Gianrico Filacchione
email: gianrico.filacchione@inaf.it

Fabrizio Capaccioni

Mauro Ciarniello

Andrea Raponi

Giovanna Rinaldi

Maria Cristina De Sanctis

Dominique Bockelée-Morvan

Stéphane Erard

Gabriele Arnold

Vito Mennella

Maria Cristina De Sanctis

Dominique Bockelèe-Morvan

Stèphane Erard

Michelangelo Formisano

Andrea Longobardo

Stefano Mottola

An orbital water-ice cycle on comet 67P from colour changes

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

SUMMARY

The solar heating reaching a cometary surface provides the energy input necessary to sustain gaseous activity through which dust is removed from the nucleus [START_REF] Gundlach | What drives the dust activity of comet 67P/Churyumov-Gerasimenko?[END_REF][START_REF] Tubiana | Diurnal variation of dust and gas production in comet 67P/Churyumov-Gerasimenko at the inbound equinox as seen by OSIRIS and VIRTIS-M on board Rosetta[END_REF]. In this dynamical environment, both coma [START_REF] Hansen | Evolution of water production of 67P/Churyumov-Gerasimenko: An empirical model and a multi-instrument study[END_REF][START_REF] Bockelée-Morvan | VIRTIS-H observations of comet 67P's dust coma: spectral properties and color temperature variability with phase and elevation[END_REF] and nucleus [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF][START_REF] Ciarniello | The global surface composition of 67P/Churyumov-Gerasimenko nucleus by Rosetta/VIRTIS. II) Diurnal and seasonal variability[END_REF] evolve during the orbit, changing their physical and compositional properties. The environment encircling an active cometary nucleus is populated by dust grains with complex and variegated shapes [START_REF] Güttler | Synthesis of the Morphological Description of Cometary Dust at Comet 67P[END_REF] lifted and diffused by gases freed from the sublimation of surface ices [START_REF] Huebner | Heat and Gas Diffusion in Comet Nuclei[END_REF][START_REF] Läuter | Surface localization of gas sources on comet 67P/Churyumov-Gerasimenko based on DFMS/COPS data[END_REF]. Visible colour of dust particles is highly variable: carbonaceous-organic material-rich grains [START_REF] Jewitt | Cometary grain scattering versus wavelength, or, "What color is comet dust?[END_REF] appear red while Mg-silicate [START_REF] Zubko | Interpretation of photopolarimetric observations of comet 17P/Holmes[END_REF][START_REF] Hadamcik | Linear polarization of light scattered by cometary analogs: new samples[END_REF] or water ice [START_REF] Beer | The grain evolution model for icy grains ejected from 9P/Tempel 1 by Deep Impact, in Deep Impact as a World Observatory Event: Synergies in Space, Time and Wavelengths[END_REF][START_REF] Fernàndez | Near-infrared light curve of comet 9P/Tempel 1 during Deep Impact[END_REF] rich grains are blue with further dependence from grain size distribution, viewing geometry, activity level and comet family type. By integrating spacecraft with telescopic data from the Earth, we know that local colour changes are associated with grain size variations, like in the bluer jets made of submicron grains on comet Hale-Bopp [START_REF] Furusho | Imaging polarimetry and color of the inner coma of comet Hale-Bopp (C/1995 O1)[END_REF] or in fragmented grains on C/1999 S4 (LINEAR) coma [START_REF] Hadamcik | Dust coma of comet C/1999 S4 (LINEAR): imaging polarimetry during nucleus disruption[END_REF]. Apart from grain size, also composition influences coma's colour response because transparent volatiles can introduce a significant blueing in scattered light as observed in the dust particles ejected after Deep Impact event [START_REF] Hodapp | Visible and near-infrared spectrophotometry of the Deep Impact ejecta of comet 9P/Tempel 1[END_REF].

Here we report about the observation of two opposite seasonal colour cycles developing in the coma dust particles and on the surface of comet 67P/CG (Churyumov-Gerasimenko) as observed by Rosetta spacecraft during its perihelion passage in 2015 [START_REF] Taylor | The Rosetta mission orbiter science overview: the comet phase[END_REF]. Spectral analysis indicates an enrichment of submicron grains made of organic material and amorphous carbon in the coma causing the escalating colour reddening observed during the perihelion passage. At the same time, the progressive removal of dust from the nucleus causes the exposure of more pristine and bluish icy layers on the surface. Far from the Sun, we find that the abundance of water ice on the nucleus is reduced due to redeposition of dust and/or dehydration of the surface layer while water ice contribute to less-red coma's colours.

MAIN TEXT

Understanding how comets work and evolve is one of the most compelling questions to which the Rosetta mission [START_REF] Taylor | The Rosetta mission orbiter science overview: the comet phase[END_REF] has been trying to answer. Unlike past flyby missions to comets, Rosetta was designed to enter the same orbit and accompany 67P through its perihelion passage giving us the unique opportunity to follow the colour changes developing on a comet nucleus and coma in its active phase through the inner Solar System. So far, several studies have investigated how dust and gas (H 2 O, CO 2 ) production [START_REF] Hansen | Evolution of water production of 67P/Churyumov-Gerasimenko: An empirical model and a multi-instrument study[END_REF] are correlated among them during one cometary rotation showing that the water ice sublimation on 67P surface is the driving mechanism for dust ejection in the coma [START_REF] Tubiana | Diurnal variation of dust and gas production in comet 67P/Churyumov-Gerasimenko at the inbound equinox as seen by OSIRIS and VIRTIS-M on board Rosetta[END_REF]. In fact, the dust emission flux appears lower above high-cohesion consolidated terrains while it is maximum when the subsolar direction is aligned above volatile-rich areas. Since the illumination conditions continuously change on 67P, rather than focusing on coma and nucleus colours variations occurring during few diurnal rotations, we analyse the entire dataset returned by VIRTIS, the Visible, Infrared and Thermal Imaging Spectrometer [START_REF] Coradini | Virtis: An Imaging Spectrometer for the Rosetta Mission[END_REF] on Rosetta. Our method allows to explore comet's colour evolution starting from January 2015 (inbound orbit, heliocentric distance 2.55 AU), encompassing perihelion passage (August 2015, 1.24 AU) until May 2016 (outbound orbit, 2.92 AU). Spectral indicators in the visible range, including the integrated radiance (I), the wavelength of the radiance peak (λ max ) and the spectral slopes (in the 0.4-0.5 and 0.5-0.8 µm ranges), are synergistically used to model composition and grain size distribution of the dust particles in the coma as a function of heliocentric distance. Those spectral indicators are derived for each spectrum acquired by VIRTIS in an annulus encircling the nucleus and comprising all the pixels in the coma located at a tangent altitude between 1 and 2.5 km above the nucleus' limb. At the same time, we monitor the colour changes occurring on 12 test-areas on the nucleus through the 0.5-0.8 µm spectral slope [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF][START_REF] Ciarniello | The global surface composition of 67P/Churyumov-Gerasimenko nucleus by Rosetta/VIRTIS. II) Diurnal and seasonal variability[END_REF]. The description of the dataset, including an example of VIRTIS images and spectra after calibration improvement, spectral indicators processing, and data modeling, are given in the Methods.

From a synergistic time-analysis of the coma and of the nucleus surface spectral properties, two opposite trends with heliocentric distance are observed. Coma integrated radiance increases (see I time-series in Figure 1 a) and colour becomes redder when the comet approaches perihelion (see λ max , 0.4-0.5 and 0.5-0.8 µm spectral slopes time-series in Figure 1 b-c-d). Conversely, on twelve control areas of the nucleus, for which we have continuous time-coverage during the entire Rosetta mission, we observe a systematic blueing of the surface (see 0.5-0.8 µm spectral slopes time-series in Figure 2), with a reduction of the spectral slope up to 50% measured between 67P's passage through the frost line (heliocentric distance 2.7 AU, occurring in October 2014 during inbound orbit and in April 2016 on the outbound) and perihelion (1.25 AU, August 2015). During the preperihelion period, we interpret the coma colour change as being the consequence of the progressive loss of the ice fraction in the dust grains ejected from the nucleus [START_REF] Gicquel | Sublimation of icy aggregates in the coma of comet 67P/Churyumov-Gerasimenko detected with the OSIRIS cameras on board Rosetta[END_REF], which makes them redder.

When the comet approaches the Sun, the dust grains lifted from the nucleus' south hemisphere, the one illuminated at that time, are warmer and become more dehydrated. Simulations based on Mie scattering theory applied to spherical grains of radius between 0.1 and 50 µm and five different compositions (see Methods for a discussion about the scattering model limitations induced by spherical shaped grains) are used to model VIRTIS spectral indicators, e.g. λ max and 0.5-0.8 µm spectral slope. Simulation results (Figures 34) are compatible with the presence of submicron grains made of organic matter and carbon during perihelion passage which could be the result of the fragmentation of mineral and organic matrix embedded in larger grains. During the outbound orbit, the simulations show that the organic material continues to be present in the coma together with an increasing percentage of different grains (water ice or Mg-silicate; both are not fully compatible with spectral indicators trends, see ED-Table 3) contributing to the progressive blueing observed in the data. In this orbital phase, the Sun shines again on the northern hemisphere, from where a greater flux of surficial water ice-rich grains [START_REF] Keller | Seasonal mass transfer on the nucleus of comet 67P/Chuyumov-Gerasimenko[END_REF] is lifted in the coma.

Conversely, the nucleus' surface becomes progressively bluer during the inbound orbit because the greater solar input causes an increase of the gaseous activity. This triggers dust ejection with consequent erosion of the surface: on average, a 0.5 m thick erosion layer is lost during each orbit [START_REF] Keller | Seasonal mass transfer on the nucleus of comet 67P/Chuyumov-Gerasimenko[END_REF]. As a result of this process, more pristine subsurface layers enriched in water ice are exposed on the surface, which turns bluer [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF][START_REF] Ciarniello | The global surface composition of 67P/Churyumov-Gerasimenko nucleus by Rosetta/VIRTIS. II) Diurnal and seasonal variability[END_REF][START_REF] Fornasier | Rosetta's comet 67P/Churyumov-Gerasimenko sheds its dusty mantle to reveal its icy nature[END_REF]. We have evidence [START_REF] Ciarniello | The global surface composition of 67P/Churyumov-Gerasimenko nucleus by Rosetta/VIRTIS. II) Diurnal and seasonal variability[END_REF], in fact, that water ice-rich layers are immediately available under the dust layer, as shown in areas of recent disruption of the surface [START_REF] Filacchione | Exposed water ice on the nucleus of comet 67P/Churyumov-Gerasimenko[END_REF] and as demonstrated by many thermal models applied to cometary nuclei [START_REF] Sanctis | Thermal evolution model of 67P/Churyumov-Gerasimenko, the new Rosetta target[END_REF][START_REF] Capria | How pristine is the interior of the comet 67P/Churyumov-Gerasimenko?[END_REF]. Between 20% [START_REF] Keller | Seasonal mass transfer on the nucleus of comet 67P/Chuyumov-Gerasimenko[END_REF] to 50% [START_REF] Hu | Seasonal erosion and restoration of the dust cover on comet 67P/Churyumov-Gerasimenko as observed by OSIRIS onboard Rosetta[END_REF] of the dust grains ejected around perihelion from the south pole, the region which receives the maximum insolation at that time, fall-back preferentially on the northern hemisphere. The fall-back flux is dominated by decimetre-sizes dust aggregates in which a small fraction of water ice can be maintained [START_REF] Keller | Seasonal mass transfer on the nucleus of comet 67P/Chuyumov-Gerasimenko[END_REF]. After perihelion, as soon as activity begins to settle, the progressive accumulation of dust on the surface covers again the exposed pristine layers making the nucleus surface redder again. This process explains the colour cycle observed by VIRTIS on the nucleus (Figure 2).

Colour of 67P coma particles can be modelled with different grain populations made of water ice before perihelion, organic material and carbon at perihelion, and water ice or possibly Mg-silicate after perihelion. Similar composition endmembers are compatible with the findings reported by previous Rosetta's studies: during outbursts the release of submicron sized water ice grains mixed with hundred microns sized refractory grains has been observed [START_REF] Agarwal | Evidence of subsurface energy storage in comet 67P from the outburst of 2016 July 03[END_REF]. At the same time, a broad emission feature between 3.4 and 3.6 µm has been detected by VIRTIS [START_REF] Bockelée-Morvan | Comet 67P outbursts and quiescent coma at 1.3 AU from the Sun: dust properties from Rosetta/VIRTIS-H observations[END_REF] resulting compatible with the sublimation of organic materials caused by the high temperatures of the grains. The colour reduction observed when the comet was far from the Sun resembles water ice grains spectral properties, whose existence in the lower coma has been confirmed by other investigations: apart the presence of submicron size water ice grains ejected during outbursts [START_REF] Agarwal | Evidence of subsurface energy storage in comet 67P from the outburst of 2016 July 03[END_REF], thermal models and OSIRIS camera images [START_REF] Gicquel | Sublimation of icy aggregates in the coma of comet 67P/Churyumov-Gerasimenko detected with the OSIRIS cameras on board Rosetta[END_REF] show that at 1.53 AU heliocentric distance the total sublimation of ice for grains of radius between 5 and 500 µm made of ice-dust layers or mixtures occurs well-beyond the 2.5 km distance from 67P nucleus considered here. This implies that water ice grains can populate the region of the coma analysed in this work. Finally, a photometric investigation of the visible colours of more than a thousand individual grains resolved on OSIRIS colour images of 67P coma [START_REF] Frattin | Post-perihelion photometry of dust grains in the coma of 67P Churyumov-Gerasimenko[END_REF] indicates the presence of three composition classes including organic material grains (steep colour slope), mixtures of silicate and organic material (intermediate slope) and water ice (flat slope). The presence of carbon, silicates and magnesium in 67P dust grains has been assessed by the COSIMA instrument on Rosetta [START_REF] Bardin | Carbon-rich dust in comet 67P/Churyumov-Gerasimenko measured by COSIMA/Rosetta[END_REF].

The fact that coma's and surface's colour spectral indicators return to the same values at beginning and at end of their time-series (Figure 1), e.g. at heliocentric distances >2.7AU, is an evidence of the establishment of an orbital cycle driven by the solar heating. Far from the Sun, with the settling down of the gaseous activity [START_REF] Hansen | Evolution of water production of 67P/Churyumov-Gerasimenko: An empirical model and a multi-instrument study[END_REF], a tenuous (I≈0 in Figure 1-a) coma surrounds a red-coloured dusty nucleus.

FIGURES CAPTIONS

METHODS

VIRTIS dataset

While the scientific objectives of the Rosetta mission [18ß13], including the study of the dust in the coma, were well-defined before the spacecraft reached 67P, the detailed planning of the scientific payload operations has been a complex and continuously evolving process due to the uncertainties of the cometary environment in which the mission had to operate. A detailed overview of the Rosetta science planning process and challenges is given in [START_REF] Vallat | The science planning process on the Rosetta mission[END_REF]. In this context, VIRTIS coma observations were performed from very different viewing and illumination geometries, spacecraft ranges from the nucleus, heliocentric distances and cometary activity levels resulting in a dataset showing a very variable spatial resolution and signal to noise ratio.

While VIRTIS-led targeted observations of the coma have been routinely executed, a large fraction of the VIRTIS dataset consisted of ridealong and serendipitous acquisitions which have been acquired while the spacecraft attitude and pointing were controlled by other instruments. For this reason, to maximize the retrieval of information about the dust particles properties, a statistical approach has been applied to the vast VIRTIS-M-VIS dataset with the scope to exploit it in its completeness.

We restrict our analysis only to the VIRTIS-M (imaging channel) VIS data covering the 0.25-1.0 µm spectral range with 432 bands and a spectral sampling <2 nm/band. A detailed description of the VIRTIS experiment is provided by [START_REF] Coradini | Virtis: An Imaging Spectrometer for the Rosetta Mission[END_REF]. Differently from the VIRTIS-M IR channel operating within the 1-5 µm spectral range, which ceased the operations on May 2015 due to a permanent failure of the cryocooler dedicated to the cooling of the IR channel detector, the VIS channel has operated flawlessly for the entire duration of the mission.

For this work we have processed coma data collected during Rosetta's MTP012-028 periods. The time intervals of each MTP (Medium Term Phase) are listed in Extended Data Table 1. The dataset consists of more than 4,500 hyper spectral cubes of the coma of 67P acquired from a range of distances from the nucleus between 27.8 to 1462.2 km, resulting in a spatial resolution between 7 and 365 m/pixel, respectively.

Each VIRTIS observation has been calibrated in spectral radiance [START_REF] Filacchione | On-ground characterization of Rosetta/VIRTIS-M. II. Spatial and radiometric calibrations[END_REF] and specific geometry parameters have been computed for each pixel falling on the coma region and the nucleus. Further details about the VIRTIS data mapping methods are given by [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF]. The nucleus solar phase and the spacecraft position and distance in the cartesian frame centred on the nucleus have been computed using SPICE kernels [START_REF] Acton | Ancillary data services of NASA's Navigation and Ancillary Information Facility[END_REF]. The spectral parameters used in our analysis to study the coma emission are computed in an annulus defined by a tangent altitude running between a min =1 km and a max =2.5 km around the nucleus. This criterion is adopted independently from the nucleus-spacecraft distance and the solar phase angle at the time of the observation. The selection of pixels placed at distances larger than 1 km allows 1) to reduce the contribution of the instrumental stray-light coming from the illuminated part of the nucleus and 2) to maximize the coverage across the dataset.

An example of a VIRTIS-M-VIS image of the coma showing the annulus definition is given in Extended Data Figure 1 -top panels. This particular image refers to observation MTP019 -STP068 -V1_00397724286 acquired on August 9th 2015 from a distance of 304 km, resulting in a spatial resolution of 75 m/px with an integration time of 16 sec/line. Such a viewing geometry is not very common because the completeness of the annulus over the 360 degrees azimuth (up to distance a max ) is limited by the instrumental Field Of View (FOV=3.6°), by the relative distance (d) between Rosetta spacecraft and comet's surface and by the spacecraft offnadir pointing direction (α). Only when the following condition is verified VIRTIS-M can acquire the full annulus:

𝛼 + 𝑎𝑟𝑐𝑡𝑔 ! !"# !! ! ≤ 𝐹𝑂𝑉 1.)
where r=1.74 km is the average radius of the nucleus [START_REF] Jorda | The global shape, density and rotation of Comet 67P/Churyumov-Gerasimenko from preperihelion Rosetta/OSIRIS observations[END_REF]. A similar condition is verified only in 248 observations (marked as red points in Figure 1-a), corresponding to about 5% of the dataset: as a consequence, integrated radiance and maximum emission wavelength values could be biased by the incompleteness of the annulus on the remaining observations. The average integrated radiance on incomplete annulus observations (black points) appears in general higher than on the ones where the annulus is entirely acquired (red points). This happens because VIRTIS is preferentially observing the coma towards the solar direction to maximise the signal to noise ratio. Apart from the above limitations, which introduce some scattering in the data points, the value of the integrated radiance is mainly driven by the number of scatterers (dust grains) along the line of sight, rather than on their composition and grain size distribution: spectral slopes and the spectral position of the radiance peak depend from them.

The overall coma brightness and spectral properties measured by VIRTIS are driven by light scattering on dust particles and are not altered by emissions from gas molecules in the coma. The instrument sensitivity at visible wavelengths in fact is not enough to measure gaseous emissions from CN, C 2 , C 3 .

Calibration update using stellar observations

With the scope to improve VIRTIS-M-VIS response in the 0.25-0.45 µm spectral range, where the standard pipeline suffers large uncertainties due to straylight introduced by the on-ground calibration setup, we have applied a radiometric correction based on stellar observations. The average signal derived from Vega (α Lyrae) observations listed in Extended Data Table 2 is used as a reference to correct the standard responsivity. Four observations of Vega acquired with the longest possible integration time, 50 s, are used to retrieve the raw signal above the noise level (about ±2 DN) estimated on the nearby deep sky pixels.

Before this step, each observation is dark-level-subtracted and despiked (see Extended Data Figure 2-top left panel, showing the signal and sky level for one of the four Vega observations). Due to the instrumental point spread function and spectral tilt, both described in detail in [START_REF] Filacchione | Calibrazioni a terra e prestazioni in volo di spettrometri ad immagine nel visibile e nel vicino infrarosso per l'esplorazione planetaria[END_REF], the Vega spectral signal is distributed across 18 spatial pixels and is averaged above these. The four observations are processed in the same way before being further averaged to improve the SNR. The resulting Vega average signal is shown in Extended Data Figure 2-top right panel. The fractional deviation of the single spectra from the average is about 0.05. The Vega flux by [START_REF] Bohlin | Hubble Space Telescope Absolute Spectrophotometry of Vega from the Far-Ultraviolet to the Infrared[END_REF] is convolved with the VIRTIS gaussian response (FWHM=2.3 nm) and then by a 4 nm wide boxcar. The spectra are then placed on an absolute wavelength scale using the centre of Balmer and Paschen intense absorption lines as references and assuming a constant dispersion. The spectral dispersion (in nm) applied is λ(b)=232.9 + 1.88515×b, with b from 0 to 431 corresponding to VIRTIS-M number of spectral bands. The resulting relative responsivity derived as the ratio between VIRTIS signal and Vega flux is shown in Extended Data Figure 2-bottom left panel. To further remove residual high-frequency noise due to the low Vega signal, a 9band running boxcar filter is applied. The response curves are normalized at the value of 58.75 at λ=0.635 µm to allow a direct comparison with the standard pipeline responsivity shown in Extended Data Figure 2-bottom right panel. Within the limits of the low Vega signal in the blue spectral range (less than 40 DN at 0.55 µm), this method allows to retrieve a better responsivity at shorter wavelengths with respect to the standard pipeline [START_REF] Filacchione | Calibrazioni a terra e prestazioni in volo di spettrometri ad immagine nel visibile e nel vicino infrarosso per l'esplorazione planetaria[END_REF]. As shown by the ratio plot (blue curve) the standard pipeline overestimates the target radiance for wavelengths λ< 0.4 µm. On the remaining spectral range, the differences are much smaller. Since the wavelength of the dust emission spectral radiance peak occurs between 0.45 and 0.55 µm, such an instrument response correction allow to improve the retrieval of left-wing of the radiance peak and the spectral slope determinations.

Coma spectral indicators

After averaging the coma signal within the annulus previously defined and applied the updated responsivity function, we compute four spectral indicators on each observation. The indicators are 1) the integrated radiance (I) across the VIS spectral range, defined as:

𝐼 = !(!,!)!" ! !! !.!" !! ! !!! ! (1)
where R(n,λ) is the spectral radiance measured on the n-th pixel of the annulus at wavelength λ and N is the total number of pixels within the annulus area; 2) the wavelength of maximum emission of the radiance (λ max ) measured on a 4th-degree fit on the average spectral radiance computed on the annulus.

After converting spectral radiance in irradiance/solar flux (I/F) we compute the two spectral slopes following [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF]. These are: 3) 0.4-0.5 µm spectral slope on I/F; 4) 0.5-0.8 µm spectral slope on I/F. The two spectral slopes are computed as angular coefficient ot eh best linear fit in the ranges 0.4-0.5 and 0.5-0.8 µm after having normalized I/F at 0.5 µm. The determination of the spectral indicators follows the scheme shown in Extended Data Figure 1, bottom panels.

Spectral indicators depend from illumination geometries and spacecraft-nucleus distance: as a consequence of the very demanding mission scenario, complex orbits, including terminator, icosahedron, flybys, and far excursions have been flown [START_REF] Vallat | The science planning process on the Rosetta mission[END_REF] resulting in a very wide range of distances and solar phases. The correlation between the integrated radiance I and distance is shown in Extended Data Figure 3 where VIRTIS-M measurements are co-located with Rosetta's position and solar phase angle with respect to the comet nucleus along the flight trajectory.

Temporal evolution of the coma colour

The integrated-radiance (I) time-series (Figure 1-a) shows an increase of the coma's brightness starting from January 2015 (MTP012, heliocentric distance 2.55 AU) to perihelion passage (MTP019, 1.24 AU, August 2015). Due to the characteristics of Rosetta's orbit around the nucleus and the different observation strategies implemented during the mission, the completeness of the annulus region on the VIRTIS dataset is reached only on a limited number of observations marked as red points in Figure 1-a. On the majority of the remaining observations (black points), partial coverage of the annulus is achieved. Notwithstanding the relative scatters of the data introduced by the variability of the observing conditions, some clear trends are identified. A local maximum 25 ≤ I ≤ 30 W/(m 2 sr), is measured about one month after perihelion. Two additional intensity peaks are measured at the end of August and September 2015, when a maximum intensity of about 50 W/(m 2 sr) is reached. These peaks are caused by energetic cometary activitytwo outbursts observed by VIRTIS on September 13-14 2015 are reported by [START_REF] Bockelée-Morvan | Comet 67P outbursts and quiescent coma at 1.3 AU from the Sun: dust properties from Rosetta/VIRTIS-H observations[END_REF][START_REF] Rinaldi | Summer outbursts in the coma of comet 67P/Churyumov-Gerasimenko as observed by Rosetta-VIRTIS[END_REF] -but appear also to be strongly correlated with the peculiar viewing geometry and spacecraft position with respect to the nucleus: in fact, at the time of these observations, Rosetta was performing far-nucleus excursions, orbiting at greater distances than usual from the nucleus, up to 450 and 1462 km, respectively. As a consequence of the increased distance from the nucleus, VIRTIS-M has recorded higher radiances boosted by the larger column density of dust particles along the line of sight and by the maximum activity occurring immediately after perihelion. After this period the integrated radiance drops rapidly from MTP021 to MTP024 where an average value of 5 W/(m 2 sr) is reached. The maximum integrated radiance measured in MTP020-021 is about a factor 10 more intense than the average value of 5 W/(m 2 sr) measured when the comet was far from the Sun (> 2 AU) on both inbound and outbound legs of the orbit. With the exclusion of the two peaks, a similar asymmetric, or cusp-like trend with a maximum occurring about one month after perihelion, has been measured by other Rosetta's instruments for the water production rate which is associated to the ejection of the dust [START_REF] Hansen | Evolution of water production of 67P/Churyumov-Gerasimenko: An empirical model and a multi-instrument study[END_REF]. Apart from the greater column density, we have clues that larger particle albedo could contribute to the increase of the integrated radiance: according to [START_REF] Bockelée-Morvan | VIRTIS-H observations of comet 67P's dust coma: spectral properties and color temperature variability with phase and elevation[END_REF] the albedo of the dust particles increases up to 20% near perihelion for observations acquired at 90° solar phase angle. Similar albedo changes could be the result of a different composition of the dominant grain population in the coma along the orbit, as discussed in the main paper.

The time-series of the wavelength of maximum emission (λ max ) (Figure 1-c) shows a cusp-like trend starting from low values dispersed around λ max =0.45 µm on January 2015 (MTP012) on the inbound leg of 67P trajectory to λ max > 0.5 µm during perihelion passage (MTP019). Moving along the outbound leg of the orbit, the wavelength of maximum emission shifts progressively towards shorter wavelengths, reaching again λ max =0.45 µm in mid-May 2016 (MTP028). While λ max and integrated radiance time-series show a similar time-trend, spectral slopes time-series (Figure 1-b andd) are characterized by a different evolution: at the two extremes of the time-series both 0.4-0.5 µm and 0.5-0.8 µm slopes are almost neutral while at perihelion they reach values dispersed at 5 and 3 µm -1 , respectively. The visible colours of the coma show a systematic reddening before perihelion passage and a progressive blueing after it. The concurrent variations occurring on all spectral indicators time-series point to a change in the dust grains composition and grain size distribution with the heliocentric distance.

Temporal evolution of the nucleus colour

When observed at a global scale, 67P surface dust appears very dark (geometric visible albedo 6.2% [START_REF] Ciarniello | Photometric properties of comet 67P/Churyumov-Gerasimenko from VIRTIS-M onboard Rosetta[END_REF]) and dehydrated, with an average water ice fraction of about 1% dispersed in submicron grains [START_REF] Capaccioni | The organic-rich surface of comet 67P/Churyumov-Gerasimenko as seen by VIRTIS/Rosetta[END_REF][START_REF] Raponi | The temporal evolution of exposed water ice-rich areas on the surface of 67P/Churyumov-Gerasimenko: spectral analysis[END_REF]. The residual water ice content, if present, on the dust grains ejected from the surface undergoes rapid sublimation once the grain is lifted [START_REF] Gicquel | Sublimation of icy aggregates in the coma of comet 67P/Churyumov-Gerasimenko detected with the OSIRIS cameras on board Rosetta[END_REF]. So far, infrared spectroscopic observations have confirmed the presence of only two ices on the surface of 67P nucleus: water ice [START_REF] Filacchione | Exposed water ice on the nucleus of comet 67P/Churyumov-Gerasimenko[END_REF][START_REF] De Sanctis | The diurnal cycle of water ice on comet 67P/Churyumov-Gerasimenko[END_REF] and carbon dioxide [START_REF] Filacchione | Seasonal exposure of carbon dioxide ice on the nucleus of comet 67P/Churyumov-Gerasimenko[END_REF].

The low thermal capacity of the dust (700 J/kg/K) and the high solar flux can raise rapidly the temperature of the grains causing the sublimation of the volatiles. A colour temperature as high as 630 K is measured on dust grains during outbursts [START_REF] Bockelée-Morvan | Comet 67P outbursts and quiescent coma at 1.3 AU from the Sun: dust properties from Rosetta/VIRTIS-H observations[END_REF] and in the 260-320 K range on quiescent coma [START_REF] Bockelée-Morvan | VIRTIS-H observations of comet 67P's dust coma: spectral properties and color temperature variability with phase and elevation[END_REF]. Besides, the grains observed by Rosetta's dust instruments appear dehydrated [START_REF] Bardin | Carbon-rich dust in comet 67P/Churyumov-Gerasimenko measured by COSIMA/Rosetta[END_REF][START_REF] Hilchenbach | Comet 67P/Churyumov-Gerasimenko: Close-up on Dust Particle Fragments[END_REF]. This probably happens because the instruments aboard the spacecraft are not kept at cryogenic temperatures allowing the dispersion of the volatile fraction of the grains after their collection. Beside from dehydration, also grain size distribution plays a role in the changes of the visible colours, as detailed later.

During the pre-perihelion phase, the nucleus' surface shows a progressive blueing until one month after perihelion when the minimum slope is reached in MTP020 (see Figure 2). In this phase, the gas activity removes the dust from the surface with greater efficiency resulting in the exposure of more pristine subsurface material enriched in ices [START_REF] Filacchione | The global surface composition of 67P/CG nucleus by Rosetta/VIRTIS. (I) Prelanding mission phase[END_REF][START_REF] Ciarniello | The global surface composition of 67P/Churyumov-Gerasimenko nucleus by Rosetta/VIRTIS. II) Diurnal and seasonal variability[END_REF][START_REF] Fornasier | Rosetta's comet 67P/Churyumov-Gerasimenko sheds its dusty mantle to reveal its icy nature[END_REF]. This trend is interrupted after the perihelion passage when a progressive surface reddening is observed. Along the outbound trajectory, the gaseous activity progressively settles resulting in the accumulation of dehydrated (red) dust on the surface. This appears to be a general mechanism, occurring on the majority of the nucleus surface, as shown in Figure 2, where the average 0.5-0.8 µm slope is shown for twelve 30 x 30 meters-wide control-areas at one-month time resolution. These control areas, selected between latitude +45.5° and -34.5°, are the ones which have been observed in daylight by VIRTIS during the entire duration of the mission allowing us to follow the seasonal colour cycle developing on the nucleus.

Dust scattering simulations

The simulations are computed following the Bohren-Huffman Mie scattering code [START_REF] Bohren | Absorption and scattering of light by small particles[END_REF] to calculate scattering and absorption by a homogenous isotropic sphere. The method relies on the following assumptions: 1) single-scattering approximation, e.g. the solar photons interact with only one particle before reaching the observer. Such a hypothesis is reasonable for the annulus region considered in this work where the optical depth is small; 2) polydisperse spherical grains size distributions with radii of 0.10-0.99 µm (90 bins, 0.01 µm/bins), 1.0-9.9 µm (90 bins, 0.1 µm/bin), 10-50 µm (40 bins, 1 µm/bin); 3) Five different grain compositions are simulated: water ice (optical constants from [START_REF] Pollack | Composition and radiative properties of grains in molecular clouds and accretion disks[END_REF]), organic material [START_REF] Cuzzi | Utilitarian Opacity Model for Aggregate Particles in Protoplanetary Nebulae and Exoplanet Atmospheres[END_REF], troilite [START_REF] Pollack | Composition and radiative properties of grains in molecular clouds and accretion disks[END_REF], amorphous carbon [START_REF] Zubko | Optical constants of cosmic carbon analogue grains -I. Simulation of clustering by a modified continuous distribution of ellipsoids[END_REF] and Mg-silicate [START_REF] Dorschner | Steps towards interstellar silicate mineralogy II. Study of Mg-Fesilicate glasses of variable composition[END_REF]. These endmembers are representative of cometary nuclei composition which is made of a macromolecular assemblage in which various organic components (both aromatic and aliphatic), minerals (including silicates, iron-sulfides like pyrrhotite and/or troilite and possibly ammoniated salt) and ices are mixed together [START_REF] Filacchione | Comet 67P/CG Nucleus Composition and Comparison to Other Comets[END_REF]; 4) spectral simulations are performed at 27 wavelengths within the 0.35-1.0 µm spectral range; 5) scattering angle θ(=180°-g) is computed at step of 1° from 55° to 155° and then averaged on 4° bins in order to match VIRTIS field-of-view (3.66°).

Following [START_REF] Fink | Coma dust scattering concepts applied to the Rosetta mission[END_REF] the single scattering intensity is given by:

𝐼 𝜆 = 𝑆 𝜆 𝑛 !"# (𝜌)𝜎𝑞(𝜆) !(!.!) !! (2.)
where S(λ) is the solar flux [START_REF]Proc. IAU Symp. 154, Infrared Solar Physics[END_REF] scaled at the comet's heliocentric distance, n col is the dust column density computed along the line of sight from an observer placed at distance ρ from the nucleus, σ is the grain geometrical cross-section, q(λ) is the scattering efficiency of a single particle and p(g, λ) is the scattering phase function computed at phase g. Rather than modeling the absolute value of the intensity, we limit here our analysis to the changes occurring in the spectral response of the average radiance emitted from the dust.

In particular, we focus in the changes of the wavelength of the maximum emission (Figure 1-c) and s2 slope (Figure 1-d) observed at different heliocentric distances. To achieve this goal we compute the spectral radiance factor, I(λ) expressed in arbitrary units, derived from eq. 2 by removing the factors depending on the dust grain distribution and properties:

𝐼 𝜆, 𝑔 ∝ 𝑆 𝜆 𝑞(𝜆)

!(!.!) !! ( 3.
)

The phase functions show scattering characteristics depending on composition and grain sizes: as a general rule, transparent grains, like water ice, are characterized by a very intense and collimated forward-scattering peak and a complex resonance peaks at intermediate phase angles. Opaque materials, like troilite, show an almost isotropic scattering function. Semi-transparent particles, like ice tholins, have an intermediate behaviour with a prevalence of backscattering response. Grain size plays a fundamental role in the scattering mechanism: in the Rayleigh regime (particle size much smaller than the wavelength) light is equally forward and back-scattered while in geometric regime (particle size much larger than the wavelength) backscattering dominates. Fixing composition and grain size, the corresponding phase functions at the 27 visible wavelengths allow a derivation of the spectral radiance according to eq. 3.

While p(g, λ) has a smooth response in the Rayleigh and in the geometric scattering regimes, the simulations, in general, show more fluctuations occurring for certain combinations of composition, grain size, and θ angle when the grain sizes are comparable to the wavelength, e.g. at about 1 µm. To mitigate this effect we have computed simulations between 30°≤g≤120°, corresponding to scattering angles 55°≤ θ ≤155° at steps of 1° and then averaged the angular response of p(g, λ) on 4° bins, similar to the VIRTIS field-of-view. Similarly, the p(g) is computed for single grain radius: 0.10-0.99 µm (90 bins, 0.01 µm/bins), 1.0-9.9 µm (90 bins, 0.1 µm/bin), 10-50 µm (40 bins, 1 µm/bin) and then averaged on each of the three families. Following this method, the I(λ,g) (from eq. 3) is derived for each composition and size distribution. The λ max and, after conversion in I/F, the spectral slope s2 are derived on the simulated I(λ,g). The corresponding values are shown in Figures 3 and4, respectively.

Modeling dust grains composition and size distribution in the coma

To disentangle the viewing and illumination geometry effects from particles' physical properties and to provide a more quantitative assessment of the changes observed in the λ max time-series, the light scattering on grains of different composition and radius has been simulated. Optical and in-situ measurements of the dust grain distribution in 67P coma by Rosetta's instruments have revealed that the particles lie mainly within the 0.1 µm -1 mm diameter range [START_REF] Rotundi | Dust measurements in the coma of comet 67P/Churyumov-Gerasimenko inbound to the Sun[END_REF]. For particles smaller than 1 mm the dust size distribution follows a power-law distribution with a coefficient varying between -2 for heliocentric distances beyond 2 AU and -3.7 at perihelion. Conversely, large grains (diameter >1 mm) show a much steeper distribution with a coefficient -4 [START_REF] Fulle | Evolution of the Dust Size Distribution of Comet 67P/Churyumov-Gerasimenko from 2.2 au to Perihelion[END_REF]. Since small grains are the predominant population, in our analysis we preferentially model the spectral behaviour of small (radius < 50 µm) compact grains. A similar grain size range has been also used by [START_REF] Bockelée-Morvan | Comet 67P outbursts and quiescent coma at 1.3 AU from the Sun: dust properties from Rosetta/VIRTIS-H observations[END_REF][START_REF] Rinaldi | Summer outbursts in the coma of comet 67P/Churyumov-Gerasimenko as observed by Rosetta-VIRTIS[END_REF] to model dust optical properties at infrared wavelengths and by [START_REF] Gicquel | Sublimation of icy aggregates in the coma of comet 67P/Churyumov-Gerasimenko detected with the OSIRIS cameras on board Rosetta[END_REF] to study thermal evolution and depletion of ice in dust aggregates along jets. VIRTIS data are interpreted through the Mie theory which can simulate the scattering properties of spherical grains of radius a and homogeneous composition having x=(2πa/λ)<1000. Such a limit corresponds to a maximum grain radius a=50 µm in the visible spectral range (wavelength 0.35≤λ≤1.0 µm). To simulate the spectral response of larger grains, including fluffy aggregates [START_REF] Güttler | Synthesis of the Morphological Description of Cometary Dust at Comet 67P[END_REF][START_REF] Fulle | Density and Charge of Pristine Fluffy Particles from Comet 67P/Churyumov-Gerasimenko[END_REF], it is necessary to use geometric optics approximation [START_REF] Grynko | Light scattering from particulate surfaces in geometrical optics approximation[END_REF] and it is beyond the scope of this work.

The changes occurring in the spectral radiance scattered by spherical grains of different composition and grain size distribution as a function of the phase angle (g) are computed for homogeneous particles made of possible cometary material endmembers, including water ice, organic ice tholin, troilite, amorphous carbon and Magnesium silicate. For a given composition and phase angle, the single particle phase function p(g,λ) modulates the intensity of the scattered spectral radiance.

The theoretical trends of λ max as a function of the scattering angle θ=180°-g for particles of different composition and three grain size distributions (radius=0.10-0.99 µm, 1.0-9.9 µm, 10-50 µm) considered in this work, are shown in Figure 3. In the same figure we display the distribution of λ max as measured from VIRTIS observations (Fig. 3-f) selected during six MTP periods encompassing pre-perihelion (MTP015-016), perihelion (MTP020-021) and post-perihelion (MTP027-028) orbital phases. These periods are chosen because they offer the widest spread in scattering angle necessary to discriminate among different compositions and grain size distributions. Our analysis shows that, with the exception of transparent grains, e.g. water ice and organic ice tholin, the response of opaque materials like amorphous carbon (Fig. 3-a) and troilite (Fig. 3-d) are characterized by a constant λ max at about 0.5 µm for the intermediate (1.0-9.9 µm) and large (10-50 µm) grain sizes distributions across the 60≤θ≤150° scattering angle range explored by VIRTIS. These grains are therefore not matching the observed distribution of the λ max . Conversely, opaque-material submicron grains show a significant shift of the λ max towards the red range, especially for θ≤120°.

Sub micron grains made of Mg-silicate (Fig. 3-b) show a linear increase trend of λ max from 0.56 µm at θ=60° to 0.63 at θ=150° resulting not compatible with VIRTIS data. On the contrary, the λ max of grains with radii larger than 1 µm is dispersed around 0.55 µm, a value too much red to reproduce VIRTIS data at θ>100° and too much blue for θ<100.

Water ice grains (Fig. 3-e) offer the only solution matching VIRTIS data taken during the pre (MTP015-016) and post-perihelion periods (MTP027-028) at scattering angles θ>100°. During these phases VIRTIS data are dispersed at λ max <0.5 µm, a behaviour compatible only with the three water ice grain size distributions we have simulated.

Apart water ice, organic material grains (Fig. 3-c) are the second endmember showing spectral similarities compatible with 67P particles: the 1-10 µm and 10-50 µm grain sizes responses are in fact characterized by a linear decrease of the λ max from θ=60° to 120° making them compatible with observations acquired during perihelion and postperihelion periods. On the contrary, submicron grains show an extreme red colour across the entire range of scattering angles: having a λ max ≥0.65 µm they are marginally compatible only with VIRTIS observations taken at low θ angles. If one assumes that during one month, e.g. during the duration of one MTP period, the dominant composition and grain size is preserved, then the VIRTIS measurements taken during MTP028 at θ>130° could be compatible not only with water ice but also with large (10-50 µm) organic material grains. As shown in Fig. 3-a, amorphous carbon sub-micron (0.1-0.9 µm) size grains are characterized by a reddening of the λ max for θ<90° similar to VIRTIS but with absolute values too low to exactly match the observations. Instead, the match is compatible for 90°<θ<120°, making submicron amorphous carbon grains a good interloper between water ice and organic grains. Finally, Mg-silicate (Fig. 3-b) and troilite (Fig. 3-d) submicron grains show λ max trends at low scattering angles not compatible with VIRTIS data.

Composition and grain size distribution of the dust particles are further analysed through the 0.5-0.8 µm spectral slope (Figure 4) derived form VIRTIS data which shows a peaked distribution at θ=100°-110° (Fig. 4-f) occurring on perihelion (MTP020-021) and post perihelion (MTP028) sequences. In our simulations a similar behaviour is compatible with submicron-sized grains made of organic matter (black points in Fig. 4-e) or with >1 µm water ice grains (blue and red points in Fig. 4-d). The absolute value of the slope on the peak (≈3 1/µm) measured at perihelion (MTP020, cyan points) is similar to theoretical values for organic matter. Being transparent, water ice particles are characterized by a peculiar behaviour: submicron grains show a blue colour response (negative slope, black points in Fig. 4-d) not compatible with any VIRTIS observation while large grains (blue and red points) are neutral to moderately red and could contribute to the VIRTIS observed slope at any θ angle. Opaque grains with sizes >1 µm show an almost constant neutral to moderately red (0.5 1/µm) slope within the entire scattering angle range (see red and blue points for amorphous carbon in Fig. 4-a and troilite in Fig. 4-b). We remark that while the λ max trends of Mg-silicate (Fig. 3-b) grains are not compatible with VIRTIS data, their spectral slopes values (Fig. 4-c) for radius > 1 µm are remarkably similar for measurements taken during the post-perihelion period.

In the Extended Data Table 3 is shown a compatibility scheme of the λ max and 0.5-0.8 µm spectral slope values for the different composition endmembers, grain radius and scattering angle compared to VIRTIS data.

Figure 1 .

 1 Figure 1. Time-series of the spectral properties of 67P coma dust. Panel a) Integrated radiance (I): full dataset, partial annulus coverage (black points); reduced dataset, complete annulus coverage (red points, see discussion in Methods section); b) 0.4-0.5 µm spectral slope; c) visible radiance wavelength peak λ max ; d) 0.5-0.8 µm spectral slope.Through the paper spectral slopes are given in 1/µm corresponding to 10%/100 nm colour slope. Rosetta's MTP intervals are marked by vertical lines between MTP012 and MTP028. Time intervals of MTP periods are listed in Table1in the Methods. Perihelion occurs during MTP019.

Figure 2 .

 2 Figure 2. Time evolution of 67P nucleus colour measured through the 0.5-0.8 µm spectral slope above 12 control areas of 67P surface. Perihelion passage occurs during MTP019 and is marked by the vertical dash line. The morphological region name and position (longitude, latitude) of each area are reported in the plots captions. The maximum error associated to the slope measurements is of the order of ±0.1 µm -1 .

Figure 3 .

 3 Figure 3. Theoretical model results of the λ max trends as function of composition and grain radius distribution. Panel a: amorphous carbon. Panel b: Mg-silicate. Panel c: organic ice tholin (λ max >0.65 for 0.10-0.99 µm radius grains). Panel d: troilite. Panel e: water ice. Panel f: 67P/CG observations by VIRTIS, median data computed on 10° bins scattering angles during different mission phases. Standard deviation computed on VIRTIS data is of the order of 0.03 µm.

Figure 4 .

 4 Figure 4. Simulations of the 0.5-0.8 µm spectral slope as a function of the scattering angle θ for spherical particles of different composition: amorphous carbon (panel a), troilite (b), Mg-silicate (c), water ice (d), organics (e). Median spectral slope derived from VIRTIS observations for pre-perihelion (MTP015-016), perihelion (MTP020-021) and postperihelion (MTP027-028) mission phases are shown in panel f). The standard deviation of VIRTIS data is ≤0.6 µm -1 .

Acknowledgments: The authors would like to thank the following institutions and agencies, which supported this work: Italian Space Agency (ASI-Italy), Centre National d'Etudes Spatiales (CNES-France), Deutsches Zentrum für Luft-und Raumfahrt (DLR-Germany). VIRTIS was built by a consortium from Italy, France, and Germany, under the scientific responsibility of IAPS, Istituto di Astrofisica e Planetologia Spaziali of INAF, Rome, which lead also the scientific operations. The VIRTIS instrument development for ESA has been funded and managed by ASI (Italy), with contributions from Observatoire de Meudon (France) financed by CNES and from DLR (Germany). The VIRTIS instrument industrial prime contractor was former Officine Galileo, now Leonardo Company, in Campi Bisenzio, Florence, Italy. This research has made use of NASA's Astrophysics Data System.

Statement of individual contributions:

The paper is a collective effort by VIRTIS dust working group. FG as main author of the paper has calibrated, processed and interpreted VIRTIS data. FC as VIRTIS PI has managed the experiment; MC, AR, GR have supported with Mie scattering calculations and data processing; FC and DBM have planned 67P coma observations by VIRTIS; FC and GF have planned 67P nucleus observations by VIRTIS; SE has provided geometry files for coma and nucleus observations; all authors, including MCDC, GA, VM, MF, AL and SM, have contributed to the discussion of the results. The authors declare no competing interests.

Data Availability Statement: The VIRTIS calibrated data are publicy available through the ESA's Planetary Science Archive website (http://www.rssd.esa.int).

EXTENDED DATA

Extended Data Table 1. Rosetta's calendar MTP (Medium Term Plan) periods dates and heliocentric distance.

Extended Data Figure 1. Example of a typical VIRTIS-M observation of 67P nucleus and coma. Top Left Panel: visible colours RGB=(0.7, 0.55, 0.44 µm) image, stretched to saturate the nucleus and enhance jets visibility in the coma. Top Right Panel: tangent altitude image where the green mask corresponds to the annulus containing all pixels having a tangent altitude between 1 and 2.5 km from the limb. Bottom Left Panel: Average Radiance spectra as derived from official pipeline (black curve) and after correction with Vega data (red curve). The 4th degree polynomial fit to the corrected radiance is shown (cyan curve). The retrieved maximum emission wavelength on the fit is indicated by the magenta dashed line. Bottom Right Panel: corresponding I/F spectra normalized at 0.5 µm. The best-fitting slopes in the 0.4-0.5 and 0.5-0.8 µm ranges are indicated by blue and green dashed lines, respectively. Extended Data Table 2. Listing of VIRTIS observations of Vega star.

Extended Data Figure 2. Vega star signal and derived VIRTIS responsivity. Top left: average spectrum of Vega, in DN, from observation V1_00402035638.QUB (red curve) and spectrum corrected for dark current, despiked, and filter notch removed (green curve). Note the correlation of negative spikes in the Vega and average sky spectrum (black curve). Due to the instrumental point spread function and spectral tilt, the signal is an average taken from 18 pixels. Top right: average spectrum of Vega derived from the four observations listed in Extended Data Table 2 after having applied a processing similar to the one shown in the previous plot. The curve is averaged with a 2-point running boxcar filter. The Vega flux [START_REF] Bohlin | Hubble Space Telescope Absolute Spectrophotometry of Vega from the Far-Ultraviolet to the Infrared[END_REF] is shown in relative units (blue curve); Bottom left: VIRTIS responsivity derived from Vega signal averaged with a 2-point running boxcar filter (red curve) and 9 points (blue curve) after normalization at 0.635 µm above the standard responsivity value. Bottom right: comparison between standard pipeline (black curve) and Vega responsivities with a 9-point running boxcar filter(red curve). The ratio between the two responses is the blue curve.

Extended Data Figure 3. Rosetta spacecraft 3D trajectory and solar phase angle variations during the time. Top panel: Rosetta trajectory in the 67P XYZ reference frame. Points along the X axis are shown starting from Rosetta's position at 2015-01-13T23:28:53 (MTP012) with an increment of 1 km every 20 minutes to improve visualization. Y axis is oriented towards the Sun and Z perpendicular to the orbital plane. The red line indicates the position of the nucleus along the X axis. The integrated radiance as measured on each observation is reported according to the colour scale. Bottom Panel: variation of the solar phase angle (Sun-nucleus centre-Rosetta) during the mission.

Extended Data Table 3. Summary scheme showing spectral indicators (λ MAX , 0.5-0.8 µm spectral slopes) compatibility between VIRTIS observations and Mie scattering simulations for a given composition, grain radius range and scattering angle. The compatibility between observations and scattering simulations is colour coded according to the scheme shown on the top right caption. Each cell is divided in four fields showing λ MAX and to 0.5-0.8 µm slope values during pre-perihelion, perihelion and post-perihelion epochs (see bottom right caption).


Sulaiman Khan
email: sulaiman.khan@ul.ie

David Newport
email: david.newport@ul.ie

Stéphane Le Calvé
email: slecalve@unistra.fr.

Low-Volume PEEK Gas Cell for BTEX Detection using Portable Deep-UV Absorption Spectrophotometry

Keywords: Gas sensors, absorption spectrophotometry, photomultiplier tubes, UV LEDs, PEEK gas cell, micro Gas chromatography

Monitoring of indoor air quality by detecting individual airborne pollutant is essential for maintaining a healthy indoor environment. UV absorption spectrophotometry coupled with gas chromatography offers a reliable, self-referenced and non-destructive technique for the identification and detection of gas molecules. This paper presents a deep-UV absorption spectrophotometer coupled with a micro gas-chromatography (µGC) for the detection of benzene, toluene, ethylbenzene and xylenes (BTEX). The spectrophotometer was developed using a low-volume gas cell made of PolyEther Ether Ketone polymer (PEEK) tube, connected with a portable deep-UV LED and photomultiplier tube.

The performance of the detection unit was evaluated with different concentrations of toluene (5-100 ppm) in nitrogen and a sensitivity of 107.1 µAU/ppm with a limit of detection of 1.41 ppm was obtained.

The detector was incorporated into a micro gas-chromatography setup and high quality chromatograms, having all the peaks separated with good repeatability were obtained for BTEX molecules. The deep-UV absorption spectrophotometer developed demonstrates low-volume, low-cost, and ease of development and integration. Whilst demonstrated for BTEX in a nitrogen carrier gas, the spectrometer has the potential to be applied to chromatographic analysis of different analytes in gas or liquid media.

Introduction

Currently, there is considerable interest in detecting and monitoring of different airborne pollutants in indoor spaces. Indoor air can contain harmful pollutants, like volatile organic compounds (VOCs) [START_REF] Koppmann | Chemistry of Volatile Organic Compounds in the Atmosphere[END_REF], [START_REF] Noziere | The Molecular Identification of Organic Compounds in the Atmosphere: State of the Art and Challenges[END_REF]. Among VOCs, Benzene, Toluene, Ethylbenzene and Xylene (BTEX) are considered to be a hazardous pollutant, and long-term exposure can harm human health. BTEX belong to the group of aromatic hydrocarbons and can be found in indoor and outdoor environments. Its concentration is relatively high in indoor spaces [START_REF] Schneider | Indoor and outdoor BTX levels in German cities[END_REF] and its primary sources of generation are cigarette smoking, combustion, coal burning, cleaning products, floor adhesives, paint and wood panelling [START_REF] Wallace | Major sources of benzene exposure[END_REF]- [START_REF] Ayoko | Volatile Organic Compounds in Indoor Environments[END_REF].

Exposure to BTEX is related to sick building syndrome [START_REF] Kawamura | Development of a novel hand-held toluene gas sensor: Possible use in the prevention and control of sick building syndrome[END_REF]. Among BTEX, Benzene is highly toxic and is recognised as carcinogenic by the International Agency for Research on Cancer [START_REF] Pyatt | A review of the potential association between childhood leukemia and benzene[END_REF]. Benzene can provoke narcosis, headache, dizziness, drowsiness, confusion, tremor and loss of consciousness in case of acute occupational exposure [START_REF] Who | Exposure to Benzene: A Major public health concern[END_REF] [START_REF]Benzene (IARC Summary &amp[END_REF]. Exposure to toluene is linked with central nervous system, liver, kidney and skin-related issues [START_REF] Patnaik | A comprehensive guide to the hazardous properties of chemical substances[END_REF]. Xylenes at a low level can cause fatigue, tremor, respiratory, kidney and cardiovascular-related problems [START_REF] Kandyala | Xylene: An overview of its health hazards and preventive measures[END_REF]. Due to their human toxicity, stringent regulations about the exposure limits to BTEX molecules are established. For instance, the US National Institute of Occupational Safety and Health (NIOSH) have defined an exposure limit of 100 ppm for air-borne toluene for 8-10 time weighted-average [START_REF] Barson | NIOSH-Pocket Guide to Chemical Hazards[END_REF].

In order to detect BTEX, a sensitive, portable, low-cost gas sensor with ease of integration with other devices, for instance, gas chromatography is needed. Different types of gas sensors have been developed

for BTEX detection, such as electrochemical sensors [START_REF] Mirzaei | Resistive-based gas sensors for detection of benzene, toluene and xylene (BTX) gases: A review[END_REF], metal oxide semiconductor (MOS) sensors [START_REF] Zhou | Recent Progress on the Development of Chemosensors for Gases[END_REF], photo-ionization detectors(PID) [START_REF] Coelho Rezende | Micro photoionization detectors[END_REF], piezoelectric sensors [START_REF] Devkota | SAW Sensors for Chemical Vapors and Gases[END_REF] and optical gas sensors [START_REF] Mcdonagh | Optical chemical sensors[END_REF] [START_REF] Khan | A review of optical interferometry techniques for VOC detection[END_REF] [START_REF] Mikolajczyk | Detection of gaseous compounds with different techniques[END_REF]. MOS sensors usually need high temperature for operation and are sensitive to external humidity. Electrochemical sensors suffer from ageing but have zero drift. PIDs have a major limitation in terms of selectivity, cost, and complex electronics. Piezoelectric-based sensors experience significant noise and also interference from humidity and temperature. On the other hand, optical gas sensors have high sensitivity with minimal drift issues and a rapid time response. Absorption based optical sensors (i.e. spectrophotometer) are considered to be a sensitive and selective technique with minimal drifts or interference issues. In such sensors, the transduction principle is based on direct measurement of the molecule's physical property (i.e. absorbance at a specific wavelength), which is often called as fringerprints of a molecule. Absorption spectrophotometry is a self-reference, non-destructive and reliable approach for detection of gas molecules. It has a quick time response with a low cross-response to other gases, and the target gas molecules are detected without changing its molecular nature [START_REF] Hodgkinson | Optical gas sensing: a review[END_REF][21] [START_REF] Pena-Pereira | Advances in miniaturized UV-Vis spectrometric systems[END_REF]. These features make absorption spectrophotometry an attractive option for gas monitoring in indoor spaces .

BTEX species absorb strongly in deep-UV range ( wavelength λ, 240-275 nm) which can be exploited to develop a deep-UV absorption spectrophotometer for BTEX detection. The common spectrophotometric instrumentation developed for visible and infrared radiation are not suitable for deep-UV applications due to the high-energy (6.89eV-4.43eV for λ=180nm-280nm) of deep-UV radiation. However, recent advancements in UV optoelectronics and semiconductor research have led to the development of efficient and portable emission sources and photodetectors such as LEDs and photomultiplier tubes (PMT) respectively. LEDs provide a portable, spatially stable with lower intensity drifts, quasi-monochromatic, low-powered, cost-effective UV emission source compared to the conventional UV emission sources, for instance, mercury lamp. PMTs offer a sensitive and portable UV photodetector with a high surface area and fast time response even for a low-intensity of light. In addition to the UV emission source and UV photodetector, a low volume gas cell is also needed to realise a portable spectrophotometer with high sensitivity. A low volume gas cell is critical in gas chromatography for the detection of low concentrations of analytes. Gas chromatographs are usually employed in conjunction with detectors such as mass spectrometer or FID which limit its portability due to their size and weight.

A deep UV absorption spectrophotometer coupled with gas chromatography offers a sensitive, reliable and portable solution for the identification and detection of BTEX molecules. Previous research in the application of deep-UV absorption spectrophotometry for BTEX detection was primarily based on improving the sensitivity of the sensor. Eckhardth et al. [START_REF] Eckhardt | Fibre-optic UV systems for gas and vapour analysis[END_REF], [START_REF] Kötschau | Gas-Analysis in the UVregion using a long-length Hollow-Core-Waveguide[END_REF] demonstrated a deep-UV detector using an aluminium-coated HCW (length, 1 m and diameter, 1 mm) using a lamp as a UV source (30W deuterium) and CCD based spectrometer as a UV photodetector. The setup was tested with a gas chromatography column (GC) for detection of aromatic hydrocarbons such as ethylbenzene and bromobenzene. Its' major drawbacks are the size of the setup (emission source and detector) and high volume of the gas cell (785 µL). Recently Bui et al. [START_REF] Bui | A deep-UV light-emitting diode-based absorption detector for benzene, toluene, ethylbenzene, and the xylene compounds[END_REF] developed a deep-UV absorbance spectrophotometer with a good sensitivity (152 μAU/ppm; limit of detection of 0.66 ppm for toluene) using a deep-UV LED (λpeak, 260nm) and photodiodes for the direct detection of BTEX molecules. An aluminium tube (length, 40 cm and inner diameter, 2 mm) with inner volume (1256 µl) was used as a gas cell. The higher inner volume limits its applicability for µGC applications. Recently, low-volume fluidics components have been developed using PolyEther Ether Ketone (PEEK), which has excellent chemical resistance, high melting temperature (343 °C) and good mechanical properties [START_REF] Schweitzer | Mechanical and Corrosion-Resistant Properties of Plastics and Elastomers[END_REF]. It is a thermoplastic polymer belongs to a polyaryleetherketone family. It is machinable which give the flexibility to design it according to the desired applications.

This work reports the development of a low volume gas cell integrated with deep-UV LED and

PMT for micro gas chromatography of BTEX using deep-UV absorption spectrophotometry. We have employed a PEEK based tubes with connectors as a gas cell owing to its low volume, chemical and optical properties. To our knowledge, the application of low-volume gas cell coupled with LED and photodetector for µGC applications has not been reported.

Material and Methods

A deep-UV LED (Mightex System, USA) with peak wavelength, 260 nm and power range, 45-80 µW was used as a source. The LED was equipped with a passive heat exchanger to minimise the temperature induced noise and shift. For stable UV signals, a constant stable current (0-100 mA) was supplied to the LED. A low-powered photomultiplier tube (H10722-210, Hamamatsu Japan) was employed as a UV-photodetector with an operating wavelength range of 230-700 nm. PEEK tube (inner diameter 500 µm, IDEX Health & Science,USA ) was used as a gas cell with custom-made ferrules and nuts for a leakage-free connection. A PEEK T-Assembly (inner diameter 1 mm, IDEX Health & Science,USA ) was micromachined to achieve a leak-free sealing and optical alignment with optical fibre. For optical connection, custom made connectors, i.e. nuts were micromachined and fitted onto the SMA connector of optical fibre (QP400-Solarization resistant, 200-1100 nm, Ocean optics) with orings to ensure sealing. The schematic of the spectrophotometric setup is given in Figure 1. The sealing of the assembly was tested with nitrogen by using a mass-flow controller at the inlet and a mass-flow meter at the outlet of the setup, and gas leakages less than 2% were observed. All the components were assembled to minimise the dead volume in the setup. The gas cell was placed in a 3D-printed holder, fixed on an optical breadboard (Thorlabs USA) to keep the fibre straight and to avoid any mechanically induced noise. The assembly was also optically and thermally insulated to avoid any stray light, and thermal-induced fluctuations A 3D-printed holders and connectors (Acrylonitrile Butadiene Styrene-ABS) were used to aligned and fixed all the components on the breadboard.

For direct injection tests, the concentration of the toluene mixture was varied by diluting the flow from the toluene cylinder (100 ppm ± 2%, Air Products, France) with N2 (99.99% N2, Air Products, France) at different flow ratios using mass flow controllers ( F-201CV, Bronkhorst, Netherland) with a full-scale range of 20 mL/min ±0.5% and 10 mL/min ±0.5%, respectively. The setup for the generation of different concentration is given in Figure S1. For gas chromatography (GC), a chromatography setup was employed as given in Figure 2. A similar prototype was investigated and optimized for BTEX detection by our research group [START_REF] Lara-Lbeas | BTEX near real-time monitoring in two primary schools in La Rochelle, France[END_REF] [START_REF] Nasreddine | Development of a novel portable miniaturized GC for near real-time low level detection of BTEX[END_REF].

A PDMS based column with length of 20 m (Inner diameter 180 µm, RXi-624Sil MS) coiled into a small circle with diameter of 7.5 cm placed inside an aluminium plate (10cm × 10cm × 1 cm) was used for separation. The column was heated with an electrical resistor with a thermocouple placed under the column. The temperature was regulated via a controller (CAL3300 Farnel, France). The column was thermally insulated and the analysis was perferomed at a constant temperature of 60°C. The µGC column was coupled with a solenoid 6-port value (MTV-6LL-N32UF-1, Takasago Japan) for diverting the flow direction during different phases of chromatrography. The sampling loop of volume 200 µL (PEEK Interchim France) was connected with the 6-port value. The data was acquired from the PMT using a custom-made software at a sampling rate of 1.0 Sample/sec. The data post-processing was performed using Matlab and Spectragryph [START_REF] Menges | Spectragryphoptical spectroscopy software[END_REF]. A photoionization detector (PID, Baseline-Mocon USA) was installed at the exit of the gas cell for validation of the signal. For spectral analysis, the emission spectra of the LED was recorded using a mini-spectrometer (Hamamatsu C10082CH, Japan).

For GC analysis, a BTEX cylinder (Air Products, France) with a total concentration of 60 ppm, with each molecule at a concentration of 10 ppm ±2% was used as a source of BTEX mixture. Different concentrations of BTEX mixture (i.e. 10 ppm, 5 ppm and 2.5 ppm) were generated using the dilution setup as shown in Figure S1 (Supplementary file). The supply of the carrier gas is maintained inside the gas chromatograph through a pressure controller (IQP600, 0-10bar ±5% Bronkhorst, Netherland).

Results and Discussion

In order to investigate the prototype for absorbance measurement of BTEX mixture, the emission spectrum of the LED was compared with the absorption spectra for BTEX molecules. The emission spectra of the LED was measured with a mini-spectrometer and mapped on the absorption spectra of BTEX molecules, as shown in Figure 3 Before testing the prototype with BTEX using the µGC, experiments were performed using different concentrations of a gaseous toluene-nitrogen mixture. PEEK optical gas cells with an optical path length of 7.5 cm, 30 cm and 50 cm were designed and coupled into the setup as shown in Figure 1. The dimensions and the corresponding total volume for each cell are summarized in Table 1. For a cell of 50 cm, the total volume was 133.52 µL by taking into account the volume of each T-assembly at the two ends of the gas cell. For the configuration of 30 cm, the two T-assemblies contribute significantly (37 %) to the total volume of the cell. Indeed, the T-assemblies were designed with a relatively higher inner diameter (1.5 mm) than the gas cell's inner diameter (0.5 mm) to avoid the optical misalignment and gas leakage.

a. Detection of Toluene mixture in N2

Different concentrations of toluene in N2 were then injected into the gas cell, and the transmitted intensity of UV through the gas cell was recorded using the PMT. The PMT tube was employed as a UV photodetector due to its high sensitivity, higher surface area and compensation for the optical losses associated with the PEEK gas cell. The absorbance was calculated using the Beer-Lambert law as expressed as,

𝐴 = 𝑙𝑜𝑔 𝐼 𝑁 2 -𝐼 𝑑𝑎𝑟𝑘 𝐼 𝑇𝑜𝑙 -𝐼 𝑑𝑎𝑟𝑘 ( 1
)
Where A is absorbance, Idark is the intensity measured when LED is OFF, while IN2 and ITol represent the average intensity, after stabilisation, measured for the nitrogen and toluene mixture injections, respectively. For instance, Figure 4 shows the intensity signal recorded with the UV absorption spectrophotometer for 30 ppm of toluene-nitrogen mixture, where N2 and toluene-nitrogen mixture were injected alternatively by closing one two-way valve and opening another. Once the reference intensity obtained with pure nitrogen, the transmitted intensity decreases when the toluene mixture is injected due to absoprtion of UV by the toluene gas molecules. In addition, it was observed that the reference transmitted intensity decreases with time, suggesting a slight decrease in light intensity with time. This baseline drift could also be attributed to the thermal fluctuations and electronic setup related noise. A narrow peak was observed at the instant of injection of toluene mixture. Note that no such narrow peaks were observed when the detection cell was coupled to the µGC (Figure 6), where the gas flow is continuous without any value opening or closing. Therefore, the gas flow dynamics inside the microtube at the instant of valve opening is a potential reason for this effect. The gas cell of length 7.5 cm, 30 cm and 50 cm were tested for different toluene concentrations, and good linearities (R 2 ~ 0.99) were obtained for all the lengths of the gas cell as shown in Figure 5. This indicates a good agreement to the Beer-Lambert law and minimal influence of dark current and stray light on the PMT. The sensitivities of 42.0 µA.U/ppm, 107.1 µA.U/ppm and 194.4 µA.U/ppm were obtained for a gas cell of 7.5cm, 30cm and 50cm, respectively. The sensitivity obtained for the gas cell of 30 cm with inner volume of 94.25 µL is comparable with the sensitivity reported by Bui et al. [START_REF] Bui | A deep-UV light-emitting diode-based absorption detector for benzene, toluene, ethylbenzene, and the xylene compounds[END_REF] for toluene using aluminum gas cell with optical path length and inner volume of 40 cm and 1256 µL respectively. A limit of detection of 1.41 ppm was estimated for the gas cell of 50cm using a concentration corresponding to a signal equal to 3 times the baseline noise.

b. Detection of BTEX mixture in N2 with µGC

The UV absorption spectrophotometer was extended for separation and detection of a BTEX mixture using a µGC. A 50 cm PEEK gas cell was employed as a gas cell by taking into account the lower absorbances of benzene and ethylbenzene molecules. The dimensions and the total volume of the gas cell are given in Table 1. The sampling, separation and detection of BTEX mixture were carried out in two modes: i.e. sampling mode and analysis mode. In the sampling mode, a mass flow controller was used to inject different concentration of BTEX into the sampling loop for a time of 15 sec. The transition from the sampling mode to the analysis mode was performed by using a solenoid 6-port valve as shown in Figure 2. The separation was carried out by a microcolumn at 60 o C with a controlled heating process.

During the sampling mode, the 6-port valve was OFF, allowing the BTEX mixture to pass through the sampling loop at a controlled flow rate of 2.0 mL/min. The carrier gas (N2) was passing through the column and detector at a flow rate around 2.45 mL/min in the sampling mode as shown Figure 2. In the analysis mode, the BTEX molecules were separated in the µGC column followed by UV absorption by means of LED and PMT. For this, the valve was turned ON which diverted the carrier gas (N2) flow direction from the exhaust into the sampling loop as represented in the inset of A 60 ppm BTEX mixture, with each component of concentration 10 ppm was injected into the CC coupled to the PEEK gas cell equipped with the UV absorption spectrophotometer. The chromatogram obtained is shown in Figure 6, where each peak represents individual BTEX species, except for the mand p-xylenes which are coeluted. The UV absorption detection exhibits the highest and lowest sensitivity for xylenes (m+p) and benzene respectively, while its sensitivity is more moderate for toluene, according to the spectral data as discussed above. The sequence of the peaks detected shows adherence to peaks sequence reported by Rouba et al. [START_REF] Nasreddine | Development of a novel portable miniaturized GC for near real-time low level detection of BTEX[END_REF] and Larin et al. [START_REF] Larin | Novel highly-integrated mems based solid state detectors for analytical gas chromatography[END_REF]. The degree of separation between the two peaks, A and B is quantified using the resolution R which is expressed by [START_REF] Harvey | Modern Analytical Chemistry[END_REF],

𝑅 = (𝑡 𝑟 ) 𝐵 -(𝑡 𝑟 ) 𝐴 0.5 (𝑤 𝐵 + 𝑤 𝐴 ) (2)
where tr and w is the retention time and baseline width (Full width at half maximum-FWHM)

respectively. The resolution for all the peaks was calculated as presented in Table 2. A photoionization detector (PID) was installed at the exit of UV detection cell to validate the results. The signal obtained for the PID is shown in the inset of Figure 6. All the peaks of BTEX molecules measured with UV absorption are well-separated, and the corresponding resolution values are higher than those of PID.

The peaks of ethylbenzene and xylene (-o) and xylenes (m+p) are clearly demarcated from each other with peaks resolution values two times higher compared to the PID ones . This detection of BTEX mixture with separated peaks is attributed to the lower volume (133.5 µL) of the PEEK cell with quick time response. For the case of PID, the gas mixture has to cross a porous membrane by diffusion. The response of the detector was tested for total BTEX concentration of 60 ppm, 30 ppm and 15 ppm

with each BTEX molecule of concentration of 10 ppm, 5 ppm and 2.5 ppm, respectively. The lower concentration (i.e. 5 ppm and 2.5 ppm) were generated by diluting the mixture of BTEX (10 ppm) with N2 at a ratio of 1:2 and 1:4 respectively with a setup given in Figure S1 (supplementary file). For the case of 5 ppm BTEX mixture, all the BTEX molecules were detected. On the other hand, for 2.

Conclusions

In this work, we have developed a novel deep-UV absorption spectrophotometer using a lowvolume (133.5µL) PEEK gas cell coupled with a LED and PMT for the detection of air-borne BTEX.

The spectrophotometer was tested with different lengths of the gas cell for detection of toluene mixtures.

A sensitivity of 107.1 µAU/ppm with LOD of 3.5 ppm was obtained for a gas cell of 30 cm. The prototype was then tested with a µGC, and all the separated BTEX components in the µGC column were detected with a separate peak for each species. It demonstrated better performance for the detection of BTEX peaks with higher value of peak resolution compared to the commercial detector used. The setup exhibited good repeatability at 10 ppm (RSD<10%) for the absorbance and retention time or peaks resolution measurement for BTEX mixture. The proposed design offers a simple, cost-effective and easy-to-made approach for the application of portable deep-UV absorption spectrophotometry, the cost of the proposed design being approximately half of the conventional lamp-based system requiring based on deuterium lamp and spectrometer. The proposed setup with low-volume cell has the potential to be extended for the chromatographic studies of analytes in liquid media by replacing the flow injection setup and the LED according to the UV-visible stectra of the target species.

Figure 1 .

 1 Figure 1. Deep-UV Absorption spectrophotometer with low volume gas cell coupled with LED and PMT.

Figure 2 .

 2 Figure 2. (a) Schematic of µGC setup with deep-UV absorption spectrophotometer for BTEX detection. (b) Value position for sampling and analysis mode of GC.

Figure 3 .

 3 Figure 3. (a) LEDs emission spectrum overlaid with the absorption spectrum of benzene, toluene and xylene(-m). Data was obtained from HITRAN and then plotted according to the scale. Each spectrum is normalized by its maximum peak value. (b) The area integral calculated for a wavelength range (245nm to 275nm).

Figure 4 .

 4 Figure 4. Variation of intensity with pure nitrogen and 30 ppm alternate toluene injections for a gas cell of 50cm. The vertical bars represent the injection duration of toluene mixture.

Figure 5 .

 5 Figure 5. Calibration curve for gaseous toluene concentration ranging between 5 and 100 ppm using different size of PEEK cell.

Figure 2 .

 2 The sampled mixture of BTEX was then pushed into the GC column and then into the UV detection cell. The analysis and detection mode run for a typical time period of about 900 sec to obtain a complete chromatogram for the BTEX mixture.

Figure 6 .

 6 Figure 6. (a) Chromatogram of 10 ppm BTEX mixture obtained using 50 cm PEEK cell at µGC column temperature of 60 o c. The inset plot is the signal obtained from PID. The order of peaks is (1) benzene, (2) toluene, (3)ethylbenzene, (4) m+p xylenes (4) and (5) o-xylene. Representation of chromatograms from (b) UV absorption spectrophotometer, and (c) PID for comparison of separation time.

  Figure 8.

Figure 7 .

 7 Figure 7. Absorbance for each BTEX component using BTEX concentration in the range 2.5-10 ppm with a 50 cm PEEK cell at a column temperature of 60 o c.

Figure 8 .

 8 Figure 8. Calibration curve obtained from the chromatograms for toluene, xylenes (m+p) and xylene-o.The experiments were repeated 5 times for 10 ppm with a GC column regulated at 60 o C and the absorbance spectra obtained are shown in FigureS2. The RSD values for the peaks were calculated for each molecule and a good repeatability was obtained for all BTEX molecules (RSD <10%) at 10 ppm of BTEX mixture, the RSD ranging between few percent and 27% for 5 ppm. The peaks resolution for the five chromatograms was calculated using Equation2. As shown in Figure9, the peak resolution values are lower than 10% for all the BTEX components. All the BTEX component species therefore, exhibit a good repeatability. Ethylbenzene shows relative higher RSD values due to its lower absorbance coefficient and closer proximity to peak of xylenes (m+p).

Figure 9 .

 9 Figure 9. Relative Standard Deviation (RSD%) for peaks area of BTEX molecule and resolution calculated for each consecutive pair of BTEX molecule.

Table 1 .

 1 The total inner volume of the gas cell assembly with different length of gas cell.

	Cell. No	Length (cm)	Gas cell Inner diameter (mm)	Volume (µL)	Length (cm)	T-Assembly Inner diameter (mm)	Volume (µL)	Total Volume (µL)
	1	7.50	0.50	14.73	2.0	1.50	35.34	50.07
	2	30.0	0.50	58.90	2.0	1.50	35.34	94.25
	3	50.0	0.50	98.17	2.0	1.50	35.34	133.52

Table 2 .

 2 Peaks resolution calculated for BTEX using UV absorption spectrophotometer and PID.

	Peaks Resolution	Detector UV absorption spectromphotometer	Benzene 10.44	Toluene	EthylBenzene 12.49 2.35	Xylene (-m,-p)	Xylene (-o) 6.21
		PID	4.28		7.69	1.15		1.50

Acknowledgements

This work was funded by European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Innovative Training Network-MIGRATE (Miniaturized Gas flow foR Applications with Enhanced Thermal Effects), grant agreement No. 643095 [H2020-MSCA-ITN-2014]. This work has also received funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation program under grant agreement No 687014 (MACAO Project).

Highlights

• A novel deep-UV absorption spectrophotometer using a low-volume (133.5µL) PEEK gas cell was developed for the detection and identification of air-borne BTEX.

• The prototype is based on using potable UV emission source and UV photodetector.

• A limit of detection of 1.41 ppm was obtained for the direct injection of toluene.

• The detector was tested with a micro gas-chromatography (µGC) for the detection and identifcations of BTEX mixture in nitrogen carrier gas and all the molecules were separated and detected.

• The design offer a low-cost and easy to fabricate setup for spectrophotometric analysis on portable platform and can extended to be used in gas or liquid media.