T Liburkin-Dan

D Schlisselberg

R Fischer-Weinberger

Pascale Pescher

E Inbar

M Ephros

D Rentsch

Gerald F Späth

Dan Zilberstein
email: danz@technion.ac.il

Stage-specific expression of the proline-alanine transporter in the human pathogen Leishmania

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Protozoan parasites of the genus Leishmania cause morbidity and mortality throughout large areas of the Old and New World and are the causative agents of a wide spectrum of human and veterinary diseases. The clinical manifestations of Leishmania infections range from lesions of the skin and mucous membranes to lethality, the latter caused by visceral species [1].

Leishmania exhibit a digenetic life cycle that includes extracellular promastigote and intracellular amastigote forms. Extracellular promastigotes develop in the alimentary tract of sand flies. Following transmission to humans, promastigotes differentiate into obligatory intracellular amastigotes within macrophage phagolysosomes [START_REF] Chang | Multiplication of a human parasite (Leishmania donovani) in phagolysosomes of hamster macrophages in vivo[END_REF][START_REF] Mcconville | Living in a phagolysosome; metabolism of Leishmania amastigotes[END_REF]. This differentiation process in the host can be mimicked in axenic culture by shifting promastigotes from an insect-like (26ºC, pH 7) to an intra-lysosomal-like environment (37ºC, pH 5.5 and 5% CO 2 ) [START_REF] Debrabant | Generation of Leishmania donovani axenic amastigotes: their growth and biological characteristics[END_REF][START_REF] Barak | Differentiation of Leishmania donovani in host-free system: analysis of signal perception and response[END_REF][START_REF] Bates | Axenic cultivation and characterization of Leishmania mexicana amastigote-like forms[END_REF]. Axenic differentiation of L. donovani has been extensively characterized over the last two decades, establishing that this is a genetically programmed process [START_REF] Rosenzweig | Retooling Leishmania metabolism: from sandfly gut to human macrophage[END_REF][START_REF] Lahav | Multiple levels of gene regulation mediate differentiation of the intracellular pathogen Leishmania[END_REF][START_REF] Tsigankov | Regulation dynamics of Leishmania differentiation: deconvoluting signals and identifying phosphorylation trends[END_REF][START_REF] Zilberstein | Proteomic analysis of posttranslational modifications using iTRAQ in Leishmania[END_REF].

During their life cycle, Leishmania move between relatively alkaline environments rich in sugar and amino acids (AAs) and acidic environments rich in fatty acids and AAs [START_REF] Mcconville | Living in a phagolysosome; metabolism of Leishmania amastigotes[END_REF][START_REF] Burchmore | Life in vacuol[END_REF][START_REF] Opperdoes | Metabolism of Leishmania: proven and predicted[END_REF][START_REF] Bringaud | Multiple roles of proline transport and metabolism in trypanosomatids[END_REF].

High AA abundance is a feature common to both environments and accordingly, the parasites display adaptive mechanisms that favor utilization of such compounds [START_REF] Opperdoes | Metabolism of Leishmania: proven and predicted[END_REF][START_REF] Rosenzweig | Retooling Leishmania metabolism: from sand fly gut to human macrophage[END_REF][START_REF] Simon | The free amino acid pool in Leishmania tropica promastigotes[END_REF]. In particular, Leishmania exhibit large intracellular AA pool, of which alanine and proline are the main components [START_REF] Simon | The free amino acid pool in Leishmania tropica promastigotes[END_REF][START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF][START_REF] Darlyuk | Arginine homeostasis and transport in the human pathogen Leishmania donovani[END_REF]. The parasites use these AAs as osmolytes and as alternative sources of carbon.

In 1999, we biochemically showed that L. donovani take up proline via three systems named A, B and C [START_REF] Mazareb | Developmental regulation of proline transport in Leishmania donovani[END_REF]. Systems A and B are active only in promastigotes whereas system C is amastigotes-specific. Similarly, proline transport in T. cruzi was considered to be mediated by multiple transporters, each possessing distinct biochemical properties [START_REF] Silber | Active transport of L-proline in Trypanosoma cruzi[END_REF]. More recently, we established that the low affinity, high capacity proline transporter in L. donovani (system A) is encoded by two identical copies of LdAAP24 (LinJ.10.0760 and LinJ.10.0770) [START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF]. Notably, we discovered that due to distinct trans-splicing sites, the two gene copies produce mRNAs and corresponding proteins that differ in size and function [START_REF] Schlisselberg | Size does matter: 18 amino acids at the N-terminal tip of an amino acid transporter in Leishmania determine substrate specificity[END_REF]. The protein encoded by LinJ. [START_REF] Zilberstein | Proteomic analysis of posttranslational modifications using iTRAQ in Leishmania[END_REF].0770 (named LdAAP24.2) transports both alanine and proline, whereas the one encoded by LinJ. [START_REF] Zilberstein | Proteomic analysis of posttranslational modifications using iTRAQ in Leishmania[END_REF].0760 (named LdAAP24.1) is 18 amino acids shorter and transports only proline.

LdAAP24 plays a critical role in maintaining intracellular AA homeostasis and in responses to hypotonic stress [START_REF] Schlisselberg | Size does matter: 18 amino acids at the N-terminal tip of an amino acid transporter in Leishmania determine substrate specificity[END_REF].

To date, our analyses of LdAAP24 activity and expression were carried out in promastigotes. Previous biochemical studies suggested that amastigotes import proline via transport systems distinct from that of promastigotes [START_REF] Mazareb | Developmental regulation of proline transport in Leishmania donovani[END_REF]. This prompted us to examine LdAAP24 expression in both intracellular and axenic amastigotes. We found that once promastigotes were exposed to conditions that initiate differentiation into amastigotes, rapid degradation of LdAAP24 protein was induced. In macrophages, down-regulation of both variants (e.g. LdAAP24.1 and LdAAP24.2) was slower than in axenic conditions. In contrast, hamsterderived amastigotes do not express LdAAP24 protein at all. Changes in protein expression did not parallel mRNA abundance indicating posttranslational regulation of stage-specific expression of LdAAP24.

Materials and Methods

Materials

Ampicillin, G418, Hygromycin B, Phleomycin, Blasticidin, medium-199 (M-199), MG-132 and Bafilomycin A1 were from Sigma. Fetal bovine serum (FBS) was from Biological Industries Ltd.. n-dodecyl β-D-maltoside (DDM) was from Calbiochem and magnetic beads-bound anti-HA were from Medical&Biological Laboratories Co., Ltd. (MBL). All other reagents were of analytical grade.

Axenic Leishmania cell culture L. donovani, MHOM/SD/00/1S cell line was used [START_REF] Saar | Characterization of developmentally-regulated activities in axenic amastigotes of Leishmania donovani[END_REF]. Promastigotes and amastigotes were grown and maintained in axenic cultures. Differentiation was performed as previously described [START_REF] Barak | Differentiation of Leishmania donovani in host-free system: analysis of signal perception and response[END_REF]. Briefly, late log promastigotes were transferred from promastigote medium at 26°C and pH 7.4 to amastigote medium at 37°C, pH 5.5 in 5% CO 2 environment.

Western blot analysis and dot blot analysis

Western blot analyses of proteins were carried out as previously described [START_REF] Darlyuk | Arginine homeostasis and transport in the human pathogen Leishmania donovani[END_REF]. Briefly, each lane was loaded with 10µg of cellular protein. Following transfer to Protean BA-83 nitrocellulose paper (Whatman ltd.), parasite proteins were exposed to Rabbit anti LdAAP24

(1:2000 serum dilution) or anti HSP83 (1:2000) antisera [START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF][START_REF] Saar | Characterization of developmentally-regulated activities in axenic amastigotes of Leishmania donovani[END_REF]. LdAAP24 band density relative to that of HSP83 was calculated using TINA2.0 software.

In vitro macrophage infection with L. donovani

THP1 macrophage maintenance and infection were carried out as previously described [START_REF] Goldman-Pinkovich | An Arginine Deprivation Response Pathway Is Induced in Leishmania during Macrophage Invasion[END_REF].

Briefly, macrophages were grown on a plate at 37°C in a 5% CO 2 incubator at a density of 10 7 cells/plate. Late log-phase L. donovani promastigotes were added to the culture for 4 hours at 1:10 macrophage to parasite ratio. Plates were then washed three times with phosphate buffered saline (PBS) and incubation continued for 48 hours. To confirm infection, round cover-slips (18mm) were added to the dishes before addition of macrophages, stained with Giemsa after the experimental procedure, and viewed in an electron microscope.

Purification of macrophage-and splenic-derived amastigotes

THP1 macrophages were grown on 8 plates at 37°C at a density of 1×10 7 cells/plate and then infected with mid-log phase L. donovani promastigotes as above. 48 hours after infection, macrophages were collected using a scraper and washed with ice-cold PBS for 4 minutes at 48Xg. Pellets were finally suspended in 1 ml PBS and transferred to microcentrifuge tubes.

Separation of amastigotes was facilitated initially by passing the pellet repeatedly through a 1 ml syringe with a 27G needle. Lysates were then centrifuged for 15 minutes at 2500Xg at 4°C. The pellet was then suspended in 45% Percoll, which built the middle layer of the Percoll gradient as described in [START_REF] Goldman-Pinkovich | An Arginine Deprivation Response Pathway Is Induced in Leishmania during Macrophage Invasion[END_REF]. Cells were then isolated from the interface between the layers and subsequently centrifuged at 3500Xg for 60 minutes at 4°C as previously described [START_REF] Chang | Human cutaneous lieshmaniasis in a mouse macrophage line: propagation and isolation of intracellular parasites[END_REF]. Spleenderived amastigotes were isolated from 100 days L. donovani-infected hamsters as described previously [START_REF] Pescher | Quantitative proteome profiling informs on phenotypic traits that adapt Leishmania donovani for axenic and intracellular proliferation[END_REF].

Confocal immunofluorescence microscopy

Immunofluorescence of LdAAP24 in axenic L. donovani promastigotes and amastigotes was carried out as in [START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF] using Zeiss LSM 510 META and Zeiss LSM 700 microscopes. For immunofluorescence of parasite-infected macrophages, cover slips were stained with anti-LdAAP24 and DAPI employing the protocol used for promastigotes [START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF].

Northern Blot

Total RNA from L. donovani promastigotes (either starved for arginine or non-starved) was prepared and subjected to Northern blotting of LdAAP3 as described before [START_REF] Saar | Characterization of developmentally-regulated activities in axenic amastigotes of Leishmania donovani[END_REF]. Probes were amplified using the following primers: LinJ.31.900 AAP3 Forward: 5'-ATCATGAATTCATGAGCAAGCCCAGCAAGT-3'. Reverse: 5'-GCTTAGTCGACCGGAAGATGATGTTGCGC-3'.

Results

Differentiation signal induces rapid degradation of LdAAP24

Exposing axenic L. donovani promastigotes to amastigote differentiation signal induced rapid disappearance of the two LdAAP24 variants (Fig. 1A). As indicated by western blot analysis, within three hours only traces of the transporter proteins remained. Time course analysis determined the rate of degradation at t 1/2 = 35±3.3 minutes (Fig. 1B). Moreover, both short (8 weeks) and long (25 weeks) passages of axenic promastigotes [START_REF] Pescher | Quantitative proteome profiling informs on phenotypic traits that adapt Leishmania donovani for axenic and intracellular proliferation[END_REF], representing virulent and highly attenuated parasites, down-regulated LdAAP24 equally (Fig. 1C). These observations are consistent with our previous report that proline transport rate in axenic amastigotes is 5 times slower than in promastigotes, likely mediated by a different transport system [START_REF] Inbar | A versatile proline-alanine transporter in the unicellular pathogen Leishmania donovani regulates amino acid homeostasis and osmotic stress responses[END_REF][START_REF] Mazareb | Developmental regulation of proline transport in Leishmania donovani[END_REF]. Further analysis of whether protein abundance down-regulation depends on the differentiation signal indicates that neither exposure to pH 5.5 nor to 37ºC alone initiated degradation (Fig. 2). Only subjecting promastigotes to the full differentiation signal initiated complete LdAAP24 protein degradation in axenic culture. Note that exposing L. donovani promastigotes to pH 5.5 alone caused minor degradation of the heavier variant of LdAAP24 (LdAAP24.2). However, degradation was complete only in cells exposed to both 37 � C and pH 5.5.

The rapid and complete degradation of LdAAP24 at the onset of L. donovani axenic differentiation prompted us to assess whether the same happens in vivo, during macrophage infection. Human THP1 monocytes were incubated with L. donovani promastigotes for four hours and then incubated for additional 48 hours [START_REF] Goldman-Pinkovich | An Arginine Deprivation Response Pathway Is Induced in Leishmania during Macrophage Invasion[END_REF]. Intracellular amastigotes were then purified from the infected macrophages and assayed for LdAAP24 protein abundance. As shown by western blot analysis (Fig. 3A), while axenic amastigotes lacked visible level of LdAAP24, macrophage-derived amastigotes expressed LdAAP24 protein, though, at lower level compared to promastigotes. This indicated that exposing parasites to phagolysosome environment induced LdAAP24 down-regulation, but not to complete disappearance as in axenic parasites.

Indirect immunofluorescence analysis validated the western blot data that whereas axenic amastigotes do not express LdAAP24 at all (Fig. 3B andC), amastigotes obtained from infected THP1 cells at 48h post-infection did express visible level of this protein (Fig. 3D). To further assess whether LdAAP24 is expressed in long-term intracellular amastigotes, they have been isolated from spleens of 100 days infected hamsters. Western blot analysis clearly demonstrated (Fig. 1C) that long-term hamster-derived L. donovani do not express LdAAP24 protein. The analysis of axenic and intracellular L. donovani indicate that in the latter LdAAP24 degrade much slower than in the host-free culture, likely due to intracellular element(s) that slow transporter degradation.

Degradation of LdAAP24 is lysosome-mediated and dependent on proteasome activity

Vince et al. [START_REF] Vince | Lysosomal degradation of Leishmania hexose and inositol transporters is regulated in a stage-, nutrient-and ubiquitin-dependent manner[END_REF] previously provided evidence for posttranslational regulation of stagespecific expression of the glucose and inositol transporters in L. mexicana. Exposure to differentiation conditions, in both axenic culture and macrophages, induced lysosome-mediated degradation. Using axenic amastigotes they showed that mono-ubiquitination triggered degradation and targeting to lysosomes. As shown in Fig. 4, addition of 10 µM of the proteasome inhibitor MG132 to axenic L. donovani differentiation medium at time zero partially (57%) inhibited LdAAP24 degradation. Bafilomycin A1 is a specific inhibitor of lysosome vacuolar ATPase that blocks acidification of this organelle [START_REF] Tapper | Bafilomycin A1 inhibits lysosomal, phagosomal, and plasma membrane H(+)-ATPase and induces lysosomal enzyme secretion in macrophages[END_REF]. Adding 1 µM Bafilomycin A1 to amastigote differentiation medium also partially (76%) inhibited degradation of LdAAP24.

To assess whether the changes in LdAAP24 protein expression correlate with similar change in mRNA abundance, we performed northern-blot of LdAAP24 open reading frame. No significant change in mRNA was observed after exposing promastigotes to differentiation signal (Fig. 5).

Discussion

This study aimed to molecularly validate the previous biochemically-based observation that L. donovani transport system A is active only in promastigotes [START_REF] Mazareb | Developmental regulation of proline transport in Leishmania donovani[END_REF]. In amastigotes another low affinity and specificity system (system C) translocates several amino acids including proline [START_REF] Mazareb | Developmental regulation of proline transport in Leishmania donovani[END_REF]. Analysis of protein and mRNA abundance in axenic amastigotes, promastigotes and intracellular amastigotes confirmed that system A, represented by LdAAP24 is expressed and active only in promastigotes. Exposing L. donovani promastigote to amastigote differentiation signal initiated rapid degradation of LdAAP24 protein. In axenic promastigotes degradation was rapid (T 1/2 =35 minutes), while in intracellular amastigotes degradation was slower, LdAAP24 protein was visible 48 hours after macrophage infection, but not in splenic amastigotes recovered after100 days of infection.

LdAAP24 stage-specific expression is regulated at the level of protein abundance (posttranslational) only. We showed that degradation was susceptible to treatment with both the proteasome inhibitor MG132 and the V-ATPase inhibitor Bafilomycin A1, suggesting that LdAAP24 degradation is mediated by both the lysosome and proteasome.

Usually, membrane protein degradation is mediated via the lysosome pathway. Vince et al. [START_REF] Vince | Lysosomal degradation of Leishmania hexose and inositol transporters is regulated in a stage-, nutrient-and ubiquitin-dependent manner[END_REF] showed that upon L. mexicana differentiation into amastigotes the promastigote-specific myo-inositol transporter D1 actively degrades via the lysosomes-mediated pathway. Similarly, the dolichol-phosphate-mannose synthase [START_REF] Mullin | Regulated degradation of an endoplasmic reticulum membrane protein in a tubular lysosome in Leishmania mexicana[END_REF], the multidrug resistance protein 1 [START_REF] Dodge | Localization and activity of multidrug resistance protein 1 in the secretory pathway of Leishmania parasites[END_REF] and the folate transporter 1 [START_REF] Richard | Growth phase regulation of the main folate transporter of leishmania infantum and its role in methotrexate resistance[END_REF] are all stage-specific whose abundance is down-regulated by the lysosome mediated pathway. Likewise, in the present study, inhibition by Bafilomycin A1 indicates a role for the lysosome in LdAAP24 degradation.

This work provides the first evidence for post-translational regulation of stage-specific expression of LdAAP24. It also provides an additional evidence that axenic Leishmania resemble intracellular parasites. Analysis was carried out using western blot analysis at indicated hours after exposing promastigotes to differentiation signal. This figure is representative of five independent repeats.

[C]. Western blot analysis of LdAAP24 in splenic amastigotes and axenic L. donovani promastigotes derived from the splenic amastigotes and maintained for 8 (8W) and 25 weeks (25W) in culture. Proteins were extracted from 100 days old splenic amastigotes or axenic promastigotes (at 0 and 3 hours after differentiation signal). In all panels LdHSP83 was used as loading control Total RNA was extracted from L. donovani promastigotes and at 0.5, 1 and 3 hours after exposure to promastigote to amastigote differentiation signal and subjected to northern analysis as described in Materials and Methods. LdAAP24 open reading frame was used as a probe. rRNA was used as loading control. This experiments is representative of three independent repeats.

Figure 1 .

 1 Figure 1. Rapid down-regulation of LdAAP24 abundance during first phase of L. donovani

Figure 2 .

 2 Figure 2. Promastigote to amastigote differentiation signal, not acidic pH or elevated

Figure 3 .

 3 Figure 3. LdAAP24 undergoes partial degradation during first 48 hours of macrophage

Figure 4 .

 4 Figure 4. LdAAP24 degradation is lysosome and proteasome-dependent.

Figure 5 .

 5 Figure 5. mRNA levels of LdAAP24 do not change during axenic differentiation.

Fig. 1 .

 1 Fig. 1. Rapid down-regulation of LdAAP24 abundance during first phase ofL. donovani axenic differentiation.

Figure 1 Time 22 Fig. 2 .Figure 2 Fig. 3 .Fig. 4 .

 1222234 Figure 1

25 Fig. 5 .Figure 5

 2555 Figure 4

8 h p o s ti n f e c 2 o n A.

Acknowledgements

We thank Dr. Harsh Pawar and Yael Bar Avraham for technical help. We also thanks Dr. Avital Bareket Samish for editing this manuscript. This study was supported by grant number 1766/16 and from the Israel Science Foundation.


Coraline Mattei

Henri Wortham

Etienne Quivet

Heterogeneous degradation of pesticides by OH radicals in the atmosphere: influence of humidity and particle type on the kinetics

Keywords: Aerosols, atmosphere, degradation, humidity, OH radical, pesticides

may come

Heterogeneous degradation of pesticides by OH radicals in the atmosphere: Influence of humidity and particle type on the kinetics Coraline Mattei, Henri Wortham, Etienne Quivet

Introduction

Pesticides are of great interest for both the scientific community and the general public due to their worldwide uses and potential adverse health or environmental impacts [START_REF] Carvalho | Pesticides, environment, and food safety[END_REF]Inserm, 2013). They are present in the atmosphere in concentration levels from some picogram per cubic meter (pg m -3 ) to several nanograms per cubic meter (ng m -3 ) [START_REF] Coscollà | Particle size distributions of currently used pesticides in a rural atmosphere of France[END_REF][START_REF] Coscollà | Particle size distributions of currently used pesticides in ambient air of an agricultural Mediterranean area[END_REF][START_REF] Désert | Spatial and temporal distribution of current-use pesticides in ambient air of Provence-Alpes-Côte-d'Azur Region and Corsica, France[END_REF][START_REF] Estellano | Assessing levels and seasonal variations of current-use pesticides (CUPs) in the Tuscan atmosphere, Italy, using polyurethane foam disks (PUF) passive air samplers[END_REF][START_REF] Lester | Key environmental processes affecting the fate of the insecticide chloropyrifos applied to leaves[END_REF][START_REF] Zivan | Airborne organophosphate pesticides drift in Mediterranean climate: The importance of secondary drift[END_REF][START_REF] Zivan | Primary and secondary pesticide drift profiles from a peach orchard[END_REF].

Most of the currently used pesticides are semi-volatile organic compounds (SVOC), consequently, they are distributed between the gaseous and particulate phases. In the atmosphere, they can undergo direct photolysis and can react with atmospheric oxidants, whose main representatives are hydroxyl radicals (OH), ozone (O3), and nitrate radicals (NO3). On the first hand their gas-phase reactivity has been extensively studied [START_REF] Borrás | Particulate and gas-phase products from the atmospheric degradation of chlorpyrifos and chlorpyrifos-oxon[END_REF]Muñoz et al., 2014;[START_REF] Vera | Atmospheric degradation of lindane and 1,3-dichloroacetone in the gas phase. Studies at the EUPHORE simulation chamber[END_REF] and numerous kinetic data, especially for the reactivity with OH radicals, is available thanks to modeling [START_REF] Bahm | A new model of tropospheric hydroxyl radical concentrations[END_REF]. On the other hand, very few studies were done on particulate phase reactivity. Moreover, the available heterogeneous degradation kinetics data are subject to large uncertainties because of experimental difficulties to study heterogeneous reactivity and to the numerous atmospheric physicochemical parameters which could influence them (relative humidity (RH), particles hygroscopicity, particle chemical composition…).

The heterogeneous degradation of some pesticides with OH radicals has already been studied [START_REF] Rashidi | The heterogeneous photo-oxidation of difenoconazole in the atmosphere[END_REF], 2014;[START_REF] Bouya | Kinetics of the heterogeneous photo oxidation of the pesticide bupirimate by OH-radical and ozone under atmospheric conditions[END_REF][START_REF] Lester | Key environmental processes affecting the fate of the insecticide chloropyrifos applied to leaves[END_REF][START_REF] Liu | Degradation study of the aerosol-borne insecticides Dicofol and DDT in an aerosol smog chamber facility by OH radical in relation to the POPs convention[END_REF][START_REF] Palm | OH radical Reactivity of Airborne Terbuthylazine Adsorbed on Inert Aerosol[END_REF][START_REF] Palm | OH radical Reactivity of Pesticides Adsorbed on Aerosol Materials: First Results of Experiments with Filter Samples[END_REF][START_REF] Palm | Atmospheric degradation of a semivolatile aerosol-borne pesticide: Reaction of OH with pyrifenox (an Oxime-Ether), adsorbed on SiO2[END_REF][START_REF] Palm | Degradation of the pesticide primisulfuron-methyl in the aerosol-borne state by OH radical[END_REF][START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF][START_REF] Zetzsch | Photochemischer Abbau in Aerosolphasen[END_REF], but conditions employed to determine kinetic constants were very diverse in terms of surface (different silica particles, quartz surface, plant leaves) and humidity (<1% RH to 70% RH). To our knowledge, no study investigated the influence of relative humidity on the degradation kinetics of pesticides with OH radicals, although this factor has an influence on the heterogeneous degradation of organic compounds by ozone [START_REF] Kaiser | Detailed heterogeneous oxidation of soot surfaces in a particle-resolved aerosol model[END_REF][START_REF] Mattei | Heterogeneous atmospheric degradation of pesticides by ozone: Influence of relative humidity and particle type[END_REF][START_REF] Pöschl | Interaction of Ozone and Water Vapor with Spark Discharge Soot Aerosol Particles Coated with Benzo[a]pyrene: O3 and H2O Adsorption, Benzo[a]pyrene Degradation, and Atmospheric Implications[END_REF]. Moreover, no study investigated the influence of the surface on the OH radicals degradation of pesticides while it has been already shown that particle surface influences the OH radicals degradation kinetics of SVOC such as polycyclic aromatic hydrocarbon adsorbed on different diesel particles [START_REF] Esteve | Relative rate constants for the heterogeneous reactions of NO2 and OH radical with polycyclic aromatic hydrocarbons adsorbed on carbonaceous particles. Part 2: PAHs adsorbed on diesel particulate exhaust SRM 1650a[END_REF].

As a result, the aim of this study is to investigate the influence of atmospheric relative humidity (RH) and particle physicochemical properties on the heterogeneous degradation of pesticides by OH radicals. To do so, laboratory experiments were performed using two model particles: hydrophobic and hydrophilic silicas at a RH level varying from 0% to 70%. The experiments were done with eight pesticides representative of various chemical classes of pesticides: cyprodinil (pyrimidine), deltamethrin (pyrethroid), difenoconazole (triazole), fipronil (pyrazole), oxadiazon (diazole), pendimethalin (dinitroaniline), permethrin (pyrethroid), and tetraconazole (triazole). The compounds under study were selected based on their distribution between gas and particle phases, their toxicity, and their presence in the atmosphere [START_REF] Désert | Spatial and temporal distribution of current-use pesticides in ambient air of Provence-Alpes-Côte-d'Azur Region and Corsica, France[END_REF]. Understanding the influence of these factors on the heterogeneous degradation kinetics of pesticides by OH radicals will help to better understand the atmospheric behavior and the atmospheric transportability of pesticides when they are adsorbed on atmospheric aerosols. This is important to adapt pesticide regulatory policies which, in the atmosphere, concern only gaseous pesticides even though currently used pesticides are often semi-volatile species.

Material and Methods

Chemicals

Analytical standards (PESTANAL®, analytical standard) of the eight pesticides under study (cyprodinil (purity 99.8%), deltamethrin (99.7%), difenoconazole (97.0%), fipronil (97.5%), oxadiazon (99.9%), pendimethalin (98.8%), permethrin (98.3%), and tetraconazole (99.0%)) as well as 2,3-dimethyl-2-butene (DMB, 98%) and m-xylene (99.5%) were purchased from Sigma-Aldrich. They were used as received. The chemical structures of the pesticides under study are depicted in Supporting Information (SI) Fig. SI1 and their physicochemical properties are given in Table SI1.

Particles

Two commercial fumed silica particles were used to mimic atmospheric mineral aerosols: AEROSIL R812 (purchased from Degussa) thereafter called "hydrophobic silica" and AEROSIL 255 (Evonik Industries) called "hydrophilic silica".

Chemical composition: Hydrophobic and hydrophilic silicas contain mainly SiO2 (> 99.8 wt%).

Surfaces of hydrophobic and hydrophilic silica particles are mainly covered by siloxanes and silanols groups, respectively. Siloxane groups are chemically inert and hydrophobic whereas silanol groups have a hydrophilic nature (i.e., readily mix with water). It was shown that 10% to 30% of atmospheric particles are composed of quartz or silica [START_REF] Finlayson-Pitts | Chemistry of the upper and lower atmosphere: theory, experiments, and applications[END_REF][START_REF] Seinfeld | Atmospheric chemistry and physics: from air pollution to climate change[END_REF], as a result, our particles are good proxies to simulate the chemical composition of crustal aerosols.

Particle size: Very few studies were done on the particle size distribution of pesticides in ambient air. However, the available results showed that most of the pesticides (40% to 80%) are accumulated in the fine (0.1-1 µm) particle size fraction, while only a small part is adsorbed on the ultrafine (0.03-0.1 µm) and coarse (1-10 µm) size ranges. On the other hand, no pesticides were detected in the size fraction > 10 µm [START_REF] Coscollà | Particle size distributions of currently used pesticides in a rural atmosphere of France[END_REF][START_REF] Coscollà | Particle size distributions of currently used pesticides in ambient air of an agricultural Mediterranean area[END_REF][START_REF] Xu | Size distribution and seasonal variations of particle-associated organochlorine pesticides in Jinan, China[END_REF]. In the present study, the individual mean size of hydrophobic and hydrophilic silica particles range from 5 nm to 50 nm (Evonik, 2015) (Fig. SI2-SI3) which is in agreement with the aerosol size observed in the experimental field measurements. However, particles can agglomerate to reach sizes ranging between 5 µm and 25 μm (Fig. SI2-SI3).

Specific surface area (SSA; BET method): Hydrophobic and hydrophilic silica particles have a specific surface area of (260 ± 30) m 2 g -1 and (255 ± 25) m 2 g -1 , respectively (Evonik, 2015).

Particle coating

Hydrophobic and hydrophilic silicas were independently coated with pesticides according to a liquid/solid adsorption process. In an amber Pyrex flask of 500 cm 3 , 600 mg of particles were mixed with 6 mL of a solution containing the 8 pesticides under study each at a concentration of 20 mg L -1 (pesticide solution in dichloromethane for HPLC, ≥ 99.8%, Sigma-Aldrich). The load of pesticides on silica particles was about 0.02% by weight. After a 5-min ultrasound treatment, dichloromethane was evaporated using a rotary evaporator (Rotavapor R-114, Büchi) at 40 °C and 850 mbar. This process allows a reproducible and realistic coating of the pesticides on the particle's surface [START_REF] Socorro | Heterogeneous reactions of ozone with commonly used pesticides adsorbed on silica particles[END_REF]. Assuming a uniform particle surface coverage for the pesticide molecules and a spherical geometry for particles, the percentage of the particle surface coated with individual pesticide was between 0.3% and 0.5% of a monolayer for hydrophobic and hydrophilic silicas respectively (SI Silica particles coating). For the eight pesticides, the total coated particle surface was 2.8% and 2.9% for hydrophobic silica and hydrophilic silica respectively, which is much less than a monolayer.

Exposition to OH radicals

Experimental set-up:

The experimental set up to expose pesticide-coated particles to OH radical is presented in Fig. 1. The exposition took place in a 500 mL amber round bottom flask, connected to a modified rotary evaporator (Laborota 4000 efficient, Heidolph) and immersed in a thermostated bath. This device allowed to mix homogeneously and continuously the particles and to maintain a constant temperature (25 ± 1 °C). The reactor was protected against light using an aluminum foil to avoid pesticide photo-degradation. All gas flows were monitored and kept constant during an experiment, of a duration of 6 hours. The total flow passing the reactor was 500 mL min -1 to ensure a total renewal of the gases in the reactor every minute.

OH radical generation:

OH radicals have an atmospheric lifetime inferior to one second [START_REF] Schlosser | Technical Note: Formal blind intercomparison of OH measurements: results from the international campaign HOxComp[END_REF] consequently, they need to be generated directly into the reactor. They were generated through the ozonolysis of an alkene, the 2,3-dimethyl-2-butene (DMB), this method is known as the "dark OH radical generation" [START_REF] Lambe | Controlled OH radical Production via Ozone-Alkene Reactions for Use in Aerosol Aging Studies[END_REF][START_REF] Person | Trifluralin: Photolysis under sunlight conditions and reaction with HO radical[END_REF][START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF][START_REF] Segal-Rosenheimer | Heterogeneous oxidation of the insecticide cypermethrin as thin film and airborne particles by hydroxyl radical and ozone[END_REF]. DMB reacts with ozone to give OH radical according to equation 1 with the rate constant k1 = (1.13 ± 0.01) x 10 -15 cm 3 molecule -1 s -1 [START_REF] Greene | Rate constants for the gas-phase reactions of O3 with a series of alkenes at 296 ± 2 K[END_REF]:

DMB + O3 → •OH + products (1)
An ozone generator (UVP, LLC Upland, UK) was providing a constant concentration of ozone and an ozone analyzer (O3 41M, Environnement S.A) measured its mixing ratio in real time.

DMB and m-xylene were constantly flowing in the reactor thanks to two permeation ovens (Pul 200 Calibrage). DMB flow (F1) was set at 109 mL min -1 . Ozone mixing ratio was kept constant at (3.4 ± 0.3) ppm (i.e., (8.55 ± 0.77) x 10 13 molecules cm -3 ) by changing the exposed surface of the UV light inducing the ozone generation with a constant flow (F3) of 100 mL min -1 .

OH radical measurement and concentration calculation:

The OH radical concentrations were determined using the consumption of a gaseous tracer injected continuously in the reactor. The tracer used was m-xylene (F2, 40 mL min -1 ) because it reacts with OH radical (equation 2) with an accurately known kinetic constant (k2 = (2,2 ± 0.2) x 10 -11 cm 3 molecule -1 s -1 [START_REF] Atkinson | Rate constants for the gas-phase reactions of the OH radical with a series of aromatic hydrocarbons at 296 ± 2 K: GAS-PHASE REACTIONS[END_REF]. This value allowed to observe its degradation during the one-minute residence time of m-xylene in the reactor.

m-xylene + •OH → products (2)
Nevertheless, m-xylene reacts also with ozone according to equation 3 with a rate constant of k3 = 4.10 -21 cm 3 molecule -1 s -1 [START_REF] Kramp | On the Uncertainties in the Rate Coefficients for OH Reactions with Hydrocarbons, and the Rate Coefficients of the 1,3,5-Trimethylbenzene and m -Xylene Reactions with OH radical in the Gas Phase[END_REF][START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF].

m-xylene + O3 → products (3)
As a result, the consumption of m-xylene in the reactor can be described according to equation 4.

-

𝑑[𝑚-𝑥𝑦𝑙𝑒𝑛𝑒] 𝑑𝑡 = 𝑘 2 × [𝑚 -𝑥𝑦𝑙𝑒𝑛𝑒] × [𝑂𝐻 (𝑔𝑎𝑠) ] + 𝑘 3 × [𝑚 -𝑥𝑦𝑙𝑒𝑛𝑒] × [𝑂 3(𝑔𝑎𝑠) ] (4)
According to the experimental conditions used, the reaction between m-xylene and O3 (k3) is negligible compared to the reaction between m-xylene and OH radical (k2) and equation 4 can be simplified into equation 5:

-

𝑑[𝑚-𝑥𝑦𝑙𝑒𝑛𝑒] 𝑑𝑡 = 𝑘 2 × [𝑚 -𝑥𝑦𝑙𝑒𝑛𝑒] × [𝑂𝐻 (𝑔𝑎𝑠) ] (5)
The integration of equation 5 gives the following equation 6: The atmospheric concentration of OH radicals ranges approximately from 10 5 molecule cm -3 [START_REF] Hübler | Groundlevel OH radical concentration: New measurements by optical absorption[END_REF] in remote areas to 10 7 molecules cm -3 in heavily polluted areas [START_REF] Tuazon | Trace pollutant concentrations in a multiday smog episode in the California South Coast Air Basin by long path length Fourier transform infrared spectroscopy[END_REF], during the day as they are formed mainly by photolysis reactions. OH radical concentration in the reactor (average value over the set of experiments: (6.61 ± 0.80) x 10 7 molecules cm -3 ) was set and kept constant prior to experiments. OH radicals concentration was measured for each experiment in order to use its exact value for kinetic constants calculations.

∫ [𝑂𝐻 (𝑔𝑎𝑠) ] 𝑡 0 × 𝑑𝑡 = ln ( [𝑚-𝑥𝑦𝑙𝑒𝑛𝑒] 0 [𝑚-𝑥𝑦𝑙𝑒𝑛𝑒] 𝑡 ) × 1 𝑘 2 (
Along each experiment, OH radicals concentration remained stable with a variation of the concentration of maximum 4.5% over 6 hours.

Humidity:

The required humidity level was obtained by mixing a clean and dry air flux with a humid air flux (close to water saturation level, i.e., 85% RH) obtained by bubbling clean dry air into a humidifier containing deionized water. Clean dry air was provided using a zero-air generator (zero air generator ZA-1500, F-DGS). Humid and dry air flow (F4 and F5) were adapted to reach the relative humidity level wanted in the reactor (0% to 70% RH). Humidity was measured before and after each experiment with a humidity probe (Hydrolog NT, Rotronic, USA, uncertainty 2% RH).

Extraction and pesticides quantification

During OH radical exposure, 30 mg aliquots of particles were regularly sampled in order to quantify the remaining adsorbed pesticides. Each 30 mg aliquot of particles was introduced in a 33 mL stainless steel cell with an internal standard solution (Triphenyl phosphate, 99.9%, Sigma-Aldrich) and pesticides were extracted by accelerated solvent extraction (ASE 350, Dionex) with dichloromethane. Afterward, the extracts were concentrated under a nitrogen flow using a concentration workstation (TurboVap II, Biotage).

Analysis of the obtained solutions was realized using gas chromatography coupled to tandem mass spectrometry (GC/MS-MS), with a Trace GC Ultra (Thermo Scientific) coupled to a TSQ Quantum™ Triple Quadrupole (Thermo Scientific) using electron impact ionization (70 eV).

More details about ASE extraction, concentration, and GC/MS-MS analysis are available in [START_REF] Socorro | Heterogeneous reactions of ozone with commonly used pesticides adsorbed on silica particles[END_REF] and in SI Detailed protocol for pesticide extraction and analysis.

Pseudo-first-order rate constant determination

Considering that OH radicals were continuously produced in the reactor and that its precursors were used in excess, a pseudo-first order kinetic constant was assumed. In the reactor, pesticides could be degraded by OH radicals, but they could also react with ozone as well as with eventual other oxidative compounds produced in the reactor, and finally, they could be hydrolyzed or desorbed from particles. As a result, the equation leading to the decay of pesticide is the following:

-

𝐼𝐼

were calculated from the first order kinetics constants according to a Langmuir-Rideal kinetic model, as detailed in SI Second-order rate constant determination.

The atmospheric pesticide half-lives (t ½ OH (part) 𝑖𝑛 s) resulting from pesticide degradation toward OH radicals were calculated for each specific experimental condition according to equation 11. For these calculations, OH radical concentration was 1.5 x 10 6 molecule cm -3 and the exposure time was 12 hours [START_REF] Lawrence | What does the global mean OH concentration tell us?[END_REF][START_REF] Palm | Degradation of the pesticide primisulfuron-methyl in the aerosol-borne state by OH radical[END_REF][START_REF] Prinn | Evidence for substantial variations of atmospheric hydroxyl radical in the past two decades[END_REF].

t ½ OH (part) = 𝑙𝑛2 𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡) 𝐼𝐼 × [𝑂𝐻 (𝑔𝑎𝑠) ] (11)
Where 𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡)

𝐼𝐼

is the second order kinetic constant (cm 3 molecule -1 s -1 ) and [𝑂𝐻 (𝑔𝑎𝑠) ] the gaseous concentration of OH radicals (molecule cm -3 ).

Results and discussion

Heterogeneous degradation by OH radicals

In order to study the heterogeneous degradation by OH radicals of eight pesticides, i.e., cyprodinil, deltamethrin, difenoconazole, fipronil, oxadiazon, pendimethalin, permethrin, and tetraconazole, experiments were performed at a relative humidity level between 0% and 70%, with pesticides adsorbed on hydrophobic and hydrophilic silica particles. The average OH radical concentration was (6.61 ± 0.80) x 10 7 molecule cm -3 . All kinetic constants obtained were corrected as explained in section 2.6 to subtract the pesticides decay induced by hydrolysis, desorption, ozonolysis, and by reactivity with possible intermediate species formed into the reactor.

Deltamethrin, permethrin, pendimethalin, and cyprodinil were degraded by OH radicals.

Analytical issues concerning cyprodinil are responsible for uncertainties on kinetic constants in average 4 times faster than for deltamethrin, permethrin, and pendimethalin. Therefore, the results are not presented here. Second-order rate constant calculated for deltamethrin, permethrin and pendimethalin ranged from (1.93 ± 0.61) x 10 -13 cm 3 molecule -1 s -1 (obtained for permethrin, hydrophobic silica, 30% RH) to (4.08 ± 0.27) x 10 -12 cm 3 molecule -1 s -1 (obtained for pendimethalin, hydrophilic silica, 0% RH).

Unreactive pesticides

Under our experimental conditions, no degradation was observed for fipronil, difenoconazole, oxadiazon, and tetraconazole (𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡) 𝐼𝐼 ≤ 10 -13 cm 3 molecule -1 s -1 , which corresponds to t ½ OH (part) ≥ 100 days) whatever the humidity level or the particle type was. These results are unexpected as these four pesticides are degraded in the gas phase, i.e., half-lives of less than 1 day (according to theoretical calculations from AOPWIN software (Atmospheric Oxidation

Program for Microsoft Windows [START_REF] Meylan | Computer estimation of the Atmospheric gas-phase reaction rate of organic compounds with hydroxyl radicals and ozone[END_REF]). Furthermore, according to the usual attack mechanism of OH radicals (i.e., for instance, OH abstraction on the C=C double bound for pyrimidine compounds [START_REF] Steenken | Addition-Elimination Paths in Electron-Transfer Reactions between Radicals and Molecules. Oxidation of Organic Molecules by the OH Radical[END_REF], and H abstraction on the -NR2 group which is the most likely mechanism as well as OH addition on the aromatic ring for dinitroaniline compounds [START_REF] Muñoz | Gas-phase degradation of the herbicide ethalfluralin under atmospheric conditions[END_REF]) and to the chemical structure of these pesticides, a chemical degradation should occur [START_REF] Borrás | Particulate and gas-phase products from the atmospheric degradation of chlorpyrifos and chlorpyrifos-oxon[END_REF][START_REF] George | Heterogeneous oxidation of atmospheric aerosol particles by gas-phase radical[END_REF]. However, these experimental results are in agreement with the few studies recently done on these compounds, first, in a previous work done with the same experimental protocol (Socorro et al., 2016a), and second in a study using a different experimental set-up which also demonstrates the non-(or very low) degradation of difenoconazole by OH radicals when adsorbed on quartz surfaces (this work: 𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡) 𝐼𝐼 ≤ 10 -13 cm 3 molecule -1 s -1 , literature : 𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡) 𝐼𝐼 = (7.1 ± 0.8) x 10 -14 cm 3 molecule -1 s -1 (Al [START_REF] Rashidi | The heterogeneous photo-oxidation of difenoconazole in the atmosphere[END_REF]). Concerning other semi-volatile organic compounds, it was shown that gas phase degradation of polycyclic aromatic hydrocarbons (PAH) might be effective, but the degradation of the same compound can be drastically inhibited when adsorbed on a surface [START_REF] Esteve | Relative rate constants for the heterogeneous reactions of NO2 and OH radical with polycyclic aromatic hydrocarbons adsorbed on carbonaceous particles. Part 2: PAHs adsorbed on diesel particulate exhaust SRM 1650a[END_REF]. These studies corroborate the fact that a compound can be degraded by OH radicals in the gas phase but have its reactivity drastically slowed down in the heterogeneous phase. As these results cannot be explained by the chemistry it is most probably due to steric hindrance or passivation when those semi-volatile organic compounds are adsorbed on particles.

Comparison with other studies

Table 1 present all kinetic data available in the literature concerning the heterogeneous degradation of pesticides by OH radicals as well as the results of this study. 1 shows that available kinetic constants of pesticides in the heterogeneous phase toward OH radicals vary from 10 -14 cm 3 molecule -1 s -1 (i.e., half-life greater than 1000 days) to 10 -11 cm 3 molecule -1 s -1 (i.e., half-life of 1.3 days) with the majority of them being around 10 -13 cm 3 molecule -1 s -1 . Values obtained in our study for pesticides degraded by OH radicals are of the order of between 10 -13 cm 3 molecule -1 s -1 and 10 -12 cm 3 molecule -1 s -1 which is in accordance with kinetic constants available in the literature calculated for other pesticides of the same or different chemical families on hydrophobic silica [START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF], hydrophilic silica [START_REF] Liu | Degradation study of the aerosol-borne insecticides Dicofol and DDT in an aerosol smog chamber facility by OH radical in relation to the POPs convention[END_REF][START_REF] Palm | Degradation of the pesticide primisulfuron-methyl in the aerosol-borne state by OH radical[END_REF][START_REF] Zetzsch | Photochemischer Abbau in Aerosolphasen[END_REF], quartz surfaces [START_REF] Bouya | Kinetics of the heterogeneous photo oxidation of the pesticide bupirimate by OH-radical and ozone under atmospheric conditions[END_REF][START_REF] Masri | A mechanistic and kinetic study of the heterogeneous degradation of chlorpyrifos and chlorpyrifos oxon under the influence of atmospheric oxidants: ozone and OH-radical[END_REF], and leaves [START_REF] Lester | Key environmental processes affecting the fate of the insecticide chloropyrifos applied to leaves[END_REF]. However, our values are of one to two orders of magnitude smaller than values determined by one research team for pesticides adsorbed on silicas [START_REF] Palm | OH radical Reactivity of Airborne Terbuthylazine Adsorbed on Inert Aerosol[END_REF][START_REF] Palm | OH radical Reactivity of Pesticides Adsorbed on Aerosol Materials: First Results of Experiments with Filter Samples[END_REF][START_REF] Palm | Atmospheric degradation of a semivolatile aerosol-borne pesticide: Reaction of OH with pyrifenox (an Oxime-Ether), adsorbed on SiO2[END_REF].

Generally, great agreement is observed between results obtained with the different experimental set-ups. To our knowledge, only one study using a different set-up shares the same pesticide (difenoconazole) with the present work [START_REF] Rashidi | The heterogeneous photo-oxidation of difenoconazole in the atmosphere[END_REF]. Regarding this pesticide, results are in accordance, showing a very low reactivity toward OH radicals, even though they studied its degradation on quartz surfaces and in a different experimental set-up. In the same way, similar degradation rates were obtained for chlorpyrifos adsorbed on quartz surface [START_REF] Masri | A mechanistic and kinetic study of the heterogeneous degradation of chlorpyrifos and chlorpyrifos oxon under the influence of atmospheric oxidants: ozone and OH-radical[END_REF] and on leaves [START_REF] Lester | Key environmental processes affecting the fate of the insecticide chloropyrifos applied to leaves[END_REF]. However, terbuthylazine showed different degradation rates according to the surface (i.e., hydrophilic or hydrophobic silica). Kinetic constants were two orders of magnitude higher on hydrophobic silica [START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF] than on hydrophilic silica [START_REF] Palm | OH radical Reactivity of Airborne Terbuthylazine Adsorbed on Inert Aerosol[END_REF]. The difference could be attributed to mass transport and shielding effect induced by different experimental techniques and conditions [START_REF] Socorro | Heterogeneous OH Oxidation, Shielding Effects, and Implications for the Atmospheric Fate of Terbuthylazine and Other Pesticides[END_REF].

It seems that experimental set-up conditions used can impact the absolute kinetic constants value measured. Given the limited amount of studies concerning OH radical degradation in the literature, it is complicated to assess which system is the most suitable for this type of work.

Nevertheless, comparing values using a given experimental set-up, as it is the case in this study, allows determining which environmental factors are likely to influence the kinetic constants.

Influence of the particle type

Two model particles were chosen to investigate the influence of the particle type on the heterogeneous reactivity of pesticides: hydrophobic and hydrophilic silicas. These two kinds of particles are similar in composition, specific surface area, and size. However, their surface properties are different due to the presence of different surface groups (siloxane vs silanol).

Hydrophilic silica is prone to adsorbed easily and rapidly water on its surface whereas hydrophobic silica is not. Fig. 2 present the second order degradation rate constants of pendimethalin, deltamethrin, and permethrin in absence of water for the two types of particles. Fig. 2: second-order kinetic constants for deltamethrin, permethrin, and pendimethalin degraded by OH radicals at 0% RH Deltamethrin, pendimethalin, and permethrin were all degraded on both particle type in absence of water. However, they were degraded 3.3, 2.4, and 4.7 times faster on hydrophilic silica than on hydrophobic silica, respectively (Fig. 2).

The faster degradation on hydrophilic silica than on hydrophobic silica for deltamethrin, pendimethalin, and permethrin suggests an influence of the particle surface properties on the degradation kinetics of the pesticides. Such an observation was already done for the degradation by OH radicals of (PAH) adsorbed on graphite and diesel particles [START_REF] Esteve | Relative rate constants for the heterogeneous reactions of OH, NO2 and NO radical with polycyclic aromatic hydrocarbons adsorbed on carbonaceous particles. Part 1: PAHs adsorbed on 1-2μm calibrated graphite particles[END_REF][START_REF] Esteve | Relative rate constants for the heterogeneous reactions of NO2 and OH radical with polycyclic aromatic hydrocarbons adsorbed on carbonaceous particles. Part 2: PAHs adsorbed on diesel particulate exhaust SRM 1650a[END_REF].

Authors attributed this influence to the variability of PAH accessibility for OH radicals. This phenomenon is not specific to reactivities with OH radicals since, in a previous work focused on the study of the heterogeneous ozonolysis of cyprodinil, deltamethrin, permethrin, and pendimethalin, a faster degradation was observed when these molecules were adsorbed on hydrophilic silica particles rather than on hydrophobic particles as well [START_REF] Mattei | Heterogeneous atmospheric degradation of pesticides by ozone: Influence of relative humidity and particle type[END_REF].

Influence of humidity

Experiments were conducted at 0% RH, 30% RH, 55% RH, and 70% RH both on hydrophobic and hydrophilic silicas to study the influence of humidity on the degradation of pesticides by OH radicals. 0% RH is a humidity level which does not exist in the atmosphere (relative humidity in the atmosphere commonly ranges from 30% RH to 100% RH), however, several studies were conducted without or almost without water [START_REF] Rashidi | The heterogeneous photo-oxidation of difenoconazole in the atmosphere[END_REF], 2014;[START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF]. Experiments in absence of water help to understand the role of water in the degradation processes of pesticides. 55% RH and 70% RH are realistic levels, often reached in the atmosphere. A previous work [START_REF] Goodman | Spectroscopic Study of Nitric Acid and Water Adsorption on Oxide Particles: Enhanced Nitric Acid Uptake Kinetics in the Presence of Adsorbed Water[END_REF] have shown that the number of water layers on silica particles (hydrophilicity not mentioned) is approximately one monolayer at 20% RH, two to three adsorbed water layers at 50% RH, and three to four at 85% RH. 70% RH, the highest level tested is, therefore, a realistic level where the aerosol is close to the state of a liquid droplet. When adsorbed on hydrophilic silica, the degradation rate of pesticides by OH radicals ranged from ≤ 10 -13 cm 3 molecule -1 s -1 (unreactive) (permethrin, 70% RH) to (4.08 ± 0.27) x 10 -12 cm 3 molecule -1 s -1 (pendimethalin, 0% RH). Deltamethrin, permethrin, and pendimethalin appeared to be degraded faster when relative humidity was minimized. Deltamethrin and permethrin were degraded respectively 3.1 and 48 times faster in absence of water compared to 70% RH.

Pendimethalin was degraded 2.7 faster at 0% RH than at 55% RH but its degradation rate was unexpectedly enhanced by the increase of relative humidity between 55% RH and 70% RH. On hydrophilic silica, relative humidity has, therefore, a strong impact on the degradation rates of pesticides sensitive to OH radical degradation.

Concerning the degradation of pesticides adsorbed on hydrophobic silica, the kinetic constants ranged from ≤ 10 -13 cm 3 molecule -1 s -1 (unreactive) (permethrin and pendimethalin, 70% RH) to (1.73 ± 0.38) x 10 -12 cm 3 molecule -1 s -1 (pendimethalin, 0% RH). Deltamethrin degradation rate was, given the large uncertainties, not influenced by the relative humidity level. Permethrin degradation rates were independent of the relative humidity level between 0% RH and 55% RH but at 70% RH, no degradation was observed. In contrast, pendimethalin reactivity was slowed down by an increase of relative humidity, its degradation rate was 13.1 times faster at 0% RH than at 30% RH and it was close to the detection limit (10 -13 cm 3 molecule -1 s -1 ) at 70% RH.

Relative humidity appeared to have an influence on the heterogeneous degradation of pesticides under study by OH radicals when adsorbed on hydrophobic silica or hydrophilic silica; the increase of water content induced a decrease in the degradation rates. However, the sensitivity of each pesticide to the influence of relative humidity is different from a compound to another.

The increase of water content on the particle surface could play a shielding effect toward OH radicals. Indeed, in the presence of water, the OH radicals must diffuse through the water layers to access the pesticide, process which is slower in water than in air. This could be responsible for the slowing down effect at high RH levels when the state of the water droplet is close to being reached. Hydrophilic silica is more prone to adsorb water on its surface than hydrophobic silica for a given relative humidity level. Thereby it is logical that the influence of increasing relative humidity level on the kinetic constants is discernable at a lower relative humidity level on hydrophilic silica than on hydrophobic silica. To our knowledge, there is no study mentioning an influence of humidity on pesticide degradation by OH radicals in the heterogeneous phase. Nevertheless, slower degradation at higher moisture level was already observed in many studies in the case of the heterogeneous degradation of organic compounds by ozone [START_REF] Kaiser | Detailed heterogeneous oxidation of soot surfaces in a particle-resolved aerosol model[END_REF][START_REF] Mattei | Heterogeneous atmospheric degradation of pesticides by ozone: Influence of relative humidity and particle type[END_REF][START_REF] Pöschl | Interaction of Ozone and Water Vapor with Spark Discharge Soot Aerosol Particles Coated with Benzo[a]pyrene: O3 and H2O Adsorption, Benzo[a]pyrene Degradation, and Atmospheric Implications[END_REF], this was often attributed to a competitive adsorption between ozone and water on the surface. Because of the very high OH reactivity, this hypothesis done for ozone, cannot be transposed directly to this work. However, it is possible that the presence of water on the particles surface implies harder pesticide access for OH radicals due to steric constraints or by protecting pesticides under water layers, leading to a competition between OH radicals and water to access the pesticides.

Water could also influence the kinetics additionally if its presence is necessary in the degradation mechanism of the pesticide, in that case, degradation mechanism would take different pathways depending on the presence or absence of water, as it could be the case for pendimethalin which is the most sensitive compound to relative humidity when adsorbed on both particle types.

Influence of pesticide nature

There is a very large number of pesticides used nowadays (352 in France in 2018 (European Commission, 2018)), they are very diverse in chemical structure and belong to many chemical families. Among the 8 pesticides used in this work, six chemical families are represented: diazole (oxadiazon), dinitroaniline (pendimethalin), pyrazole (fipronil), pyrethroid (permethrin, deltamethrin), pyrimidine (cyprodinil), and triazole (difenoconazole, tetraconazole). Depending on the pesticide, significant differences are observed in this work on the second-order kinetic constants while the same experimental conditions were used. This was previously observed in other studies concerning heterogeneous degradation of pesticides by OH radicals [START_REF] Rashidi | Heterogeneous oxidation of folpet and dimethomorph by OH radical: A kinetic and mechanistic study[END_REF][START_REF] Masri | A mechanistic and kinetic study of the heterogeneous degradation of chlorpyrifos and chlorpyrifos oxon under the influence of atmospheric oxidants: ozone and OH-radical[END_REF][START_REF] Palm | OH radical Reactivity of Airborne Terbuthylazine Adsorbed on Inert Aerosol[END_REF].

The chemical structure of pesticides seems to have a significant influence on their reactivity since the two pesticides of the pyrethroid chemical family (deltamethrin and permethrin) were degraded by OH radicals whereas the two pesticides of the triazole chemical family (difenoconazole and tetraconazole) were not (or very slowly) degraded. Indeed, the triazole reactivity toward OH radicals in the gas phase (i.e., an OH-addition onto carbons atoms of the triazole cycle) was considered as a very slow reaction at ambient temperature [START_REF] Derbel | Tropospheric Reactions of Triazoles with Hydroxyl Radicals: Hydroxyl Addition Is Faster than Hydrogen Abstraction[END_REF], which might explain our results. The number of pesticides studied in each of these two families is too limited to come to a conclusion, nevertheless, a similar behavior might be extended to other compounds of these families of pesticides.

Deltamethrin and permethrin are both of the pyrethroid family, but reactivity of deltamethrin was influenced by water only when adsorbed on hydrophilic silica, while reactivity of permethrin was influenced by water when absorbed on both particle type. It was previously shown that water plays a role in the heterogeneous degradation mechanism of deltamethrin and permethrin with ozone as well (Socorro et al., 2016b). These results show that the way humidity influences the degradation rate of a pesticide can then hardly be extended to other pesticides even within the same chemical family.

Atmospheric implications

Fig. 4 shows the extent of particulate half-lives determined in this study regarding OH radicals and the half-lives calculated with the AOPWIN software [START_REF] Meylan | Computer estimation of the Atmospheric gas-phase reaction rate of organic compounds with hydroxyl radicals and ozone[END_REF] concerning gas-phase OH radical degradation. OH radical concentration used for the calculation was 1.5 x 10 6 molecule cm -3 and the average exposure time was 12 hours [START_REF] Palm | Degradation of the pesticide primisulfuron-methyl in the aerosol-borne state by OH radical[END_REF][START_REF] Lawrence | What does the global mean OH concentration tell us?[END_REF][START_REF] Prinn | Evidence for substantial variations of atmospheric hydroxyl radical in the past two decades[END_REF]. which correspond to OH radical concentration measured in medium polluted areas [START_REF] Hard | Tropospheric free radical determination by fluorescence assay with gas expansion[END_REF][START_REF] Hübler | Groundlevel OH radical concentration: New measurements by optical absorption[END_REF]. Half-lives corresponding to the heterogeneous degradation of the pesticides by OH radicals were calculated using the experimental second order kinetic constants obtained in this study. Finally, half-lives for pesticides in the gaseous phase and particle phase together were calculated using theoretical partitioning of the pesticides between the two phases based on the Junge-Pankow model. Fig. 4: Half-lives of pesticides in the gas phase, in the particle phase, and in both phases combined and according to their theoretical partitioning between gas and particle phases regarding OH radical reactivity (for an OH radical concentration of 1.5 x 10 6 molecule cm -3 and an exposure time of 12h) Heterogeneous half-lives calculated for deltamethrin, pendimethalin, and permethrin ranged from 3 days to more than 100 days. Half-life values were distributed widely, as can be seen in Fig. 4, for permethrin, deltamethrin, and pendimethalin tested in different conditions with OH radicals. This highlight the fact that degradation conditions affect the heterogeneous lifetime of pesticide in the atmosphere and should, therefore, be chosen carefully when making experiments to determine realistic atmospheric half-lives values.

The software AOPWIN allows the calculation kinetic constants for the degradation of organic molecules by OH radicals in the gas phase. AOPWIN calculations were already proven to give results similar to the experimental ones in the case of the degradation in the gas phase of metolachlor [START_REF] Chao | The Reaction Mechanism and Kinetics for the Reaction of OH radical with Atmospheric Metolachlor[END_REF], as well as of prosulfocarb and S-ethyl N,N244 dipropylthiocarbamate (Munoz et al., 2018), even though disagreement between theory and experimental results were highlighted concerning organonitrogen compounds [START_REF] Borduas | Experimental and Theoretical Understanding of the Gas Phase Oxidation of Atmospheric Amides with OH Radicals: Kinetics, Products, and Mechanisms[END_REF]. AOPWIN calculations indicate that in the gas phase the eight pesticides under study should react with OH radicals, with associated half-lives varying from 0.1 days (cyprodinil) to 2.1 days (tetraconazole). Concerning pesticides reacting with OH radicals in the particle phase, half-lives calculated are all superior to 3 days. Also, degradation of tetraconazole, difenoconazole, oxadiazon, and fipronil, which is effective in the gas phase, was hindered in the particle phase. Concerning pesticide under study, heterogeneous degradation by OH radicals is, therefore, slower than homogeneous degradation. Differences in reactivity of pesticides between gas and particle phases were already highlighted in previous studies (El [START_REF] Masri | A mechanistic and kinetic study of the heterogeneous degradation of chlorpyrifos and chlorpyrifos oxon under the influence of atmospheric oxidants: ozone and OH-radical[END_REF]El Rashidi et al., 2014;[START_REF] Lester | Key environmental processes affecting the fate of the insecticide chloropyrifos applied to leaves[END_REF][START_REF] Papagni | Heterogeneous Oxidation of Terbuthylazine by "Dark" OH radical under Simulated Atmospheric Conditions in a Flow Tube[END_REF]Socorro et al., 2016).

The theoretical partitioning of pesticides between the gas phase and the particle phase allows calculation of half-lives regarding OH radicals in both phases combined. For pesticides present mainly in the gas phase, combined half-lives are close to those concerning the gas phase only, as for instance for pendimethalin and tetraconazole. For other pesticides, taking into account the heterogeneous degradation in the calculation of combined half-lives induces significant differences on the results. For deltamethrin and permethrin, the combined half-lives are therefore widely distributed (2.2 days to 4 days and 3.3 days to 14.4 days, respectively) and are dependent on the conditions (relative humidity and particle type).

Atmospheric half-lives of pesticides help to understand their fate in the atmosphere, for instance, with half-lives of several dozens of days, they might be able to be transported at a global scale, possibly impacting human health and the environment far away from their application location. However, significant half-lives will in fact not be observed in the atmosphere as it is commonly accepted that particles have an atmospheric lifetime of approximately 10 days.

According to the Stockholm convention (UNEP, 2001), the atmospheric half-life in the gas phase is the criteria used to determine if a compound is a persistent organic pollutant (t1/2 > 2 days). Therefore, the good determination of atmospheric degradation rates and half-lives is crucial for regulatory purposes. For all pesticides under study half-lives calculated regarding OH radicals in the particle phase only, are all above 2 days and half-lives regarding the gas phase only are all under 2 days. However, taking in account both the particle phase and gas phase, permethrin, deltamethrin, and difenoconazole have halves-lives superior to 2 days regarding OH radicals (2.2 days to 4 days, 3.3 days to 14.4 days, and 4.4 days to 4.5 days, respectively). They should, therefore, be considered as persistent organic pollutants regarding this oxidant, and heterogeneous degradation is thus important to take into account for determining pesticides atmospheric half-lives.

Conclusion

Heterogeneous degradation of pesticides by OH radicals was investigated, with various relative humidity level and particle type. Cyprodinil, deltamethrin, permethrin, and pendimethalin were reactive with OH radicals, with degradation rates consistent with the literature. OH radical degradation kinetics were dependent on relative humidity, particle surface type, and chemical nature of the adsorbed pesticides. Degradation rates were up to 5 times faster on hydrophilic silica than on hydrophobic silica, suggesting an influence of the surface properties on the kinetics. Generally, an increase of relative humidity induced a decrease in the degradation kinetics, with diminution factors up to a few dozen times. The influence of the water content might be due mainly to the formation of a water protection layer on the surface lowering the accessibility for OH radicals. These findings imply that relative humidity and particle type must be considered to determine kinetic rate constants and that studies carried out in absence of water cannot be considered as representative of the atmospheric conditions. Also, a significant difference in half-lives values regarding OH radical with only the gas phase (0.1 days to 2.1 days) or the gas phase and the particle phase together (2.2 days to > 100 days) was found. This shows that the heterogeneous degradation should be taken into account when calculating halflives for regulatory purposes.

Fig. 1 :

 1 Fig. 1: Experimental setup to study heterogeneous oxidation of pesticides by OH radicals

  6) Where t (s) is the residence time of compounds in the gaseous phase in the reactor, [m-xylene]0 and [m-xylene]t (molecule cm -3 ) are the initial and final concentrations of m-xylene in the reactor, k2 is the rate constant (equation 2) and [OH(gas)] is the OH radical concentrations in the reactor during the experiment. DMB degradation products (m/z = 85, 71, 57, 43, and 41) and m-xylene (m/z = 107) (Fig. SI4) concentrations were monitored with a time resolution of 10 seconds using an High-Sensitivity Proton Transfer Reaction Mass Spectrometer (HS-PTR-MS, Ionicon Analytik). A negative shift in the concentration of m-xylene and a positive shift in DMB degradation products were observed in presence of ozone, corresponding to the loss of m-xylene due to its consumption by OH radical and the products formed by the ozonolysis of the DMB. Parameters for HS-PTR-MS analysis are given in SI.

Fig. 3 a

 3 Fig.3 a, and b present the degradation rates of deltamethrin, permethrin, and pendimethalin at

Fig. 3 a

 3 Fig. 3 a, and b: Second-order rate constants for the OH degradation of pesticides adsorbed on

Table 1 :

 1 Available data for the heterogeneous degradation of pesticides by OH radicals

	283
	Chemical family	Pesticide	Relative Humidit y (%)	Temperature (°C)	OH radical concentration (molecule cm -3 )	Surface	𝑘 𝑂𝐻 (𝑝𝑎𝑟𝑡) 𝐼𝐼 (cm 3 molecule -1 s -1 )	t ½ OH (part) (days) a	Reference
	Pyrethroid	Deltamethrin Permethrin	0-70 55 0-70 55		6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8 6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8	Hydrophobic / hydrophilic silica Hydrophobic silica Hydrophobic / hydrophilic silica Hydrophobic silica	(5.64 ± 0.53) x 10 -13 to (2.88 ± 0.27) x 10 -12 (6.9 ± 0.2) x 10 -13 ≤ 10 -13 to (2.57 ± 0.09) x 10 -12 (5.5 ± 0.1) x 10 -13	4 to 19 33.5 4 to ≥ 100 42.1	This study Socorro et al., 2015 This study Socorro et al., 2015
	Dinitroaniline	Pendimethalin	0-70 55		6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8	Hydrophobic / hydrophilic silica Hydrophobic silica	≤ 10 -13 to (4.08 ± 0.27) x 10 -12 (4.3 ± 0.3) x 10 -13	3 to ≥ 100 53.8	This study Socorro et al., 2015
	Pyrimidine Diazole	Cyprodinil Oxadiazon	0-70 55 0-70 55	25	6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8 6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8	Hydrophobic / hydrophilic silica Hydrophobic silica Hydrophobic / hydrophilic silica Hydrophobic silica	≤ 10 -13 to (2.50 ± 0.14) x 10 -12 (9.7 ± 0.2) x 10 -13 ≤ 10 -13 < (4.3 ± 0.3) x 10 -13	4 to ≥ 100 23.9 ≥ > 53.8	This study Socorro et al., 2015 This study Socorro et al., 2015
	Pyrazole	Fipronil	0-70 55		6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8	Hydrophobic / hydrophilic silica Hydrophobic silica	≤ 10 -13 < (4.3 ± 0.3) x 10 -13	≥ > 53.8	This study Socorro et al., 2015
		Tetraconazole	0-70 55		6.61 x 10 7 6.1 x 10 7 -1.45 x 10 8	Hydrophobic / hydrophilic silica Hydrophobic silica	≤ 10 -13 < (4.3 ± 0.3) x 10 -13	≥ > 53.8	This study Socorro et al., 2015
	Triazole		0-70		6.61 x 10 7	Hydrophobic / hydrophilic silica	≤ 10 -13	≥	This study
		Difenoconazole	55		6.1 x 10 7 -1.45 x 10 8	Hydrophobic silica	< (4.3 ± 0.3) x 10 -13	> 53.8	Socorro et al., 2015
			0.7	29	/	quartz	(7.1 ± 0.8) x 10 -14	326	Al Rashidi et al., 2011

Table

Acknowledgment

This work has been carried out thanks to the support of the COPP'R project funded by the PRIMEQUAL -AGRIQA « Agriculture et qualité de l'air » program. C. Mattei received a doctoral grant from the French Environment and Energy Management Agency (ADEME) and the Region Provence-Alpes-Côte d'Azur.


Aurélia Secroun
email: secroun@cppm.in2p3.fr

Jean-Claude Clémens

Anne Ealet

William Gillard

Benoît Serra

Julien Zoubian

Rémi Barbier

Sylvain Ferriol

Bogna Kubik

Cyrille Rosset

Euclid flight H2RG IR detectors: per pixel conversion gain from on-ground characterization for the Euclid NISP instrument

Keywords: Euclid, NISP, IR detectors, H2RG, Conversion factor, Conversion gain, Telemetry

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

INTRODUCTION

Euclid is a major ESA mission due to launch in 2021 aimed at mapping the geometry of the dark Universe. Euclid is optimized for two probes, weak gravitational lensing and baryonic acoustic oscillations, [START_REF] Laureijs | Euclid definition study report[END_REF] which will be measured thanks to a visible imager (VIS) and an infrared spectrometer and photometer (NISP) both designed and built by the Euclid Consortium teams. The NISP instrument 2 will hold a large focal plane array of 16 nearinfrared H2RG detectors which are a key element to the performance of the NISP, and therefore to the science return of the mission. Thorough on-ground testing of the detectors has started at CPPM since June 2017 for characterization and calibration purposes with a view to producing a reference database of pixel maps of detector performances in terms of dark current, noise and quantum efficiency, among others. Most important characterization is on parameters such as persistence and non-linearity for which models should be defined on ground as they are difficult to characterize in flight. These will be addressed in a future paper. Dedicated test benches as well as the whole acquisition and L1 level (Data Quality Checking) analysis codes have been previously designed, built and validated thanks to several pilot runs. This work has led to an efficient and reliable fully integrated acquisition and validation system and a thorough test flow whose main features are presented in the first part. The second part presents some first results and methods focusing on the derivation of a per pixel conversion gain for two detectors taken as an example.

CHARACTERIZATION OF H2RG DETECTORS

Characterization has been going on continuously for more than a year at CPPM. Detectors are tested four by four in two twin test benches specifically designed and fabricated for the purpose of detector characterization. Characterization is closely linked to the NISP instrument calibration both on ground and in flight since detectors are a major part of the instrument chain. Its aim is to provide pixel maps of detector performance that will allow the mission to reach 1% accuracy on the galaxy measured flux after correction. Thanks to a fully automated chain of acquisition and a thorough flow of tests developed between IPNL (in charge of acquisition software) and CPPM (in charge of setup), some 20 TB of data are acquired for each detector with an average of 85% efficiency in acquisition time.

Detectors

The focal plane of the NISP instrument holds 16 H2RG detectors specifically designed for the Euclid mission with a 2.3 µm cutoff and 18 µm pixel pitch. These detectors have been procured and qualified by NASA following a ranking done in collaboration with the Euclid Consortium Detector Scientist. For the purpose of characterization, the detectors are readout by sidecar cold electronics (SCE) provided by Teledyne and Markury Scientific EGSE which allows simultaneous readout of two detectors (and potentially up to 16 as will be tested on the NISP instrument). Their configuration includes 15 dB gain and 500 mV bias voltage to optimize dynamic range according to Euclid needs. In particular, the saturation of ADC voluntarily takes place before the saturation of full well. The matrix is readout through 32 channels. Reference pixel correction has been defined and optimized previously in order to minimize noise. [START_REF] Kubik | Impact of common modes correlations and time sampling on the total noise of a h2rg near-ir detector[END_REF] Among the 16 detectors, two of them are used as an example to show some methods and results. Their flat field illuminations are shown in figure 1 where singular patterns may be observed. Dark currents at the level of 10 -3 e/s have been measured as may be seen in table 1.

Test flow

Four types of acquisitions allow to evaluate the detector performance: tests in dark condition for dark current and science mode noises (photometry and spectroscopy), tests under changing flux illumination to study nonlinearity and persistence, tests under changing wavelength illumination to derive flat fielding maps, and electrical tests to sort out non-linearity of the detector from that of the ASICs.

Most tests are done at three temperatures since the flight operating temperature is not known precisely yet: 80K, 85K and 90K (dark tests are also done at 100K). This will allow to adjust the calibration to the onboard operating temperature thanks to the derivation of temperature dependent models of various parameters, such as dark current and persistence. Herein presented results are derived at 85K.

To evaluate conversion factor, illumination with changing flux of various types may be used: alternate flux and short dark, alternate flux and long dark, alternate flux and "zodi", * and continuous illumination. Illumination ramps are based on the spectroscopy mode of the NISP instrument, namely a duration of 560 seconds. These various illumination types should allow to decorrelate effects of trapping and detrapping competing within the pixels.

Test bench performance

Two parameters are particularly critical to the measurements done in the above described test flow: the thermal stability of the focal plane array which must be controlled to the mK in order to limit thermal effects and the stability and homogeneity of the flux received on the detector. The thermal stability of focal plane array has been checked to be better than 2mK. [START_REF] Secroun | Characterization of h2rg ir detectors for the euclid nisp instrument[END_REF] A Thorlabs 1600P LED (with 1550 nm central wavelength at room temperature) is used to provide homogeneous flux. Spatial homogeneity has been checked previously to better than 2%. [START_REF] Secroun | Characterization of h2rg ir detectors for the euclid nisp instrument[END_REF] Moreover, controlling current allows to vary the incoming flux from less than 1 e/s to more than 4000 e/s. The flux stability of LED is continuously monitored: a cooled reference photodiode directly faces the LED and measures its flux. A stability of better than 0.5% over the whole time of acquisition has been obtained. As may be seen in figure 2, the LED flux is stable to better than 0.1% over single acquisitions (duration of up to 15 hrs). On the contrary, detector response shows stronger variations during the first few ramps and it may be seen (dashed lines) that this variation is stronger for continuous-illumination acquisitions, up to 4%. This variation may be due to detrapping from the previous ramp. These effects are quite disturbing for the derivation of the conversion gain as will be seen below.

CONVERSION GAIN

To validate that the detector fulfills science requirements and derives actual fluxes from observed galaxies, measured signal should be expressed in physical terms (electrons or photons) rather than the arbitrary digital unit (ADU) that is the result from the analog-to-digital conversion (ADC) of the charge present in the photodiode.

For that matter, the detector conversion gain or conversion factor must be evaluated precisely. For the Euclid mission it is a fundamental step in order to derive fluxes with 1% accuracy. Most of all, a pixel map of the gain should be produced if, as will be shown hereafter, it is not spatially homogeneous.

Method

Conversion gain is generally defined as the number of electrons represented by each ADU, and may be considered as the combination of two terms: the charge-to-voltage conversion (V/e) and the analog-to-digital conversion (ADU/V). Many methods have been derived to calculate the conversion gain among which the two main ones, which actually end up being mathematically equivalent, are the photon transfer [START_REF] Janesick | Ccd characterization using the photon transfer technique[END_REF][START_REF] Janesick | Photon Transfer: DN → λ[END_REF] and the mean variance. [START_REF] Holdsworth | A time-delay integration charge-coupled device camera for slot-scanned digital radiography[END_REF] More recent works have also proposed solutions taking into account finer effects such as non-linearity 8 or interpixel capacitance. [START_REF] Finger | Conversion gain and interpixel capacitance of cmos hybrid focal plane arrays[END_REF][START_REF] Moore | Interpixel capacitance in non-destructive focal plane arrays[END_REF] The standard "variance vs. signal" method is of interest for it allows to derive the conversion gain in the presence of read noise, which is the case at low fluxes, where our detectors are expected to be linear. This general method assumes a linear response of the detector, Poisson statistics of incident photons and negligible gain variance.

Then, the output signal S is given by

S (ADU ) = G (ADU/e) • N e (e) (1)
where G is the conversion gain and N e , the mean number of signal electrons, is supposed to follow Poisson statistics. Applying the quadratic propagation of errors, one may derive the conversion gain through:

σ 2 S = G • S + σ 2 R , (2)
where G is the conversion gain (in ADU/e), S is the output signal (ADU), σ S is the illumination dependent noise and σ R represents illumination independent fluctuations (read noise). Thus with a simple least square fit, the gain may be obtained as the slope of the fit, while the read noise will come from the intercept of the fit.

Figure 3, left, shows the beginning of scs2 "variance vs. signal" curve for which several fluxes have been combined and seem to nicely align. Figure 3, right, shows the residual from the least square fit obtained for signals up to 4000 ADU. This method seems well adapted to our experiment and has been applied here to evaluate the conversion gain of the detectors. Experimentally, the conversion gain has been derived from pairs of ramps, referred to as "fast PTC" technique. While the standard technique requires to acquire N ramps at a number of fluxes between dark and saturation, here only two ramps may be sufficient to evaluate the conversion gain, making this method much faster. Also, through the subtraction of the ramps, it allows to get rid of the fixed pattern noise. Then the spatial mean and the spatial variance are derived for each frame of the ramp as

S = mean S 1 + S 2 2 , (3)
σ 2 S = variance S 2 -S 1 2 , (4)
where mean and variance are taken over a chosen area of pixels and S 1 and S 2 are obviously the signals in the two ramps respectively.

In any case, the calculation requires proper selection of pixels to avoid non-linear pixels, as described in more details in 3.2, and choice of incoming fluxes and ramp length to remain within the linear regime of the detector. Part 3.3 shows how telemetry gives us evidence of the quality of the data taken, while part 3.4 gives some results and compares gains obtained for different configurations.

Pixel selection

Since signal and noise are calculated over a group of pixels, respectively as their mean and variance values, it is important to exclude pixels whose signal or noise, for some reason, lies in the tail of the distribution. A simple 5-σ cut would lead to a proper result but is nevertheless not satisfying in that it has no physical meaning. Consequently, our selection of pixels has followed several criteria: 1. remove disconnected pixels: basically, this excludes a few hundreds of pixels 2. remove pixels with high baseline (over 30,000 ADU), as we want to work in the linear regime: another few hundreds of pixels excluded 3. remove non-linear pixels with a Quality Factor on the linearity of the ramp 4. aggregate pixels according to their interpixel capacitance (IPC) value which modifies the gain

Selection with regard to linearity

Beyond selecting a proper range of fluxes, some pixels appear to have a strong non-linearity, whatever the flux. Non-linearity has been evaluated thanks to a quality factor (QF) based on χ 2 calculations. This quality factor is described in details elsewhere. [START_REF] Kubik | A new signal estimator from the nir detectors of the euclid mission[END_REF] It is derived for each ramp and each pixel with a view to validating the calculated flux. Figure 4, left, shows the normalized histogram of QF for scs2 for an incoming flux of 52 e/s. † The width of the peak depends on the incoming flux and gets larger with higher fluxes. A very long tail may also be observed that definitely needs to be cut, as it corresponds to highly non-linear pixels. A cut on QF beyond 10 has thus been applied to all ramps.

Selection with regard to IPC

Interpixel capacitance (IPC) has been measured thanks to the Single Pixel Reset (SPR) technique. 9 IPC histogram of scs2 seen in figure 4, center, shows three peaks: the main one, on the left, corresponds to the majority of pixels ; the second peak, to the right, includes pixels with lower IPC and the third peak corresponds to boundary pixels between those two regions. Thus, two regions may be defined with "low" and "high" IPCs. The difference is actually due to the process of fabrication taking place during the "gluing" of the sensitive MCT area onto the indium bumps. These two regions will turn out, as seen below, to have rather different conversion gains and should thus be treated separately.

Telemetry

Euclid firmware, loaded in the SCE, provides powerful analog telemetry. Each frame coming from the cold readout electronics (SCE) contains an additional column sheltering digitized values of main bias voltages and currents, temperature sensors and logical states of the SCE. This allows us to verify, on an almost real time basis, the overall system stability.

The preamp gain for bias voltages is of -3dB (0.707) giving a resolution of about 80 µV/ADU. Figure 5, left, displays the histogram of the main analog voltage VDDA over a 12 hour acquisition (i.e. 27000 frames). Notice that the stability of the voltage (even combined with the readout noise of the system) given by the RMS of the distribution is of 0.3 mV (0.1%). The chronogram of the same voltage for all runs of a detector full characterization, that is over 45 days of acquisition, combining the four temperatures, is given in figure 5, right. Again, the bias value digitized by the SCE is very stable, which is a good indicator of the goodness of data taken.

Mean gain

After initially working over the whole matrix to which the above described pixel selection has been applied, smaller areas have been chosen (channels, columns, pixels), which requires many data in order to obtain acceptable statistical error on the resulting gain. Various results are presented in figure 6 and detailed hereafter. Part 3.5 is dedicated to the per pixel conversion gain measurement method itself.

Gain vs. ramp length

While, in the general case, the conversion gain is expected to be constant, we took a look at its variation with the length of the ramp (in other words the integrated incoming signal). For that matter, we applied the mean variance method and calculated the conversion gain on partial ramps of N frames (namely selecting frames from first frame to frame N) and varying N from 10 to 400, the total length of the acquired ramps. The derived conversion gain is plotted against the number N of selected frames in figure 6, for various configurations. Some discrepancies may be seen, most probably a consequence of persistence and this issue should be explored further. The gain has been calculated over 20 ramps of continuous illumination acquired at 52 e/s incoming flux. Error bars shown in figure 6 are calculated from the standard deviation of all 19 pairs of ramps.

First let us look at the black curve on the left for which the whole matrix and the whole ramp were used, with reference pixel correction (as mentioned above). It may be observed, as expected, that the statistical error is larger at the beginning of the ramp where the readout noise is dominating. Similarly, at larger signals (end of ramp) the decreasing slope is due to the non-linearity of the detector, which thus seems to start already at the 100 th frame, namely around 5000 ADU.

Reference pixel correction

In comparison to the black curve, the red curve shows the gain obtained with no reference pixel correction. Clearly, both red and black curves show the same slope of non-linearity. However, there is a strong effect at the beginning of the ramp that shows that spatial variance contains more than shot noise. Reference pixel correction improves the accuracy and reduces systematic errors due to correlations.

Start of ramp

The blue curve is obtained with reference pixel correction, but after removing the first 100 frames. As expected the new beginning of the ramp is then much neater and the slope of the non-linearity still the same.

Odd and even columns

In figure 6, right, we compare three subsets of pixels: channels, odd columns and even columns. For each subset, conversion gain is initially derived for individual channel or column and then an average value for all columns or all channels is represented in figure 6. Error bars are calculated over centered gains from all subsets over the 19 values obtained. Thus the values obtained give a maximum error since it includes the actual error plus the RMS of the distribution of all values in the subset. Some discrepancies may be seen, most probably due to outliers that have not been rejected by our quality factor. This should be looked into in order to find more efficient selection criteria.

Finally, even columns and channels are almost superimposed, while odd columns are very slightly off. No effect seems connected to the channel output buffer. Odd and even columns have different current sources and the slight variation could be connected to different clocking.

Gain per pixel

If scs2 has been chosen for calculations over the matrix, allowing to exclude very few pixels (less than 0.8%, including the "IPC" area), it is more interesting to work here with scs1 which shows a larger "IPC" area that will be hereafter referred to as the "Fish". In order to observe spatial variations of the gain and to be sure to get enough statistics:

1. reference pixel correction has been applied to all pixels, 2. pixel selection has been applied as described above, but both "IPC" areas have been included here, 3. pixels have been grouped into larger pixels composed of 16x16 pixels, or 64x64 pixels, 4. the length of the ramps has been limited to 5000 ADU integrated flux so as to limit non-linearity effects, 5. many acquisitions taken at incoming fluxes varying from 4 e/s up to 52 e/s have been combined together to increase the statistics.

Again the conversion gain is obtained from the "fast PTC" technique fitting the variance vs. signal ramp obtained from the combination of numerous ramps limited to an integrated signal of 5000 ADU. The combination of ramps from various fluxes seems natural, as seen in figure 3. However the combination of acquisitions of various types is not that obvious. Indeed, figure 7 shows three maps with 16x16 pixels grouping for the three types of acquisitions. The Fish distinctly comes out with a gain 5% higher than the rest of the map. But the background of the "flux" acquisition is quite different from the two others and may be understood looking at figure 8. Indeed, the latter figure shows the 20 ramps cumulated for an incoming flux of 52 e/s. The beginning of the "flux" ramps shows a decrease, synonymous of detrapping, while the two other types of ramps "zodi" and "dark" start by increasing, synonymous of charge trapping. Consequently, "zodi" and "dark" acquisitions may be combined together, but not with "flux". As a result (not shown here), even if this combination of ramps gives an error on the gain smaller than 1%, the spatial variations of the gain are still embedded in noise. A first sight of a 64x64 pixels map of the conversion gain is given in figure 9 with a view to getting a better insight into spatial variations. Conversion gain has been calculated from 170 values of gain. Figure 9, left, represents the distribution of all the 64x64 pixels, where the secondary peak of the Fish sticks out. Both peaks of the histogram show an RMS error of 0.53% which combines the dispersion of the super pixel gains and an error of 0.26% on the super pixel conversion gain (as calculated from the 170 values of gain obtained for each pixel). At this level of error, one can start to see the spatial variations of the gain as seen in figure 9, right: the lower right area clearly tends to be redder, thus higher gains, while the left of the matrix tends to bluer colors, or smaller gains. The variations are very small (less than 1%) but should be taken into account for the Euclid mission.

mean = 0,5007, std = 7,40×10 It has been mentioned above (3.2) that what differentiates the Fish and the background is their IPC. Other authors have indeed mentioned the necessity to correct for IPC in order to get a proper estimation of the conversion gain. [START_REF] Moore | Interpixel capacitance in non-destructive focal plane arrays[END_REF][START_REF] Fox | The 55fe x-ray energy response of mercury cadmium telluride near-infrared detector arrays[END_REF] Indeed IPC modifies the pixel capacitance by adding a parasitic capacitance. If we compare the image of figure 9 with the IPC image we obtained by SPR technique, the gain difference between the Fish area and the rest of the detector is roughly compatible with the coefficient 1 -8α (where α is the coupling coefficient over four adjacent pixels) given in literature.

CONCLUSION AND FUTURE WORK

We have presented in this paper the setup and first results on the characterization of the Euclid flight H2RG detectors done at CPPM since June 2017. We have focused on the conversion gain, which is a fundamental parameter essential to evaluate actual fluxes in terms of incident photons. It has been seen to be influenced by many aspects: spatial variations along pixels or columns (at a smaller degree), IPC, and history of illumination (following trapping or detrapping in link with persistence effect). A conversion gain map with "super pixels" of 64x64 pixels has been produced showing not only that spatial variations become visible with an error smaller than 1%, but also that a small scale (16x16 pixel or smaller) map of the detector conversion gain is attainable and should be derived for the purpose of the science mission. In order to get a better map, to the single pixel level, it will be necessary to improve statistics by combining more acquisitions and to apply a finer selection of pixels. Correction of non-linearity and IPC would certainly improve the quality of the data and thus the measurement of the conversion gain.

Figure 1 .

 1 Figure 1. Flat field illumination shows a "fish-shape" on scs1 [left] and a small "oval" on scs2 [right].

Figure 2 .

 2 Figure 2. Photodiode [top] and detector [bottom] normalized relative flux responses for three typical incoming fluxes from the LED. Dashed lines correspond to continuous illumination, while continuous lines correspond to alternation of illumination and zodi or dark. * "zodi" refers to a flux of 2 e/s equivalent to the zodiacal background that the NISP instrument will see onboard.

Figure 3 .

 3 Figure 3. Variance vs. signal of scs2 [left] and residual from the least square fit [right]. Several fluxes and ramps of data are accumulated here [dots of various colors]. Fit is superimposed on the curve [black dashed line].

Figure 4 .

 4 Figure 4. Normalized QF histogram [left], IPC histogram [center] and map [right] for scs2.

9 Figure 5 .

 95 Figure 5. Histogram of VDDA over a 12 hour acquisition [left] and chronogram of VDDA over the whole characterization flow (45 days) [right]. Colors show the changing temperatures.

Figure 6 .

 6 Figure 6. Conversion gain calculated over the length of the ramp for three configurations: full ramp with pixel correction, full ramp without pixel correction, and starting ramp at frame 100 [left]. Comparison of conversion gain for three subsets of pixels: channels, odd columns and even columns [right]

Figure 7 .

 7 Figure 7. Maps of pixel gains obtained for super pixels of 16x16 pixel area for the three types of acquisitions: flux zodi [left], flux dark [center], flux [right]

Figure 8 .

 8 Figure 8. Ramps for 52e/s LED setpoint are shown for the different types of acquisitions. One may see the different behaviors of the detector according to history of illumination.

Figure 9 .

 9 Figure 9. Per pixel conversion gain of scs1 for 64x64 pixels showing their distribution [left] and the gain map [right]

Table 1 .

 1 Dark current and noise at 85K

		scs1	scs2
	Dark current [median]	0.006 e/s	0.010 e/s
	CDS noise [median]	18.90 e ( 9.96 ADU ) 15.98 e ( 8.74 ADU )
	(Assuming a gain of 0.50 for scs1 and 0.51 ADU/e for scs2)

† 52 e/s is the LED setpoint, the actual flux might be slightly different.

ACKNOWLEDGMENTS

Thanks to EC collaboration. Project funded by CNES and ESA. Thanks also to NASA Goddard and JPL for fruitful discussions. Special thanks to Augustyn Waczynski with whom we had a close collaboration working on acceptance tests at DCL.