Héctor Valdés
email: hvaldes@ucsc.cl

Andrés L Riquelme

Víctor A Solar

Federico Azzolina-Jury

Frederic Thibault-Starzyk

Frédéric Thibault-Starzyk

Removal of chlorinated volatile organic compounds onto natural and Cu-modified zeolite: The role of chemical surface characteristics in the adsorption mechanism

Keywords: Adsorption mechanism, Brønsted acid sites, chlorobenzene, infrared spectroscopy, natural zeolite, perchloroethylene

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

Introduction

Chlorinated volatile organic compounds (VOCCls) are one of the major sources of air and water pollution [START_REF] Huang | The effect of synergy between Cr2O3-CeO2 and USY zeolite on the catalytic performance and durability of chromium and cerium modified USY catalysts for decomposition of chlorinated volatile organic compounds[END_REF][START_REF] Vu | Removal of hazardous chlorinated VOCs over Mn Cu mixed oxide based catalyst[END_REF]. VOCCls play an important role in the chemical and pharmaceutical industries, where they are used as solvents and reagents. They are employed in aerosols, adhesives and in degreasers in many industrial manufacturing processes as well as in the dry cleaning industry [START_REF] Huang | The effect of synergy between Cr2O3-CeO2 and USY zeolite on the catalytic performance and durability of chromium and cerium modified USY catalysts for decomposition of chlorinated volatile organic compounds[END_REF][START_REF] Lemus | Removal of chlorinated organic volatile compounds by gas phase adsorption with activated carbon[END_REF]. About 1.5 million tons of chlorinated compounds are released into the atmosphere each year [START_REF] Sidebottom | The atmospheric fate and impact of hydrochlorofluorocarbons and chlorinated solvents[END_REF]. Most of these compounds are man-made and are known to be irritants, toxics, carcinogens, and ammables [START_REF] Hsua | Adsorption of chlorinated volatile organic compounds using activated carbon made from Jatropha curcas seeds[END_REF]. VOCCls are mainly regarded as xenobiotics, resistant to biodegradation and therefore they are very persistent in the environment [START_REF] Iranpour | Literature review of air pollution control biofilters and biotrickling filters for odor and volatile organic compound removal[END_REF].

Among VOCCls, carbon tetrachloride, trichloroethane, trichlorethylene and trichlorotoluene can cause significant damage to the environment [START_REF] Usepa | EPA s Terms of Environment Glossar , Abbreviations, and Acron ms[END_REF]. Emissions of these compounds into the atmosphere contribute to the destruction of the ozone layer, to the formation of photochemical smog and global warming. In many countries, the concern about the emissions of VOCCls has increased in the last years; which has led to the emergence of stronger and more restrictive environmental regulations [START_REF] Lemus | Removal of chlorinated organic volatile compounds by gas phase adsorption with activated carbon[END_REF][START_REF] Huang | Chlorinated volatile organic compounds (Cl-VOCs) in environment sources, potential human health impacts, and current remediation technologies[END_REF].

There are some available emission control techniques for the elimination of VOCCls; each one has its own advantages and limitations. Among more conventional treatment processes to control the emissions of VOCCls; adsorption, thermal oxidation, wet scrubbing, catalytic oxidation and biofiltration are included [START_REF] Sidebottom | The atmospheric fate and impact of hydrochlorofluorocarbons and chlorinated solvents[END_REF][START_REF] Khan | Removal of volatile organic compounds from polluted air[END_REF][START_REF] Ghoshal | Selection of appropriate adsorption technique for recovery of VOCs: an analysis[END_REF][START_REF] Van Craeynest | AOPs for VOCs and odour treatment[END_REF]. Adsorption has been widely used as a reliable alternative process to abate VOCCls from industrial emissions due to flexibility, low energy consumption and cheap operating costs [START_REF] Lemus | Removal of chlorinated organic volatile compounds by gas phase adsorption with activated carbon[END_REF][START_REF] Guillemot | Adsorption of perchloroethylene (PCE) in gas phase on zeolites of faujasite type: In uence of water vapour and of Si/Al ratio[END_REF][START_REF] Mouvet | Adsorption isotherms of tri-and perchloroethylene by various natural solids[END_REF]. Microporous materials such as activated carbons, synthetic and natural zeolites have been used as adsorbents in the elimination of VOCCls, since their microporosity acts as a gaseous reservoir [START_REF] Englert | Characterization and environmental application of a Chilean natural zeolite[END_REF].

Activated carbons are commonly selected as adsorbents in many industrial cases due to their high adsorption capacities. However, activated carbons are relatively expensive and difficult to regenerate due to their sensibility to high temperatures and the possibility to ignite [START_REF] Khan | Removal of volatile organic compounds from polluted air[END_REF][START_REF] Baek | Design of dual functional adsorbent/catalyst system for the control of VOC s b using metal-loaded hydrophobic Y-zeolites[END_REF]. On the other hand, synthetic and natural zeolites have been used as adsorbents in the removal of VOCCls from waste gas streams [START_REF] Guillemot | Adsorption of perchloroethylene (PCE) in gas phase on zeolites of faujasite type: In uence of water vapour and of Si/Al ratio[END_REF][START_REF] López-Fonseca | Enhanced activity of zeolites by chemical dealumination for chlorinated VOC abatement[END_REF][START_REF] Chintawar | Adsorption and catalytic destruction of trichloroethylene in hydrophobic zeolites[END_REF][START_REF] Clausse | Adsorption of chlorinated volatile organic compounds on hydrophobic faujasite: correlation between the thermodynamic and kinetic properties and the prediction of air cleaning[END_REF], being attractive alternatives from the technical and economic point of view [START_REF] Englert | Characterization and environmental application of a Chilean natural zeolite[END_REF]. Zeolites have a high thermal stability [START_REF] Hosseini | Sono-dispersion of ceria and palladium in preparation and characterization of Pd/Al2O3-clinoptilolite-CeO2 nanocatalyst for treatment of polluted air via low temperature VOC oxidation[END_REF], which makes them easy to regenerate and to reuse for further process cycles [START_REF] Abdullah | Performance of H-ZSM-5-supported bimetallic catalysts for the combustion of polluting volatile organic compounds in air[END_REF][START_REF] Guillemot | Volatile organic compounds (VOCs) removal over dual functional adsorbent/catalyst system[END_REF]. Unfortunately, the low adsorption capacities of natural zeolites toward VOCCls make them uncompetitive in comparison to activated carbons. Such limitation can be overcome by chemically modifying natural zeolites in order to increase their adsorption capacities. Recent results show an increase in the removal of VOCs using modified natural zeolite with low cost transition metals such as Co, Cu, Mn, and Fe [START_REF] Pozan | Total oxidation of toluene over metal oxides supported on a natural clinoptilolite-type zeolite[END_REF][START_REF] Özçelik | Catalytic combustion of toluene over Mn, Fe and Coexchanged clinoptilonite support[END_REF][START_REF] Yosefi | Abatement of toluene from polluted air over Mn/Clinoptilolite CeO2 nanopowder: Impregnation vs. ultrasound assisted synthesis with various Mn-loading[END_REF][START_REF] Jamalzadeh | Synthesis and physicochemical characterizations of nanostructured Pd/carbon-clinoptilolite-CeO2 catalyst for abatement of xylene from waste gas streams at low temperature[END_REF]. A surface response methodology based on a D-Optimal design of experiments has been applied to identify the transition metal-modified natural zeolite with the highest adsorption capacity for VOCCls [START_REF] Riquelme | Application of D-optimal design for modelling the adsorption of Cl-VOCs onto modified natural zeolites[END_REF]. A succession of ionexchange with ammonium (0.1 mol dm -3 ), thermal out-gassing (350°C), and ion-exchange (0.05 mol Cu 2+ dm -3 ), followed by calcination and reduction at 350°C, is claimed to produce a modified natural zeolite with optimal adsorption properties for the elimination of VOCCls [START_REF] Riquelme | Application of D-optimal design for modelling the adsorption of Cl-VOCs onto modified natural zeolites[END_REF].

Unfortunately, there is a lack of information on the influence of chemical surface characteristics of natural and Cu-modified zeolite on the adsorption of VOCCls. This work aims at some of these issues. In this study, the nature and strength of acidic surface sites of natural and Cu-modified zeolite are characterised by infrared Fourier transform spectroscopy (FTIR) using pyridine and deuterated acetonitrile as probe molecules. Two different VOCCls (perchlorethylene and chlorobenzene) are used here in order to evaluate the effect of the chemical properties of the adsorbate on the adsorption mechanism. In addition, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) is applied to study the adsorption of VOCCls on natural and Cu-modified zeolites. Surface active centres are identified and the nature of their interaction with VOCCls are characterised at a molecular level. Moreover, temperature-programmed desorption (TPD) experiments are conducted in order to obtain information about the adsorption energetic of the VOCCls/zeolite interactions.

Finally, a surface mechanism is proposed for the adsorption of VOCCls over natural and Cumodified zeolites.

Experimental

Materials

Natural zeolite (NZ) was supplied b the Chilean mining compan Minera Formas . NZ was ground and sieved to 0.300 0.425 mm; then it was rinsed with ultra pure water, ovendried at 125°C for 24 h, and stored in a desiccator until its further use. This zeolite is composed of clinoptilolite (53%), mordenite (40%), and quartz (7%) and has been previously characterised using standard techniques, as indicated elsewhere [START_REF] Abreu | Ethylene adsorption onto natural and metal modified Chilean zeolite: an Operando DRIFTS approach[END_REF]. Table 1 summarises the main physical-chemical properties of this zeolite sample. Perchlorethylene (PERC) and chlorobenzene (CLB) were supplied by MERCK (Darmstadt, Germany) with a purity > 99% and were used without further purification. The inlet concentration of the target VOCCl was fixed by vaporising the liquid phase of the VOCCl in a thermally controlled saturator chamber by bubbling argon and then was diluted by mixing with another fresh stream of argon, until reaching the desired inlet concentration, as described in a previous publication [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. Gas flow rates were controlled by mass flow controllers provided by Aalborg Instruments & Controls, Inc. (New York, NY, USA).

All gases used in this study were supplied by PRAXAIR Chile Ltda (Concepción, Chile). Argon 99.999% purity was used as a carrier gas, containing O2 (<1 ppm), N2 (<3 ppm), H2O (<2 ppm), CO2 (<1 ppm) and CO (<1 ppm). Oxygen with 99.8% purity, containing H2O (<3 ppm), THC (<0.5 ppm) was used in the calcination treatment. Hydrogen at 5% (v/v) in argon was applied in the zeolite post-treatment.

Cu was used here as an active transition metal for natural zeolite modification. It was supplied in the form of metal salt by MERCK (Darmstadt, Germany) as copper nitrate (Cu(NO3)2 . 3H2O) with a purity > 99%. Water used in chemical modification treatments was ultra-pure water ( 18.0 M cm) and was obtained from an EASY pure RF II s stem (Barnstead|Thermolyne Corp., Dubuque, IA, USA).

Modification treatment of natural zeolite

The natural zeolite (NZ) was chemically and thermally modified by a succession of two ion-exchange pre-treatments using ammonium salt, followed by thermal out-gassing at 350°C; where Cu 2+ ions were brought into the natural modified zeolite by ion-exchange, followed by calcination in O2 flow at 350°C and reduction in H2 flow at 350°C. A more detailed description of each modification step is given below: Firstly, NZ was modified by two successive ion-exchange treatments using an ammonium sulphate solution (0.1 mol dm -3 ) in order to remove any unwanted cation and prepare the purely acidic form of the zeolite. A ratio of 1.0 g of NZ per 10 cm 3 of solution was applied.

Then, the mix was shaken for 2 h at 90°C and 27 rpm in a thermo-regulated bath (LSB-015S model, Korea). After that, the sample was rinsed with ultra-pure water at 90°C and 27 rpm for 2 h. Ultra-pure water was renovated two times, each one after 1 hour of washing to eliminate the excess of salt. Subsequently, a second ion-exchange using the ammonium sulphate solution was conducted, following the same steps and experimental conditions as described before. Finally, ammonium-exchanged zeolite sample was dried at 125°C for 24 h. Secondly, the purely acidic form of the zeolite was obtained by thermally out-gassing the ammonium-exchanged zeolite sample in a vertical tubular furnace at 350°C. The sample was placed in a quartz U-shaped fixed-bed flow contactor (4 mm ID) and heated at a rate of 1°C min -1 , under argon flow (100 cm 3 min -1 ). When the sample reached a temperature of 350°C, isothermal conditions were kept for 2 h, before quenching to room temperature. The succession of two ion-exchanges using ammonium salt followed by a thermal out-gassing at 350°C were applied since, as it is reported elsewhere [START_REF] Abreu | Ethylene adsorption onto natural and metal modified Chilean zeolite: an Operando DRIFTS approach[END_REF][START_REF] Alejandro | BTX abatement using natural zeolite: the role of Brønsted acid sites[END_REF][START_REF] Alejandro | Oxidative regeneration of toluenesaturated natural zeolite by gaseous ozone: the influence of zeolite chemical surface characteristics[END_REF], these modification pretreatment steps decrease the content of compensating cations with an increase in the content of Brønsted acidic sites and without a significant change in the Si/Al ratio. A lower content of compensating cations improve the diffusion of target VOCs inside the zeolite framework [START_REF] Abreu | Ethylene adsorption onto natural and metal modified Chilean zeolite: an Operando DRIFTS approach[END_REF][START_REF] Alejandro | BTX abatement using natural zeolite: the role of Brønsted acid sites[END_REF][START_REF] Alejandro | Oxidative regeneration of toluenesaturated natural zeolite by gaseous ozone: the influence of zeolite chemical surface characteristics[END_REF]. Moreover, experimental evidences have proved that a reduction in the amount of compensating cations united to the generation of new Brønsted acid sites after thermal outgassing at 350°C plays a fundamental role increasing surface interactions among VOCs and Brønsted active sites [START_REF] Abreu | Ethylene adsorption onto natural and metal modified Chilean zeolite: an Operando DRIFTS approach[END_REF][START_REF] Alejandro | BTX abatement using natural zeolite: the role of Brønsted acid sites[END_REF][START_REF] Alejandro | Oxidative regeneration of toluenesaturated natural zeolite by gaseous ozone: the influence of zeolite chemical surface characteristics[END_REF].

After that, the sample under acidic form was ion-exchanged in a thermo-regulated bath (LSB-015S model, Korea) using a solution of copper nitrate (0.05 mol dm -3 ). Ion-exchange took place using a ratio of 1.0 g of the out-gassed sample per 10 cm 3 of copper nitrate solution, under constant shaking (27 rpm) at 90°C for 2 hours. Later, the Cu-exchanged zeolite sample was rinsed using ultra-pure water, applying the same washing procedure as described before and oven-dried at 125°C for 24 h. Subsequently, two sequence posttreatments were applied to the Cu-exchanged zeolite sample. Post-treatments were performed in a vertical tubular furnace. The Cu-exchanged zeolite sample was loaded into the quartz Ushaped fixed-bed flow contactor and calcined under oxygen flow (100 cm 3 min -1 ), heated at 1°C min -1 and isothermal conditions were kept for 4 h at 350°C. After that, the sample was cooled down to 100°C under the same oxygen flow. Then, the sample was let down to room temperature in the absence of any flow. The calcined sample was further subjected to a reduction post-treatment using H2 at 5% (v/v) in argon flow (20 cm 3 min -1 ) with a heating rate of 1°C min -1 , up to 350°C. After that, the reduced sample was cooled down to 100°C under the same H2 /argon flow. Then, the H2 /argon flow was cut and the sample was cooled to room temperature. It has been demonstrated that the incorporation of copper cations into the zeolite structure improves the adsorption capacity toward VOCs due to the increase of cationic adsorption centres and their interactions with -electrons of the target VOC molecules [START_REF] Riquelme | Application of D-optimal design for modelling the adsorption of Cl-VOCs onto modified natural zeolites[END_REF][START_REF] Abreu | Ethylene adsorption onto natural and metal modified Chilean zeolite: an Operando DRIFTS approach[END_REF]. Thus, the Cu-modified natural zeolite sample (NZ-Cu) was ready to contact the target VOCCl.

Physical-chemical characterisation of natural and Cu-modified zeolite samples

The crystallinities of natural zeolite (NZ) and Cu-modified zeolite (NZ-Cu) samples were verified using a PANal ticalX Pert PRO diffractometer equipped with CuK radiation ( = 0.15418 nm, 40 mA, 45 kV). Diffraction data were collected between 2 values of 5° and 50° at intervals of 0.1° and speed of 2° per min. Specific surface area and pore volume of natural and Cu-modified zeolite samples were determined by nitrogen adsorption-desorption measurements at -196°C using the Brunauer-Emmet-Teller (BET) method and the Barret-Joyner-Halenda (BJH) method in a Micrometrics sorptometer Tri Star 3000. Before nitrogen adsorption, zeolite samples were out-gassed at 350 C for 2 hours.

Fourier transform infrared spectroscopy (FTIR) was used to identify active surface sites of natural and Cu-modified zeolite samples. Zeolite samples were ground using an agate mortar; the resulting powders were pressed (10 7 Pa) into self-supported wafers (2 cm 2 area, 10-20 mg). Then, a wafer was placed into a home-made low temperature quartz cell equipped with KBr windows. A quartz sample holder was used to expose the wafer to the IR beam and to displace it inside a furnace located at the top of the cell for thermal treatments. The IR cell was connected to a vacuum line for evacuation and activation steps (Presidual 10 -3 -10 -4 Pa). A Nicolet Magna 750 IR spectrometer equipped with an MCT detector was used for the acquisition of spectra between 4000 cm -1 and 400 cm -1 . Natural and Cu-modified zeolite samples were activated at 350°C for 6 h under secondary vacuum. The heating rate was set to 0.5°C min -1 in order to avoid any structure damage. Infrared spectra were recorded before (a) and after (b) activation of zeolite samples. Then, samples were cooled down to 150°C under secondary vacuum. After that, pyridine was introduced into the infrared cell system using a calibrated volume of 1.56 cm 3 (6-8 mbar) in order to determine Brønsted and Lewis acidities.

IR spectra were recorded at 150°C during the pyridine dosing process.

Quantification of pyridine was also done in the desorption mode: it was introduced into the IR cell (2 Torr at equilibrium pressure) at 200°C for 30 min to ensure good diffusion inside zeolite channels. Afterwards, secondary vacuum was applied during 15 min at the same temperature in order to eliminate physisorbed pyridine over zeolites. Spectra were then recorded at different temperatures from 200°C to 350°C. IR bands at 1545 and 1454 cm -1 were integrated. In order to quantify Brønsted and Lewis acidic sites, molar absorption coefficients 1545 cm-1 = 1.8 cm.µmol -1 and 1454 cm-1 = 1.5 cm.µmol -1 of the bands at 1545 and 1454 cm -1 for Brønsted and Lewis acidic sites were used, respectively [START_REF] Emeis | Determination of integrated molar extinction coefficients for infrared absorption bands of pyridine adsorbed on solid acid catalysts[END_REF]. The accessible amount of OH groups was estimated by comparing the IR band areas at 3612 cm -1 between the activated samples (without pyridine) and those having pyridine adsorbed on their surface (2 Torr at equilibrium pressure) at 200°C. Finally, the accessibility of OH groups in small pores and even within the side pockets of the mordenite part of natural and Cu-modified natural zeolite samples was quantified using deuterated acetonitrile (CD3CN) by comparing the IR band areas at 3612 cm -1 between the unloaded samples (without deuterated acetonitrile) and those having CD3CN adsorbed on their surface (2 Torr at equilibrium pressure) at 200°C. Deuterated acetonitrile (CD3CN) is preferred over acetonitrile (CH3CN) in order to avoid Fermi resonance between the vibration (CN) and the combination (CH3) + (CC) frequencies [START_REF] Bordiga | Probing zeolites by vibrational spectroscopies[END_REF].

Adsorption experimental procedures

VOCCls adsorption experiments were conducted under dynamic conditions in a quartz Ushaped fixed-bed flow adsorber (4 mm ID) that was connected to a gas chromatograph (GC) coupled with a flame ionisation detector (FID) (Clarus 500 GC, Shelton, CT, USA), as reported elsewhere [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. Argon was used as a carrier gas containing the target VOCCl and circulated over the adsorber already loaded with the selected zeolite sample (NZ or NZ-Cu).

The outlet concentration of VOCCl,

Cl t VOC C
(µmol cm -3 ), was recorded continuously by gas chromatography at the adsorber outlet as a function of time, until the zeolite sample reached the VOCCl saturation. More detailed information about the analytical method used for VOCCl detection and quantification can be found in a previous publication [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. The total amount of VOCCl dynamically adsorbed, q (µmol g -1 ), was obtained from the breakthrough curve, as follows:

t 0 1 s Cl Cl in Cl in t VOC VOC VOC F C C q d t m C ( 1
)
where m is the zeolite mass (g), F is the volumetric flow rate (cm 3 min -1 ), ts is the time needed to reach the zeolite saturation with VOCCl (min), and

Cl in VOC C and t Cl VOC C
are the concentration of the target VOCCl (µmol cm -3 ) at the adsorber inlet and outlet streams as a function of time, respectively.

DRIFTS study of surface interactions among zeolite samples and target VOCCl

Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was applied here to allow distinguishing the various chemical interactions between surface sites on the zeolites and the target VOCCl. DRIFTS operando experiments were performed using a commercial PIKE DiffusIR cell (PIKE Technologies, Fitchburg, WI, USA), containing two ZnSe windows (32 × 3 mm) and a gas flow system that was installed in a Nicolet iS 50 spectrometer (Thermo Fisher Scientific Inc., Waltham, MA, USA) equipped with a DTGS detector, as described in a previous publication [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. A powder sample of natural (or pretreated) zeolite was loaded into a ceramic cup with a porous base. After that, the loaded cup was placed into the DiffuIR chamber. A mirror signal was used here as a reference. Before the measurement, the sample was post-treated inside the DiffuIR chamber, following the same calcination and reduction procedures at 350°C as in Section 2.2. Then, a spectrum of the adsorbate free sample was measured. Spectra were collected with 60 scans at a resolution of 4 cm -1 over the range of 4000 1100 cm -1 . In DRIFTS operando experiments, the adsorption of the target VOCCl (perchloroethylene and chlorobenzene) was conducted using an inlet concentration of 7.6 mol dm -3 at 20°C. The inlet concentration was fixed by vaporising the target VOCCl in a thermally controlled saturator chamber, as described in Section 2.1. The argon stream containing the target VOCCl was passed through the DiffuIR chamber until reaching the saturation and spectra were registered as a function of time. PIKE TempPro software was used for temperature control and data collection. Results were processed with OMNIC 9.0 software.

Temperature-programmed desorption (TPD) of the adsorbed VOCCl

VOCCl TPD experiments were conducted in a temperature-programmable flow microcontactor loaded with 0.3 g of zeolite sample (NZ or NZ-Cu) and coupled to a GC FID for VOCCl detection. Firstly, the target VOCCl (perchloroethylene or chlorobenzene) was injected (50 cm 3 min -1 , 7.6 mol dm -3) over the zeolite sample (NZ or NZ-Cu) until saturation was reached at 20°C and the excess of VOCCl was flushed out using argon (50 cm 3 min -1 ) at the same temperature. The VOCCl was then progressively desorbed using a TPD procedure, as described elsewhere [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. The saturated-sample was heated up to 550°C at a heating rate of 3°C min -1 under an argon flow (100 cm 3 min -1 ). A TPD profile of the evolved VOCCl was obtained using GC FID analysis, as described in a previous publication [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF]. A concentration profile of the evolution of the desorbed VOCCl was recorded as a function of temperature. The total amount of desorbed VOCCl (perchloroethylene or chlorobenzene) per mass of zeolite was determined by integrating the area under the TPD concentration curve, using OriginPro 8 SR0 v8.0725 (B725) software. Physical characteristics of NZ and NZ-Cu are summarised in Table 1. Results show that specific surface area and pore volume increase after the sequences of physicochemical treatments applied here. Such increases in the values of surface area and pore volume could be related to unblocking porous structure of NZ. It has been reported in previous publication that a combination of ion-exchange treatment using ammonium sulphate followed by thermal out-gassing at 350°C reduces the amount of compensating cations in natural zeolite without significant change on the zeolite framework [START_REF] Valdés | Natural zeolite reactivity towards ozone: The role of compensating cations[END_REF]. The presence of different kinds of compensating cations inside of zeolite framework has been responsible to pore clogging [START_REF] Valdés | Natural zeolite reactivity towards ozone: The role of compensating cations[END_REF].

Results and Discussion

Physical-chemical characterisation of natural and Cu-modified zeolite samples

On the other hand, the observed increase on water adsorption capacity on NZ-Cu could be not only related to physical adsorption of water, but also to water interaction with new Lewis acid surface sites formed after Cu 2+ ions inclusion inside the zeolite framework. This could, in turn, generate new (weak) Brønsted acid sites. This band is attributed to the bending vibration (NH) of the NH groups [START_REF] Perra | Remarkable acid strength of ammonium ions in zeolites: FTIR study of low-temperature CO adsorption on NH4FER[END_REF], indicating that this zeolite sample is partially in the NH4 + form before activation, as a consequence of the ion-exchange pre-treatment with ammonia. After activation, NH4 + are removed and NZ-Cu presents free acidic hydroxyl groups. Two IR bands are observed after the activation procedure at 3746 cm -1 and 3612 cm -1 .

These bands are attributed to the vibration of silanol groups (Si-OH) and to the vibration of bridge hydroxyl groups (Si-OH-Al), respectively [START_REF] Thibault-Startzyk | Infrared spectroscopy[END_REF]. The latter band (3612 cm -1 ) is generated after the ion-exchange step pre-treatment of natural zeolite, creating Brønsted acidity. It is worth noting that no band are visible between 3660 cm -1 and 3680 cm -1 , indicating that there is very little or no extra-framework aluminic OH phases formation during the activation of zeolite samples [START_REF] Bordiga | Probing zeolites by vibrational spectroscopies[END_REF]. It is known that depending on the applied zeolite activation method (elimination of water), it can provoke partial dealumination of zeolite with the appearance of extra-framework aluminium (EFAL) species. The latter are usually detected upon pyridine adsorption, showing characteristic IR bands between 3660 and 3680 cm -1 [START_REF] Benaliouche | NH3-TPD and FTIR spectroscopy of pyridine adsorption studies for characterization of Ag-and Cuexchanged X zeolites[END_REF][START_REF] Agudelo | In uence of steam-calcination and acid leaching treatment on the VGO hydrocracking performance of faujasite zeolite[END_REF]. In this work, experimental evidences indicate that under the carried out activation procedure under secondary vacuum a dealumination process is quite unlikely to take place.

Fig. 3-A and 3-B depict IR bands evolution during pyridine dosing at 150°C on NZ and NZ-Cu, respectively. Curves (a) and (f) indicate the smaller and the higher applied doses of pyridine, respectively. Inserted graphs represent IR difference spectra between pyridineadsorbed and activated (pyridine-free) samples. As it can be seen, the band at 3612 cm -1 decreases as a consequence of pyridine interaction with OH acidic groups. Nevertheless, this band does not disappear completely, even after introduction of relatively high amounts of pyridine. This could be due to some of the acidic sites not being accessible to pyridine.

As indicated before, NZ is composed mainly of clinoptinolite (53%) and mordenite (40%).

In the case of the porous framework of mordenite, it is formed by two types of elliptical channels. One of them is a 12-membered oxygen ring channel (6.7 x 7.8 A) and the other one is an 8-membered o gen ring channel (2.9 5.7 A) often called side pockets [START_REF] Król | Theoretical and experimental study of ionexchange process on zeolites from 5-1 structural group[END_REF][START_REF] Gounder | Effects of partial confinement on the specificity of monomolecular alkane reactions for acid sites in side pockets of mordenite[END_REF][START_REF] Nesterenko | Accessibility of the acid sites in dealuminated smallport mordenites studied by FTIR of co-adsorbed alkyl pyridines and CO, Micropor[END_REF] and usually not accessible to pyridine molecules. The overall amount of OH groups accessible to pyridine molecules in our samples remains low (lower than 4%) (see Table 2). It is possible that after Cu 2+ ions incorporation, the opening windows of the 12-membered oxygen ring channel of the mordenite part of natural zeolite are partially blocked. IR bands at 1545, 1492 and 1454 cm -1 increase due to pyridine interaction with accessible Brønsted (B), Lewis and Brønsted (B+L) and Lewis (L) acid sites of zeolites, respectively. and Cu-modified zeolite as temperature increases in the range 200 to 350°C, respectively. As it can be seen, natural zeolite presents a relatively high amount of Lewis acidic sites, probably due to the presence of Al 3+ in the zeolite framework as a consequence of the low Si/Al molar ratio of this zeolite (Si/Al = 5.4). In the case of Cu-modified zeolite, during the ion-exchange pre-treatment step using ammonia, compensating cations balancing the zeolite framework negative charge are replaced by NH4 + ions which will give place to bridged hydroxyl groups generation after the out-gassing procedure at 350°C, creating thus Brønsted acidity. After Cu 2+ ions incorporation into the zeolite sample, Lewis acidity is enhanced. However, it still remains lower compared to that of NZ. It is known that the temperature chosen for zeolite thermal treatments, the solution pH during the ion-exchange process, as well as the nature of the transition metal have a significant influence on the acidic character of zeolite samples [START_REF] Azzolina-Jury | Synthesis and characterization of MEL and FAU zeolites doped with transition metals for their application to the fine chemistry under microwave irradiation[END_REF]. The acidity presented in NZ-Cu could be explained by partial dealumination which causes zeolite dehydroxylation during the earlier thermal treatments applied to natural zeolite.

The creation of several stacking faults in zeolite framework as well as the formation of copper clusters blocking the pores could explain the quite low accessibility of the OH groups of this sample. It is worth noticing that pyridine also interacts with isolated weakly acidic silanol groups (see the diminution of the IR band at 3746 cm -1 ) as a consequence of the partial obstruction of more acidic OH groups in both samples. Results listed in Table 2 reveal the presence of acidic surface sites of different strength.

The amount of pyridine that remains adsorbed after heating zeolite samples from 200 to 350°C is related to the strength of Brønsted and Lewis acidic sites. Low (200 250ºC), mid (300°C) and high (350ºC) temperature ranges could be related to the desorption of pyridine from weak, middle and strong acidic sites, respectively. Thus, the strongest Brønsted and Lewis acidic sites are calculated as the amount of pyridine retained after heating the samples up to 350°C. On the one hand, the strength of Brønsted acidic sites is found to be enhanced after physicochemical transformation of natural zeolite (61.6% of pyridine remains adsorbed in NZ-Cu compared to 13.9% in NZ) and could be related to the sequence applied treatments of ammonium exchange, thermal out-gassing followed by post-calcination and hydrogen reduction at 350°C; as well as to copper position within the zeolite framework. On the other hand, the strength of Lewis acidic sites in natural zeolite is not significantly modified after the applied chain of treatments conducted here (41.3% of pyridine remains adsorbed on NZ after out-gassing at 350°C compared to 47.7% for NZ-Cu).

The accessibility of deuterated acetonitrile (CD3CN) to OH groups is presented in Table 3.

As it can be noticed, OH groups of natural zeolite are not accessible, even using CD3CN.

However, the amount of accessible OH groups of Cu-modified zeolite using CD3CN is higher than those when pyridine (C5H5N) is applied (see Table 1). CD3CN is a basic probe with a smaller molecular size than C5H5N. Nonetheless, the OH groups accessibilit is still far awa from 100%, confirming partial zeolite pore blockage.

Table 3. Accessible OH groups to deuterated acetonitrile (CD3CN) of natural (NZ) and Cumodified zeolite (NZ-Cu).

Sample Accessible OH groups (%)

NZ -NZ-Cu 68.24

DRIFTS study of surface interactions among zeolite samples and target VOCCl

DRIFTS spectra of natural (NZ) and Cu-modified zeolite (NZ Cu) during the adsorption of target VOCCl are depicted in Fig. 5 and6, respectively. Fig. 5 Infrared vibration bands at 3730 cm -1 , 3700 cm -1 , and 3570 cm -1 are probably perturbed after zeolite exposure to gaseous VOCCl (perchloroethylene and chlorobenzene) due to their interaction with zeolite active sites. The presence of new Lewis acid sites after Cu 2+ incorporation into NZ lattice, are responsible for the observed enhancement of water adsorption. Therefore, new Brønsted acid sites are induced in Cu-modified zeolites upon water adsorption. In the presence of water, introduced copper over zeolite framework may first tend to coordinate water molecules that then through a dissociative chemisorption led to the observed increase in the IR signal of OH groups. In both samples, the IR bands between 3730 and 3570 cm -1 are ascribed to OH groups of adsorbed water from carrier gas coming together with VOCs. An IR band located at 1629 cm -1 in both samples corresponds to flexion vibrations of the OH groups of residual water [START_REF] Thibault-Startzyk | Infrared spectroscopy[END_REF][START_REF] Mariey | FT-IR study of coked HY zeolite regeneration using oxygen or ozone[END_REF][START_REF] Byrappa | Characterization of zeolites by infrared spectroscopy[END_REF]. This band is closely related to IR bands from 3730 to 3570 cm -1 . Vibrational IR modes in the range between 1300 and 600 cm -1 correspond to zeolite lattice structure. These IR bands are caused by the stretching and bending modes of the T-O units. Double ring vibrations are found in the IR region between 650-600 cm -1 and between 1300-700 cm -1 related to O-T-O and T-O-T symmetric and antisymmetric stretching vibrations, respectively [START_REF] Jentys | Introduction to Zeolite Science and Practice[END_REF][START_REF] Ballandras | Communication: Evidence of structural phase transitions in silicalite-1 by infrared spectroscopy[END_REF]. Such bands have little or no modification during the adsorption and desorption of the VOCCl.

In the spectrum of perchloroethylene adsorption (see Fig. 5-A and Fig. 6-A), a decrease in the intensity of the IR bands from 3730 to 3570 cm -1 is observed for both NZ and NZ-Cu.

Additionally, a wide band around 1629 cm -1 is recorded in the low wavenumbers of the spectral range (see Fig. 5-A and Fig. 6-A). This band could be related to water reappearance coming in the carrier gas. In both samples, it is also observed an IR band increasing upon contact with perchloroethylene at 920 cm -1 . This band is assigned to perchloroethylene in gas phase after sample surface saturation. Perchloroethylene interacts, in both NZ and NZ-Cu samples, with their weakly acidic OH groups formed through water adsorption on zeolites. In the case of NZ-Cu, unlike NZ samples, the interaction of perchloroethylene with OH groups of adsorbed water is much higher because of the introduction of new Lewis acid sites (Cu 2+ ).

Similar behaviours to perchloroethylene interactions are observed in the case of chlorobenzene adsorption (see Fig. 5-B and Fig. 6-B). A decrease in the intensity of the IR bands from 3730 to 3570 cm -1 is also noticed in both zeolite samples. Analogous to perchloroethylene adsorption, in the case of chlorobenzene a band at 1629 cm -1 is also registered at lower wavenumbers (see Fig. 5-B and Fig. 6-B). This signal is also ascribed to the reappearance of residual water coming in the carrier gas. In the case of NZ-Cu, in contrast to NZ samples, chlorobenzene interacts more strongly with new OH groups formed as a consequence of water adsorption over new Lewis acid sites generated by the insertion of copper. Additionally, the stretching vibrations of the aromatic ring of chlorobenzene molecule in the gas phase at 1589 and 1500 cm -1 (spectrum not shown here) [START_REF] Govindarajan | FT-Raman and UV spectral investigation: Computed frequency estimation analysis and electronic structure calculations on chlorobenzene using HF and DFT[END_REF][START_REF] Reichenbächer | Challenges in Molecular Structure Determination[END_REF] are recorded, indicating that both zeolite samples reach saturation by chlorobenzene. profiles of perchloroethylene and chlorobenzene, respectively. In the case of perchloroethylene desorption from both zeolite samples, two overlapping peaks are observed.

Temperature-programmed desorption (TPD) of the adsorbed VOCCl onto zeolite samples

Lower temperature peaks reach a maximum around 109°C, being close to the boiling point of perchloroethylene (121°C). Such results could be related to the desorption of physisorbed perchloroethylene molecules. Second non-resolved peaks with a maximum desorption temperature around 200°C point out the presence of adsorption sites of higher strength. The evolution of perchloroethylene at 200°C from both zeolite samples could be related to perchloroethyelene interaction with strong acid sites. It is well known that the required energy to release a base probe molecule from acid sites is associated to the strength of the chemical bonds (acid strength) [START_REF] Valdés | Natural zeolite reactivity towards ozone: The role of compensating cations[END_REF]. However, different results are exhibited for chlorobenzene evolution, where TPD profiles reveal two well-defined peaks in both samples. The first peaks with a maximum at 72°C could be related to the desorption of physisorbed chlorobenzene molecules, being congruent with its boiling point (131ºC). Second resolved peaks with a maximum around 300°C reflect how strongly some chlorobenzene molecules are bonded to active surface sites. In addition, the amounts of thermally desorbed perchloroethylene and chlorobenzene are lower than the adsorbed amounts (see Table 4). These results not only reflect the influence of molecular size of the target VOCCl on the adsorption capacity but also corroborate the existence of chemical surface interactions between the VOCCl and the active surface sites of zeolite samples. In particular, the highest observed adsorption capacity of NZ-Cu towards perchloroethylene could be related to a higher migration of perchloroethylene molecules through the channels of this zeolite sample, reaching more available adsorption sites in the small cages, compared to NZ zeolite. Results listed in Table 4 show that perchloroethylene and chlorobenzene are thermally desorbed from NZ-Cu at 74% and 30%, respectively; whereas from NZ they are thermally evolved at 93% and 52%, respectively. The lowest desorbed amount of chlorobenzene molecules from NZ-Cu zeolite might be a consequence of strong chemical interactions between chlorobenzene molecules and Brønsted acid sites of this zeolite framework. Such results are in agreement with those obtained by DRIFTS analyses.

These results suggest that chlorobenzene and perchloroethylene are bonded to different types of OH groups of NZ-Cu surface with varying adsorption strength distributions. A higher amount of evolved perchloroethylene at mid temperature could be related to the interaction with OH groups original present on the zeolite surface; whereas upper temperature evolution of chlorobenzene could be associated to strong interactions with OH groups formed after the applied modification treatments. Therefore, TPD results evidence the different adsorption strength of the formed electron pair donor-acceptor surface complex, as described in another publication [START_REF] Lercher | Infrared studies of the surface acidity of oxides and zeolites using adsorbed probe molecules[END_REF].

Mechanistic approach

Perchloroethylene and chlorobenzene adsorption onto NZ and NZ-Cu could be represented by a mechanism that incorporates the interaction not only with Brønsted (Z-OH) sites present on the original natural zeolite framework; but also with new Brønsted acid sites, formed as a consequence of dissociative chemisorption of water molecules over new Lewis acid sites generated due to the insertion of copper after the successive treatments applied in this work (see Fig. 8). (2):

Z-OH + VOCCl Z-OH•••VOCCl (2)
The adsorption interaction of VOCCls with active surface sites of natural and Cu-modified zeolites is modelled using the Langmuir adsorption approach. The rate of adsorption- ) is the concentration of the target VOCCl. An analogous adsorption mechanism has been suggested to represent the adsorption of VOCs onto acidic zeolites [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF][START_REF] Knozinger | IR spectroscopy of small and weakly interacting molecular probes for acidic and basic zeolites[END_REF].

When the equilibrium is reached, the rates of adsorption and desorption are the same and the adsorption equilibrium constant is described, according to Eq. ( 4):

ad des Cl Z OH Cl eq Z OH v VOC k {Z OH VOC } K k { Z OH }C (4)
where Keq (dm 3 mol -1 ) is the adsorption equilibrium constant of the VOCCl surface complex formation at Brønsted acid sites.

A site balance is used to eliminate the unknown acidic surface site concentration,{Z-OH}v. Thus, the total concentration of Brønsted acid sites, Zt (mol m -2 ), is given by Eq. ( 5):

t v C l Z {Z OH} {Z OH VOC } (5)
Replacing Eq. ( 5) into Eq. ( 3) results in Eq. ( 6), which is the usual form of the Langmuir equation:

Cl Cl Cl Cl eq VOC t VOC A Z OH VOC eq VOC K C Z S N 1 K C (6)
where As it can be seen in Table 5, the values of maximum adsorption capacities (Zt) of Cumodified zeolite toward both target VOCCls are increased after the successive chemical and thermal treatments applied to the natural zeolite. These results agree with those previously reported for the adsorption of different kind of VOCs onto synthetic mordenite zeolites, natural and acid-treated natural mordenite [START_REF] Valdés | Control of released volatile organic compounds from industrial facilities using natural and acid-treated mordenites: The role of acidic surface sites on the adsorption mechanism[END_REF][START_REF] Kim | Binary adsorption of very low concentration ethylene and water vapor on mordenites and desorption by microwave heating[END_REF][START_REF] Arletti | Location of MTBE and toluene in the channel system of the zeolite mordenite: Adsorption and host guest interactions[END_REF][START_REF] Martucci | Adsorption mechanism of 1,2-dichloroethane into an organophilic zeolite mordenite: A combined diffractometric and gas chromatographic study[END_REF]. The highest adsorption capacity obtained by NZ-Cu zeolite could be due to a combination of physical and chemical factors.

As discussed before, the physicochemical transformation of NZ into NZ-Cu, produces a zeolite with a higher specific surface area, pore volume and with a similar strength of Lewis acidic sites but with stronger Brønsted acidic sites. The small cross-sectional area of perchloroethylene molecules (0.18 nm 2 ) as compared to chlorobenzene molecules (0.24 nm 2 ) might allow easier access for perchloroethylene molecules to acidic sites in the small pores of both zeolite samples. In the case of NZ, narrow pores impose higher spatial constraints, reducing the adsorption capacity of this sample toward perchloroethylene and chlorobenzene molecules. Indeed, results suggest that NZ might inhibit the access of chlorobenzene molecules to acidic surface sites, leading to a reduction on the observed adsorption capacity of this zeolite sample. In the case of NZ-Cu zeolite the adsorption capacity is less affected.

Chlorobenzene molecules could migrate inside this zeolite framework, having a dual-site interaction at acidic hydroxyl sites such as Si(OH)Al and silanol groups original present in natural zeolite and also at OH groups formed over Lewis acid sites like Cu + cations due to dissociative chemisorption of water in modified natural zeolite surface, forming adsorption complexes [START_REF] Lercher | Infrared studies of the surface acidity of oxides and zeolites using adsorbed probe molecules[END_REF].

Conclusions

Results indicated that a succession of ion-exchange with ammonium salt, thermal outgassing at 350°C, and ion-exchange using Cu 2+ salt (0.05 mol dm

Fig. 1 .

 1 Fig. 1. X-ray powder diffraction patterns: (A) natural zeolite, NZ, (B) Cu-modified natural

Fig. 2 -

 2 Fig. 2-A and 2-B display IR spectra recorded before (a) and after (b) activation of NZ and NZ-Cu, respectively. The IR band at 1630 cm -1 is assigned to the bending vibration of OH

Fig. 2 .

 2 Fig. 2. Infrared spectra of zeolite samples: (A) natural zeolite, NZ, (B) Cu-modified zeolite,

1 2Fig. 3 .Fig. 4 -

 134 Fig. 3. Evolution of infrared bands of zeolite samples during pyridine dosing process at

1 20Fig. 4 .

 14 Fig. 4. Evolution of infrared bands during pyridine desorption from zeolite samples at

  -A and 5-B show DRIFTS evolution during perchloroethylene and chlorobenzene adsorption onto NZ sample, respectively; while Fig. 6-A and 6-B show DRIFTS evolution during perchloroethylene and chlorobenzene adsorption onto NZ-Cu sample, respectively. It is worth noticing that the quality of Figures 5 and 6 are quite much lower than that of Figures 2 to 4, since Fig. 5 and 6 were obtained using DRIFTS under flow conditions and Fig. 2 to 4 were acquired under partial vacuum using IR transmission technique.

Fig. 5 .Fig. 6 .

 56 Fig. 5. Variation of DRIFTS spectra as a function of contact time during VOCCl adsorption

Fig. 7

 7 Fig. 7 displays the TPD profiles of the target VOCCls previously adsorbed on natural

Fig. 7 .

 7 Fig. 7. Temperature-programmed desorption profiles of adsorbed VOCCl: (A)

b

  Total amount of desorbed VOCCl after heating the sample under Ar flow (100 cm 3 min -1 ) up to 550 ºC at 3 ºC min -1 .

Fig. 8 .

 8 Fig. 8. Schematic representation of the interaction of perchloroethylene and chlorobenzene

Fig. 9 -

 9 Fig. 9-A and Fig 9-B display adsorption equilibrium data obtained at 20 ºC of

Fig. 9 .

 9 Fig. 9. Influence of acidic sites of zeolite samples on the adsorption of VOCCl: (A)

- 3 )

 3 followed by calcination and reduction under hydrogen at 350°C produced a Cu-modified zeolite with increased adsorption capacity for the elimination of VOCCl compared to the natural zeolite. DRIFTS assays revealed that the modified zeolite contains mainly a single class of active site for the adsorption of VOCCl. DRIFTS spectra indicated that the modified NZ-Cu zeolite exhibits an enhanced acidic character due to the presence of Brønsted acid sites present on the original natural zeolite framework together with new Brønsted acid sites formed after the applied modification treatments. In the presence of water, water was adsorbed on new Lewis acid sites generated after copper incorporation into the zeolite structure, leading to the formation of new Brønsted acid sites through a dissociative chemisorption. Hence, Brønsted acid sites play a fundamental role in the adsorption mechanism of VOCCl. Assessed targets VOCCl interacted with Brønsted acid sites, forming hydrogen bonds. A combination of chemical and thermal treatment results in a powerful procedure to improve the adsorption capacity of natural zeolitic materials as potential adsorbents for the removal of VOCCl from contaminated industrial streams.

Table 1 .

 1 Physical characterisation of natural (NZ) and Cu-modified zeolite (NZ-Cu).

	Properties

Cu Surface area a (m 2 g -1 )

		Si/Al	5.32	5.17
		Si	65.39	67.67
		Al	12.29	13.08
		Ca	11.13	4.12
		Fe	5.27	4.72
		Na	2.12	0.30
		K	1.90	0.88
	Elemental analysis b (%)	Ti	0.89	0.74
		Mg	0.53	0.24
		Mn	0.13	0.08
		Sr	0.12	0.08
		S	0.05	0.05
		Zr	0.05	0.04
		Zn	0.02	0.02
		Cu	ND	7.88
		BET	241	312
		t-Plot Micropore	224	284
		t-Plot External	17.8	28.8
		Micropore	0.07	0.11
	Pore volume a (cm 3 g -1 )	Mesopore	0.05	0.06
		Total	0.12	0.17
		BET	2.2	2.2
	Average pore diameter a (nm)	BJH	10.5	8.6
		D-H	9.9	8.3
	Water adsorption capacity (%wt-dry)	11.8	13.1

a Determined from nitrogen adsorption-desorption isotherms b Determined by X-Ray Fluorescence

Table 2 .

 2 Lewis and Brønsted acidic site content (µmol g -1 ) of natural (NZ) and Cu-modified zeolite (NZ-Cu), detected by quantifying the amount of pyridine retained after heating the samples from 200 to 350°C.

	Sample	Heating Temperature (°C)	Lewis acid sites (µmol g -1 )	Brønsted acid sites (µmol g -1 )	Total acidity (µmol g -1 )	Accessible OH groups
		200	115.6	23.7	139.3
		250	80.5	25.4	105.9
	NZ					-
		300	69.6	17.9	87.5
		350	60.3	9.9	70.2
		200	27.7	11.2	38.9
		250	20.0	11.2	31.2
	NZ-Cu					3.4%
		300	17.2	11.5	28.7
		350	12.4	9.4	21.8

Table 4 .

 4 Comparison of perchloroethylene and chlorobenzene adsorption and desorption on natural zeolite (NZ) and Cu-modified zeolite (NZ-Cu).

		Qa a ( mol g -1 )	Qd b ( mol g -1 )
	VOCCls
		NZ	NZ-Cu	NZ	NZ-Cu
	Perchloroethylene	68.5	177.9	63.8	131
	Chlorobenzene	51.8	166.5	26.8	50.3
	a Total amount of adsorbed VOCCl at 20°C.

Table 5

 5 lists the equilibrium parameters of the Langmuir model, such as: the maximum adsorption capacity, Zt, and the adsorption equilibrium constant, Keq, together with the correlation factor R 2 . Adsorption data are well-adjusted to the Langmuir model.

Table 5 .

 5 Comparison of Langmuir adsorption equilibrium constants of perchloroethylene and chlorobenzene onto natural (NZ) and Cu-modified zeolite (NZ-Cu) at 20ºC.

	Sample	VOCCl	Zt ( mol g -1 )	Zt (m 2 m -2 )	Keq (dm 3 mol -1 )	R 2
		Perchloroethylene	93	0.42	1.52	0.89
	NZ
		Chlorobenzene	71	0.43	1.25	0.94
		Perchloroethylene	222	0.77	0.61	0.96
	NZ-Cu
		Chlorobenzene	179	0.82	0.63	0.87

Acknowledgements

This research was financially support by CONICYT, FONDECYT/Regular (Grant No. 1130560). A.L. Riquelme thanks the Programa de Magíster en Ingeniería Industrial from the Universidad Católica de la Santísima Concepción for providing a Master research fellowship.


Alexandre Tissier
email: alexandre.tissier2@insa-rennes.fr

Wassim Hamidouche

J Vanne

F Galpin

Daniel Menard
email: dmenard@insa-rennes.fr

CNN ORIENTED COMPLEXITY REDUCTION OF VVC INTRA ENCODER

Keywords: Versatile Video Coding (VVC), Convolutional Neural Network (CNN), Multi-Type Tree (MTT), Complexity

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

INTRODUCTION

The explosion of IP video traffic [START_REF]Cisco Visual Networking Index : Forecast and Trends, 2017-2022[END_REF] alongside emerging video formats like 4K/8K and 360-degree videos call for novel video codecs whose coding efficiency goes beyond the limits of the current High Efficiency Video Coding (HEVC) standard [START_REF] Sullivan | Overview of the High Efficiency Video Coding (HEVC) Standard[END_REF]. The International Telecommunication Union (ITU) and ISO/IEC Moving Picture Experts Group (MPEG) formed the Joint Video Expert Team (JVET) to address this new challenge by introducing a video coding standard called Versatile Video Coding (VVC) [START_REF] Bross | Versatile Video Coding (Draft 6)[END_REF]. JVET is also developing a VVC reference software called VVC Test Model (VTM) that implements all normative VVC coding tools for practical rate-distortioncomplexity evaluation and conformance testing. The latest version of VTM is VTM6. 1. This work addresses the All Intra (AI) coding configuration of VTM6.1. It is shown to improve intra coding efficiency by 24% [START_REF] Bossen | AHG report: Test model software development (AHG3)[END_REF] over that of the HEVC reference implementation HEVC test Model (HM)16.20. According to [START_REF] Wieckowski | Fast Partitioning Decision Strategies for The Upcoming Versatile Video Coding (VVC) Standard[END_REF], around one third of this coding gain (8.5%) is obtained by extending a Quad-Tree (QT) block partitioning scheme of HEVC with a MTT partitioning, which also supports Binary-Tree (BT) and Ternary-Tree (TT) splits.

This work is partially supported by the French FUI project EFIGI, the REACTIVE project funded by Brittany region, the ANR CominLabs Labex, and the Academy of Finland (decision no. 301820) Fig. 1(a) illustrates the split types specified in VVC. As in HEVC, the QT split divides a Coding Unit (CU) into four square sub-CUs of the same size. In addition, VVC specifies the BT and TT split types that allow rectangular CU shapes. The BT split divides a CU into two sub-CUs of equal size whereas the TT split yields three sub-CUs with the ratio 1:2:1. The BT and TT splits are allowed in both horizontal (BTH and TTH) and vertical directions (BTV and TTV). However, the QT split is forbidden after either one BT or TT split has been initiated in the partitioning. The VTM encoder relies on the Rate-Distortion Optimization (RDO) process that calculates Rate-Distortion (RD)-cost for each split and finally selects the block partitioning with the lowest RD-cost. Fig. 1(b) shows a possible CTU partitioning with the QT, BT, and TT splits.

Split QT Split BT-V Split BT-H Split TT-V Split TT-H No Split (b) (a)
In this paper, we propose an efficient, CNN-based complexity reduction technique for VTM6.1 intra encoder. The CNN is fed with a 64×64 pixels luminance CU and it creates a vector that gives probabilities of having edges at the 4×4 boundaries of the block. This probability vector is further exploited by the encoder to skip unlikely splits. Our previous CNN based technique was already proposed in [START_REF] Galpin | CNN-Based Driving of Block Partitioning for Intra Slices Encoding[END_REF] to reduce the encoding complexity of an earlier version of VVC reference software with obsolete split types. This work extends our previous approach [START_REF] Galpin | CNN-Based Driving of Block Partitioning for Intra Slices Encoding[END_REF] to the latest VVC split types as well as the newly introduced coding tools in VTM6.1. To the best of our knowledge, no complexity reduction technique is currently based on a CNN for complexity reduction of the VTM encoder.

The remainder of this paper is organized as follows. Section 2 briefly describes state-of-the-art techniques. Section 3 introduces the proposed method and its integration into the VTM6.1 encoder. Section 4 presents the experimental setup and assesses the complexity Fig. 2: The CNN structure with convolution layers in orange and yellow, max-pooling layers in red and fully connected layer in purple.

reduction under the VVC Common Test Conditions (CTC). Finally, Section 5 concludes the paper.

RELATED WORKS

In recent years, several approaches have dealed with VVC complexity reduction. The existing techniques reduce the MTT partitioning search space of QT, BT and TT splits [START_REF] Amestoy | Tunable VVC Frame Partitioning Based on Lightweight Machine Learning[END_REF], [START_REF] Fu | Fast CU Partitioning Algorithm for H.266/VVC Intra-Frame Coding[END_REF]- [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] or evaluate a reduced set of intra prediction modes [START_REF] Yang | Low Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding[END_REF], [START_REF] Ryu | Machine Learning-Based Fast Angular Prediction Mode Decision Technique in Video Coding[END_REF]. Additionally, our previous study [START_REF] Tissier | Complexity Reduction Opportunities in the Future VVC Intra Encoder[END_REF] presents the complexity reduction opportunities in the VVC intra encoder of intra mode prediction, multiple transform choice and MTT partitioning. It shows that the MTT partitioning has the largest opportunities in term of complexity reduction. Fu et al. [START_REF] Fu | Fast CU Partitioning Algorithm for H.266/VVC Intra-Frame Coding[END_REF] proposed two distinct fast block partition techniques through Bayesian decision rule. The first one explores information of previously tested BTH split to skip vertical split with a binary classification. The second technique intends to skip TTH split, depending on both sub-CUs partitioning and intra prediction mode. TTH split can also be skipped based on RD-cost difference between BTH and BTV. Yang et al. [START_REF] Yang | Low Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding[END_REF] focused first on MTT partitioning search through several binary classification problems. They used global texture information, local texture information, and context information for the classification. Secondly, they proposed a fast intra mode decision using one-dimensional gradient descent search. Lei et al. [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF] proposed a technique to pre-process prediction information in order to skip redundant partition modes. Hadamard cost determines first the intra prediction mode for sub-CUs of the BT split. The optimal intra mode is further evaluated by using accumulated RD-cost of sub-CUs as an estimate of the RD-cost of their parent partition in order to prune sub-optimal modes. Park et al. [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] used a probabilistic approach and exploited the RD-cost of a previously encoded CU with BT splits to skip TT splits The decision to skip the RDO process of TT splits depends on the difference of RD-cost between BTH and BTV.

Compared with prior-art, our solution takes a step forward and reduces the complexity of VTM6.1. Unlike the others, it uses a CNN to predict optimal coding partitions and reduce the complexity of MTT partitioning search.

PROPOSED METHOD

In the VTM encoder, MTT partitioning has high complexity due to its exhaustive RDO search process, which goes through all possible splits to get the optimal partitioning. This section presents the CNN structure, the CNN training, and its integration into VTM6.1.

CNN structure

The BT and TT splits introduced in the VTM push machine learning techniques to multiply the number of classifiers [START_REF] Amestoy | Tunable VVC Frame Partitioning Based on Lightweight Machine Learning[END_REF], [START_REF] Yang | Low Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding[END_REF]. For instance, in [START_REF] Yang | Low Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding[END_REF], the authors proposed a cascade decision framework through 5 binary classifiers. This multiplication of classifiers can be an issue with their high computational inference time. CNN is computationally intensive that makes it necessary to limit the number of inferences as well as the CNN structure size. The objective of our solution is to limit the access to the CNN by predicting output probabilities for all recursive splits within 64×64 CU at a time.

The CNN illustrated in Fig. 2 is inspired by ResNet [START_REF] He | Deep Residual Learning for Image Recognition[END_REF]. The orange layers represent a convolution with 3x3 kernel (Conv 3x3), whereas the yellow layers denote a convolution with 1x1 kernel (Conv 1x1) that allows the addition (marked in green) between layers with different dimensions. The red layers represent a maxpooling with a window of 2x2 (Max Pool). Finally, the purple layer is a fully connected layer (Dense) that predicts the vector of 480 probabilities which represents the 64×64 CU partitioning.

The CNN input is a 65×65 luminance block composed of a 64×64 CU plus one additional line on the top and left of the CU for intra mode computation. The prediction is a probability vector that corresponds to the 4×4 block boundaries of the 64×64 CU partitioning. The input and output sizes of the CNN correspond to the maximum CU size of the luminance in AI configuration (64×64). Fig. 3 presents the matching between the CU partitioning and the probability vector. For instance, the first value of the vector corresponds to the first bottom boundary of the top-left 4×4 block.

S4

Fig. 3: Correspondence between a predicted probability vector and a partitioning of 64×64 CU.

Training process

The training process optimizes the CNN weights in order to minimize the loss function, which is defined as

L = ||y -ỹ|| 2 2 + λ k c k , (1)
where y is the ground truth probability vector, ỹ is the predicted probability vector, || • ||2 stands for the l2 norm, and λ = 10 -5 . Regularizers are applied on the kernels of convolutional layer c k . These penalties are incorporated in the loss function.

Optimization of the CNN is performed using Adam optimizer with the default parameters provided in [START_REF] Diederik | Adam: A Method for Stochastic Optimization[END_REF]. The training is carried out under Python3.6 with the Keras framework [START_REF] Franc | [END_REF] running on top of Tensorflow [START_REF] Abadi | TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems[END_REF]. The model is trained for 10 epochs with a batch size of 256 on a GPU (RTX 2080 Ti).

An input dataset of 65×65 luminance blocks and its corresponding ground truth vectors is conceived. The 65×65 luminance blocks are extracted from Div2k [START_REF] Agustsson | NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study[END_REF] and 4K image [START_REF] Makov | [END_REF] datasets. These datasets are only composed of still images as our solution focuses on AI configuration. This brings more diversity than a training with video datasets only. No CTC [START_REF] Bossen | JVET common test conditions and software reference configurations for SDR video[END_REF] sequences are used for the training. The CNN takes as an input a 65×65 luminance block normalized between [0 , 1]. The input dataset is encoded by VTM6.1 anchor under AI configuration in order to establish the corresponding ground truth. The MTT partitioning information is gathered for each 64×64 CU and converted to the output format of the CNN, i.e. ground truth vectors of 480 probabilities composed of one (split) and zero (not split).

Inference in VTM

The proposed solution is implemented in the VTM6.1. The CNN inference is carried out in C++ through the frugally-deep library [START_REF] Hermann | Frugally Deep[END_REF] with a trained Python model. This framework offers a conversion from the model trained in Python to a file interpretable in C++.

Fig. 3 illustrates the skip process for the horizontal splits, i.e. BTH and TTH splits. Their probabilities are deduced as follows. The mean probabilities are first computed on the segments S1, S2, S3, and S4, denoted by P(S1), P(S2), P(S3), and P(S4), respectively. The probability of the BTH split, denoted by P(BT H), is the minimum between the probabilities of S2 and S3 as defined in P(BT H) = min(P(S2), P(S3)).

(2)

The probability of the TTH split is computed with its respective segments as (min(P(S1), P(S4)). The vertical splits, i.e. BTV and TTV splits, follow the same procedure but with vertical segments.

Regarding the QT split probability, P(QT ) is calculated from the probabilities of the BTH and BTV splits as

P(QT ) = min(P(BT H), P(BT V )). (3)
In all these cases, a split S ∈ {QT, BT H, BT V, T T H, T T V } is skipped if P(S) is below a predefined threshold value β. By means of this threshold, our solution is able to offer different rate-distortioncomplexity characteristics. The higher the threshold value β, the less splits take place, which results in both higher complexity reduction and coding loss. Our solution supports a threshold value range of β ∈ {0, 100}.

EXPERIMENTAL RESULTS

This section details the experimental setup and analyses our results over the state-of-the-art techniques. Several configurations of our solution are assessed in order to propose different rate-distortioncomplexity trade-offs.

Experimental setup

All our experiments were conducted under AI configuration with VTM version 6. [START_REF] Bjontegaard | Calculation of average PSNR differences between RD-curves[END_REF] and complexity reduction with ∆ Encoding Time (∆ET) that is determined as

∆ET = 1 4 QP i ∈{22,27,32,37} TR(QPi) -TC (QPi) TR(QPi) , (4)
where TR is the reference encoding time of the VTM6.1 anchor and TC encoding time of VTM6.1 with the proposed complexity reduction techniques. The execution time of the CNN is not included in TC as it highly depends on the processor performance. However, for the sake of comparison, the CNN is able to compute all inferences for benchmarked 4K test sequences in less than 2% of the VTM encoding time. Furthermore, it can be done in parallel with the RDO process.

Results and analysis

There are several existing techniques that seek to reduce the complexity of MTT partitioning search in VTM. The most competitive ones have been implemented by Lei et al. [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF] in VTM3.0 and Park et al. [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] in VTM4.0. Thereafter, various new coding tools have been adopted to VTM, such as low frequency non-separable transforms [START_REF] Koo | Low frequency non separable transform[END_REF], intra sub-partitioning [START_REF] De-Luxán-Hernández | An Intra Subpartition Coding Mode for VVC[END_REF], and joint chroma residual coding [START_REF] Helmrich | Joint chroma residual coding with multiple modes[END_REF]. However, the partitioning search is kept unchanged, so the comparison between our technique in VTM6.1 and techniques in [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF], [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] remains still relevant and fair.

Tab. 1 presents our results with β = 10, 20, 30 over the techniques in [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF], [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF]. The first proposed configuration with β = 10 limits the BD-BR increase to only 0.26% with 29.8% complexity reduction. The second configuration with β = 20 still features a negligible BD-BR increase of 0.75% and a high complexity reduction of 42.2%. Our last configuration with β = 30 halves the complexity for 1.45% BD-BR increase.

In VTM3.0, Lei et al. [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF] achieved quite the same complexity reduction but for an increase of 0.28% BD-BR compared to our second configuration. Park et al. [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] obtained 33.7% complexity saving for 1.02% BD-BR increase, so it lags behind our second solution both in terms of complexity and BD-BR.

Our solution achieves better coding performance on high resolution sequences especially on classes A-B. For instance, our proposal with β = 10 almost halved the complexity with only 0.35% BD-BR increase for class A1. For β = 30, the complexity reduction reaches 62.9% with 1.55% BD-BR increase. For low-resolution C-D classes, our solution is able to reduce the complexity by 35.2% with 1.01% BD-BR increase. The training database is mainly composed of 4K and Full HD images, so our CNN performs better with them.

Fig. 4 plots the relative complexity reduction (∆ET) versus BD-BR increase over the CTC classes A-E (marked with crosses) for the proposed four configurations (β = 10, 20, 30, 40) and related works [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF], [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF]. Tackling the VVC coding complexity is of particular importance to higher resolutions so the corresponding results are also separately given for classes A-B (marked with circles).

With high-resolution sequences, the complexity saving of our proposal ranges from 40.8% to 66.7% and BD-BR increase from 0.30% to 2.37%. With β = 20, the overall complexity reduction is 42.2% for only 0.75% BD-BR increase. For classes A-B, the respective metrics are 53.5% and 0.82%. Compared with previous configuration (β = 20), [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF] achieves 10.3% lower complexity reduction for a BD-BR increase of 0.12%. It also outperforms [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] in terms of both BD-BR and complexity reduction.

To conclude, our solution is able to achieve higher complexity reduction and BD-BR gain than [START_REF] Lei | Look-Ahead Prediction Based Coding Unit Size Pruning for VVC Intra Coding[END_REF], [START_REF] Park | Context-Based Ternary Tree Decision Method in Versatile Video Coding for Fast Intra Coding[END_REF] with high-resolution sequences, comparable results with smaller resolutions, and averagely better coding performance with the entire CTC test set. Multiple threshold values also make our implementation more configurable to various operating points, like practical video encoders with several presets.

CONCLUSION

This paper presented a CNN-based complexity reduction technique for a VVC reference encoder VTM6.1. The CNN is used to analyze the texture inside each 64×64 coding block and predict vector probabilities for 4×4 boundaries inside these blocks. From the probability of boundaries, a split probability is deduced and compared with a predefined threshold. The execution time of the CNN is negligible compared to the VTM encoding time. In VTM6.1 intra coding, the proposed solution enables 42.2% complexity reduction for a slight BD-BR increase of 0.75%. With high-resolution sequences, the speedup is even higher, up to 54.5% at a cost of 0.85% BD-BR overhead. Our proposal allows several configurations and the majority of them overcome the state-of-the-art techniques.

These promising results motivate us to push our approach a step further and examine the database disparity and the CNN performance. A statistical behaviour of threshold values will also be investigated through in-depth statistical analysis.

Fig. 1 :

 1 Fig. 1: Coding Tree Unit (CTU) partitioning in VVC. (a) VVC split types. (b) Example.

Fig. 4 :

 4 Fig. 4: Performance comparison between the proposed solution and state-of-the-art techniques. Circles are results of Full Hd and 4K sequences. Crosses are results of CTC classes without class F.

Table 1 :

 1 Performance of the proposed solution in VTM6.1 with different threshold values β in comparison with state-of-the-art techniques. Class Lei et al. [13], VTM3.0 Park et al. [9], VTM4.0 Proposed β = 10 Proposed β = 20 Proposed β = 30

		BD-BR	∆ET	BD-BR	∆ET	BD-BR	∆ET	BD-BR	∆ET	BD-BR	∆ET
	Class A1	0.79%	44.9%	0.67%	32.0%	0.35%	45.3%	0.87%	56.3%	1.55%	62.9%
	Class A2	0.96%	39.5%	1.07%	33.0%	0.30%	40.1%	0.83%	52.6%	1.47%	60.0%
	Class B	1.06%	45.1%	0.98%	33.0%	0.26%	36.9%	0.75%	51.5%	1.41%	61.1%
	Class C	1.09%	48.3%	1.17%	35.0%	0.15%	13.9%	0.56%	26.4%	1.20%	37.9%
	Class D	0.97%	44.2%	0.88%	35.0%	0.08%	13.0%	0.33%	22.7%	0.83%	32.5%
	Class E	1.32%	47.9%	1.34%	34.0%	0.42%	29.5%	1.18%	43.8%	2.29%	54.4%
	Mean	1.03%	45.0%	1.02%	33.7%	0.26%	29.8%	0.75% 42.2%	1.45%	51.5%
	Class F	Nan	Nan	Nan	Nan	0.21%	15.2%	0.75%	25.4%	1.61%	36.3%