high boiling point products are

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converted into more valuable lighter ones (gasoline), while S, As and Pb negatively affect Pt used for catalytic reforming, the process aimed at upgrading low-octane naphtha to the high-octane material suitable for blending into motor gasoline fuel[2].

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As far as environmental impact is concerned, lead, manganese and sulfur are twofold problematic:

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they both reduce the catalytic converter performances aboard vehicles, thus increasing the amount of toxic NO x and CO gases from the exhaust, and constitute a direct threat, e.g. sulfur producing SO2. Their maximum amount in gasoline and diesel is regulated: for example, European Union set

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10 g/g for S, 5 mg/L for Pb and 2 mg/L for Mn[4].

Moreover, metals such as Fe, Cu, Zn and Pb affect the thermal stability of light and middle

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distillates, by catalyzing oxidative reactions of compounds at g/g level, e.g. nitrogen and sulfur-

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containing species, organic acids and reactive olefins, which eventually turn into solid deposit, called gum. Fuel decomposition and gum accumulation on engine parts negatively affect its

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performance. According to literature[5], even concentrations below 50 ng/g can be highly detrimental, especially for jet fuel: in fact, this is also used as a heat-exchange medium between the airframe and the engine, which further speeds up the temperature-dependent oxidation reaction. The deposition of gum may reduce the fuel flow by clogging filters, induce thermal inhomogeneity in the combustion chamber by affecting the fuel injector nozzles and compromise the aircraft meters reading and thus the engine control[6]. For example, U.S. Navy has been trying to fix contamination issues, after investigations showed that JP-5 jet fuel aboard aircraft carriers was contaminated with copper at levels as high as 1 g/g, due to uptake from the copper-nickel alloy piping system[7]. Resulting additional maintenance costs have been projected at $1 billion annually, a figure that has stimulated keen interest in devising a solution[8]. In order to reduce the metal catalytic activity, chelating agents, called metal deactivator additives (MDA), have been developed over the years: however, there exists a fuel-dependent maximum allowable limit of MDA over which detrimental effects are expected. A robust analytical method that yields reliable trace element concentrations in the ng/g range is accordingly actively sought.

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Journal Pre-proof Currently, trace element quantification in light and middle distillates is performed by Inductively Coupled Plasma Atomic Emission Spectroscopy and Mass Spectrometry (ICP-AES, ICP-MS)[9], Electrothermal Atomic Absorption Spectroscopy (ETAAS)[10] and X-Ray Fluorescence (XRF)[11]. Each of them is supported by an ASTM test method covering a different number of analytes, with ICP-AES and ICP-MS allowing the quantification of a large number of elements[12,13]. Sample treatment includes dilution of the distillate in xylene, or other suitable solvent, followed by direct aspiration into the plasma: besides the need of dedicated instrument calibrations, the presence of volatile organic solvents is critical for plasma stability, signal drift due to cone clogging and carbonbased polyatomic interferences[3]. Total Reflection X-Ray Fluorescence (TXRF) has been previously applied to gasoline and diesel by

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Pasti et al.[14], who could quantify S and Pb at the g/g level, with limits of detection (LOD) of 50

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g/g and 9 ng/g, respectively. Zhang et al.[15] focused on the detection of S, Mn, Fe, Cu, Pb in similar matrices after microwave-assisted digestion to prove TXRF suitability for meeting Chinese

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regulatory limits in the range 1-10 mg/L. Their LOD ranged from 4 to 200 ng/g.

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The aim of the present work is to set a reliable TXRF method involving a fast sample treatment process for the detection of trace elements at the ng/g level, with special emphasis on metals

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catalyzing gum formation in engines. The method exploits on-site enrichment, previously proposed by some of the authors in petrochemical products[16] and spirits[17], in order to achieve the

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2. Materials and Methods

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required LOD values.

2.1 Xylene blank spiking and production fuels Standard reference materials for trace element concentrations in light fuels are not available and a spiking strategy was used to validate the method. Xylene (VWR xylene, mixture of isomers, ≥98.5%

R NORM P R®

C

R

. Ph. E .

analytical reagent) was chosen as the spiked matrix because it is a solvent typically used in dilution procedures for fuel[3], with the number of carbon atoms per hydrocarbon molecule in the range spanned by gasoline and kerosene. Recovery tests for the elements of interest were performed at two different concentration levels, representing possible real cases, namely 85 ng/g and 21 ng/g. These trace element concentrations were obtained by spiking xylene with the metallo-organic standard solution VHG V21+K wear metals standard at 900 µg/g in hydrocarbon oil, comprising Ag, Al, B, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Pb, Si, Sn, Ti, V, Zn. Recovery for arsenic and cobalt was determined employing an LGC Custom metallo-organic standard VHG XLGC 1520 with As, Bi, Ce, Co, In, Li, Sb, Sr, W, Zr at 850 µg/g in mineral oil. 3

Journal Pre-proof Production fuels were provided by AmSpec Italia: two standard gasoline samples (S13, S14), two racing gasoline samples (RS5, RS21) and four jet fuels (S9, S10, S11, A1).

2.2 Spectrometer configuration A benchtop TXRF spectrometer (Horizon, G.N.R. Italy), equipped with a 600 W X-Ray source monochromatized to Mo-K (17.44 keV) by a W/Si multilayer, was used to excite the fluorescence signal from the sample. A 20 mm 2 Silicon Drift Detector from KETEK GmbH, equipped with a 900 nm graphene window, collimator and polymeric foil, was placed about 2 mm above the sample to

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collect the fluorescence spectrum.

Analysis software featured automatic background and spectrum identification and fitting; quantification was performed by the internal standard method and relative sensitivity curves. In

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contrast to traditional analytical techniques for trace element identification, no matrix-matched

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2.3. Sample preparation and acquisition

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calibration curves are required. Outlier detection was performed by using modified Z-score[18].

Sample preparation steps followed ISO/TS 18507[19]: the sample was spiked with metallo-organic gallium at a concentration of about 20 ng/g in a 30 mL borosilicate glass vial with phenolic screw

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cap. The internal standard had been obtained previously by dissolving the adequate mass of G ( ) β-diketone (Alfa Aesar) in N-methyl pyrrolidone (Fluka). After homogenization, a variable

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number (three to thirty) of 8 L aliquots were pipetted onto a siliconized quartz reflector (Serva

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Silicone solution) and dried between 100 °C and 150° C on a hot plate. Despite the fact that the siliconization process usually aims at obtaining a hydrophobic surface, it was found to be slightly helpful with fuels too, by limiting the spread of the deposited droplet in comparison with the bare reflector. As regards the cleanliness of reflectors, our standard procedure involving mechanical pre-cleaning with the aid of a degreaser followed by several washes at 90° C in ultrapure water (Carlo Erba, Ana y

G

≤0. μ /

) with a volume fraction of 5% HNO3 (Merck pro analysis

65%) was applied. Then, blank reflector measurements were performed just before the depositions. The subsequent depositions of small (8 µL) sample aliquots allowed the on-site enrichment of the analytes in view of the expected very low element concentrations (this procedure was already reported by some of the authors[16] ). In order to push the method to its limit, the integration time was set at 1000 s per specimen, with a cumulative deposited volume of 240 L, corresponding to an enrichment factor of 30. See section 3.1 for a justification for this choice. Taking into account that non-volatile organic matter accumulates progressively on the quartz reflector with repeated depositions, Atmospheric Pressure-Vapor Phase Decomposition (AP4

Journal Pre-proof VPD)[20] in HNO3 vapor was also performed, in those cases in which the organic deposit was detrimental to detection capabilities, i.e. large Compton scattering and background signal. Reflectors were directly placed at the bottom edges of a large beaker, and a smaller one filled with a HNO3+H2O2 (3:1) mixture was placed in the center. The reaction environment was then isolated with a watch glass as a lid before moving the assembly onto a hot plate.

3. Results and discussion

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3.1 Recovery tests and LOD

Recovery tests were performed to assess the accuracy and precision of the proposed method. As a first step, xylene blank measurements were performed after 40 enrichments and showed traces

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of Cr, Ni, Cu, Zn below 1 ng/g and Fe below 4 ng/g.

Recovery test at 85 ng/g after 10 depositions and 21 ng/g after 30 depositions showed that the

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majority of elements of interest, i.e. Cr, Fe, Ni, Cu, Zn, As, Pb, were within the range from 90% to

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110%. Only V, Mn and Co were slightly out at lower concentration. Nevertheless, they were all within the range expected for this concentration by the guidelines of the Association of Official Analytical Chemists (AOAC)[21], i.e. from 60% to 115% for 10 ng/g level.

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Corresponding LODs are about 1 ng/g or below. These low values, achieved through 30 deposition on-site enrichment, can be justified by equation 1a, which recasts the usual expression of LOD for

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analyte x as three times the standard deviation of the background signal (Nback ) equivalent

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concentration[22,23]. The latter is calculated through the sensitivity (Sx ) of the analyte x (equation 1b)[24], i.e. the ratio between the net intensity (Nx ) of the peak representing the analyte and its concentration (c x ), which are determined according to the internal standard method of quantification. Moreover, it is possible to make the time (t) dependence explicit by using the count rate (Ri=Ni/t), where i=x or back. ( ⁄

)⁄(

√ ⁄

) (

(

)⁄(

√ ⁄ )



)

( √

⁄ ) ⁄( ⁄

⁄ )

(

)

(

)

Given that concentration (c x ), background (Rback ) and exciting beam (R 0) count rate, geometry factor (G) and fluorescence efficiency (Ex * ) for analyte x were fixed, the adjustable parameters for LOD improvement were the deposited mass per unit area (m/A) and the acquisition time (t) [17]. A sound value for the latter was estimated by collecting spectra of test sample at 21 ng/g with an average enrichment level, 80 L, well within the thin film approximation threshold[24]. Then, 5

Journal Pre-proof several enrichment steps were performed in order to find the maximum one for which the approximation was still valid[16]. Given the linear dependence of LOD on the reciprocal of deposited mass, a simple fit can provide the slope of the line to estimate the required mass for achieving the desired detection capabilities. Figure 1A reports the spectra at 21 ng/g at three different enrichment levels, showing the progressive increase of peak heights, while the background remains almost the same: this is the reason why there is a progressive reduction of LOD with increasing deposited volume for analytes of interest and internal standard, as shown in Figure 1B. It is apparent that after one batch of 10 depositions the method can already fit the purpose of detecting trace elements at 10 ng/g, assuming the limit of quantification (LOQ) as three times the LOD. Moreover, a twofold reduction is achieved by doubling the enrichment level: in this

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way, according to equation 1a, the same 10 ng/g LOQ could be reached by reducing the counting time by a factor 4, being the time dependence under square root. On the other hand, the total analysis time tm comprises both sample preparation and acquisition ones (equation 2). The

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previous is given by the product of the number of deposition batches (nd) and the drying time per single deposition batch (td) required for a given LOD, while the latter is a function of the number of

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specimens (ns ), the acquisition time (t) for a single deposition batch and nd. It must be pointed out

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that ns specimens can be dried together within the t d time and that a single deposition batch may be constituted by more than one deposition (or enrichment). Each deposition may require up to three minutes for drying, so that there is a threshold value beyond which the contribution of the

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sample preparation time outweighs the reduction in the acquisition one. This threshold (nd*) can be found by equating the total analysis time (equation 2) for nd* with the one for nd=1 (equation 3). For

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example, assuming td=600 s for a three-enrichment sample deposition batch, a triplicate

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measurement (ns =3) and acquisition time t=1000 s, the threshold value is about 6 times the starting enrichment level, i.e. 6 three-enrichment batches. Moreover, an optimum number of deposition batches (ndm ) for a given LOD can be estimated by differentiating equation 2 with respect to nd (equation 4): taking the previous example parameters, the optimum number of threeenrichment batches is 2.

In order to further appreciate the flexibility of the method, the LOD for analytes at higher concentration (85 ng/g) after only 3 depositions is reported too: it is apparent that, given the increased dried mass per single deposition, the detection capabilities compare to those at larger enrichment level for a lower concentration.



(

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Figure 1. (A): portion of spectra for artificial sample at 21 ng/g (V21+K, Ga internal standard) at three different enrichment levels. (B): LOD variation as a function of the enrichment level. The values for a larger concentration are reported too. The dashed line at 1 ng/g is a reference for the eye.

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As is well known[22], LOD improves with atomic number (Z) for the same fluorescence line series, K in this case. Lead is an exception, because with the chosen excitation energy only L lines are accessible. For comparison, literature values for ICP-AES[25], ICP-MS[25–27] and ETAAS[10] are reported in Table 1:

for these LOD is determined as three times the standard deviation of repeated blank

measurements, usually xylene. The values found in this work are between those of the ICP-MS and the ICP-AES equipped with an ultrasonic nebulizer. The most relevant work using TXRF[15] determined LODs by spiking isooctane with single element standards in oil: however, their values

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are 3 to 50 times larger.

LOD (ng/g)

0.94 0.75 0.49 0.29 0.34 0.28 0.21 0.20 0.22 0.32

0.98 0.65 0.45 0.29 0.26 0.25 0.20 0.18 0.15 0.33

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1.11 0.77 0.51 0.48 0.44 0.37 0.35 0.31 0.10 0.41

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Jet fuel

ICP-AES (+USN) 9 (2.4) 15 (2.4) 2.4 (0.3) 9 (0.3) 15 (2.4) 15 (2.4) 15 (2.4) 6 (0.3) 150 (15)

ICP-MS

ETAAS

TXRF

1.2

9 26

0.7

1

0.18 0.03

0.18 0.15 48 4 0.01

5

LODs for the elements of interest at 21 ng/g in xylene and real fuels (median values) after

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Table 1.

Gasoline

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V Cr Mn Fe Co Ni Cu Zn As Pb

Literature

Racing gasoline 1.80 1.26 1.00 0.57 0.68 0.33 0.38 0.33 0.33 0.52

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This w ork Standards in xylene

depositing 240 L. For comparison literature data grouped by analytical technique are reported: ICP-

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AES[25], ICP-MS[25–27], ETAAS[10] and TXRF[15]. USN: ultrasonic nebulizer.

Despite the possibility of getting rid of interfering Ar K-lines by means of helium flux, cadmium was not considered, because its available fluorescence lines (L) have a low sensitivity and may be hidden by sulfur K-lines, especially in jet fuels, where this element ranges between 500 and 1000 g/g[6]. Sulfur was not considered because it might have been in volatile form[14], which is not compatible with the chosen preparation method. In general, when on-site enrichment is performed, elements with characteristic emission lines below 4 keV may be more affected by matrix effects, due to the increased deposited mass[24]. Taking into account that Fe, Cu, Zn and Pb are the most detrimental to engine performance even at very low levels, importance was given more to the reduction of their LOD than to the fulfillment of the thin film approximation for low emission energies.

3.2 Gasoline and jet fuel samples 8

Journal Pre-proof Preliminary experiments were performed to assess if real samples could benefit from vapor phase decomposition in terms of detection capabilities. Contrary to xylene multiple depositions, nonnegligible amounts of non-volatile species are expected in real samples as they are a mixture of hydrocarbons covering a wide range of boiling points: fractions with boiling points over 200 °C are commonly found in jet fuels[6]. Accordingly, gasoline and jet fuel samples were deposited and dried at temperatures of 150 or 120 °C, depending on whether AP-VPD treatment was adopted or not. Actually, its effectiveness was moderate for both petroleum distillates, with a reduction in LOD by a factor of two in the best cases: this can be ascribed to the incomplete decomposition of the heavy organic fraction by VPD. Nevertheless, LODs calculated for real fuels are between half and twice those calculated during the recovery test (Table 1) and comparable among them, with those

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calculated in racing gasoline slightly higher. The reason could be the presence of additives to boost fuel characteristics. The spectrum for a racing gasoline sample is reported in Figure 2, where Fe, Cu and Zn peaks are clearly visible. Results for analytes with concentration above the

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detection limit are reported in Figure 3, together with data range from the limited number of available literature data[5,26–28]. The elements present in largest amounts and with the highest

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variability are Fe, Zn, Cu, as reported in reference publications. On the other hand, no analyte of

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interest was found at concentrations beyond 100 ng/g in this work. In order to further assess the accuracy of the method, a recovery test was performed by adding a known amount of V21+K standard to one of the analyzed fuels, A1, which was then measured following the same procedure

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of the original sample. The additional amount of standard was chosen as two times the largest concentration value for the analytes of interest in A1, i.e. 33 ng/g. Results are reported in Table 2:

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the recovery values range between 78% to 113%, being thus compatible with those found in

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section 3.1 for standards diluted in xylene.

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Figure 2. Example spectrum of racing gasoline after 30 depositions and AP-VPD at 150° C, acquisition time

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1000 s. Note that the y-axis is in log scale.

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Figure 3. Results with corresponding standard deviation (3 replicates) for analytes in gasoline (A) and jet fuel (B) samples. Ranges in ng/g from literature[5,26–28] are in square brackets. Note that the y-axis is broken for clarity.

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V Cr Mn Fe Ni Cu Zn Pb

Table 2.

Concentration (ng/g) A1 A1+V21K <1 25±1 <0.6 35±2 <0.4 35±4 16±3 48±3 0.6±0.1 33±2 16±3 49±4 5.8±0.8 34±1 <0.3 37±5

Recovery (%) 78±1 107±6 107±13 96±12 97±6 101±15 86±4 112±16

Results and recovery values with standard deviation (3 replicates) for A1 sample spiked with 33

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ng/g of V21+K standard.

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As far as repeatability is concerned, the Relative Percentage Standard Deviation (RSD%) for the triplicate measurements of the analytes in each sample was evaluated according to AOAC

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guidelines based on the Horwitz equation [21]: 84% of the data are below 30%, the threshold value for concentrations from 1 to 10 ng/g. The dispersion of data may be ascribed to the sample

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preparation: in fact, the enrichment process requires prolonged deposition and drying time, up to one hour, which may result in an increased probability of external contamination. Moreover, taking

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into account that the RSD% values for test samples in xylene (section 3.1) are below 10%, there may be hint of an occurrence of metal phases as particulate, which affects the sample

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homogeneity. Furthermore, it cannot be excluded that there is a dependence on the amount of non-volatile species in the matrix and how it dries on the siliconized surface of the reflector,

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considering that real fuels are blends of hydrocarbons. For comparison, ICP-MS and ETAAS RSD literature[9,26]. 4. Conclusions

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values for samples with similar trace element concentration are reported to be below 10% in the

In this work the detection capabilities of TXRF for trace elements in light and middle petroleum distillates were assessed: by simply adding the metallo-organic internal standard and performing on-site enrichment, LOD values below 1 ng/g were achieved, thus showing its suitability for a demanding task in processing and transportation. Determined concentrations are consistent with those reported in the available literature using ICP-MS and ICP-AES, with LODs closer to the previous than to the latter. Moreover, the quantification by using relative sensitivities, obtained in aqueous matrix, and the agreement between recoveries for trace elements in both xylene and real fuel provide a proof of negligible matrix effect, which in turn shows the validity of thin film approximation, i.e. the fundamental assumption of the TXRF technique. The peculiar sample preparation method exploited in this work can be tuned, depending on the desired detection limits and available acquisition time, provided that the deposited amount fulfills the thin film approximation requirement. As an example, a simple threefold enrichment (sample 12

Journal Pre-proof preparation time of 10 minutes) enables the detection of V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As and Pb at the 10 ng/g level. Furthermore, it requires only a balance, a micropipette and a hotplate, making the proposed method perfectly suitable for application in production and storage sites as well as in end user facilities. Sample preparation time, in case extreme detection capabilities are not required, compares very favorably with sulfate ashing and does not show big differences with respect to solvent dilution. Regarding total analysis time, a reduction, keeping the detection limit constant, is possible by simply increasing the deposited mass amount and in turn shortening the acquisition time. Moreover, the method allows to estimate both an optimum number of depositions to minimize the total analysis time and a threshold value beyond which there is a detrimental increase of it, with respect to the starting deposited mass one.

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On the other hand, repeatability seems not to compare with atomic spectrometric methods, probably because of dishomogeneity in the deposition process. Scanning Electron Microscope (SEM) examinations would be helpful in tackling this issue together with the drop in deposition time and the minimization of h

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ontribution by automation, which is still of concern to TXRF

users.

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Moreover, different sample treatment methods, e.g. digestion and extraction, should be

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investigated in order to understand their influence on detection capabilities, repeatability and

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possibility of extending the number of analytes of interest.

Acknowledgements

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The authors are grateful to KETEK GmbH for the loan of the Silicon Drift detector and related

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quantification in light fuels by total reflection X-ray

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V,Cr, Mn, Fe, Co, Ni, Cu, Zn, As and Pb were detected in light fuels by TXRF



On-site enrichment allowed to get detection limits below 1 ng/g



Detection limit can be controlled by tuning acquisition time and enrichment level



TXRF efficiently combines easy detection and minimal sample preparation

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Journal Pre-proof Author Statement Contributor Roles Taxonomy A. Cinosi: Conceptualization, Investigation, Methodology, Supervision; G. Siviero: Investigation, Methodology, Formal analysis, Roles/Writing – original draft; Writing – review & editing, Visualization; D. Monticelli: Methodology, Validation, Writing – review & editing;

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R. Furian: Conceptualization, Resources;

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Journal Pre-proof Declaration of interests ☒ 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.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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