Christophe Dutouquet
email: christophe.dutouquet@ineris.fr

G Wattieaux

L Meyer

E Frejafon

L Boufendi

Determination of the elemental composition of micrometric and submicrometric particles levitating in a low pressure RF (Radio-Frequency) plasma discharge using LIBS (Laser-Induced Breakdown Spectroscopy)

Keywords: agglomerates of composite nanoparticles, RF discharge cell, LIBS (Laser-Induced Breakdown Spectroscopy), reduced pressure, particles in levitation, particle trap

The LIBS (Laser-Induced Breakdown Spectroscopy) technique has shown its potential in many fields of applications including that of aerosol analysis. The latter is usually carried out on the particle flow, thereby allowing quantitative detection in various experimental conditions such as ambient air analysis or exhaust stack monitoring, to name but a few. A possible alternative method for particle analysis has been experimented combining a low pressure RF (Radio Frequency) plasma discharge with the LIBS technique. Such approach has two peculiar features in comparison to usual LIBS analysis. First, the particles injected in the RF plasma discharge are trapped in levitation. Second, the analysis is performed at a reduced pressure of around 1mBar.

LIBS detection at such low pressure has this peculiar that particle vaporization is assumed to be achieved through direct laser particle interaction whereas it is caused by a laser-induced plasma ignited in the gas at atmospheric pressure. The use of such particle trap could allow improving particle sampling, making organic particle analysis possible (by using an inert gas for RF plasma ignition) and even (depending on the pressure) obtaining a better signal to noise ratio. Detection of the elements nanoparticle agglomerates were made of following their injection in the RF discharge has demonstrated the feasibility of such approach. Future experiments are intended to explore its potentialities when tackling issues such as process control or ambient air monitoring.

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Introduction

Nanotechnology is a dynamic, growing field of activity in many industrialized countries. Considerable investments have been made in research and development in this fast-developing industry said to be that of the 21 st century. Expectations are high to see rising a new generation of products with remarkable features and numerous new applications. Many economical sectors are to be impacted, of which areas related to materials, pharmaceutical and electronics to name but those the most frequently cited. Everyday life may be affected in many ways as well [START_REF] Park | Current and future applications of nanotechnology[END_REF][START_REF] Ostiguy | Engineered Nanoparticles, current knowledge about OHS risks and prevention measures[END_REF].

Elaborating nanostructured materials with advanced properties, calls for nanoparticle production processes. Particles were indeed demonstrated to gain specific properties when designed at nanometric scale displaying for instance unusual strength, conductivities or optical properties. These are usually incorporated, mixed with other compound so that the resulting material gain enhanced functionalities. To take but a few examples, engineered nanoparticles of titanium dioxide are used for self-cleaning windows. Nanoparticles of silver are embedded in medical dressings whereas those of SiC are employed to design high temperature resistant materials in the nuclear industry.

Along with the rise of nanoparticle production grows the need for nanometrology. Control of nanoparticle properties and functionalities entails the development of adapted new instruments. Furthermore, though research remains active to keep production processes reliable and to assure constant quality production, disruptions that may occur while synthesizing ENPs (Engineered nanoparticles) and affect the resulting lots are not to be underestimated. Possible losses of ENP batches caused by sudden diversion from the usual operating conditions resulting in the ENPs not displaying expected properties and therefore useless for targeted applications clearly highlight the need for on-line monitoring instruments.

There exist various manufacturing processes leading to nanoparticle production. Among these, processes allowing continuous synthesis such as laser pyrolysis arouse interest for production at industrial scale.

Details on this technique are not described here for they were presented in a previous paper [START_REF] Amodeo | On-line monitoring of composite nanoparticles synthesized in a pre-industrial laser pyrolysis reactor using Laser-Induced Breakdown Spectroscopy[END_REF]. This method is deemed very promising for nanocomposite particle synthesis owing to its particular qualities. Properties of these nanoparticles strongly depend on the relative abundance of each element (or stoichiometry) they are made of.

Though laser pyrolysis is known to assure a good control of compound stoichiometry, diversion from the expected chemical composition is not to be excluded, as emphasized above. On-line Monitoring of composite nanoparticle synthesizing seems therefore necessary.

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The LIBS technique is considered as a potential candidate to deal with such issues [START_REF] Radziemski | Time-resolved laser-induced breakdown spectrometry of aerosols[END_REF][START_REF] Hahn | Detection and analysis of aerosol particles by laser-induced breakdown spectroscopy[END_REF][START_REF] Mukherjee | Quantitative laser-induced breakdown spectroscopy for aerosols via internal calibration: Application to the oxidative coating of aluminum nanoparticles[END_REF][START_REF] Hahn | Laser-Induced Breakdown Spectroscopy (LIBS), Part I: Review of Basic Diagnostics and Plasma-Particle Interactions:Still-Challenging Issues Within the Analytical Plasma Community[END_REF]. LIBS consists in focusing a powerful laser pulse on a material (solid, liquid, gas, nanoparticle flow) whose elemental composition is to be determined. The strong heating of the sample at the focusing spot leads to the ignition of a plasma. Simultaneous detection of all the elements the analyzed material is made of is then achieved through optical emission spectroscopy. Being all optical, LIBS is not intrusive and remote or stand-off analyses are even possible. Besides, samples do almost not need preparation. The aforementioned features do make LIBS a promising analytical chemistry method intended to be operated at industrial sites. This issue of composite particle stoichiometry monitoring was first dealt with using Laser-Induced Breakdown Spectroscopy (LIBS) right on the nanoparticle flow [START_REF] Amodeo | On-line monitoring of composite nanoparticles synthesized in a pre-industrial laser pyrolysis reactor using Laser-Induced Breakdown Spectroscopy[END_REF]. With the final aim in view to enhance detection and to facilitate possible other laser diagnostics, preliminary experiments were carried out coupling the LIBS analyzer with a low pressure RF (Radio Frequency) plasma discharge acting as a particle trap. Agglomerates of composite nanoparticles of SiC and Al 2 O 3 were injected into the RF plasma discharge where they were trapped in levitation [START_REF] Thomas | Complex plasma laboratory PK-3 Plus on the International Space Station[END_REF][START_REF] Hayashi | Observation of submicron dust particles trapped in a diffused region of a low pressure radio frequency plasma[END_REF][START_REF] Mikikian | Fortov and the PKE-Nefedov team, Results in the Laboratory and under Microgravity Conditions[END_REF][START_REF] Selwyn | Rastered laser light scattering studies during plasma processing: Particle contamination trapping phenomena[END_REF]. LIBS detection was eventually achieved with a satisfying signal to noise ratio at a reduced pressure of 0.25 mBar instead of the atmospheric pressure. The observation of the particle cloud was this peculiar that it did not reveal a bright flash of light, consequence of the ignition of a laser-induced plasma in a gas at a pressure of around 1 atm.

Accordingly, particle vaporization was concluded to be caused by direct interaction between laser pulses and the particles whereas it is achieved by the laser-induced plasma when operating at atmospheric pressure. Thus, this coupling presents several advantages. All injected particles are trapped and can potentially be analyzed, thereby improving sampling. Organic particle analysis is made possible without interferences with the C, H, N, O, elements already present in the air when using an inert gas such as argon or helium for RF plasma generation. In addition, the signal-to-noise ratio may be better at reduced pressure than at atmospheric pressure. Last but not least, other laser diagnostics may be envisaged as well.

In this paper, we report the preliminary results obtained when operating such coupling. A first appraisal of the LIBS signal evolution as a function of time delay and pressure was made. Rough estimations of particle number concentrations and plasma temperature were made as well. Eventually, the obtained results demonstrate the feasibility of chemical identification of elements constituting particles combining LIBS and an RF plasma.

Experiments specifically dedicated to composite nanoparticle stoichiometry determination remain to be done.

Such set up could be envisaged to be integrated in a pyrolysis production unit. Laser particulate interaction experiments using an RF discharge have already been investigated in past studies [START_REF] Stoffels | Laser-Particulate interactions in a dusty RF plasma[END_REF][START_REF] Boufendi | Study of initial dust formation in an Ar-SiH4 discharge by laser induced particle explosive evaporation[END_REF]. However, chemical identification of particles is to our knowledge reported for the first time in such experimental conditions.

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Experimental Set-up

The experimental set-up is presented on figure 1.

The RF discharge cell

The RF cell presents itself as a 10 cm wide and 10 cm high rectangular-shaped stainless steel cell fitted with four optical windows allowing particle observation using optical diagnostics. A pair of 6 centimeter diameter parallel disc-shaped electrodes with a 5 cm gap separation is enclosed within the cell in horizontal position. The electrode from the bottom is connected to the ground, while that of the top is fed by an RF generator. The latter operates at 13.56 MHz delivering a power of 4 W through a matching network assuring impedance adaptation between the generator and the plasma. The RF cell is vacuumed using a BOC Edwards XDS-5 pump down to a pressure of 0.25 mBar. Background gas is then flowed in from the top of the cell using a precision valve. Air was favored in these experiments instead of an inert, plasmagene gas such as argon for a micro leak was detected when starting the experiments. A Baratron gauge (MKS Instruments) monitors the pressure within the chamber. A particle injector positioned on the top of the RF cell and described below was employed to flow in particles into the low pressure plasma. The RF cell rested upon locknuts screwed on four M6 threaded posts fixed on the experimental bench. Laser probing along a vertical axis was therefore achieved by positioning the locknuts and therefore the RF cell they support at the desired vertical position.

The nanoparticle injector

The injection unit is made up of two components, namely the injector mechanism and a small reservoir containing agglomerated ENP powders. The 1 cm diameter and 0.5 cm height cylindrical-shaped metallic receptacle was manually filled in, taking precautions inherent to ENP handling. Manipulations were conducted in a hood wearing gloves. The receptacle is capped with a 5 µm step mesh grid facing the inner plasma RF discharge chamber when placed in operational position. It was made integral with a metallic rod, part of the injection mechanism. When activated, an electro magnet makes the rod and therefore the receptacle move up and down along its axis, thereby exerting a shaking action on the powders, forcing them through the grid right into the plasma discharge. One millimeter metal beads laid within the reservoir helped particles passing through the grid.

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Laser spectroscopy set-up

Laser pulses with energies of 300 mJ and durations of 6 ns fired by a 1064 nm Q-switched laser (Quantel Brilliant) operating at 20 hz were first spatially expanded to three times the initial beam diameter. Such increase in radius aims at reducing the power density deposited on the window when focusing laser pulses inside the cell. A dichroïc mirror fully reflective at 1064 nm and 355 nm but otherwise transparent directed the beam toward a 85 mm focal length lens allowing focusing laser pulses within the cell. The mirror was positioned so as to make a 90 degree angle between the optical axis of the beam expander and that of the focusing lens. Such optical path makes light collection along the focusing axis possible, given that the dichroïc mirror is transparent to almost all wavelengths but that of the laser. Light emitted by particle disintegration was then collected through the very lens utilized for laser focusing and focused on the entrance of a 600 µm core diameter optical fiber (Ocean Optics) using another 50 mm focal length lens. Optical emission spectra were retrieved from a spectrometer (iHR320) equipped with a gated intensified CCD camera (Andor iStar model DH734-18F-03).

Time resolved measurements are made possible with such detector by triggering signal recording when the laser pulses are fired and recorded over the required duration by selecting the appropriate integration time (with accessible time resolution of around 2 ns).

Foreword

Brief description of particle batches

The experiments were performed on two different batches of composite nanoparticles. These first tests were run with SiC and Al 2 O 3 powders. Both nanoparticle lots were synthesized by laser pyrolysis technique [START_REF] Amodeo | On-line monitoring of composite nanoparticles synthesized in a pre-industrial laser pyrolysis reactor using Laser-Induced Breakdown Spectroscopy[END_REF].

Particle characteristics were observed using SEM (Scanning Electron Microscopy) prior to these experiments.

SEM observations showed that SiC agglomerates were formed. Their median and upper size values were found to be of around 800 and 1200 nm respectively. Particles of Al 2 O 3 displayed a rather monodisperse distribution with sizes of around 350 nm. Their morphologies proved to be different as particles of Al 2 O 3 are rather spherical whereas those of SiC present a more complex structure.

Injection procedure

Nanoparticle injection operation is carried out while the RF discharge is being operated. A white light lamp illuminating one of the four windows and making the hovering nanoparticle cloud visible through diffusion was employed as a basic monitoring tool (based on eye observation). Through former studies, particles are

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known to gain a negative charge when injected in an RF plasma cell [START_REF] Merlino | Dusty plasmas and applications in space and industry[END_REF][START_REF] Wattieaux | Electrical time resolved metrology of dust particles growing in low pressure cold plasmas[END_REF]. This has two major consequences on their behavior. First, agglomerates tend to de-agglomerate under electrostatic repulsion forces. Second, particles were demonstrated to levitate within the RF plasma discharge [START_REF] Thomas | Complex plasma laboratory PK-3 Plus on the International Space Station[END_REF][START_REF] Hayashi | Observation of submicron dust particles trapped in a diffused region of a low pressure radio frequency plasma[END_REF][START_REF] Mikikian | Fortov and the PKE-Nefedov team, Results in the Laboratory and under Microgravity Conditions[END_REF][START_REF] Selwyn | Rastered laser light scattering studies during plasma processing: Particle contamination trapping phenomena[END_REF]. The two main forces exerted on particles, that of gravity and the electrostatic force originating from the electric field created by the RF discharge, happen to balance [START_REF] Wattieaux | Discharge impedance evolution, stray capacitance effect, and correlation with the particles size in a dusty plasma[END_REF], thereby resulting in particles being in levitation. Trapping occurs at a height mainly dependent on particle surface [START_REF] Bleecker | Modeling of the formation of nanoparticles in dusty plasmas[END_REF]. As a consequence, particles distribute according to their sizes along the cylindrical symmetry axis passing through the electrodes, larger particles being preferentially located near the bottom electrode. Conversely, smaller particles tend to occupy the upper part of the cloud hovering in the RF cell.

Results and discussion

Temporal settings and spectrum acquisition mode

The LIBS signal was recorded after each laser shot by selecting proper time delay and integration time values. The latter two parameters were arbitrarily set to 1 µs and 5 µs respectively when running the first tests for time delays optimizing the LIBS signal were not known yet. Detector settings were arranged so that emission stemming from each laser shot could be recorded in individual spectra. Such recording mode presents the advantage of allowing monitoring of spectroscopic signal emission from individual particle hit by laser pulses.

Comments on injection of Al 2 O 3 and SiC

Two first series of experiments were successively carried out by probing Al

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The particle cloud was also observed when probed by the laser pulses. This observation did not reveal bright light emission such as that usually seen when igniting a laser-induced plasma at atmospheric pressure. It strongly suggested that particle vaporization is the consequence of direct laser particle interaction within the focusing volume whereas it is mainly caused by the laser-induced plasma at atmospheric pressure. This point is worth emphasizing for LIBS literature related to particle analysis is mainly performed at atmospheric pressure.

LIBS signal is assumed originating from a microplasma formed when particles are vaporized.

Analysis of recorded spectra

Following injection, both clouds were interrogated by LIBS. 2a).

Though oxygen lines could be detected using optical emission spectroscopy, these were not selected for a first

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Probability of detection is therefore expected to decrease as the focused volume or sampling zone moves upward from the bottom plate electrode. Given these observations, a rough estimation of the sizes of the detected particles can be made. Sizes of the largest particles were found to be of around 1.2 µm under SEM analysis. As previously explained, particles immersed within the RF plasma are known to repel one another and therefore do not agglomerate to form larger particles. As a consequence, sizes of particles leading to signal emission are estimated of around 1 µm or so. Such dependence was not observed when dealing with the Al 2 O 3 cloud. Though Al 2 O 3 particle distribution was rather monodisperse, particles were not all found to be located at the same height in the RF discharge as expected. The rather high concentration of particles squeezed into the cell (the injection being facilitated by particle shape as previously explained), thereby leading to the formation of a large, dense cloud may explain their not distributing along the symmetry axis according to the pattern briefly described in section 3.2.

SiC probing presents another peculiarity in comparison with that of Al 2 O 3 . Data processing related to the latter showed that all laser shots did occasion aluminum line detection. Conversely, careful examination of the SiC spectra makes stand out the non systematic rise of Si line for each laser shot. Only 9% of the recorded spectra displayed Si detection. This seems obviously connected to particle number density. Indeed, line emission can only occur when a particle is sampled within the laser focusing volume. The lower the particle number density, the lower the sampling rate and therefore the probability to record lines corresponding to the elements the probed particles are made of. This observation has two consequences. First, it points out that detection of single particle is possible. Indeed, analysis of series of spectra shows that several hundreds of ms can elapse between two consecutive recorded lines. This fuels the hypothesis of single particle detection, the latter being entirely vaporized or repelled out of the focusing area before the next pulse. Signal recording recurs when a particle pops up in the focusing area again. Single particle detection may be of great interest when it comes to dust formation within plasma reactors such as RF discharges. Second, this mode of detection both inherent to the transient nature of the LIBS signal and to the discrete nature of particle implies a specific data processing to make the most of the recorded spectra. Stochiometry determination may motivate the obtaining of a spectroscopic signal with high signal to background ratio. The usual way to deal with such issue consists of ensemble-averaging all recorded individual spectra. Still, such approach may be inadequate with low sampling rates, as already emphasized by Hahn et al. [START_REF] Hahn | Discrete particle detection and metal emissions monitoring using laser-induced breakdown spectroscopy[END_REF] when carrying out LIBS experiments at atmospheric pressure.

When faced with low sampling rates, discarding spectra free of signal prior to averaging is beneficial to the intensity of signal to background ratio. Applying such procedure reported as conditional analysis [START_REF] Hahn | Discrete particle detection and metal emissions monitoring using laser-induced breakdown spectroscopy[END_REF] is

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undoubtedly helpful when less than 20 % of individual spectra contain signal. Average spectra of Al and Si lines were therefore obtained applying ensemble-averaging and conditional analysis [START_REF] Gallou | Aerosols Analysis by LIBS for Monitoring of Air Pollution by Industrial Sources[END_REF] respectively. They are presented on figures 3a&3b and display satisfying signal to background ratio.

Particle concentration estimation

Though particle number concentrations cannot easily be determined in the framework of these experiments, their limit values (upper limit for SiC and lower limit for Al 2 O 3 ) were roughly estimated combining the stochastic nature of particle sampling and a calculation of the focusing volume. The latter is approximately expressed using the following equation [START_REF] Parriger | Laser-induced breakdown in gases: experiments and simulation[END_REF], assuming a Gaussian radial profile:

V = 19.2 (f/D) 4  3
where f is the focusing lens length, D the laser beam diameter, and  the laser beam wavelength. Taking into account that a lens with focusing length of 85 mm was used and that the laser beam diameter and laser wavelength values were of around 18 mm and 1064 nm respectively, the focal volume was estimated to be of around 10 -8 cm -3 . Eventually, this estimation of the focal volume combined with statistical considerations on line recording allows assessing number densities within the RF discharge. Indeed, systematic particle hit was observed through Al 2 O 3 ENP spectroscopic measurement leading to a sampling rate of 100% whereas the latter value fell to 9% when probing the less concentrated cloud of SiC. The former case highlights the fact that particles were always present within the focusing volume when irradiating Al 2 O 3 whereas this condition was not fulfilled when letting laser pulses passing through the SiC cloud. Considering that the average number of particles within the focusing volume may be calculated using the following formula:

N = cV
where c is particle number concentration and V the focusing volume, an estimation of limit values for each case may be given. Assuming that there was at least always one Al 2 O 3 particle within the focusing volume, the corresponding minimum particle number concentration may be assessed with a value of around 10 8 part per cc or more. The SiC concentration is contrariwise estimated to be lower than the latter value given the sampling rate obtained when probing SiC particles.

LIBS signal evolution as a function of time delay

Temporal evolution of aluminum lines was investigated when analyzing Al 2 O 3 particles. The results are presented on figure 4 where the obtained spectra were ensemble-averaged over one thousand and four hundred

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laser shots. First, these spectra display very low background emission [START_REF] Effenberger | Effect of Atmospheric Conditions on LIBS Spectra[END_REF] remaining at the same intensity level for time delays ranging from 100 ns to 5µs. In comparison is the background intensity of spectra recorded when detecting particles disintegrated at atmospheric pressure within a hot laser-induced plasma much higher for similar time delays. Second, time delays maximizing the LIBS signal were found to be much shorter than those usually used when carrying out LIBS experiments at atmospheric pressure. Aluminum line intensities were found to increase with decreasing time delays, the maximum LIBS intensity being recorded for the shortest time delay employed in the allotted time of these preliminary experiments, namely 100 ns. Values of a few to a few dozens of microseconds were contrariwise reached at atmospheric pressure. This might be accounted for by the difference in plasma temperature. Indeed, each line corresponding to the elements particles may be made of were shown to maximize their intensity at a preferential temperature [START_REF] Amodeo | On-line determination of nanometric and sub-micrometric particle physicochemical characteristics using spectral imaging-aided Laser-Induced Breakdown Spectroscopy coupled with a Scanning Mobility Particle Sizer[END_REF][START_REF] Hohreiter | Calibration effects for laser-induced breakdown spectroscopy of gaseous sample streams: analyte response of gas-phase species versus solid-phase species[END_REF][START_REF] Fisher | Temporal gating for the optimization of laserinduced breakdown spectroscopy detection and analysis of toxic metals[END_REF]. According to the plasma cooling speed, the time necessary for a line of a given element to reach its preferential temperature does impose the time delay for which the LIBS signal is to the maximum. Examination of the spectra of figure 4 reveals an additional line at 391.44 nm when recording spectra 100 and 500 ns subsequently to laser pulses. The latter stands for nitrogen molecular ion, whose spectroscopic features are reported in table 2. Line intensities of this molecule appear to taper off as a function of time delay and are therefore concluded to be related to LIBS signal. Such correlation tends to indicate that molecular emission originates from LIBS signal and not from the RF plasma discharge. The atoms of nitrogen dissociated in the early times of particle ablation within the focusing volume recombine when the microplasma cools down, thereby resulting in the formation of the N 2 + ionized, and excited molecule. Temperature of a plasma may be inferred through such molecular emission [START_REF] Chelouah | A new method for temperature evaluation in a nitrogen discharge[END_REF]. They usually do not exceed a few thousand degree Kelvin, range within which the microplasma temperature may vary. Though neither the exact microplasma temperature value nor the time delay maximizing the LIBS signal were precisely determined, the obtained results seem consistent with those of a previous study at atmospheric pressure showing a preferential temperature of around 7500 K to optimize the Al 396 nm line recording [START_REF] Amodeo | On-line determination of nanometric and sub-micrometric particle physicochemical characteristics using spectral imaging-aided Laser-Induced Breakdown Spectroscopy coupled with a Scanning Mobility Particle Sizer[END_REF]. As to possible more intense background emission that may be recorded in the early time delay range not explored in the present paper, literature sheds light on possible continuum emission. Stoffels et al. [START_REF] Stoffels | Laser-Particulate interactions in a dusty RF plasma[END_REF] concluded, when investigating laser-particulate emission interactions in a dusty RF plasma, that blackbody-like emission observed when irradiating particles with µs and ns laser pulses originated from particle surfaces and by no means by excited atomic vapor expanding fast under reduced pressure. The latter would be worth studying in order to ascertain or not the need for gated detectors when carrying out such experiments.

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Discussion on difficulties of carbon detection and carbon line emission as a function of pressure

As explained above, the final objective of these experiments is to assess stoichiometry, thereby necessitating the detection of all the elements composing the powders. Carbon line at 247.85 nm was not observed when vaporizing SiC particles in the RF cell under pressure of 0.25 mBar. Several reasons may have caused this line not to be seen under the aforementioned conditions. Spectroscopic characteristics of the 247.85 nm carbon line make it harder to detect than aluminum and silicon given its transition probability and the upper state energy level (see table 1). In addition, this line was found to be maximized for a temperature higher than that found for aluminum, namely around 11000 K [START_REF] Amodeo | On-line determination of nanometric and sub-micrometric particle physicochemical characteristics using spectral imaging-aided Laser-Induced Breakdown Spectroscopy coupled with a Scanning Mobility Particle Sizer[END_REF]. Moreover, carbon happens to recombine with nitrogen in the early times of plasma formation, thereby reducing the number of carbon emitters. These latter two points suggest the selection of a short time delay. In addition to these intrinsic properties of the transitions, the window transmittance of the RF cell was measured to be of around 30%. Eventually, the ICCD response efficiency decreasing with decreasing wavelength ends up listing the weaknesses hindering carbon detection.

Based on this failure to detect the expected line, decision was made to try again to detect carbon using an alternative experimental set-up. The RF discharge reactor was changed for a quartz four-way cross chamber.

The injector was fixed on its top and vacuuming was assured using the very pumping system utilized for all the other experiments. The focused laser pulses were let in through the chamber with the focusing volume positioned right beneath the injector. The injector was activated while the laser was being operated so as falling powders be intercepted by the focusing volume. Spectra were taken following the one shot / one spectrum recording pattern presented above with a 500 ns time delay (the optimized value was not known) and a 7 µs integration time.

Carbon line intensity was monitored as a function of inner chamber pressure. Acquisitions were stopped as the carbon line intensity was fading until signal collection was no longer possible. Some of the resulting spectra are presented on figure 5 for two different pressures. The signal to noise ratio values of the carbon line were found to approximately vary from around 14 to 10 within about two decades of pressure range, namely from 500 to 1 mbar. Such observation suggests that the carbon line could have been detected at 0.25 mBar using proper LIBS settings and set-up. Results obtained in this additional experiment are quite encouraging for the next steps.

Conclusion

Preliminary experiments aiming at identifying elemental composition of agglomerates of composite ENPs with the final objective to measure their stoichiometry were performed envisaging a new approach. It rests on the combination of a low pressure RF plasma discharge with LIBS. Contrary to the analysis on a particle flow

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at atmospheric pressure, the particles are trapped and maintained in levitation. As the reduced pressure precludes the ignition of a hot plasma in the gas, particle vaporization is therefore assumed to be the consequence of direct laser interaction. Eventually, aluminum and silicon lines recorded in spectra obtained when probing Al 2 O 3 and SiC ENP clouds were successfully observed. The Al 2 O 3 particle density within the RF cell was estimated to be of around 10 8 cm -3 or more whereas that of SiC was assessed lower than that. Time resolved recordings performed within the 100 ns to 5 µs delay range showed that maximum LIBS intensity was reached for the shortest delay set when carrying out these experiments, namely 100 ns. Time delays maximizing signal to background ratio were concluded have to be selected close after the end of the laser pulse. Carbon line detection proved to be more difficult. However, its detection is deemed feasible provided proper temporal settings and experimental set-up be employed.

Many questions remain open as to the potentialities of such combination. The dependence of the spectroscopic signal with particle sizes should be investigated. Particle ablation rate could be computed provided the absorption coefficient and enthalpy of evaporation of the targeted compound be found in the literature.

Particle size range accessible to such analysis could be envisaged to be lowered through the use of proper laser wavelength and both focusing and collection optical paths. Appraising whether stoichoimetry may be inferred from such analysis will be the next step, involving upgrade of the laser set-up and better understanding of laser particulate matter interaction. Such approach may also be of interest for particle formation monitoring when carrying out experiments in the field of dusty plasmas. analysis algorithm [START_REF] Gallou | Aerosols Analysis by LIBS for Monitoring of Air Pollution by Industrial Sources[END_REF]) laser shots respectively. The recordings were performed using time delays after the laser pulse of 1 µs and integration time of 5 µs. The entrance slit width of the spectrometer was set to 400 µm, thereby reducing spectral resolution to enhance photon collection, the latter being of more importance for these preliminary tests.

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  2 O 3 and SiC clouds of particles with the aforementioned settings. A total of five hundred individual spectra corresponding to the same number of laser shots were recorded for each series. A first basic diagnostic was performed looking at the nanoparticle cloud from the beginning to the end of the injection procedure. Direct eye observation by white light diffusion suggested that the Al 2 O 3 cloud was much denser than that of SiC. Such difference in concentration recurrently observed throughout the whole campaign of experiments may be accounted for as follows. SiC particle injection happened to be arduous. As already underlined above, SEM observations of the suspended particles revealed that Al 2 O 3 particles are spherical-shaped whereas non-sphericity of SiC particles was blatant. Connecting these two facts hints that non sphericity of SiC particles may preclude them from flowing smoothly through the grid of the reservoir. Spherical-shaped Al 2 O 3 particles are contrariwise more prone to traverse the holey grid. The Al 2 O 3 ENP cloud was therefore always denser than that of SiC.

  trial. The impossibility to tell apart oxygen of the air used as background gas in the RF discharge from that contained in the alumina ENPs resulted in our not insisting on trying to detect these lines. Data analysis demonstrated that each laser shot caused Al lines to rise from the background noise in each corresponding spectra. This result was achieved regardless of the vertical position of the focal volume above the bottom electrode. Detection of the elements constituting SiC (figure2b) turned out to be different in every way.Attention was focused on the detection of Si lines and that at 288.15 nm (table 1) emerged when scanning vertically the ENP cloud along the RF cell symmetry axis. Carbon detection was not achieved in the course of our experiments. Difficulties inherent to carbon line detection are discussed further below. Eventually, recording of the Si line could only be fulfilled when probing the bottom of the cloud. Contrary to the observations made when dealing with the Al 2 O 3 particle cloud, successive recordings of single spectra corresponding to unique shots did not always occasion line emergence. Only a slight fraction of the total number of spectra exhibited the searched line.The obtained results point out a predictable influence of 1) the position of the focal volume along the symmetry axis of the RF discharge and 2) the concentration within the cloud on particle detection.The detection dependence with the position of the focal volume seems consistent with the aforementioned described pattern of size distribution of particles along the symmetry axis of the RF discharge, larger particulates of SiC being located at the bottom of the cloud. Larger particles are very likely to yield larger amount of mass when vaporized by a laser pulse. As spectroscopic detection sensitivity depends on this mass yield, particles with larger sizes are more likely to be detected than those of tinier radius.

Figure 1 :

 1 Figure 1: Experimental set-up

Figure

  Figure 3a & 3b: Spectra acquired when probing (a) Al 2 O 3 and (b) SiC particles hovering in the RF plasma discharge under 0.25 mBar pressure and ensemble averaged over 500 and 90 (after having used conditional

Figure 4 :

 4 Figure 4: Temporal evolution of ensemble averaged spectra acquired when probing Al 2 O 3 particles within the RF plasma discharge under 0.25 mBar pressure. Integration time was fixed to 5 µs. Spectra were ensemble averaged over 1400 laser shots. The spectrometer entrance slit width was set to 200 µm instead of 400 µm given the rather fair signal to background ratio obtained when recording these spectra.

Figure 5 :

 5 Figure5: Spectra acquired consecutive to one unique laser shot when probing SiC particles at 500 and 1 mBar in the four way cross cell. Time delay and integration time were set to 500 ns and 7µs respectively. Next to the carbon line can be seen the Si quintuplet lines. The corresponding spectrum is poorly resolved given the wide entrance slit selected to enhance carbon detection.

Figure 1 AFigure 4 Figure 5 A 25 HIGHLIGHTS

 14525 Figure 1

  The results are presented on figure 2. Al lines at 394.40 and 396.15 nm (see table 1) were recorded while interrogating the Al 2 O 3 ENP cloud (figure

Table 1 .

 1 Wavelengths , transition probabilities A ki , lower E i and upper E k energy levels of neutral lines detected when analyzing SiC x and Al 2 O 3 particles (Lines on line [26])

	Element	λ (nm)	A ki (10 7 s -1 )	E i (eV)	E k (eV)
	Al I	394.40058	4.93	0.0	3.1427210
		396.15200	9.8	0.0138938	3.1427210
	C I	247.856	2.8	2.684011	7.684766
	Si I	288.1579	21.7	0.7809578	5.0823456

Table 2 .

 2 Spectroscopic characteristics of N 2 + molecular line including bandhead wavelength λ, upper electronic state T e and transition probability A ki .(Rosen, 1970 [27])

	Species	System	Transition	Band	 (nm)	T e (eV)	A ki (10 8 s -1 )
	N2+	FNS	B 2 Σ u + -X 2 Σ g +	(0,0)	391.44	3.17	---

Acknowledgments:

This research was supported by the French National Research Agency (ANR), the ERDF (European Regional Development Fund) and the French "Région Centre".

A C C E P T E D

M A N U S C R I P T


A Albinet

S Tomaz

F Lestremau

A really Quick Easy Cheap Effective Rugged and Safe (QuEChERS) extraction procedure for the analysis of particle-bound PAHs in ambient air and emission samples

Keywords: Polycyclic aromatic hydrocarbons, B[a]P, QuEChERS, Extraction, Analysis, Aerosol, Particulate matter

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

A really quick easy cheap effective rugged and safe (QuEChERS) extraction procedure for the analysis of particle-bound PAHs in ambient air and emission samples Alexandre Albinet, Sophie Tomaz, François Lestremau To cite this version:

Alexandre Albinet, Sophie Tomaz, François Lestremau. A really quick easy cheap effective rugged and safe (QuEChERS) extraction procedure for the analysis of particle-bound PAHs in ambient air and emission samples. Science of the Total Environment, 2013, 450-451, pp.31-38. 10.1016/j.scitotenv.2013.01.068. ineris-00961801

Introduction and objectives

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental contaminants widely studied due to their known toxicity (carcinogenic and/or mutagenic properties) [START_REF] Iarc | Some non-heterocyclic polycyclic aromatic hydrocarbons and some related exposures[END_REF]. In the atmosphere, they are released in both gaseous and particulate phases as by-products from the incomplete combustion of organic matter and fossil fuel [START_REF] Ravindra | Atmospheric polycyclic aromatic hydrocarbons: source attribution, emission factors and regulation[END_REF]. In many countries, including Europe and USA, particle-bound PAHs are regulated and monitored in ambient air (ATSDR (Agency for Toxic Substances and Disease Registry), 1995;European Official Journal, 2005;[START_REF] Ravindra | Atmospheric polycyclic aromatic hydrocarbons: source attribution, emission factors and regulation[END_REF]. In Europe, a target value for benzo [a]pyrene (B[a]P) in PM 10 (particulate matter < 10 µm) (B[a]P -as a marker for the suite of PAH compounds) has been set to 1 ng m -3 on annual average for every single monitoring station (European Official Journal, 2005).

Particle-bound PAHs are generally sampled by air sampling using different media (e.g. quartz or glass fibre filters). Common methodologies used for the quantification of particle-bound PAHs include solvent extraction and analysis generally achieved using HPLC-Fluorescence detection or by GC-MS (European Committee for Standardization (CEN), 2008;[START_REF] Pandey | A review of techniques for the determination of polycyclic aromatic hydrocarbons in air[END_REF]. Other existing analytical techniques include, for example, HRGC-MS/MS, GC-TOF-MS, GC-FID, GC-ECD [START_REF] Pandey | A review of techniques for the determination of polycyclic aromatic hydrocarbons in air[END_REF] (20 -200 mL) are then reduced under a nitrogen flow to a final volume lower than 1 mL. The analytical procedure could also include a purification step of the extract by solid phase extraction before analysis. We can also cite in this category the supercritical fluid extraction (SFE) using pure CO 2 [START_REF] Hawthorne | Extraction and recovery of organic pollutants from environmental solids and tenax-GC using cupercritical CO 2[END_REF][START_REF] Hawthorne | Comparisons of Soxhlet extraction, pressurized liquid extraction, supercritical fluid extraction and subcritical water extraction for environmental solids: recovery, selectivity and effects on sample matrix[END_REF][START_REF] Pandey | A review of techniques for the determination of polycyclic aromatic hydrocarbons in air[END_REF]. Beside, solvent-free based extraction techniques were developed by different authors using notably thermal-desorption coupled with GC-MS (TD-GC-MS) [START_REF] Pandey | A review of techniques for the determination of polycyclic aromatic hydrocarbons in air[END_REF][START_REF] Van Drooge | Thermal desorption gas chromatography-mass spectrometry as an enhanced method for the quantification of polycyclic aromatic hydrocarbons from ambient air particulate matter[END_REF] and, in a lesser extent, laser desorption/ionization coupled to time-of-flight mass spectrometry (LDI-ATOFMS) [START_REF] Zimmermann | Application of single-particle laser desorption/ionization time-of-flight mass spectrometry for detection of polycyclic aromatic hydrocarbons from soot particles originating from an industrial combustion process[END_REF].

If all these extraction techniques are really efficient, they are time-consuming, labor-intensive, requires the use of a large volume of organic solvent (toxic), laborious clean up procedures and a high cost of investment and maintenance (ASE, TD-GC-MS, SFE) (Table 1).

The QuEChERS procedure (Quick Easy Cheap Effective Rugged and Safe) was developed with the objective to simplify and shorten the extraction step of organic compounds. This kind of procedure was initially developed for the extraction of pesticides in food matrices (vegetables and fruits) [START_REF] Anastassiades | Fast and easy multiresidue method employing acetonitrile extraction/partitioning and "dispersive solid-phase extraction" for the determination of pesticide residues in produce[END_REF][START_REF] Wilkowska | Determination of pesticide residues in food matrices using the QuEChERS methodology[END_REF]. It is considered as a soft extraction method (less interfering compounds are extracted) which involves extraction with acetonitrile (ACN) followed by an optional clean up procedure by dispersive solid-phase extraction (d-SPE). The total extraction + clean up time is generally about 1 to 5 minutes and the quantity of solvent used (ACN) from 5 to 15 ml [START_REF] Wilkowska | Determination of pesticide residues in food matrices using the QuEChERS methodology[END_REF]. The QuEChERS approach requires fewer steps and time than traditional extraction procedures. This is significant, as every additional analytical step complicates the procedure and represents also a potential source of errors.

Additionally, no important cost of investment is required (only a vortex and a centrifugation apparatus). Since the development and the publication of the method [START_REF] Anastassiades | Fast and easy multiresidue method employing acetonitrile extraction/partitioning and "dispersive solid-phase extraction" for the determination of pesticide residues in produce[END_REF],

QuEChERS has been gaining significant popularity from academia and industry to quickly being established as a reference method for foodstuff analysis (European Committee for Standardization (CEN), 2009). The QuEChERS procedure was then later successfully applied to other matrices like fish, shellfish, soils and sediments and also to other compounds like PBDEs, VOCs, PCBs, pharmaceuticals, chlorinated compounds and PAHs (e.g; [START_REF] Asensio-Ramos | Evaluation of a modified QuEChERS method for the extraction of pesticides from agricultural, ornamental and forestal soils[END_REF][START_REF] Bragança | QuEChERS: A new sample preparation approach for the determination of ibuprofen and its metabolites in soils[END_REF][START_REF] Cai | Ultra high performance liquid chromatography-atmospheric pressure photoionization-mass spectrometry for high-sensitivity analysis of US Environmental Protection Agency sixteen priority pollutant polynuclear aromatic hydrocarbons in oysters[END_REF][START_REF] Forsberg | Determination of parent and substituted polycyclic aromatic hydrocarbons in high-fat salmon using a modified QuEChERS extraction, dispersive SPE and GC-MS[END_REF][START_REF] García Pinto | A simplified Quick, Easy, Cheap, Effective, Rugged and Safe approach for the determination of trihalomethanes and benzene, toluene, ethylbenzene and xylenes in soil matrices by fast gas chromatography with mass spectrometry detection[END_REF][START_REF] Gratz | Screening and determination of polycyclic aromatic hydrocarbons in seafoods using QuEChERS-based extraction and high-performance liquid chromatography with fluorescence detection[END_REF][START_REF] João Ramalhosa | Analysis of polycyclic aromatic hydrocarbons in fish: evaluation of a quick, easy, cheap, effective, rugged, and safe extraction method[END_REF][START_REF] Kalachova | Simplified and rapid determination of polychlorinated biphenyls, polybrominated diphenyl ethers, and polycyclic aromatic hydrocarbons in fish and shrimps integrated into a single method[END_REF][START_REF] Pule | Analysis of polycyclic aromatic hydrocarbons in soil with Agilent bond elut HPLC-FLD[END_REF][START_REF] Smoker | Determination of polycyclic aromatic hydrocarbons (PAHs) in shrimp[END_REF][START_REF] Wilkowska | Determination of pesticide residues in food matrices using the QuEChERS methodology[END_REF].

To our knowledge, the QuEChERS extraction procedure was never applied for the analysis of PAHs, or other organic compounds, from atmospheric particulate matter or wood burning emissions. Only one simplified extraction method comparable to the QuEChERS approach is described in the literature [START_REF] Delgado-Saborit | Determination of atmospheric particulate-phase polycyclic aromatic hydrocarbons from low volume air samples[END_REF]. The major differences of this method, using mechanical shaking, lie in the longer agitation time (15 min) and the purification steps.

Considering the total duration time of the method (estimated > 45 min), this protocol could not be classified as a QuEChERS (quick) extraction procedure.

The objective of this study was to evaluate and to report on the applicability of QuEChERS extraction procedure for the analysis of PAHs in atmospheric particulate matter. The developed QuEChERS approach was applied to the analysis of ambient and emission (wood combustion) air samples using HPLC-Fluorescence detection (HPLC-FLD). Results were compared with those obtained with ASE extraction method (Dionex) according to the European standard reference method EN 15549 (European Committee for Standardization (CEN), 2008). The methodology was validated by the analysis of the NIST standard reference material SRM 1649a (urban dust).

Experimental section

Particulate samples

Ambient particulate samples were collected at INERIS (Verneuil-en-Halatte, France; 49°16'20"N, 2°30'14"E), in February 2012. Sampling site could be classified as suburban. Six PM 10 samples were collected using a high volume sampler (Graseby Andersen, 70 m 3 h -1 ) on quartz fibre filter (Whatman QMA, 20.3 x 25.4 cm) previously heated for 12 h at 500 °C. Sampling duration was 24 h. After collection, filters were wrapped in aluminium foil, sealed in polyethylene bags and stored at -18 °C until analysis. Collected filters were cut into sixteen smaller filter sections (Ø = 47 mm) (filter surface equivalent to a 24 h sampling at 2.3 m 3 h -1 ) in order to perform the development of the QuEChERS extraction procedure and the comparison with ASE extraction method using the same filter. Homogeneity of the ambient air sampling filters used (Andersen) was evaluated and no significant disparity between filter sections was observed for PAHs (σ = 3 -8 %) (Leoz-Garziandia et al., 2010).

Emission particulate samples were collected during the research program PEREN 2 BOIS [START_REF] Fraboulet | PEREN 2 BOIS: Evaluation technico-économique des meilleures techniques disponibles de réduction des émissions de poussières fines et de composés organiques pour les appareils de combustion domestique utilisant la biomasse (French language)[END_REF][START_REF] Fraboulet | PEREN 2 BOIS: techno-economical evaluation of the energetic and environmental performance of the best available technologies for reducing fine particle and organic compound emissions from domestic combustion devices using biomass (French language)[END_REF]. Briefly, the measurement procedure consisted of the sampling in non-isokinetic conditions (sampling velocity > airflow speed in the exhaust pipe), of the total suspended particulate matter (TSP) emitted by wood combustion in a stove, on a heated quartz fibre filter (125 ± 10 °C) (Whatman QMA,  = 74 mm). Sampling duration was 30 min.

Filters were divided in 1.5 cm² sections to perform comparative tests between ASE and QuEChERS extraction procedures. Note that, the homogeneity of the emission filters was not guaranteed (non uniform repartition of the particles at the surface of the filter, Fig. A1 in the appendix A.)

Extraction and purification

DCM and ACN were purchased from Aldrich (HPLC grade). Water used was Milli-Q quality (Millipore, 18 MΩ). 6-Methylchrysene (10 µL of a solution at 10 ng µL -1 in ACN, Supelco, 99 % purity) was added before extraction as surrogate standard according to EN 15549 (European Committee for Standardization (CEN), 2008).

Extractions of ambient air and emission particulate samples, and SRM, were performed using ASE (Dionex, ASE 200) with DCM as solvent. Extraction procedure was the following: 11 mL cells were used with extraction parameters set at 120 °C, 140 bars, 3 cycles of 6 minutes, flush 90 % and purge 120 sec. Then, extracts (≈ 30 ml) were reduced under a nitrogen stream at a volume of 0.2 ml (Zymark, Tubovap II) and dissolved (adjusted to 1 ml) into ACN for PAH analyses. This is the traditional extraction procedure used by our group and reported in previous articles (Albinet et al., 2007a(Albinet et al., 2007b;;Albinet et al., 2008aAlbinet et al., 2008b;;[START_REF] Goriaux | Field comparison of particulate PAH measurements using a low flow denuder device and conventional sampling systems[END_REF]Ringuet et al., 2012aRinguet et al., 2012b)).

For QuEChERS extraction procedure, samples (filter sections or SRM 1649a) were placed in centrifuge glass tubes ( = 16 mm, L = 100 mm, screw cap with PTFE septum face, Duran, VWR)

and totally immerged with 7 mL of solvent (ACN or DCM or ACN/H 2 O (5/2, v/v)). The influence of the addition of salts was also investigated (2 g of Na 2 SO 4 or MgSO 4 ) (see section 3.1). Samples were shaken/vortexed using a multi-position vortex for 30 s to 2 min (IKA, Vortex Genius 3; 8 positions/simultaneous extractions). Next, they were centrifuged for 5 min at 4500 rpm (Sigma, 3-16 PK centrifuge. 1 ml of supernatant was collected for direct analysis and 3 ml were reduced under a nitrogen stream (0.5 ml) (Zymark, Tubovap II) and adjusted to 1 ml (reduction time was about 10 min for 6 simultaneous samples). In both cases, supernatants were filtered using a 0.20 μm PET syringe filter (Macherey-Nagel, Chromafil Xtra PET 20/25) and collected in an autosampler vial for analysis. The analysis of both, direct and reduced extracts, was performed.

A clean up procedure by (d-SPE) was also applied for emission samples. After extraction and centrifugation, 200 mg of Florisil ® was added to 3 mL of collected supernatant and put in a centrifuge tube containing (from SPE cartridges: Aldrich, Supelclean). Samples were vortexed for 1.5 min, centrifuged for 5 min, filtered and analysed.

Analysis

PAHs were analysed by HPLC-FLD (Dionex P580 / Dionex RF200). The column used was a Supercosil LC-PAH C18 (250 mm × 4.6 mm × 5 µm) (Supelco) thermostated at 30 °C (column oven Croco-Cil). Chromatographic gradient (1.5 mL min -1 ) was applied as follow: 55/45 (v/v) of a mixture of ACN/water for 14 minutes, followed by a gradient up to 100 % ACN at 67 min. The

]F), benzo[k]fluoranthene (B[k]F), benzo[a]pyrene (B[a]P), dibenzo[a,h]anthracene (D[a,h]A), benzo[g,h,i]perylene (B[g,h,i]P), indeno[1,2,3-cd]pyrene (Ind[1,2,3-cd]P))
. The limit of detection and quantification were evaluated at about 6 pg and 20 pg of injected compound, respectively and for all quantified PAHs. Note that, in the case of emission samples, extracts were diluted by a factor of about 20 and 100 for QuEChERS and ASE extracts, respectively, conducing to similar final dilution factors for both extracts (7 ml × 20 = 140 and 1 ml × 100 = 100 for QuEChERS and ASE, respectively).

Results and discussion

The et al., 2003). However, no significant differences and/or improvements were noticed in these conditions (Figs. A2 and A3 in the Appendix A). The addition of water to the extraction solvent seemed to decrease the PAH extraction efficiency. PAH losses were more important in this case for the reduced extracts due to the presence of water which required more extensive evaporation conditions.

Finally, ACN (without addition of salts or water) was used in the final PAHs extraction protocol.

Entire filter vs filter cut in 4 pieces

Extraction procedures using sonication or microwave extraction generally include the preparation of the sample (filter) by cutting it in small pieces in order to increase the surface of exchange with the solvent. The influence of the sample configuration was evaluated (entire filter section vs filter section cut in 4 pieces) on the efficiency of the QuEChERS extraction procedure (Fig. 2). No significant differences of PAH extraction efficiency were observed (Student test applied on every independent PAH, α = 0.05). To minimize supplementary filter handling and reduce the potential additional source of errors, the extraction of the entire filter sample (filter section  = 47 mm) was chosen for the QuEChERS extraction procedure.

Extraction time

The QuEChERS extraction procedure to guarantee the robustness of the method while preserving a short extraction time. However, fundamentally, there is no significant difference of extraction efficiency between 1 to 2 min of agitation.

Application to ambient air PM 10 samples

The adopted protocol (extraction of the entire filter  =47 mm with 7 ml of ACN using vortex agitation during 1 min 30s following by 5 min of centrifugation at 4500 rpm and filtration of the extract using syringe filter at 0.2 µm) was then applied to the analysis of PAHs in ambient air PM 10 samples and compared to the traditional extraction procedure using ASE (Fig. A4). Average PAH concentration ratios obtained using QuEChERS and PLE extraction procedures (concentrations obtained using QuEChERS method divided by concentrations obtained with ASE extraction) ( ) are presented on Fig. 4.

The results obtained demonstrated that for the heavier PAHs (from fluoranthene to Ind[1,2,3cd]P) extraction efficiencies using QuEChERS and ASE procedures were equivalent (R (QuEChERS/PLE) equal or close to 1). Significant differences were observed for the lighter PAHs (fluorene, phenanthrene and anthracene) with ratios greater than 1 (from 1.4 to 5.1), indicating larger recoveries for these compounds using the QuEChERS extraction procedure (notably for the direct injection of the extracts). Larger quantities of solvent are used with the ASE procedure, which implies a solvent evaporation step is required increasing the risk of loss for the more volatile PAHs during this step. By avoiding or shortening the solvent evaporation step of the extracts using QuEChERS approach, losses by volatilisation of the lighter (volatile) compounds are minimized.

Note that, the larger standard deviations observed for these compounds (fluorene, phenanthrene and anthracene) were due to the larger standard deviations obtained with ASE (not visible on Fig. A4 due to the really low concentration levels of these compounds).

Validation on standard reference material urban dust (SRM 1649a)

Six samples (about 50 mg, balance precision = 0.01 mg) of the SRM 1649a (urban dust) were analyzed to validate the accuracy and the precision of the investigated QuEChERS method.

Experimental concentrations were compared with the certified concentrations and the concentrations determined using ASE (

Evaluation of the uncertainties of measurement

The European reference method EN 15549 requires to provide the uncertainty of measurement of B[a]P concentrations associated to the PM 10 (European Committee for Standardization (CEN), 2008). Uncertainties of measurement were evaluated by the GUM approach (Guide to the expression of Uncertainty in Measurement) (Macé et al., 2010). In both cases, ASE and QuEChERS, 90 % of the global uncertainty (sampling + analysis) is due to the analytical procedure.

Details and results of the calculations are reported in the Appendix A. Using ASE, they were in the range 43 -89 % (59 % in average) and for QuEChERS they ranged from 25 to 84 % (43 % in average) (Table A1). For both, higher uncertainties were observed for fluorene due to its low concentration in the SRM 1649a. Finally, the results obtained showed that global uncertainties of measurement using QuEChERS extraction procedure are largely lower than the ones obtained using ASE. By reducing the number of steps and sample handling, experimental errors as such the uncertainties of measurement are minimized using the QuEChERS procedure.

Application to emission samples (wood combustion)

The adopted QuEChERS protocol was then applied to the analysis of PAHs from emission for QuEChERS + d-SPE (Table A2). The application of the QuECHERS + d-SPE procedure resulted to obtain "cleaner" chromatograms improving the PAH quantification.

Clean up procedure by d-SPE using Florisil® was also applied to ambient air PM 10 samples.

Results obtained did not show any significant differences (Student test applied on every independent PAH, α = 0.05) of extraction efficiency by comparison with a simple QuEChERS extraction procedure (Fig. A6). Contrary to emission samples, for this type of sample, the purification step using d-SPE does not appear to be necessary.

Conclusions

The QuEChERS extraction procedure developed in this work for the analysis of particle-bound PAHs in ambient air and emission samples produced identical results compared to the traditional extraction method using ASE. Comparable or improved PAH extraction efficiencies were obtained for different nature of particulate samples (ambient air PM 10 and wood combustion emission). The method was also validated with the analysis of a standard reference material (NIST SRM 1649a).

The QuEChERS extraction procedure is a really quick, easy and effective method which necessitate a minimum of sample handling and steps allowing time saving. It can be reasonably assume that about 200 to 300 sample extractions can be processed per working day using this protocol (8 b Extraction solvent was acetonitrile (ACN) and the direct injection of the sample extracts was realised.

simultaneous
C The recoveries are calculated relative to the certified values of the reference material.

Table 3

Typical limits of quantification (LQ) of atmospheric particle-bound PAH concentrations using the QuEChERS method for three types of particulate samplers (filter section of  = 47 mm).

Calculation of uncertainties of measurement

Uncertainties of measurement of PAH concentrations were evaluated by the GUM approach (Guide to the Expression of Uncertainty in Measurement) (Macé et al., 2010).

Uncertainties due to the analytical procedure and to the sampling procedure were evaluated separately:

² ² ² ² ² ² ² ² ² ² ² ²
With:

  injection volume was 20 µL for ASE extracts and 60 µL for QuEChERS extracts (except for emission samples, 20 µL for both extraction methods). Injection volumes for both extraction methods were different in order to get similar amounts of compounds injected on the HPLC column (QuEChERS extracts were more diluted). Twelve PAHs were quantified by external calibration (Supelco, PAH mix standard solution, 5 points, from 1 to 20 ng ml -1 ) (fluorene, phenanthrene, fluoranthene, pyrene;, benz[a]anthracene (B[a]A), chrysene, benzo[b]floranthene (B[b

  development of the QuEChERS extraction procedure required the evaluation of the influence of different parameters on the PAH extraction efficiency such as, the nature of the solvent of extraction, the shape of the sample, the agitation (extraction) time and the necessity of a clean-up procedure using dispersive-SPE. 3.1. Solvent of extraction ACN and DCM were investigated to determine their suitability as extraction solvent for the QuEChERS based approach. Results obtained are displayed in Fig. 1. Overall, mass of PAH extracted using both solvents were similar. Minor differences were observed for B[a]A, chrysene, B[b]F, B[k]F and B[g,h,i]P. By taking into account the recovery rate of the surrogate standard (6methylchrysene), these differences were not significant (Student test applied on every independent PAH, α = 0.05). According to these results, ACN seemed the most appropriate solvent due to its direct compatibility with the analysis by HPLC-FLD (no solvent concentration step and/or solvent exchange). Other combinations were also tested such as a mixture of ACN/H 2 O (5/2, v/v) and the addition of salts like Na 2 SO 4 or MgSO 4 to ACN, DCM or ACN/H 2 O. The addition of water should favour the partitioning of polar compounds between organic and aqueous phases. The joint addition of desiccant (Na 2 SO 4 or MgSO 4 ) could have improved the PAH extraction (the hydration of the desiccant is an exothermic process potentially increasing the extraction efficiency) (Anastassiades

  results of the influence of the time of agitation (vortex) on the PAH extraction efficiency are presented for phenanthrene, B[a]P and B[g,h,i]P in Fig. 3. After only 30 s of agitation, the PAH extraction was almost complete and the extraction efficiency reached a plateau after 1 min of agitation. Finally, an extraction time (vortex agitation) of 1 min and 30 s was selected for the final

  samples of wood combustion (residential heating) to evaluate a potential effect of the sample matrice (mainly soot in this case) on the efficiency of the extraction method. Obtained extracts were opaque and dark. Their purification was proceeded using a d-SPE clean up procedure with Florisil® as solid sorbent. Purified extracts obtained were yellow/green translucent with Florisil® removing polar components that could interfere during the analysis of PAHs by HPLC-FLD.Average mass of PAHs per filter section quantified using the three different procedures (ASE, QuEChERS and QuEChERS + d-SPE) are presented in Fig.5. It can be emphasized that for the three methods used, the standard deviations obtained were quite large (coefficient of variation -Standard Deviation/Mean -in the range 5 -67 %) due to inhomogeneous repartition of the particulate matter at the surface of the sampling filter. Most of the compounds did not present statistically significant differences between the three extraction methods (Student test applied on every independent PAH, α = 0.05) with the exception of the heavier compounds namely B[g,h,i]P and Ind[1,2,3-cd]P and in a lesser extent B[a]P. For these compounds, higher quantities per filter section were quantified using QuEChERS and QuEChERS + d-SPE procedures. By comparison with ASE, QuEChERS is a soft extraction technique. The extraction is more selective resulting in lower amount of interfering components which induces a noticeable lower noise level in the chromatograms. In combination with the clean up procedure by d-SPE, noise level is even more decreased (Fig.A5). For instance, average signal to noise ratios (S/N) calculated for the B[g,h,i]P, In[1,2,3-cd]P and B[a]P were in the range 14 -50 for ASE, 33 -66 for QuEChERS and 135 -270

  extractions of about 5 to 15 min in total time in comparison to about 20 extractions using ASE). The developed procedure is equally cheap and safe considering the really low volume of solvent used (7 ml). A cost per sample extraction can be estimated (including the cost in solvent and of the different consumables) about 1.7 € in comparison to about 9 € using ASE and more using other solvent based extraction methods. Additionally, no important cost of investment and no maintenance are required ranking the QuEChERS extraction procedure as a really cheap and rugged alternative technique in comparison to all other extraction methods such as SFE or TD-GC-MS. The simplicity of the developed method allows also to minimize the experimental errors and thus the uncertainties of measurement. Obtained quantification limits are in agreement with a mandatory monitoring of PAHs in ambient air (Table 3) and could be proposed as an alternative extraction procedure for the reference methods of measurement of PAHs in ambient air or emission samples (e.g. EN 15549, (European Committee for Standardization (CEN), 2008) as for pesticides in foods of plant origin (EN 15662) (European Committee for Standardization (CEN), 2009). Finally, extractions procedures based on a QuEChERS approach could be applied for the chemical characterization of atmospheric organic particulate matter.

Fig. 1 .

 1 Fig. 1. Comparison of the average PAH quantity extracted according to the extraction solvent used

Fig. 2 .

 2 Fig. 2. Comparison of the average PAH quantity extracted using an entire filter section or with a

Fig. 3 .

 3 Fig. 3. Comparison of the average PAH quantity extracted for phenanthtrene, B[a]P and B[g,h,i]P

Fig. 4 .

 4 Fig. 4. Average PAH concentration ratios determined using QuEChERS and ASE extraction

Fig. 5 .

 5 Fig. 5. Comparison of the average quantity of PAH per filter determined according to the used

  Fig. A3. Comparison of the average PAH quantity extracted according to the extraction

Fig. A4 .

 A4 Fig. A4. Comparison of the average quantity of PAH per filter determined according to the

Fig. A5 .

 A5 Fig. A5. Examples of chromatograms obtained for the analysis of particulate emission

Fig. A6 .

 A6 Fig. A6. Comparison of the average quantity of PAH per filter quantified according to the

  Table 2). The mean experimental concentrations obtained in this study using ASE and QuEChERS extraction methods were generally consistent with the certified values of concentrations with the exception of fluorene. Using QuEChERS method,

	recoveries relative to certified values were in the 81 -111 % range for B[g;h,i]P and fluoranthene /
	pyrene, respectively. For ASE, they were in the 94 -119 % range for B[k]F and D[a,h]A,
	respectively. In both cases, recoveries for fluorene were lower than 80 % (61 and 78 for
	QuEChERS and ASE, respectively). The really low concentration content of this compound in the
	SRM 1649a could explain these results. Overall, using the QuEChERS extraction procedure, all the

PAH recoveries were in the range 80 -120 % in agreement with the European reference method EN 15549 (European Committee for Standardization

(CEN), 2008)

. Standard deviations obtained using QuEChERS protocol were 2 to 5 times lower than the ones obtained with ASE. Experimental errors using a simple extraction method, like QuEChERS, are minimized. The results obtained demonstrated the validity of the extraction procedure developed in this study for the analysis of atmospheric particulate PAHs.

Table 1

 1 Comparison of different particle-bound PAH extraction procedures in terms of time-consumption, solvent volume (per sample) and cost of investment.

	Extraction	Solvent	Extraction	Reduction	Optional clean up	Cost of
	procedure	(volume)	time	time	procedure	investment
	Reflux	Toluene (20 -60 ml)	30 min -1 h	15 -40 min	X	0.2 -1 k€
		Toluene, DCM,
	Soxhlet	hexane:acetone	1 -48 h	> 1 h	X	0.2 -20 k€
		(100 -200 ml)
	Microwave (MAE)	Hexane:acetone (15 -30 ml)	20 min -1 h	15 -30 min	X	25 -35 k€
		Toluene, DCM,
	ASE	DCM:hexane	15 -30 min	15 -30 min	X	50 -100 k€
		(10 ml -40 ml)
	Ultrasonication	DCM, toluene (20 -80 ml)	30 -60 min	15 -40 min	X	0.5 -2 k€
	SFE	CO 2 + DCM, Toluene (5 -15 ml)	30 -45 min	10 -20 min	-	50 -100 k€
	TD-GC-MS	-a	-a	-a	-a	50 -100 k€

a Not applicable (solvent-free method)

Table 2

 2 PAH certified and experimental concentrations (mg kg -1 ) (dry-mass basis) for NIST SRM 1649a (urban dust) and calculated recoveries using ASE and QuEChERS extraction procedures. about 50 mg of SRM 1649a extracted, n = 6. Mass fraction were corrected from the moisture content (4.76 %, Moisture analyser HR 73, Mettler Toledo) and from the recovery of the surrogate standard 6-methylchrysene.

		SRM 1649a	ASE a			QuEChERS a, b
	Compounds	Mass fraction	Mass fraction	Recovery c	Mass fraction	Recovery c
		(mg kg -1 )	(mg kg -1 )	(%)	(mg kg -1 )	(%)
	Fluorene	0.23	± 0.05 0.179 ± 0.024	78	0.139	± 0.012	61
	Phenanthrene	4.14	± 0.37 4.547 ± 0.677	110	4.294	± 0.146	104
	Fluoranthene	6.45	± 0.18 7.118 ± 1.162	110	7.167	± 0.233	111
	Pyrene	5.29	± 0.25 5.501 ± 0.825	104	5.869	± 0.280	111
	B[a]A	2.208 ± 0.073 2.117 ± 0.284	96	2.242	± 0.185	102
	Chrysene	3.049 ± 0.06 3.116 ± 0.529	102	3.074	± 0.144	101
	B[b]F	6.45	± 0.64 6.117 ± 0.947	95	5.432	± 0.413	84
	B[k]F	1.913 ± 0.031 1.807 ± 0.268	94	1.612	± 0.080	84
	B[a]P	2.509 ± 0.087 2.401 ± 0.430	96	2.077	± 0.123	83
	D[a,h]A	0.288 ± 0.023 0.343 ± 0.057	119	0.264	± 0.022	92
	B[g,h,i]P	4.01	± 0.91 4.267 ± 0.703	106	3.228	± 0.272	81
	Ind[1,2,3-cd]P	3.18	± 0.72 3.520 ± 0.590	111	2.612	± 0.107	82

a

  Macé, T., Lalere, B., Labarraque, G., Ravantos, C., Leoz-Garziandia, E., Alleman, L. and Mathé, F. Rédaction de guides pratiques de calcul d'incertitudes et formation des AASQA -Estimation des incertitudes sur les mesurages des B[a]P réalisés sur site dans la fraction PM 10 (3/5) (French language). LCSQA / INERIS / LNE / EMD, 2010, http://www.lcsqa.org/system/files/guides_incertitude_partie3_lne_nov2010_v2.pdf.

Acknowledgements

The authors wish to thank the French Ministry of Ecology, Sustainable Development and Energy (MEDDE) for its financial support and Nadine Guillaumet for her help in HPLC-FLD analyses.

Appendixes A. Supplementary material

Supplementary data associated with this article can be found, in the online version, at http://www.journals.elsevier.com/science-of-the-total-environment. Calculations of uncertainties of measurement are based on samplings realized using high volume samplers DA-80 (Digitel Elektronik AG) (30 m 3 h -1 , 24 h, quartz fibre filters  = 150 mm, Pallflex). We assumed that error made on filter cuts ( = 47 mm) is the same for both, ASE and QuEChERS extraction procedures, and could be considered as negligible (negligible looses of particles). Note that, about 90 % of the global uncertainty is due to the analytical procedure.

Table A2

Average signal-to-noise ratios (S/N) determined for B[a]P, B[g,h,i]P and Ind[1,2,3-cd]P using ASE, QuEChERS and QuEChERS + d-SPE extraction procedures (emission filter sample, n =

3) (see also Fig. A4).