Clotilde Johansson

Philippe Bataillard

Coralie Biache

Catherine Lorgeoux

Stéfan Colombano

Antoine Joubert

Thierry Pigot

Pierre Faure
email: pierre.faure@univ-lorraine.fr

Ferrate VI oxidation of Polycyclic Aromatic Compounds (PAHs and polar PACs) on DNAPL-spiked sand: degradation efficiency and oxygenated by-product formation compared to conventional oxidants

Keywords:

come

FerrateVI oxidation of polycyclic aromatic compounds (PAHs and polar PACs) on DNAPL-spiked sand: degradation efficiency and oxygenated by-product formation compared to conventional oxidants

Introduction

The coke used in steelwork industry is obtained by coal purification through the coking process, which generates coal-tar as by-product. Coal-tar corresponds to a mixture of thousands of Polycyclic Aromatic Compounds (PACs) including Polycyclic Aromatic Hydrocarbons (PAHs) and polar-PACs containing one or more heteroatoms (oxygen, nitrogen or sulphur) [START_REF] Benhabib | Characteristics of a solid coal tar sampled from a contaminated soil and of the organics transferred into water[END_REF][START_REF] Birak | Dense non-aqueous phase liquids at former manufactured gas plants: Challenges to modeling and remediation[END_REF][START_REF] Tian | Diversity and Abundance of High-Molecular-Weight Azaarenes in PAH-Contaminated Environmental Samples[END_REF][START_REF] Wehrer | Contaminants at Former Manufactured Gas Plants: Sources, Properties, and Processes[END_REF]. PAHs are well known for their toxicity, carcinogenicity, mutagenicity and reproductive toxicity (Marin-Morales, MA ; Leme, DM ; Mazzeo, 2009; [START_REF] Mumtaz | Toxicological profile for polycyclic aromatic hydrocarbons[END_REF]. Due to their high hydrophobicity, PAHs are preferably adsorbed on natural organic matter or mineral phases present in soil, what contributes to their persistence [START_REF] Bandowe | Analysis of Polycyclic Aromatic Hydrocarbons and Their Oxygen-Containing Derivatives and Metabolites in Soils[END_REF][START_REF] Delle Site | Factors Affecting Sorption of Organic Compounds in Natural Sorbent/Water Systems and Sorption Coefficients for Selected Pollutants[END_REF].

Sixteen representative PAHs are targeted by the US Environmental Protection Agency as priority pollutants, while no polar-PACs are regulated, despite their proven toxicity -sometimes even higher than PAHs -towards a wide variety of organisms [START_REF] Varel | Polar Compounds Dominate in Vitro Effects of Sediment Extracts[END_REF][START_REF] Lundstedt | Sources, fate, and toxic hazards of oxygenated polycyclic aromatic hydrocarbons (PAHs) at PAH-contaminated sites[END_REF][START_REF] Zamfirescu | Occurrence and attenuation of specific organic compounds in the groundwater plume at a former gasworks site[END_REF]. With higher polarities, these compounds have a higher solubility into water, and consequently a better mobility in soil than parent compounds [START_REF] Biache | Low temperature oxidation of a coking plant soil organic matter and its major constituents: An experimental approach to simulate a long term evolution[END_REF][START_REF] Hanser | Evolution of dissolved organic matter during abiotic oxidation of coal tar -comparison with contaminated soils under natural attenuation[END_REF][START_REF] Lundstedt | Sources, fate, and toxic hazards of oxygenated polycyclic aromatic hydrocarbons (PAHs) at PAH-contaminated sites[END_REF].

Accidental spills of coal-tars, or former waste management practices, have contributed to soil and groundwater pollution at many industrial sites. Due to environmental-and health-risks, decontamination of these wastelands is of great concern. In Situ Chemical Oxidation (ISCO) represents a group of reactions able to break down PACs directly in the soil or groundwater.

Ideally, the oxidation is complete, and PACs are mineralized into CO2 and water. When the oxidant dose is insufficient, the reaction may generate some harmful oxygenated PACs (ketones) [START_REF] Biache | Low temperature oxidation of a coking plant soil organic matter and its major constituents: An experimental approach to simulate a long term evolution[END_REF][START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF][START_REF] Lampi | Photoinduced toxicity of Polycyclic aromatic hydrocarbons to Daphnia Magna: Ultraviolet-mediated effects and the toxicity of polycyclic aromatic hydrocarbon photoproducts[END_REF][START_REF] Lundstedt | Sources, fate, and toxic hazards of oxygenated polycyclic aromatic hydrocarbons (PAHs) at PAH-contaminated sites[END_REF][START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF][START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF][START_REF] Russo | PAHs contaminated soils remediation by ozone oxidation[END_REF].

Several oxidants, such as permanganate, activated persulfate or iron II catalysed hydrogen peroxide, named Fenton or Fenton-like processes, have been well studied and are commonly used for soil remediation [START_REF] Huling | In-Situ Chemical Oxidation -Engineering Issue[END_REF][START_REF] Itrc | Technical and Regulatory Guidance for In Situ Chemical Oxidation of Contaminated Soil and Groundwater[END_REF][START_REF] Ranc | Selection of oxidant doses for in situ chemical oxidation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs): A review[END_REF]. Permanganate is an oxidant reacting with oxido-reductive pathway (two electron transfers) known to persist (weeks to months) in soils and aquifers (de Souza e [START_REF] Silva | Phenanthrene and pyrene oxidation in contaminated soils using Fenton's reagent[END_REF][START_REF] Huling | In-Situ Chemical Oxidation -Engineering Issue[END_REF][START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF]. It shows a long-lasting efficiency, but generates MnO2 precipitates which can alter soil permeability and can inhibit regrowth of vegetation [START_REF] Sirguey | Impact of chemical oxidation on soil quality[END_REF] and can alter or change micro-organisms diversity [START_REF] Liao | Effect of various chemical oxidation reagents on soil indigenous microbial diversity in remediation of soil contaminated by PAHs[END_REF]. Very effective to degrade PAHs (Boulangé et al., 2019b;[START_REF] Lemaire | Chemical oxidation efficiency for aged, PAH-contaminated sites: An investigation of limiting factors[END_REF][START_REF] Liao | Effect of various chemical oxidation reagents on soil indigenous microbial diversity in remediation of soil contaminated by PAHs[END_REF][START_REF] Liao | Enhanced degradation of polycyclic aromatic hydrocarbons by indigenous microbes combined with chemical oxidation[END_REF][START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF], its efficiency on PACs is dependent on molecular size and aromatic condensation structure [START_REF] Clar | Polycyclic hydrocarbons[END_REF][START_REF] Forsey | Oxidation kinetics of polycyclic aromatic hydrocarbons by permanganate[END_REF][START_REF] Wang | Reducing polycyclic aromatic hydrocarbons content in coal tar pitch by potassium permanganate oxidation and solvent extraction[END_REF]. Catalyzed Hydrogen peroxide in Fenton reactions forms the hydroxyl-radical (HO), a highly reactive radical with a short lifespan, which degrades organic matter without selectivity [START_REF] Ferrarese | Remediation of PAH-contaminated sediments by chemical oxidation[END_REF][START_REF] Rivas | Polycyclic aromatic hydrocarbons sorbed on soils: A short review of chemical oxidation based treatments[END_REF][START_REF] Watts | Mineralization of a sorbed polycyclic aromatic hydrocarbon in two soils using catalyzed hydrogen peroxide[END_REF]. This reaction is catalysed by iron II in solution at low pH (2-5) [START_REF] Gallard | Effect of pH on the oxidation rate of organic compounds by Fe-II/H2O2. Mechanisms and simulation[END_REF][START_REF] Kwan | Decomposition of Hydrogen Peroxide and Organic Compounds in The Presence of Iron and Iron Oxides[END_REF]. Fenton-like reactions can also be conducted under circumneutral pH, more compatible with soils, with heterogeneous catalytic systems where the iron is present in a mineral phase such as magnetite [START_REF] Biache | Effect of pre-heating on the chemical oxidation efficiency : Implications for the PAH availability measurement in contaminated soils[END_REF]Boulangé et al., 2019b;[START_REF] Jung | Effect of pH on Fenton and Fenton-like oxidation[END_REF][START_REF] Munoz | Preparation of magnetite-based catalysts and their application in heterogeneous Fenton oxidation -A review[END_REF]Usman et al., 2012a;[START_REF] Voinov | Surface-mediated production of hydroxyl radicals as a mechanism of iron oxide nanoparticle biotoxicity[END_REF]. The efficiencies of all Fenton type reactions to degrade PAH [START_REF] Cheng | Hydroxyl radicals based advanced oxidation processes (AOPs) for remediation of soils contaminated with organic compounds: A review[END_REF][START_REF] Trellu | Removal of hydrophobic organic pollutants from soil washing/flushing solutions: A critical review[END_REF], especially in contaminated soils are widely discussed in the literature [START_REF] Usman | Fenton oxidation to remediate PAHs in contaminated soils: A critical review of major limitations and counter-strategies[END_REF][START_REF] Venny | Modified Fenton oxidation of polycyclic aromatic hydrocarbon ( PAH )-contaminated soils and the potential of bioremediation as post-treatment[END_REF][START_REF] Yap | Fenton based remediation of polycyclic aromatic hydrocarbonscontaminated soils[END_REF]. Persulfate can be activated by heat, metallic catalysts, high or low pH, hydrogen peroxide (H2O2), or UV-light to generate sulfate radicalanion (SO4-), almost as reactive as the hydroxyl radical. Depending on the catalyst used and how the contact with the oxidant is efficient, hydrogen peroxide and persulfate may persist in soils and release radicals over longer time periods, compared to the short radical lifespan. Persistence in soils is usually higher for persulfate (weeks), than hydrogen peroxide (minutes to hours) as persulfate is more stable in sub-surface [START_REF] Huang | Kinetics of Heat-Assisted Persulfate Oxidation of Methyl tert -Butyl Ether (MTBE)[END_REF]. Activated persulfate have shown high efficiency for PAHs degradation [START_REF] Cassidy | Combining in situ chemical oxidation , stabilization , and anaerobic bioremediation in a single application to reduce contaminant mass and leachability in soil[END_REF][START_REF] Chen | Removal of polycyclic aromatic hydrocarbons from sediments using sodium persulfate activated by temperature and nanoscale zero-valent iron[END_REF][START_REF] Kakosová | Effect of various chemical oxidation agents on soil microbial communities[END_REF][START_REF] Lemaire | Chemical oxidation efficiency for aged, PAH-contaminated sites: An investigation of limiting factors[END_REF][START_REF] Liao | Effect of various chemical oxidation reagents on soil indigenous microbial diversity in remediation of soil contaminated by PAHs[END_REF][START_REF] Liao | Enhanced degradation of polycyclic aromatic hydrocarbons by indigenous microbes combined with chemical oxidation[END_REF][START_REF] Peng | Ultrasound assisted, thermally activated persulfate oxidation of coal tar DNAPLs[END_REF][START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF][START_REF] Song | Zero-valent iron activated persulfate remediation of polycyclic aromatic hydrocarboncontaminated soils: An in situ pilot-scale study[END_REF]. Sulfate radical-anion shows selectivity towards low molecular mass compounds [START_REF] Gryzenia | Production and accumulation of surfactants during the chemical oxidation of PAH in soil[END_REF]Usman et al., 2012a). Its main drawback is the formation of sulfates and sulfuric acid as oxidation end-products, inducing a drastic pH decrease.

Recently, the use of ferrates VI as a water treatment to oxidize organic pollutants (laboratory experiments) has been well documented. This strong oxidant reacts on a wide range of agents as pharmaceuticals, pesticides, phenols, cyanide, heavy metals, microorganisms, natural organic matter [START_REF] Bielski | Reactivity of ferrate(V) with carboxylic acids: A pre-mix pulse radiolysis study[END_REF][START_REF] Filip | Mechanisms and Efficiency of the Simultaneous Removal of Metals and Cyanides by Using Ferrate(VI): Crucial Roles of Nanocrystalline Iron(III) Oxyhydroxides and Metal Carbonates[END_REF][START_REF] Gan | Investigation of disinfection byproducts formation in ferrate(VI) pre-oxidation of NOM and its model compounds followed by chlorination[END_REF][START_REF] Hrabak | Chemical degradation of PCDD/F in contaminated sediment[END_REF][START_REF] Jiang | The application of potassium ferrate for sewage treatment[END_REF][START_REF] Johnson | Kinetics and mechanism of the reduction of ferrate by oneelectron reductants[END_REF][START_REF] Liu | Kinetics and mechanism of the oxidative degradation of parathion by Ferrate(VI)[END_REF][START_REF] Manoli | Pharmaceuticals and pesticides in secondary effluent wastewater: Identification and enhanced removal by acid-activated ferrate(VI)[END_REF][START_REF] Peings | Removal of pharmaceuticals by a potassium ferrate(VI) material: from practical implementation to reactivity prediction[END_REF][START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF][START_REF] Rai | A critical review of ferrate(VI)-based remediation of soil and groundwater[END_REF][START_REF] Sharma | Ferrate(VI) and ferrate(V) oxidation of organic compounds: Kinetics and mechanism[END_REF][START_REF] Sharma | Oxidative transformations of environmental pharmaceuticals by Cl2, ClO2, O3, and Fe(VI): Kinetics assessment[END_REF][START_REF] Yngard | Ferrate(VI) Oxidation of Weak-Acid Dissociable Cyanides[END_REF], and aromatic structures like BTEX [START_REF] Lacina | Use of the ferrates (FeIV-VI) in combination with hydrogen peroxide for rapid and effectIVe remediation of water -Laboratory and pilot study[END_REF][START_REF] Pepino Minetti | In situ chemical oxidation of BTEX and MTBE by ferrate: pH dependence and stability[END_REF], water lixiviates from bitumen [START_REF] Wang | Comparison of UV/hydrogen peroxide, potassium ferrate(VI), and ozone in oxidizing the organic fraction of oil sands process-affected water (OSPW)[END_REF] and PAHs [START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF]. It releases O2, HO -and ends as Fe(OH)3, which has flocculent properties and is nontoxic towards the environment. This oxidant can follow two reaction pathways: free radicals with one electron transfer and oxidoreductive with two electrons exchange, often via oxygen atom transfer, supported by the reactions:

Fe VI + R (organic compound) à Fe V /Fe IV + RO/R • à Fe III /Fe II -hydroxides + R' (organic by-products)
Fe VI can also react with an induced radical R to form Fe V and RO species [START_REF] Sharma | Ferrate(VI) and ferrate(V) oxidation of organic compounds: Kinetics and mechanism[END_REF]. Therefore, reactions on PAHs are expected to form O-PACs, which has been attested by [START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF].

Ferrate also shows selectivity towards nucleophilic sites [START_REF] Sharma | Ferrate(VI) and ferrate(V) oxidation of organic compounds: Kinetics and mechanism[END_REF]. [START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF] have applied this oxidant on a real wastewater mixture containing numerous organic pollutants. They have shown that the organic bulk enters in competition with pollutants towards oxidation, but the degradation remains selective: with enough oxidant, nearly all contaminants are degraded whereas the dissolved organic carbon is less affected.

To our knowledge, among the published studies presenting the ferrate's oxidation potential, only few deal with the oxidation of PAHs on soil (or solid matrix) and subsequent formation of polar-PACs by ferrates [START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF], and none concern ISCO treatment to degrade a real wasteland Dense Non Aqueous Phase Liquids (DNAPL).

This study is linked to the BIOXYVAL project, aimed to propose adapted treatment solutions for sites highly impacted by organics, especially connected to a workshop site, former coking plant, contaminated by DNAPL. As a matter of fact, all the oxidants compared in this study were selected to be compatible with field application.

Therefore, the aim of this contribution is to investigate the efficiency of two potassium ferrate (of semi-industrial grade) to degrade DNAPL on a solid matrix, compared with conventional oxidants for soil treatment: potassium permanganate, heat activated persulfate and Fenton-like (magnetite-activated).

Sand spiked with DNAPL (sampled on the coking plant wasteland) was immerse in deionized (DI) water to mimic an ideal groundwater-like system. The 16 US EPA PAHs and some polar-PACs, either present in the initial coal-tar or identified as potential by-products (12 O-PACs, 5 N-PACs and 4 S-PACs), were targeted.

Materials and methods

Chemicals

For analysis and organic extraction, dichloromethane DCM (Biosolve), methanol (Carlo Erba), acetone (Biosolve), and hexane (Biosolve) of HPLC grade were used.

Sodium azide (NaN3, 99.0% Sigma Aldrich) was used as biocide (200 mg/L).

Deionized (DI) water was produced with a Pure-Lab Option system from Elga.

Matrices

Dense Non Aqueous Phase Liquid (DNAPL)

DNAPL was sampled in summer 2016 at 3-4 m deep by pumping it from a pool present in groundwater layer at a former coking plant (Lorraine, -France). The coking plant was in operation from 1912 to 1973.

The DNAPL was first separated from its aqueous phase by decantation, then filtered on glass microfiber filters (GF/D-Whatman).

In order to limit further loss of compounds by evaporation and the subsequent overestimation of the degradation efficiency, DNAPL was previously treated on a Rotovap R-215 BUCHI to remove the most volatile compounds. Additionaly, bentonite (4 g) was added to the batch before freezing and drying the samples, for its ability to retain Low Molecular Weight (LMW) PAHs [START_REF] Lee | Organoclays as Variably Permeable Reactive Barrier Media to Manage NAPLs in Ground Water[END_REF]. Its elevated specific area (55-75 m 2 /g) limited pollutant evaporation but did not impact the extraction step. These pretreatments decreased losses of quantified molecules by evaporation to an average of 10 %, same order of magnitude than the uncertainty of our mesures.

For the sand spiking, this DNAPL was diluted in dichloromethane at 17 g/L and kept in a brownglass flask at 4 °C.

Elementary analysis (C, H, O, N, S) was done by the laboratory of Physical Measurements of Montpellier University-France, by catalytic combustion in an Elementar Vario Micro Cube.

Solid matrices

Fontainebleau sand (180-500 µm, Carlo Erba Reagents) was previously cleaned by accelerated solvent extractor (Dionex ASE 350), with DCM/methanol (50/50 v/v) at 130 °C and 100 bars, with a static time of 2 min.

Bentonite from Georgia was cleaned twice with a DCM/methanol (50/50 v/v) mixture agitated under softly warming at 35-40 °C, and then dried under nitrogen flux before use.

Oxidants

Four different oxidants were used:

-Potassium permanganate (KMnO4 99+%, Acros Organics),

-Hydrogen peroxide (H2O2 30%, Analar Normapur VWR Chemicals), catalyzed by a Fenton-like process with magnetite (Fe3O4 -97%, 44 µm, Alfa Aesar) at room temperature, -Sodium persulfate (Na2S2O8, 95+%, Fisher Scientific), heat activated at 60°C.

-Ferrates: K2FeO4 12% in form of millimetric pellets (named ferrate ( 1)) prepared from patented procedure FR2908128 [START_REF] Castetbon | Procédé de préparation de ferrates de métaux alcalins[END_REF] (France), and Envifer K2FeO4 38.6% as pulverulent powder (named ferrate (2)) from Nano Iron (Czech Republic). Both are synthesized following less expensive processes, capable of producing semi-industrial-scale quantities (compared with ferrate of higher purity, not affordable for site application). These two semi-industrial ferrates are, to our knowledge, of the only ones currently available on the market, and therefore representative of potential products for field applications. The impurity of ferrate ( 1) was demonstrated to have no impact on its oxidative activity on phenols [START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF]. PACs are expected to follow same trend.

Batch oxidations

Initial conditioning: sand (4 g) was spiked with 50 mg DNAPL (2.94 mL of the 17 g/L solution) in a 250 mL round-bottom glass flask. The mixtures were homogenized by agitation and the solvent was evaporated at room temperature overnight. DI water with NaN3 (50 mL) was then added into the bottle (except for the persulfate as toxic gas could be emitted due to medium acidification). This sample corresponds to the starting point t0.

Oxidant dose: Oxidations were performed at one Stoichiometric Oxidant Demand (SOD), calculated from a Stoichiometric Molar Ratio (SMR) of the complex mixture of pollutants by measuring the Extractable Organic Matter (EOM) content and the elementary composition of the DNAPL, following the method proposed by Ranc et al [START_REF] Ranc | Selection of oxidant doses for in situ chemical oxidation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs): A review[END_REF] (Supplementary Information 1.).

Oxidation procedure: The oxidants were poured as one single addition (839 µL H2O2 30%, 874 mg of KMnO4, 2.037 g of persulfate and 9.0 and 2.8 g of ferrate ( 1) and ( 2), respectively) just before closing the bottle. For the Fenton-like reaction, a molar ratio H2O2/Fe of 10/1 was chosen according to previous studies [START_REF] Jung | Effect of pH on Fenton and Fenton-like oxidation[END_REF][START_REF] Pera-Titus | Degradation of chlorophenols by means of advanced oxidation processes: a general review[END_REF][START_REF] Silva | Phenanthrene and pyrene oxidation in contaminated soils using Fenton's reagent[END_REF]Usman et al., 2012b). The magnetite was added to the bottle before the oxidant. H2O2 (30%) solution was then introduced drop by drop in the batch by pipetting it over one minute, to limit the oxidant's auto-degradation. Control samples were performed with DI water and biocide (without oxidant) at ambient temperature, and at 60°C as a reference for activated persulfate oxidation. The bottles were placed in darkness and magnetically stirred at room temperature for 3 h, 24 h and 7 days (triplicates). Initial pH was measured on the blanks. During the oxidation, bottles were hermetically closed to avoid loss of compounds by evaporation.

Oxidized sample processing: At the sampling time, the bottles were opened, and pH was measured during 10 min before adding bentonite. The frozen samples were freeze-dried with a Cryotec freezedryer connected to an Edwards RV5-vacuum pump.

Extractable Organic Matter (EOM) isolation (DNAPL)

The EOM represents the fraction of organic matter that is recovered by adding DCM (40 mL) to the sample and heated (36 °C) under stirring and reflux conditions for 30 minutes. The supernatant was then isolated by filtration through a glass-microfiber filter (GF/F-Whatman). The extraction was carried out twice. Solvent was then evaporated under N2 flux and the volume adjusted to 20 mL. Aliquots (3 mL)

were transferred in pre-weighed vials and the EOM contents were determined by weighing the vials after solvent evaporation at room temperature overnight. The remaining EOMs were kept in the dark at 4 °C.

As the DNAPL is fully soluble in DCM, EOM is assumed to represent the whole pollution.

Analytical methods

PAC quantification by Gas Chromatography-Mass Spectrometry

Sixteen PAHs (US EPA PAHs), 12 O-PACs, 5 N-PACs and 4 S-PACs were quantified by Gas Chromatography coupled to a Mass Spectrometer (GC-MS) using internal deuterated standards (naphthalene D8, acenaphthene D10, phenanthrene D10, pyrene D10, chrysene D12, perylene D12, benzo(ghi)perylene, quinoline D7, 9H fluorenone D8). Two calibration curves were drawn for low (0, 0.06, 0.12, 0.18, 0.3 and 0.6 µg/mL), and high concentrations (0.18, 0.3, 0.6, 1.2, 3, 6 and 9.6 µg/mL).

The instrument used was a GC Agilent Technology 6890N equipped with a column DB-5MS (60 m × 0,25 mm d.i. × 0,25 µm film thickness -Agilent Tech.) coupled to an Agilent 5973 inert Mass Selective

Detector. One microliter of sample was injected at 300 °C in splitless mode. The GC oven temperature was programmed from 70 °C (held 2 min) to 130 °C at 15 °C/min, then from 130 to 315 °C (held 30 min) at 4 °C/min. The carrier gas was helium at 1.6 ml/min at constant flow.

Three analyses were carried out on each EOM sample: (i) quantitative analysis in Single Ion Monitoring (SIM) mode (Online Resources Table ESM_1), to lower the detection limit for all targeted molecules, (ii) qualitative analysis in Scan mode, and (iii) qualitative analysis (Scan mode) of the EOM previously derivatized (BSTFA-TMCS (99:1 Sylon BFT, Supelco)/sample (50/50 v/v) heated at 60 °C for 30 min [START_REF] Wenclawiak | GC / MS-FID analysis of BSTFA derivatized polar components of diesel particulate matter[END_REF]) to detect acids and alcohols.

Infra-Red spectroscopy

The recording was done on the EOM dried residue by light-transmission measurements with the instrument Bruker IFS 55 (resolution 2 cm -1 , 64 scans/sample) coupled to a 250 mm narrow band MCT detector cooled to 77 K. A small drop of the residue was placed on a diamond window (2 mm large, 1 mm thick). Selection of the analysed area was done with a visible light ×10 objective. A restrictor was then placed to limit the beam width to 60 µm. Background was first done on an empty part of the diamond window and sample was measured afterwards.

Assignments of the main infrared bands were determined by reference to previous works [START_REF] Bellamy | The Infrared Spectra of Complex Molecules[END_REF][START_REF] Landais | Reliability of semiquantitative data extracted from transmission microscopy-Fourier transform infrared spectra of coal[END_REF].

Mössbauer and ICP OES

Ferrate (2) and its dry residue after seven days of reaction were analysed to characterize the iron speciation before and after oxidation. Mössbauer spectroscopy analyses were conducted at 300 K, 77 K and 14-15 K (Laboratoire de Chimie Physique et Microbiologie pour les Matériaux et l'Environnement LCPME -CNRS -University of Lorraine, France).

Iron was quantified in the ferrate modalities by ICP-OES (ICP 720 ES Varian) -(Laboratoire Interdisciplinaire des Environnements Continentaux LIEC -CNRS -University of Lorraine, France).

Results

Initial samples DNAPL characterization

The molecular distribution of the DNAPL was mainly dominated by two and three-ring PACs (Online Resources Figure ESM_1). PAC quantification (Table 1) revealed the predominance of Acenaphthene, The Fourier Transformed InfraRed spectroscopy (FTIR) analysis (Fig1a) depicts the type of chemical bonds present in the DNAPL. Aromaticity is clearly expressed with intense νCHaro (3100 -3000 cm -1 ), νC=C (1650 -1550 cm -1 ) and γCHaro bands (900 -700 cm -1 ; with 1H centred on 875 cm -1 , 2-3H on 830 cm -1 and 4-5H centred on 750 cm -1 ). The 4-5H bands predominance in the γCHaro area attests the low condensation degree of the pollutants.

Aliphatic bands were also observed: νCHali (3000 -2800 cm -1 ) and δCHali (1470 -1440 cm -1 ). They are suspected to mostly represent the ramifications on benzenic rings with short chain adducts (methyl, ethyl) as the intensity of νasCH2 (2880 cm -1 ) is lower than the νasCH3 (2920 cm -1 ).

Some heteroatom bands reveal the occurrence of nitrogen (νC-N: 1220 -1020 cm -1 and νN-H: 3500 -3050 cm -1 ) and oxygen (νC=O: 1750-1700 cm -1 and νC-O: 1300 -1170 cm -1 ) functions.

The elemental composition (C: 84.1%, H: 5.8%, N: 0.3%, O: 5.3% and S: 4.1% in weight %) of the DNAPL is typical of a dominated aromatic structure (low H/C atomic ratio: 0.83). The DNAPL elemental composition allows us to calculate a theoretical molecular formula C53H43.5O2.5N0.2S, used for the stoichiometric oxygen demand (SOD) determination.

Ferrate characterisation

The Mössbauer analysis on ferrate (2) led to relative abundance (R.A) respectively (Online Resources Figure ESM_2a) of 42% attributed to the cations Fe VI , 27% for hematite, and 28% with goethite signature (Online Ressources Table ESM_2a). Crossed with iron content (200 g/kg) of ferrates (2), a purity of 29.8 wt % was calculated which differed from the supplier's data (38.9 wt %), probably due to deactivation of the oxidant by contact with CO2 or moisture from the air during the transportation.

Therefore, the oxidant dose calculated on the supplier's information was incorrect, and consequently, for all experiments with Ferrate (2), the oxidant stoichiometric amount was 0.77 SOD and not 1 SOD as for other oxidants.

Oxidized samples

pH and iron mineral modifications

Oxidations impacted the solution's pH (Table 2). It differed from a drastic acidification in the case of the persulfate (pH dropped from neutral to 1), to rather basic conditions after use of permanganate (pH 9) or ferrates (pH > 13). For both ferrates, pH rose, due to the impurity (KOH) highly present in the ferrate powder, and due to the reaction. At these basic conditions, ferric sludge precipitated. Volume of dry residue, collected after freeze-drying step, was barely impacted by the oxidations, except for the ferrate (1) (less pure) whose precipitates doubled the final solid layer.

Mössbauer analysis carried out on the extraction residue from the sample oxidized by ferrate (2)

showed no remaining Fe VI in the sample after seven days (Online Resources Figure ESM_2b and Table ESM_2b). It revealed as much sextet Fe 3+ attributed to Fe(OH)3 as Fe VI initially present in the oxidant, attesting that ferrihydrite is the main by-product obtained from ferrate's oxidation under our conditions.

Hematite and goethite phases, initially present, were not impacted by oxidation.

Total Extractable Organic Matter EOM

Quantitative evolution

To be representative of the oxidation efficiency, degradation rate and weight loss were calculated based on the blank tests (Fig2). DNAPL samples spiked and immediately following the extraction protocol (t0) and blanks (at room temperature) carried out in contact with water over the reaction times, showed systematically 30.0 wt % EOM mass loss, due to protocol (evaporation). Heated blanks (60°C) were losing higher EOM mass proportions: 56.2 wt %. As a matter of fact, the degradation yields calculated in this study (for EOM and later PACs) correspond exclusively to oxidation but probably underestimate degradation efficiencies, as evaporated compounds lost in the blanks may have been previously oxidized during treatment, before the freeze drying and extraction procedures responsible for evaporation. The Fenton-like reaction resulted in 34.7 wt % EOM weight loss. The two tested ferrates were more effective: Ferrate ( 1) and (2) induced a weight loss of 65.8%, and 44.4 %, respectively.

With 82.6 wt % and 84.4 wt %, permanganate and heat-activated persulfate resulted in the highest degradation.

Qualitative evolution -Fourier Transformed Infra-red Spectroscopy (FTIR) analysis

Like the initial DNAPL, FTIR spectra (Fig1) obtained after oxidation are dominated by aromatic bands (νCHaro, νC=C and γCHaro), except in the case of persulfate oxidized sample where those bands have lower intensity.

After oxidation, only EOM from permanganate and the two ferrate treated samples showed an intense νC=O band (1750-1700 cm -1 -Fig1cde), suggesting an enrichment in oxygenated compounds. Neither activated persulfate nor Fenton-like oxidized sample exhibited this band.

Quantified PAC evolution

The Whatever the oxidant, the degradations were intense in the beginning of the reaction (first 3 to 24 hours), before a slowing down (Fig3).

After one week, the highest PAC abatements were observed with heat activated persulfate and permanganate with a decrease of 96% and 98% in PAH (Fig3a), 98.5% and 98.0% in S-PAC (Fig3d) concentrations, respectively, and close to 100% in N-PAC content (Fig3c, concentrations below detection limit). In the case of the two furan O-PACs, the efficiency for the heat-activated persulfate is higher (95.7%) than the permanganate (48.8%). The Fenton-like reaction did not drastically decrease the PAC content (between 28.5% for PAHs, 17.4% for furan O-PACs, 63.7% for N-PACs and 31.2%

for S-PACs). After seven days of reaction, PAH, furan O-PAC and N-PAC contents decreased of 77.9%, 78.5% and 85.6% for ferrates (1), and 57.0%, 63.0% and 68.7% for ferrates (2), respectively. In contrary, S-PAC decrease was more limited with 45.7% and 31.1% for ferrates ( 1) and (2), respectively.

O-PAC ketone formation

Most of the 10 targeted O-PAC ketones were detected in the initial DNAPL at low concentrations or close to the GC-MS detection limit (Table 1), except for the 9H fluorenone, slightly higher (2.3 mg/gDNAPL).

During oxidation, the abundance of O-PAC ketones increased in the case of permanganate and ferrates treatments and was still high after a week (Fig4). Their concentrations sharply rose in the beginning of the reaction (3 h) and was reduced only with permanganate oxidation after seven days. Discrepancies were observed between the two ferrates: ferrate (2) samples created lower amounts of O-PAC ketones than ferrate [START_REF] Landais | Reliability of semiquantitative data extracted from transmission microscopy-Fourier transform infrared spectra of coal[END_REF].

Results obtained with the Fenton-like reaction show a small increase in O-PAC ketone contents (from 42 to 99 µg/g after one week), whereas persulfate induced a decrease in those compound concentrations.

Controls stayed constant, at 40 µg/g at 20°C and at 25 µg/g at 60°C, (data not shown).

To investigate the production of other oxygenated by-products, a silylation was performed on the organic extracts before GC-MS analysis. No alcohols or acids were detected (data not shown).

Discussion

Effect of the different oxidants on the pollutant content

Except for the Fenton-like oxidation, main degradation of PACs is obtained in the three first hours, and may occur even sooner than our first measurement as other studies have already shown [START_REF] Biache | Effect of pre-heating on the chemical oxidation efficiency : Implications for the PAH availability measurement in contaminated soils[END_REF][START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF][START_REF] Hanna | Synthesis of the mixed oxides of iron and quartz and their catalytic activities for the Fenton-like oxidation[END_REF][START_REF] Peng | Ultrasound assisted, thermally activated persulfate oxidation of coal tar DNAPLs[END_REF].

As it could be seen with the DNAPL's composition, the PACs are standing for 16.2 wt % of the DNAPL.

Whatever the oxidant, the EOM depletion was higher than those 16.2%, implying that degradation affected the targeted PACs, but also other compounds in the DNAPL (Table 3).

However, PACs abatement most often showed better yields than EOM decrease, suggesting that the oxidants are selective to the PACs.

Fenton-like:

The Fenton-like reaction showed lower efficiency in EOM and PAC degradation compared to the other oxidants: 34.7 wt % and 25.2 %, respectively. The conditions used in our experiments were not optimized as the hydrogen peroxide was poured drop by drop in one single addition (can undergo auto-decomposition if too concentrated), and the catalysis was probably disturbed.

Permanganate and persulfate:

The best abatement efficiencies were obtained for heat activated persulfate (EOM decreased by 84.4 wt % and all PACs by 94.0 %) and permanganate (EOM 82.6 wt %, PAHs 98.1 % and all PACs 76.9 %). These two oxidants have shown highest efficiencies in other comparative studies (Boulangé et al., 2019a;[START_REF] Lemaire | Chemical oxidation efficiency for aged, PAH-contaminated sites: An investigation of limiting factors[END_REF][START_REF] Liao | Effect of various chemical oxidation reagents on soil indigenous microbial diversity in remediation of soil contaminated by PAHs[END_REF][START_REF] Liao | Enhanced degradation of polycyclic aromatic hydrocarbons by indigenous microbes combined with chemical oxidation[END_REF]. The lower yield obtained on EOM depletion than on PAHs suggest a selectivity of these oxidants towards the targeted PACs, except for permanganate with the furans. Similar results were obtained by Biache et al [START_REF] Biache | Effect of pre-heating on the chemical oxidation efficiency : Implications for the PAH availability measurement in contaminated soils[END_REF] on LMW PAHs in a gas plant soil and a fresh PAH-contaminated wood-treatment facility soil with permanganate oxidation: PAHs seem preferentially degraded compared to the total EOM.

Ferrates: Due to the lower content of Fe VI in Ferrate (2) compared to the expected value (section 3.1 -Ferrate characterization), the degradation rates obtained with Ferrate (1) are systematically higher than those of ferrate (2): 65.8 % and 44.4 % for EOM and 75.5 % and 57.1 % for total measured PACs, respectively. Consequently, estimated efficiencies based on 1 SOD have been recalculated in the case of ferrate (2) (Table 3), giving similar yields between the two ferrates.

Ferrates are very reactive and unstable in water, especially over 0.4 g/L (supplier data). The more concentrated, the more unstable the solution is [START_REF] Wagner | Factors Affecting Stability of Aqueous Potassium Ferrate (VI) Solutions[END_REF]. In this study, ferrates were used above this concentration. Loss of oxidant by undesired side-reactions may explain their lower efficiency compared to permanganate or persulfate. After seven days, PACs degradation was higher than the percentage of EOM depleted (Table 3) suggesting that ferrates degrade the bulk EOM but are selective towards the PACs. Similar results were obtained by Peings et al. [START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF] on wastewater effluent, where phenol was selectively oxidized despite the occurrence of other dissolved organic matter.

Only the S-PACs seemed less affected by ferrate oxidation.

The application of one SOD oxidant turned out to be successful for permanganate and persulfate.

Degradation rates were slightly lower for both ferrates, but that could be explained by their autodecomposition. The protocol was less optimized for the Fenton-like reaction. Other studies have highlighted formation of O-PACs during oxidation [START_REF] Lampi | Photoinduced toxicity of Polycyclic aromatic hydrocarbons to Daphnia Magna: Ultraviolet-mediated effects and the toxicity of polycyclic aromatic hydrocarbon photoproducts[END_REF]Lundstedt et al. 2007a;[START_REF] Russo | PAHs contaminated soils remediation by ozone oxidation[END_REF][START_REF] Biache | Low temperature oxidation of a coking plant soil organic matter and its major constituents: An experimental approach to simulate a long term evolution[END_REF][START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF][START_REF] Peings | Mechanism for the oxidation of phenol by sulfatoferrate(VI): Comparison with various oxidants[END_REF][START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF]Boulangé et al. 2019).

That is why the monitoring of these oxygenated by-products is of importance.

Formation of oxygenated by-products

Because O-PACs (especially ketones) can be formed as reaction intermediates from incomplete PAH oxidation [START_REF] Forsey | Oxidation kinetics of polycyclic aromatic hydrocarbons by permanganate[END_REF]Lundstedt et al., 2007a), this study focused on ketone by-products.

With persulfate, no O-PAC ketones were generated, or were immediately degraded (Fig1f) and the ones occurring in the initial DNAPL were consumed. [START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF] observed the same tendency on a contaminated soil from the vadose zone: heat activated persulfate degraded the initial O-PACs without generating new ones.

On the contrary, in case of permanganate and ferrate treatments, samples showed an enrichment in these oxygenated compounds (Fig4).

The formation and the degradation of O-PAC ketones could be explained by the type of reactional mechanism occurring: (i) an oxido-reductive pathway with two electron-transfer like permanganate, which goes through a cyclic-ester formation before breaking into C-OH or C=O bonds (Petri et al., 2011a), (ii) the radical mechanism of activated persulfate and the Fenton-like reactions which attack the organic pollutant by hydrogen abstraction, hydroxyl addition or a single electron transfer [START_REF] Bossmann | New Evidence against Hydroxyl Radicals as Reactive Intermediates in the Thermal and Photochemically Enhanced Fenton Reactions[END_REF]. Mechanisms with two electron-transfer are going through formation of ketones or aldehydes, whereas radical reactions are not systematically. According to this observation, and knowing that the ferrates can follow oxido-reductive mechanism as well as a radical one [START_REF] Sharma | Ferrate(VI) and ferrate(V) oxidation of organic compounds: Kinetics and mechanism[END_REF], the formation of oxygenated by-products (Fig4) suggests that ferrates highly react, under our conditions, according to an oxido-reductive pathway. Similarly, formation of O-PAC ketones with the Fenton-like oxidation suggests that the catalytic activation was incomplete, letting hydrogen peroxide reacts by an oxidoreductive pathway (Petri et al., 2011b). This could explain its lower efficiency.

In the case of permanganate treatment, when almost all PAHs have reacted, production of O-PAC ketone stops, and their degradation starts to be visible (after 24 hours), but reaction is not complete after seven days. However, permanganate is known to be persistent in soil for several weeks [START_REF] Huling | In-Situ Chemical Oxidation -Engineering Issue[END_REF][START_REF] Lemaire | Oxidant selection to treat an aged PAH contaminated soil by in situ chemical oxidation[END_REF]. With the oxidant dose of 1 SOD, batch reaction should continue further.

Ranc et al. [START_REF] Ranc | Comparison of the effectiveness of soil heating prior or during in situ chemical oxidation (ISCO) of aged PAH-contaminated soils[END_REF] measured an oxidative activity of the permanganate even after 3 months, and also observed formation of numerous O-PAC ketones during oxidation of the contaminated coking plant soil (vadose zone, from the same site as our DNAPL), with a decrease in their concentrations after one month.

The O-PAC ketone formation obtained with ferrate (2) is about half the concentration obtained with ferrate (1). This difference is linked to the lower percentage of PACs degraded in the case of ferrate (2), this latter being used at a lower SOD dose. The formation of O-PACs is in accordance with the study of [START_REF] Guan | Preparation and Aromatic Hydrocarbon Removal Performance of Potassium Ferrate[END_REF] who showed generation of ketones and aldehydes after ferrate oxidation of individual PAH (phenanthrene, pyrene and naphthalene). The main by-product they measured for phenanthrene degradation was the 9,10-phenanthraquinone, with 9H-fluorenone also significantly observed. Unlike this study, the DNAPL oxidized in our experiments is a mixture of many PACs, and despite its complex composition, only high production of 9H-fluorenone and, to a smaller extend, anthraquinone were observed.

Conclusion

Batch oxidation of DNAPL were carried out in order to compare oxidants commonly used for soil treatment to ferrates (mainly studied for water treatments), in terms of PAC (PAH and polar PAC) degradation and oxygenated-PAC formation.

The Fenton-like reaction with magnetite addition was not successful on our samples probably due to problems with the catalytic activation (single H2O2 addition…).

Thanks to its radical activation, heat activated persulfate degraded almost all pollutants with no O-PAC ketone formation. Its main drawback is the massive decrease in pH and high increase in ionic strength (sulfate release). An alternative could be the use of an alkaline activation to limit pH decrease. However, ionic strength would still be increased in the water.

Permanganate was also very effective for DNAPL degradation. However, its oxido-reductive pathway and slower reactivity led to O-PAC ketone generation, and it released manganese salts (MnO2 and KMnO4) which are known to have an impact on life redevelopment [START_REF] Sirguey | Impact of chemical oxidation on soil quality[END_REF]).

Ferrate's efficiency was attested for the degradation of a complex PAC mixture (DNAPL) from a polluted site, measured on sand, but it highly rose the pH. Despite its use in high concentration (therefore unstable), it showed high degradation yields. The relatively high production of O-PAC ketones observed in our experiments suggests that oxidation followed an oxido-reductive pathway, similarly to the permanganate. Even if this potential O-PAC formation needs to be followed for field applications, this oxidant has the advantage of turning into nontoxic ferric sludge (which can adsorb and flocculate the remaining pollutants, data not observed in this study as water was freeze-dried).

The industrial production of ferrates is not currently fully developed, the ferrate powder is still very expensive today. Therefore, DNAPL degradation by ferrate on solids should be economically improved.

Especially, some experiments with low concentrations of ferrate could be interesting to limit the selfdegradation of the oxidant. Moreover, thanks to the presence of ferric sludge and other iron species (hematite, goethite) in the ferrate powders we used, a combination of ferrates with hydrogen peroxide as Fenton-like reaction could be tested to investigate if a synergy exists between the two oxidants, as other studies seem to reveal [START_REF] Lacina | Use of the ferrates (FeIV-VI) in combination with hydrogen peroxide for rapid and effectIVe remediation of water -Laboratory and pilot study[END_REF]. Therefore, new batchs on DNAPL spiked sand are planned to explore those ideas. Additionally, some batchs will be conducted on DNAPL contaminated soil, instead of sand, to optimize the treatment and understand the impact of the soil's mineralogy and natural organic matter on oxidation reactions.

Declaration of interest:

Funding: This study was funded by the French Environmental Agency (ADEME) and the French National Association for Research and Technology (ANRT). The funding sources had no other involvement in this study.

(

  Hanna Instrument HI 255 pH/mV Combined Meter -HI 1131 electrode). At the end of the reaction time, bentonite (4 g) was added to the sample and stirred for 30 minutes before being freezed. For the 60°C-experiments (persulfate), temperature was lowered by placing the flasks into cold water (15°C)

Fluorene

  and Phenanthrene (PAHs), Dibenzofuran (O-PAC), Dibenzothiophene (S-PAC), Quinoline and 9H-Carbazole (N-PACs). Compounds with more than three aromatic rings were observed in limited abundance (mainly Fluoranthene and Pyrene). Calculated from the individual PAC quantifications, the quantified molecules represent only 16.2 wt % of the total DNAPL mass, which attests a complex pollutant mixture.

  PAC evolution is described by families: 16 PAHs, 2 furan O-PACs, 10 O-PAC ketones, 7 N-PACs and 4 S-PACs. As for the EOM, the individual PAC degradation is calculated by comparison to the control sample (blanks). The concentration in those blanks, calculated in comparison to the t0 samples, showed an average decrease in PAH, O-PAC, N-PAC and S-PAC concentrations of -1.1%, -1.8% 17.2% and -1.5%, respectively. At 60°C, concentration decreases were higher with 46.3% for PAH, 46.4 % for O-PAC, 38.8% for N-PAC and 26.3% for S-PAC. Similarly, degradation yields are probably underestimated (especially at high temperature) by this blank-correction as oxidant may degrade part of compounds lost by evaporation due to extraction-protocol. PAH and polar-PAC (excepted O-PAC ketone) degradation

Fig2Fig3Fig4Fig2Fig3Fig4

  Fig2Mass loss of the Extractable Organic Matter (EOM) at different oxidation times (time in logarithmic scale) for each oxidant (Fenton-like, permanganate, ferrate (1) and (2) and heat activated persulfate)

Table 1 -

 1 Composition of the DNAPL: 40 targeted PAH and polar-PAC concentrations in the DNAPL

		Initial DNAPL		Initial DNAPL
	PAHs (mg/kg)		O-PACs (mg/kg)
	Naphthalene	127	Dibenzofuran	46 666
	Acenaphthylene	2 659	4-methyldibenzofuran	6 808
	Acenaphthene	26 073	9H-fluorenone	2 284
	Fluorene	25 543	Perinaphtenone	346
	Phenanthrene	27 372	Anthraquinone	679
	Anthracene	5 942	Cyclopenta[def]phenanthrone	88
	Fluoranthene	4 801	Methylanthracene-9,10-dione	324
	Pyrene	2 293	Benz[a]fluorenone	342
	Benz[a]anthracene	372	Benzanthrone	47
	Chrysene	197	Benzoanthracenedione	<
	Benzo[b]fluoranthene	134	Naphtacene-5,12-dione	<
	Benzo[k]fluoranthene	99	Benzo[cd]pyrenone	<
	Benz[a]pyrene	165	S 12 O-PACs (mg/kg)	57 584
	Perylene	77	S 2 O-PACs Furanes (mg/kg)	53 474
	Indeno[1,2,3-cd]pyrene	101	S 10 O-PACs ketones (mg/kg)	4 110
	Dibenz[a,h]anthracene	<	N-PACs (mg/kg)
	Benzo[ghi]perylene	62	Quinoline	1 001
	S 16 PAHs (mg/kg)	95 900	Benzo[h]quinoline	517
	S-PACs (mg/kg)		Acridine	<
	Benzothiophene	48	Carbazole	1 335
	2-methylbenzo[b]thiophene	50	Benzo[c]acridine	124
	Dibenzothiophene	4 621	Nitropyrene	108
	4-methyldibenzothiophene	266	S 5 N

-PACs (mg/kg) 3 085 S 4 S-PACs (mg/kg) 4 985

Table 2 -

 2 pH evolution of the water phase after seven days of reaction for each oxidant

	Oxidant	pH (after 7 days)
	Blank (water)	7.9
	Fenton-like (magnetite)	6.5
	Permanganate (KMnO4)	9.1
	Ferrate 1 (K2FeO4)	13.9
	Ferrate 2 (K2FeO4)	13.9
	Heat activated Persulfate (Na2S2O8)	1.2

Table 3 -

 3 Abatement (%) of total organic extract mass (EOM) and PAC family concentrations after oxidations, calculated by comparison to the blanks after seven days of oxidation. (* recalculated for 1 SOD considering linear proportion)

	Abatement (%)	Fenton-like (magnetite)	Ferrate 1 (K2FeO4)	Ferrate 2 (K2FeO4)	Ferrate 2 (K2FeO4)	Permanganate (KMnO4)	Heat activated persulfate (Na2S2O8)
		1 SOD	1 SOD	0.77 SOD	1 SOD (recalculated*)	1 SOD	1 SOD
	EOM	34.7	65.8	44.4	57.7	82.6	84.4
	S16 PAHs	28.5	77.9	57.0	74	98.1	96.1
	S10 O-PACs Furans	17.4	78.5	63.0	81.8	48.8	95.7
	S5 N-PACs	63.7	85.6	68.7	89.2	100	100
	S4 S-PACs	81.2	45.7	31.1	40.4	98.0	98.5
	Total PACs (without O-PAC ketones)	25.2	75.5	57.1	74.2	76.9	94.0

Acknowledgement

This work was supported by the French Environmental Agency (ADEME) and the French National Association for Research and Technology (ANRT). The funding sources had no other involvement in this study. We thank ARCELORMITTAL FRANCE for the assistance provided in the BIOXYVAL project, particularly for the provision of a site that allowed proper execution of the project's work. We also thank the GISFI (French Scientific Interest Group -Industrial Wasteland) for materials and Mr G. Bessaque from GeoRessources for his help in designing/constructing useful equipments. Dr Mustapha Abdelmoula from LCPME-UMR expertise in Mössbauer spectroscopy, and both Jérôme Frayret from IPREM, UMR CNRS. The anonymous reviewers are thanked for their constructive comments to improve the paper's quality.

Conflict of interest: the authors declare that they are no conflict of interest.


María Santolaria-Otín
email: santolariaotin.maria@gmail.com

Javier García-Serrano

Martin Ménégoz

Joan Bech

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter North Atlantic Oscillation

Keywords: North Atlantic Oscillation, Teleconnection, Sea Ice, Snow Cover

Sea ice concentration (SIC) in the eastern Arctic and snow cover extent (SCE) over central Eurasia in late autumn have been proposed as potential predictors of the winter North Atlantic Oscillation (NAO). Here, maximum covariance analysis is used to further investigate the links between autumn SIC in the Barents-Kara Seas (BK) and SCE over Eurasia (EUR) with winter sea level pressure (SLP) in the North Atlantic-European region over 1979-2019. As shown by previous studies, the most significant covariability mode of SIC/BK is found for November. Similarly, the covariability with SCE/EUR is only statistically significant for November, not for October. Changes in temperature, specific humidity, SIC/BK and SCE/EUR in November are associated with a circulation anomaly over the Ural-Siberian region that appears as a precursor of the winter NAO; where the advection of climatological temperature/humidity by the anomalous flow is related to SCE/EUR and SIC/BK anomalies.

Introduction

The North Atlantic Oscillation (NAO) is the most prominent pattern of atmospheric circulation variability in the Euro-Atlantic sector and has a strong influence on the regional surface climate (e.g., ?, ?). Understanding the processes that potentially drive the NAO state is crucial to improve its predictability. Many recent studies have stressed the potential predicting role of eastern Arctic sea ice and continental snow over Eurasia in autumn, with a reduction of sea ice concentration (SIC) in the Barents-Kara Seas and an increase of snow cover extent (SCE) across Siberia that would favor a negative NAO phase during the subsequent winter (e.g., ?, ?, ?, ?, ?).

Sea ice reduction acts as a source of heat and moisture fluxes that can impact both local and large-scale atmospheric circulation. Observational studies (e.g., ?, ?) and numerical simulations with both atmospheric general circulation models (AGCMs) (e.g., ?, ?, ?, ?) and coupled climate models (e.g., ?, ?) have found that an anomalous anticyclone over northern Eurasia related to low SIC/BK in late-autumn tends to evolve into a negative NAO-like pattern in winter through a lagged stratospheric pathway.

The tropospheric anomalies related to low SIC/BK display a Rossby wave-like anomaly crossing Eurasia, reinforcing the climatological wave pattern. An upward propagation of wave activity finally reaches the stratosphere and weakens the polar vortex. The downward response decelerates the westerlies in the North Atlantic sector shifting the storm-tracks southward, which is tied to a negative NAO phase (e.g., ?, ?). Yet, causality in this chain of processes has to be confirmed (?, ?, ?).

Snow cover variations affect the atmosphere via changes in reflected shortwave solar radiation (albedo), emissivity of longwave radiation, insulation of the atmosphere from

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO3 the soil layers below, and latent-heat and water release in association with melting (e.g., ?). Observational studies (e.g., ?) and GCM experiments (e.g., ?, ?, ?, ?, ?, ?, ?)

showed that an increase in the continental SCE over Eurasia (SCE/EUR) in late autumn can also favor a negative NAO phase in winter via troposphere-stratospheretroposphere interactions. The mechanism relies on the regional radiative cooling induced by positive SCE anomalies over central Eurasia, which modifies the structure and vertical propagation of planetary-scale wave activity eventually triggering a similar stratospheric pathway as described above. But again, as for SIC/BK, causality related to SCE/EUR has yet to be fully established (?, ?).

The stationarity of the SIC-NAO and SCE-NAO relationships has been questioned (e.g., ?, ?) due to the shortness of the observational record and the modulation of the polar vortex by the Quasi-Biennal Oscillation (?, ?). Besides, the connection between these two potential predictors of the winter NAO, i.e. SIC/BK and SCE/EUR, is still an open question (?). Although previous observational and modeling studies have shown that sea-ice reduction over the eastern Arctic is associated with increased snowfall over Siberia (e.g., ?, ?, ?, ?, ?, ?, ?, ?), the physical processes underlying this relationship are unclear. There is also a lack of consensus to determine both the respective contributions of sea-ice and snow-cover anomalies to the winter NAO predictability and the exact timing of their lagged influence on the atmospheric circulation (e.g., ?).

The aim of this study is to comprehensively set the observed statistical relationship between SIC/BK and SCE/EUR with the winter NAO and discuss the associated atmospheric circulation, in order to assist model validation in targeted sensitivity experiments to come (?, ?). The novelty relies on getting insight into the dynamics underlying the SIC/BK and SCE/EUR anomalies linked to the atmospheric precursor of the winter NAO, namely the Ural-Siberian pattern.

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO4

Data and Methodology

In this study, empirical orthogonal function (EOF; ?) and maximum covariance analysis (MCA; ?) are used to describe the spatio-temporal structure of SIC/BK and SCE/EUR variability as well as their covariability with winter SLP anomalies over the period 1979-2019. EOF analysis has been employed to test the robustness of the MCA results. The NAO index is defined as the leading principal component (PC), namely standardized time series, corresponding to the leading mode (first EOF) of sea level pressure anomalies in the North-Atlantic-European region (Figure 1a)(NAE:

20 o N -90 o N, 90 o W -40 o E; e.g. ?).
MCA is a singular value decomposition (SVD) applied to the covariance matrix of two fields that share a common sampling dimension (the actual time) but can be spatially independent. The output consists of pairs of spatial patterns, each one corresponding to a field, and associated standardized time-series called expansion coefficients (ECs).

Each MCA mode is characterized by the squared covariance (sc) which is the eigenvalue of the covariance matrix, the squared covariance fraction (scf) which is a measure of the fraction of explained covariance compared to other modes, and the correlation between the expansion coefficients (cor). On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO6

MCA is respectively applied to SIC in the

Results

Covariability: SIC/BK and SCE/EUR

The leading MCA mode based on September SIC/BK anomalies explains 58% of scf (p-value 29%), with a sc of 1.35 × 10 7 (p-value 16%) and yields a cor of 0.56 (p-value 27%)(Table 1). These high p-values indicate a low confidence level for this relationship, associated with a low signal-to-noise ratio and non-significant predictability (e.g., ?, ?).

For October, the leading MCA mode explains 85% of scf (p-value 1%), with a sc of 5.09 × 10 7 (p-value 0%),and yields a cor of 0.60 (p-value 3%)(Table 1). The leading MCA mode based on November SIC/BK anomalies explains 82% of scf (p-value 2%), with a sc of 3.35 × 10 7 (p-value 0%) and yields a cor of 0.63 (p-value 1%)(Table 1).

The MCA-SIC/BK in October is also significant, but there is no clear atmospheric mechanism responsible for a lagged relationship with the winter NAO (see ?). According to ?, the potential influence of October SIC/BK anomalies on the winter Euro-Atlantic climate would rely on its contribution to November SIC/BK anomalies. On the other hand, the dynamics associated with SIC/BK anomalies in November are much more plausible and largely reported. It could involve a stratospheric pathway (e.g., ?, ?, ?) and represent a suitable predictability source of the winter Euro-Atlantic climate (e.g., ?,?,?,?). Thereby, the analysis is focused hereafter on November SIC/BK variability.

To simplify the nomenclature, we will refer to the MCA covariability mode between SIC/BK in November and SLP/NAE in winter as MCA/SIC N .

Figure 1b shows the regression map of SIC anomalies in November onto the SIC expansion coefficient of MCA/SIC N . The resulting SIC pattern shows negative anomalies (i.e. sea-ice reduction) over the northern Barents Sea and the whole Kara Sea. The SLP covariability pattern of MCA/SIC N (not shown) strongly resembles the negative phase of the NAO (Figure 1a). The SLP expansion coefficient of MCA/SIC N

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO7 Statistically significant areas at 95 % confidence level based on a two-tailed Student's test are contoured. Green contours stand for the climatological sea-ice edge estimated at 15% in (b) and the climatological snow cover edge estimated at 50% in (c); the full field of SIC and SCE climatology can be found in Figure S1.

has indeed a correlation of -0.99 with the winter NAO index, illustrating that the NAO has been effectively captured as predictand.

Caution is required to assert cause and effect based on observational data and MCA results. Concerning the former, several studies using AGCM simulations (e.g., ?, ?, ?)

have also found a lagged teleconnection between SIC/BK anomalies and the NAO, although the timing may be model dependent (?). As for the latter, we further explore the suitability of SIC/BK as predictor. The SIC expansion coefficient of MCA/SIC N is compared with the leading principal component (PC1) of SIC over the eastern Arctic

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO8

and over the Northern Hemisphere in November: the SIC expansion coefficient yields a high correlation with both the regional PC1 (0.98) and the hemispheric PC1 (0.93).

Likewise

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO9 non-significant, namely not discernable from noise. However, we found that November SCE/EUR anomalies tend to be followed by NAO-like atmospheric variability, a result consistent with the monthly analysis of ?.

This finding is supported by the lagged regression maps of autumn SCE/EUR anomalies onto the winter NAO index, where October does not show statistically significant anomalies over Eurasia (not shown) but November does so (Figure S2b).

Thus, in the following the analysis is restricted to November SCE/EUR. As for SIC, we will refer to the leading MCA covariability mode between SCE/EUR in November and SLP/NAE in winter as MCA/SCE N for the sake of readability. Figure 1c shows the covariability mode of SCE from MCA/SCE N , exhibiting statistically significant positive anomalies (i.e. snow cover increase) over central-eastern Eurasia. The SLP covariability of MCA/SCE N displays a negative NAO-like pattern (not shown, but similar to Figure 1a) and its expansion coefficient correlates at -0.99 with the winter NAO index.

The SCE expansion coefficient of MCA/SCE N attains only a correlation of 0.58 (0.30) with the first (second) EOF of November SCE/EUR. The fraction of explained variance of the two leading EOFs is very low (EOF1=15%, EOF2=12%), indicating that they are not well separated statistically (following ?) and illustrating that SCE is a noisy field. This result implies, as opposed to the case of November SIC/BK, that the covariability of MCA/SCE N does not rely on a dominant variability mode of snow cover itself, which questions the feasibility of using SCE/EUR as a potential predictor for the NAO.

Repeating the analysis with snow depth (SD) from ERA-Interim yields consistent results: namely, the MCA with October SD not being significant and the one with November SD showing hints of significance. In the latter case, as opposed to using satellite-derived SCE, sc and scf are higher but above 10% significance level, while the

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO10 correlation between expansion coefficients is smaller but significant at 3% (cor=0.52).

204

The MCA/SD N pattern (not shown) and the regression of November SD/EUR anomalies 205 onto the winter NAO index (Figure S3) display positive anomalies over central Eurasia,

206

particularly west of the Baikal Lake. over western Europe. The identification of this surface anticyclone has been ambiguous in the literature. It appears to be related to Ural blocking at daily time-scales (e.g., ?, ?), but it also constitutes a prominent mode of variability at monthly and seasonal time-scales (e.g., ?, ?). ? tentatively named it as the Russian (RU) pattern, but here it will be referred to as the Ural-Siberian (U-S) pattern. Interestingly, the centers of action of EOF1 (Figure 2b) tightly project on the areas of maximum interannual variability (i.e. standard deviation; green contours in Figure 2a), as it is also the case for the mid-(500hPa; ?) and upper-tropospheric (200hPa; ?) geopotential height. The leading

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO12 mode of Eurasian geopotential height variability in the mid-upper troposphere, which has a better-defined wave-like signature (Figure S4a at 300hPa; e.g., ?), can be more easily identified as the Scandinavian (SCAND) pattern, a mode of internal variability associated with Rossby wave propagation dynamics and maintained by transient-eddy feedback (e.g., ?, ?). Note that the U-S pattern of SLP corresponds to the surface projection of the SCAND pattern at upper levels, and the other way around, since they show a marked barotropic structure (e.g., ?, ?).

The statistically significant SLP anomalies preceding the winter NAO also show a dipole-like structure (Figure 2e), projecting on the centers of the U-S pattern over the Siberian coast and the British Isles (Figure 2b). At 300hPa, the winter NAO is preceded by a wave-like structure over Eurasia, which also projects on the SCAND pattern at upper levels (Figure S4c). These results are consistent with ?, ?, ? and ? who showed that the winter NAO tends to be preceded by a wave-like anomaly over Eurasia, which triggers a stratospheric pathway. These findings suggest that the U-S/SCAND pattern in November may eventually evolve into the winter NAO with a 1-month lead time and might be considered a precursor of the winter NAO. This line of reasoning has been recently confirmed by ?. The anomalous dipole-like pattern associated with MCA/SCE N (Figure 2d) has a strong resemblance to EOF1 (Figure 2b), which is consistent with previous studies using other autumnal Eurasian SCE indices (e.g., ?, ?). It is worth noting that there is no signal over the Siberian High region (reddest areas at mid-latitudes of Figure 2a), which would be expected from the radiative feedback linked to Eurasian snow cover anomalies (Figure 1c andS2b). However, the anomalous Ural-Siberian anticyclone in Figure 2b has been

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO13 usually interpreted as a north-westward expansion of the Siberian High in response to increased SCE over central Eurasia (?, ?, ?, ?, ?), although the U-S pattern develops over the subpolar low-pressure belt along the Siberian coast (blue shading in Figure 2a), linked to local transient-eddy activity (e.g., ?) and cyclone tracks (e.g., ?). In fact, no AGCM study prescribing positive Eurasian SCE anomalies has reported such a circulation response. Instead, they have found a regional baroclinic structure associated with a reinforced Siberian High at surface and cyclonic circulation anomalies in the upper troposphere (? ,?,?,?,?,?,?,?); the most significant being the reinforcement of the Siberian High (?, ?). Thus, there is no modelling evidence supporting the impact or triggering role of SCE/EUR anomalies on the U-S/SCAND pattern. This line of reasoning suggests that the SCE/EUR anomalies in November related to the winter NAO (Figure 1c and S2b) might be potentially driven by the Ural-Siberian anticyclone (Figure 2b) rather than the other way around, which is in agreement with ? and ? and further discussed in Section 3.4.

On the other hand, the dipole-like pattern of SLP anomalies associated with MCA/SIC N (Figure 2c) is slightly different from the other patterns, as the centers of action are located downstream, with the anticyclonic anomalies shifted toward the continent and the cyclonic anomalies displaced toward the Nordic Seas. The vertical structure of the anticyclonic anomalies over the Siberian coast reveals some baroclinicity(cf. Figure S4a), in agreement with AGCM simulations (e.g., ?), which suggests a possible contribution of SIC/BK variability on the U-S pattern (?) that is further discussed in section 3.4.

Linkage between SIC/BK and SCE/EUR

To explore the relationship between November SIC/BK and SCE/EUR in relation to the winter NAO, regional near-surface conditions of temperature (T925), specific humidity

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO14 (q925) and horizontal wind are analyzed at 925hPa (Figure 3). As our framework does not allow disentangling cause and effect, the analysis below is focused on lagged regressions in November onto the winter NAO index, thereby assessing the observed NAO precursors in an objective way. Regressions onto the expansion coefficients of MCA/SCE N or MCA/SIC N yield very similar results.

Climatology in this region shows a cold and dry environment east of Scandinavia (eastern Arctic/eastern Siberia), whereas in western Europe warm and wet conditions prevail (Figure 3a,b). Figure 3c and3d show regression maps of November T925 and q925 onto the winter NAO index, respectively. Warm and wet anomalies are found over the Barents-Kara Seas in relation to sea-ice reduction (c.f. Figures 1b,S2a) while cold and dry anomalies extend across Eurasia in association with the increase in snow cover (c.f. Figures 1c,S2b), although only the latter is statistically significant. SIC/BK reduction and SCE/EUR increase are source and sink of humidity, respectively, as discussed in previous observational and modelling studies (e.g., ?, ?, ?). Noteworthy, it is usually assumed that the connection between SIC/BK and SCE/EUR is as follows:

sea-ice reduction providing extra evaporation, increased moisture flux inland, and enhanced snowfall over Eurasia (e.g., ?, ?). However, model results show that the direct impact of sea-ice reduction on snowfall would mainly apply to the Siberian coast (e.g., ?, ?, ?). Hence, there is room for further exploring the winter NAO-related SIC/BK and SCE/EUR anomalies.

The target diagnostics are the linear advection terms of T925 and q925: namely, the advection of climatological T925/q925 by the anomalous flow [-v . ∇( T , q)] and the advection of anomalous T925/q925 by the climatological flow [-v.∇(T , q )]; the non-linear advection terms are negligible in terms of amplitude (not shown) (e.g., ?).

The advection of anomalous T925/q925 driven by the southwesterly climatological

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO16 flow (Figure 3e,f), bringing warm and wet air masses from the Mediterranean, yield statistically significant anomalies upstream and over the Ural Mountains, i.e. windward.

These warm and wet conditions do not contribute to the snow dipole preceding the NAO shown on Figure 1c. On the other hand, the advection of climatological T925/q925 by the anomalous flow yield statistically significant anomalies downstream (downwind) the Urals, namely over Siberia (Figure 3g,h). It implies that the wind anomalies preceding the NAO transport cold and dry air from the Arctic into Eurasia, indicative of land cooling and humidity sink associated with snowfall, particularly west of Baikal Lake (cf.

Figures 1c,S3

). This south-eastward transport, together with the induced warm and wet advection over the Mediterranean region (Figure 3g,h), suggests that the anomalous U-S anticyclone is the responsible of pushing the snow edge northward over western Eurasia and southward over eastern Eurasia, thereby generating the anomalous continental-scale dipole of snow cover (Figure 1c) and surface conditions(Figure 3c,d). These results contrast with previous works suggesting that increased SCE/EUR is a consequence of the moisture increase due to SIC/BK reduction (e.g., ?, ?), while our results suggest that the relationship is determined by the advection of climatological cold air from the Arctic, mediated by the anomalous atmospheric circulation.

Causality between SIC/BK, SCE/EUR and the U-S pattern

To gain insight on the causality between SIC/BK, SCE/EUR and the regional atmospheric circulation, turbulent (THF; sensible (SHF) plus latent (LHF)) and radiative (RHF; shortwave (SWR) plus longwave (LWR)) surface heat fluxes in November are analyzed (Figure 4).

Over the ocean, THF anomalies associated with the U-S pattern are dominated by downward heat flux, that is by ocean heat uptake, over the Norwegian Sea and the southern, ice-free Barents Sea (Figure 4a). These negative THF anomalies are likely A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO17 A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO18 related to the southerly advection of warm and moist air induced by the anticyclonic circulation in the Siberian coast and the cyclonic circulation over the British Isles (Figure 2b); note that both SHF and LHF anomalies contribute almost equally (Figure S5).

This anomalous THF pattern strongly resembles the atmosphere-driven THF EOF1 of ?. And, consistently with this interpretation, the U-S/SCAND mode also shows negative RHF anomalies (Figure 4b), which are determined by increased downwelling LWR (Figure S6; e.g., ?, and references therein). On the other hand, THF anomalies associated with MCA/SIC N display enhanced upward heat flux over the Kara Sea and northern Barents Sea (Figure 4c). These positive THF anomalies, with contribution from both SHF and LHF (Figure S5), are related to sea-ice reduction and its retreat of the edge (Figure 1b). In this case, the anomalous THF pattern projects on the icedriven THF EOF2 of ?, associated with heat release over the newly-opened oceanic area (e.g., ?). Note that this positive THF anomaly over BK is accompanied by a negative THF anomaly sharply south of the sea-ice edge (cf. Figures 1b,4c), which is the expected response to sea-ice reduction due to the modification of the air mass as it encounters open water (?, ?, ?, ?), although in this framework we cannot discard a role from atmospheric advection as in Figure 4a. Consistent with the ice forcing of the atmosphere, note likewise that there is a positive RHF anomaly over BK (Figure 4d), controlled by emission of LWR (Figure S6). THF anomalies associated with MCA/SCE N (Figure 4e) and the winter NAO (Figure 4g) show contributions from both signals, i.e.

ocean heat uptake related to the U-S pattern (Figure 4a) and ocean heat release linked to SIC/BK (Figure 4c), with a larger and statistically significant influence of atmospheric advection/forcing over the Norwegian Sea for the former. It is worth stressing that both MCA/SCE N and the winter NAO display positive THF anomalies over BK, which suggests that SIC/BK anomalies may contribute to tropospheric anomalies projecting

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO19 on U-S/SCAND-like variability (Figure 2). Several AGCM studies have reported U-S/SCAND circulation anomalies over Eurasia in response to SIC/BK reduction (e.g., ?, ?, ?, ?, ?, ?, ?, ?, ?, ?).

Over the continent, the snow-related THF anomalies depict statistically significant upward heat flux over central Eurasia, west of Baikal Lake, consistently among the regression maps onto the four time-series (Figure 4-left column). These positive THF anomalies are the result of the balance between snow melting and sublimation, with negative LHF anomalies (atmospheric cooling; Figure S5), and the heat transfer related to the advection of climatological cold air from the Arctic (Figure 3g) encountering a warmer surface, with positive SHF anomalies (atmospheric warming; Figure S5) that overcome the former. On the other hand, RHF anomalies systematically show downward heat flux over the same central Eurasian region, maybe weaker for the winter NAO (Figure 4-right column). In this case, the downwelling of LWR (atmospheric cooling) is stronger than the reflection of SWR (albedo effect leading to atmospheric warming; Figure S6). Note that over the snow-covered area south of Baikal Lake (Figures 1c, 2c-d) LWR and SWR anomalies are fully compensated (Figure S6). Finally, it is worth highlighting that over central Eurasia the net radiative cooling has to counteract the net turbulent warming (Figure 4), which may imply a low signal-to-noise atmospheric response to realistic snow anomalies.

Conclusions

According to previous observational studies (e.g., ?, ?, ?), November SIC/BK represents the most robust "potential" predictor of the winter NAO based on eastern Arctic SIC variability. This work revealed that it corresponds to the leading EOF of SIC at regional and hemispheric scale, i.e. over the whole Arctic.

A c c e p t e d m a n u s c r i p t

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO20 Another aspect stressed in this study is that the Ural-Siberian anticyclone appears 385 not to be associated with the Siberian High but with the regional, subpolar low-pressure

  Barents-Kara Seas (BK: 50 o N -90 o N, 30 o W -120 o E ), and Eurasian SCE (EUR: 20 o N -90 o N, 0 o -150 o E) for autumn (from September to November) as predictor fields and winter SLP/NAE as predictand field (seasonal average for DJF). The first MCA mode is analyzed in both cases. A Monte Carlo test based on 100 permutations shuffling only the atmospheric field (i.e. SLP) with replacement is performed to determine the statistical significance of these MCA modes. By performing MCA upon each resampling we generate a probability density function (PDF) that is used to compute the significance level (hereafter simply p-value) which corresponds to A c c e p t e d m a n u s c r i p t On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO5 the number of randomized values (sc, scf or cor) that exceed the actual value being 99 tested (e.g., ?). 100 Monthly SIC data are provided by HadISST (Hadley Center Sea Ice and Sea 101 Surface Temperature; ?) at 1.0 o × 1.0 o resolution and SCE data from the Global Snow 102 Laboratory at Rutgers University (?). For SCE, October is defined as the average of the 103 calendar weeks 40-44 (?), and November of the weeks 44-48. Compared to ? for SCE 104 and ? for SIC, our choice of dataset does not affect results. Monthly data of atmospheric 105 variables are given by ERA-Interim reanalysis available from the European Center for 106 Medium-Range Weather Forecasts (ECMWF) at 2.5 o × 2.5 o resolution (?). Forecast-107 accumulated turbulent (sensible plus latent) and radiative (shortwave plus longwave) 108 heat fluxes initialized twice a day (00, 12h) from ERA-Interim are also used; upward 109 is positive, from surface to atmosphere. All anomalies are detrended before analysis 110 to focus on the interannual variability, aiming to exclude any long-term relationship 111 among variables. Different detrending methods (1st-, 2nd-and 3th-order polynomial 112 fits) have been evaluated to assess robustness of the results; in the manuscript we only 113 show cubicly detrended anomalies because of the strong non-linear trends in SIC/BK, 114 but the results are largely insensitive to the detrending method. 115 To explore the dynamics involved in the statistical relationships, regression maps 116 are computed by projecting different anomalous fields onto a time-series, either the NAO 117 index or the MCA expansion coefficients. In this case, the statistical significance of the 118 regressed anomalies is evaluated with a two-tailed Students t-test at 95% confidence 119 level.

Figure 1 .

 1 Figure1. (a) Leading EOF of detrended sea level pressure anomalies (hPa) in winter (DJF) over the North Atlantic-European (NAE) region, with a fraction of explained variance of 47.9 % ; note that the negative phase of the NAO is shown. Leading MCA mode between (b) SIC over Barents-Kara Seas (%) and (c) SCE over Eurasia (%) in November with winter (DJF) SLP over the North Atlantic-European region (hPa). Statistically significant areas at 95 % confidence level based on a two-tailed Student's test are contoured. Green contours stand for the climatological sea-ice edge estimated at 15% in (b) and the climatological snow cover edge estimated at 50% in (c); the full field of SIC and SCE climatology can be found in FigureS1.

207 3 . 2 .Figure 2 .

 322 Figure2bshows the regression map of Northern Hemisphere (NH) SLP anomalies

Figure

  Figure 2c and 2d show the regression map of contemporaneous SLP anomalies onto

Figure 3 .

 3 Figure 3. (a,b) Climatology of November air temperature (T925 ; o C ) and specific humidity (q925 ; g/kg). Climatological wind at 925hPa (ū, v; m/s) is overplotted with vectors. (c,d) Regression map of detrended T925 ( o C) and q925 (g/kg) anomalies in November onto the winter NAO index-multiplied by -1. Anomalous wind at 925hPa (u',v'; m/s) is overplotted with vectors. (e,f) Regression map of the advection of anomalous T925 ( o C/s) and q925 ((g/kg)/s) by the climatological flow in November onto the winter NAO index -multiplied by -1. (g,h) Regression map of the advection of climatological T925 ( o C/s) and q925 ((g/kg)/s) by the anomalous flow in November onto the winter NAO index -multiplied by -1.

Figure 4 .

 4 Figure 4. Regression map of detrended turbulent heat flux anomalies (W • m -2 ; a,c,e,g) and radiative heat flux anomalies (W • m -2 ; b,d,f,h) in November onto (a,b) the leading PC from the EOF analysis of November SLP over Eurasia (see Figure2b), (c,d) the MCA/SIC N expansion coefficient, (e,f) the MCA/SCE N expansion coefficient and (g,h) the winter NAO index -multiplied by -1. Statistically significant areas at 95 % confidence level based on a two-tailed Student's test are contoured.

386system.

  The Ural-Siberian pattern stands for the third most prominent atmospheric 387 pattern in the Northern Hemisphere after the PNA in the North Pacific and the 388 NAO in the North Atlantic (e.g., ?). Particularly in November, the Ural-Siberian 389 anticyclone represents the leading EOF of SLP and is associated with the leading EOF 390 of geopotential height at the upper troposphere (e.g., ?, ?); which corresponds to the 391 SCAND pattern (e.g., ?, ?). 392 Finally, the variability of the Ural-Siberian pattern, which may include some 393 SIC/BK forcing, appears to be responsible for the connection between the winter NAO 394 and November SCE/EUR anomalies via advection of climatological temperature and 395 humidity by the anomalous winds, transporting cold and dry air from the Arctic into 396 Eurasia. The (potential) contribution of SCE/EUR to the Ural-Siberian pattern is 397 questioned due to the competing effect of the associated radiative and turbulent heat 398 flux anomalies over the snow-covered areas.

  , the lagged regressions of winter SLP onto the two PC1s are almost identical to that of the SIC expansion coefficient (not shown), which is consistent with alternative approaches based on area-averaged SIC indices (?, ?). Hence, the covariability mode of MCA/SIC N is associated with a leading mode of SIC variability per se. Note that the SIC pattern of MCA/SIC N corresponds to the second EOF of turbulent heat flux

	value 26%), and yields a cor of 0.69 (p-value 33%). For November, the leading MCA
	explains 74% of scf (p-value 0%), with a sc of 4.89 × 10 7 (p-value 0%) and yields a
	cor of 0.76 (p-value 13%). Extending the period using reanalyzed SCE data (instead
	of satellite-derived products) would probably not lead to better statistical results (?)
	especially when considering the potential non-stationarity of the snow-NAO relationship

in ?, with a strong ocean-to-atmosphere forcing (see also ? and ?); which is unrelated to the so-called "Warm Arctic-Cold Siberia" (WACS) pattern in winter. It follows that November SIC/BK anomalies can be considered as a potential predictor of the subsequent winter NAO. Lagged regression of SIC anomalies in November onto the winter NAO index (Figure

S2a

) support this conclusion. Analogous to the procedure followed for SIC/BK, MCA based on SCE/EUR anomalies in late autumn (October, November) have been performed. Note that September has not been considered because there is almost no snow cover over the continent at that time of the year (e.g., ?). The leading MCA mode for October SCE/EUR anomalies explains 52% of scf (p-value 45%), with a sc of 1.90 × 10 7 (p-(?). In contrast to previous studies that suggested a statistically significant relationship between October SCE/EUR and the winter NAO (e.g., ?, ?, ?), these results reveal that the covariability of October SCE/EUR with winter SLP/NAE is largely statistically

Table 1 .

 1 Results of the MCA covariability analysis between autumn SIC/BK and SCE/EUR with winter SLP/NAE for the period 1979-2019. The squared covariance fraction (scf), the squared covariance (sc) and the correlation between the expansion coefficients (cor) are listed for each mode, together with the significance level (p-value).

		September	October	November
	(MCA/SIC N )
	scf (p-value)	58 % (29%)	85 % (1%)	82% (2%)
	sc (p-value)	1.35 × 10 7 (16 %) 5.09×10 7 (0%) 3.53 × 10 7 (0%)
	cor (p-value)	0.56 (27 %)	0.60 (3%)	0.63 (2%)
	(MCA/SCE N )
	scf (p-value)	/	52 % (45%)	74 % (0%)
	sc (p-value)	/	1.90 × 10 7 (26%) 4.89 × 10 7 (0%)
	cor (p-value)	/	0.69 (33%)	0.76 (13%)

  Concerning SCE/EUR, the leading covariability with winter SLP in the North 377 Atlantic-European region is not statistically significant for October SCE, in contrast 378 to previous observational studies using different approaches (e.g., ?, ?); while it is 379 marginally significant for November SCE, in agreement with ?. However, SCE/EUR 380 does not display a dominant mode of variability in November which implies that it 381 should not be considered as an "actual" predictor. It seems that the high correlation 382 between November SCE/EUR and the winter NAO relies on the atmospheric precursor 383 of the NAO itself, namely the Ural-Siberian anticyclone, in agreement with ? and ?.

	384

On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter NAO21

Acknowledgments

The research leading to these results has received funding from the European Commissions H2020 projects APPLICATE (GA 727862) and PRIMAVERA (GA 641727).JG-S was supported by the Ramón y Cajal programme (RYC-2016-21181).

MM was supported by the MINECO project VOLCADEC (CGL201570177-R). JB has been supported by MINECO projects CGL2016-81828-REDT (AEI) and RTI2018-098693-B643-C32 (AEI). The authors thank Hervé Douville (CNRM/Météo-France) and Guillaume Gastineau (LOCEAN/IPSL, France) for useful discussions.

Data availability statement

The data that support the findings of this study are openly available.

• Sea Ice data HadISST (Hadley Center Sea Ice and Sea Surface Temperature (DOI:10.1029/2002JD002670) • Snow Cover data from the Global Snow Laboratory at Rutgers University (DOI: 10.7289/V5N014G9) • Atmospheric variables data from ERA-Interim reanalysis available from the European Center for Medium-Range Weather Forecasts (ECMWF)(DOI:10.1002/qj.828).