Julien Moussou

Guillaume Pilla
email: guillaume.pilla@ifpen.fr

Julien Sotton

Marc Bellenoue

Fabien Rabeau

High-frequency wall heat flux measurement during wall impingement of a diffusion flame

Keywords: Diesel combustion, heat flux, high-frequency measurement, convection coefficient

The efficiency of internal combustion engines is limited by heat losses to the wall of the combustion chamber. A precise characterization of wall heat flux is therefore needed to optimize engine parameters. However, the existing measurements of wall heat fluxes have significant limitations; time resolution is often higher than the timescales of the physical phenomena of flame-wall interaction. Furthermore, few studies have investigated diesel flame conditions (as opposed to propagation flames). In this study, the heat flux generated by a diffusion flame impinging on a wall was measured with thin-junction thermocouple, with a time resolution of the whole acquisition chain better than 0.1 ms. The effects of variations in ambient gas temperature, injection pressure and injector-wall distance were investigated. Diesel spray impingement on the wall is shown to cause strong gas-wall thermal exchange, with convection coefficients of 6-12 kW/m 2 /K. Those results suggest the necessity of close-wall aerodynamic measurements to link macroscopic characteristics of the spray (injection pressure, impingement geometry) to turbulence values.

Introduction

Internal combustion (IC) is forecasted to remain a major source of energy and be present in the majority of automobile engines in the next decades. [START_REF] Scharf | Gasoline engines for hybrid powertrains: high tech or low cost? FEV white paper[END_REF][START_REF] Meszler | CO2 reduction technologies for the European car and van fleet: a 2025-2030 assessment[END_REF] Growing concerns about emissions of CO 2 and pollutants demand further increases in efficiency. Heat transfer losses are around 10%-40% of the total fuel energy, depending on engine operating point and conditions, [START_REF] Holmberg | Global energy consumption due to friction in passenger cars[END_REF][START_REF] Johnson | Exploring the pathway to high efficiency IC engines through exergy analysis of heat transfer reduction[END_REF][START_REF] Mukai | The effects of design factors of the combustion chamber on heat balance in a gasoline engine[END_REF] and thus are a major source of inefficiency; future efficiency targets can only be met by reducing wall heat transfer losses over an engine cycle. It is therefore necessary to accurately determine heat losses during each phase of the combustion cycle, in order to identify guidelines for the future optimization of engine operating parameters. Because the highest heat fluxes are found during the combustion event, that phase of the combustion cycle is the focus of this study.

In order to replicate combustion in engine conditions, multiple configurations have been used: constant volume combustion chamber (CVCC), [START_REF] Boust | Unsteady heat transfer during the turbulent combustion of a lean premixed methane-air flame: effect of pressure and gas dynamics[END_REF] rapid compression machine (RCM) [START_REF] Labuda | Experimental study of single-wall flame quenching at high pressures[END_REF] or instrumented IC engines. [START_REF] Gingrich | Experimental investigation of piston heat transfer in a light duty engine under conventional diesel, homogeneous charge compression ignition, and reactivity controlled compression ignition combustion regimes[END_REF] CVCC and RCM enable easy sensor access to the combustion chamber while maintaining conditions similar to IC engines.

Because heat transfers vary significantly during the engine cycle, accurate information can only be obtained with in-cycle thermal measurements, which requires temporal resolutions of the millisecond or less. For instance, at an engine speed of 1200 r/min, temporal resolution to the crankshaft angle degree (°CA) corresponds to a time resolution of 0.15 ms or a cutoff frequency of 7.2 kHz. This proves challenging because of thermal inertia effects in standard sensors.

Multiple diagnostics have been used to measure incycle thermal information on the surface of the combustion chamber, in particular thermocouples, [START_REF] Gingrich | Experimental investigation of piston heat transfer in a light duty engine under conventional diesel, homogeneous charge compression ignition, and reactivity controlled compression ignition combustion regimes[END_REF][START_REF] Hendricks | Experimental investigation of piston heat transfer under conventional diesel and reactivity-controlled compression ignition combustion regimes[END_REF] resistance temperature detectors (RTD), [START_REF] Dejima | Three-point MEMS heat flux sensor for turbulent heat transfer measurement in internal combustion engines[END_REF][START_REF] Demuynck | A fuel independent heat transfer correlation for premixed spark ignition engines[END_REF] thermopiles, [START_REF] Demuynck | Local heat flux measurements in a hydrogen and methane spark ignition engine with a thermopile sensor[END_REF][START_REF] Lejsek | Investigations on the transient wall heat transfer at start-up for SI engines with gasoline direct injection[END_REF][START_REF] Broekaert | Evaluation of empirical heat transfer models for HCCI combustion in a CFR engine[END_REF] laser-induced phosphorescence (LIP) [START_REF] Luo | Simultaneous in-cylinder surface temperature measurements with thermocouple, laser-induced phosphorescence, and dual wavelength infrared diagnostic techniques in an optical engine[END_REF][START_REF] Luo | In-cylinder wall temperature influence on unburned hydrocarbon emissions during transitional period in an optical engine using a laser-induced phosphorescence technique[END_REF] and infrared thermometry. [START_REF] Luo | Simultaneous in-cylinder surface temperature measurements with thermocouple, laser-induced phosphorescence, and dual wavelength infrared diagnostic techniques in an optical engine[END_REF][START_REF] Jansons | Infrared spectral analysis of engine preflame emission[END_REF] The most common is thin-junction thermocouple and is the one used here; as with every other method but thermopiles, a surface temperature is measured, which allows us to recover heat flux via a mathematical model. Thermopiles provide direct heat flux information with minimal data processing, but require a large surface area (causing significant spatial averaging) and have larger response times than other methods. [START_REF] Demuynck | A fuel independent heat transfer correlation for premixed spark ignition engines[END_REF][START_REF] Demuynck | Local heat flux measurements in a hydrogen and methane spark ignition engine with a thermopile sensor[END_REF][START_REF] Broekaert | Evaluation of empirical heat transfer models for HCCI combustion in a CFR engine[END_REF] Few RTD sensors exist, none of them commercially available, although recent developments suggest that the technology can be as accurate as thermocouples. [START_REF] Dejima | Three-point MEMS heat flux sensor for turbulent heat transfer measurement in internal combustion engines[END_REF] LIP and infrared thermometers use emissions from heated body or activated phosphors and are difficult to apply in compression-ignition (CI) conditions due to interference between the optical signal and soot radiation. [START_REF] Jansons | Infrared spectral analysis of engine preflame emission[END_REF][START_REF] Someya | Instantaneous 2D imaging of temperature in an engine cylinder with flame combustion[END_REF][START_REF] Nau | Wall temperature measurements at elevated pressures and high temperatures in sooting flames in a gas turbine model combustor[END_REF] Further comparisons of the methods of heat flux measurement can be found in the literature. [START_REF] Demuynck | A fuel independent heat transfer correlation for premixed spark ignition engines[END_REF][START_REF] Wimmer | Heat transfer to the combustion chamber and port walls of IC engines: measurement and prediction[END_REF] Previous studies on premixed flames for spark-ignition (SI) engines show the main features of transient heat flux curves. [START_REF] Boust | Unsteady heat transfer during the turbulent combustion of a lean premixed methane-air flame: effect of pressure and gas dynamics[END_REF][START_REF] Labuda | Experimental study of single-wall flame quenching at high pressures[END_REF][START_REF] Boust | A thermal formulation for single-wall quenching of transient laminar flames[END_REF][START_REF] Zhao | Analysis of the flame-wall interaction in premixed turbulent combustion[END_REF] The heat flux first increases in a fraction of millisecond from zero to a few MW/m 2 and decreases in about the same time. That heat flux spike is attributed to flame wall interaction (FWI) processes: the hot flame front, close to the adiabatic flame temperature, approaches the wall until heat losses cause flame quenching.

In CI engines, the combustion phenomena are different (spray mixing, diffusion flame). [START_REF] Dec | A conceptual model of DI diesel combustion based on laser-sheet imaging[END_REF] Heat flux measurements therefore yield different features, [START_REF] Gingrich | Experimental investigation of piston heat transfer in a light duty engine under conventional diesel, homogeneous charge compression ignition, and reactivity controlled compression ignition combustion regimes[END_REF][START_REF] Hendricks | Experimental investigation of piston heat transfer under conventional diesel and reactivity-controlled compression ignition combustion regimes[END_REF][START_REF] Enomoto | Heat transfer coefficient on the combustion chamber wall surfaces in a naturally aspirated direct-injection diesel engine[END_REF] with heat fluxes as high as 10 MW/m 2 exhibiting a plateau of a few milliseconds rather than a spike of heat flux. [START_REF] Mayer | Experimental investigation of flame-wallimpingement and near-wall combustion on the piston temperature of a diesel engine using instantaneous surface temperature measurements[END_REF][START_REF] Li | Heat transfer from impinging diesel flames to the combustion chamber wall[END_REF] Extensive studies [START_REF] Bruneaux | Combustion structure of free and wallimpinging diesel jets by simultaneous laser-induced fluorescence of formaldehyde, poly-aromatic hydrocarbons, and hydroxides[END_REF][START_REF] Dec | Diffusion-flame / wall interactions in a heavy-duty DI diesel engine[END_REF][START_REF] Le | The planar imaging of laser induced fluorescence of fuel and hydroxyl for a wallinteracting jet in a single-cylinder, automotive-size, optically accessible diesel engine[END_REF] about diesel jet impingement showed that a cool flame develops close to the wall, due to either higher premixing or because of extinction of the diffusion flame or dying flame, although it is still surrounded by high temperature reactions at the diverted tip, in some cases leading to the deposition of soot. [START_REF] Bruneaux | Combustion structure of free and wallimpinging diesel jets by simultaneous laser-induced fluorescence of formaldehyde, poly-aromatic hydrocarbons, and hydroxides[END_REF][START_REF] Dec | Diffusion-flame / wall interactions in a heavy-duty DI diesel engine[END_REF] Thermal transfer during jet impingement is not understood as well as in SI engines.

In this study, a high-frequency thermocouple measurement of wall temperature is made during spray impingement in a CVCC. Variations are performed on injection pressure, injector-wall distance and ambient gas temperature. The highly resolved temperature measurements (temporal resolution better than 0.15 ms) allow us to capture the characteristics of each heat flux curve throughout the combustion, without the need for ensemble averages of data. The scales of rise of heat flux in time and maximum flux are analyzed and compared with relevant phenomenological observations. That experiment also highlights the capabilities of that new experimental setup for further study.

Methods

Combustion environment

Experiments were conducted using a high temperature high pressure chamber, later-on referred to as constant volume (CV) chamber. This chamber, previously described in the literature, [START_REF] Pickett | Comparison of diesel spray combustion in different high-temperature, high-pressure facilities[END_REF] aims at creating thermodynamic conditions close to engines, with pressures up to 150 bar and temperatures up to 1500 K. To achieve this, the CV chamber is initially preheated at 465 K. A premixed, lean inflammable mixture with fan-induced turbulence is then ignited by spark plugs, causing a precombustion phase of less than 100 ms that greatly increases gas temperature and pressure inside the chamber. In the following few seconds, pressure and temperature of chamber gases decrease due to cooling via wall heat losses. Finally, a direct fuel injection can be synchronized to a target pressure and temperature during the cooling process within a 1% reproducible precision. Depending on the final mixture composition after the precombustion event, the fuel spray can autoignite.

A pressure sensor (AVL GU21D) monitors the instantaneous pressure inside the CV chamber. The CV chamber is also equipped with sapphire windows allowing optical access across the chamber volume. Imaging of the spray and the combustion can therefore be performed. In this study, a Schlieren imaging technique was applied perpendicularly to the injection axis allowing us to capture qualitative spray shape information.

The experimental setup is shown in Figure 1. A flat obstacle is placed inside the combustion chamber as to simulate jet impingement on a wall. The obstacle, a 40mm diameter stainless steel (APX4) disk, is placed perpendicular to the injection axis and aligned with it. A thermocouple is flush mounted at its center for thermal measurements described later. The insertion system is such that the distance d between the injector nozzle and the obstacle can be adjusted.

Experimental conditions

A single-hole injector was used (Bosch common rail solenoid, 90-mm nozzle outlet diameter, ECN #13) with pure n-dodecane as fuel. A single injection of 1.5 ms duration was performed, giving an injected mass of 3.6 6 0.1 mg for an injection pressure of 1500 bar.

Thermodynamic conditions in which the spray was injected in the CV chamber were taken close to the ECN spray A temperature and density targets. [START_REF] Pickett | Comparison of diesel spray combustion in different high-temperature, high-pressure facilities[END_REF] A reference point was chosen from which injection pressure, ambient gas temperature at injection and distance between injector nozzle and obstacle were varied one at a time. The experimental conditions are given in Table 1. Each experimental condition was repeated at least five times to allow statistical analysis of the data.

Due to the large volume of the combustion chamber (1.4 L), the global air/fuel ratio in the chamber is very high (above 100). Transient pressure recordings with a resolution below 0.5bar show no impact of the diesel combustion on chamber pressure.

Gas composition at the start of injection is equivalent to that found in engines for 25% (molar) exhaust gas recirculation.

Thermal measurements

The temperature inside the CV chamber was held constant for a sufficient long time before the precombustion to assume that heat flux is zero before this event; temperature before the precombustion is always in the 465-475 K range. The wall temperature (as recorded by the thermocouple) is about 25-35 K higher at the start of injection than before precombustion. Finally, during the injection event, wall temperature increases by 5-20 K. All those temperature changes are estimated to have a negligible effect on the thermal properties of the wall.

It is also assumed that heat conduction is monodimensional (normal to the wall). That assumption can be justified by a Fourier number analysis: as the duration of the heat transfer event during and after injection is 10 ms or less, heat diffusion distances in the thermocouple at the relevant timescales are about 0.1 mm, whereas both the expected spatial inhomogeneities of the incident flux and the geometry of the thermocouple have characteristic sizes of about 1 mm. In these conditions, the mathematical problem of thermal diffusion can be solved analytically. Indeed, the measurement of wall temperature is sufficient to compute the heat flux using 31

q t ð Þ = ffiffiffiffiffiffiffiffiffiffi ffi krC p p r ð t t 0 = À' ∂T w ∂t dt 0 ffiffiffiffiffiffiffiffiffiffi ffi t À t 0 p ð1Þ
where q(t) is the transient heat flux in W/m 2 , ffiffiffiffiffiffiffiffiffiffi ffi krC p p is the thermal effusivity of the thermocouple junction material (chromel) and T w is the measured wall temperature in K. The manufacturer's specification ffiffiffiffiffiffiffiffiffiffi ffi krC p p = 8430W:s 0:5 :m À2 :K À1 was used for the effusivity value.

The starting point for the integral is chosen before the precombustion event. Although significant heat fluxes are calculated during precombustion itself (2-3 MW/m 2 ), it decreases down to about 0.05 MW/m 2 (below the measurement resolution) in about 500 ms, well before the injection event; therefore, no background flux subtraction is necessary.

Wall temperature on the obstacle was measured similarly to previous studies [START_REF] Ma | Non-equilibrium wall-modeling for internal combustion engine simulations with wall heat transfer[END_REF] : the output of a K-type thin junction thermocouple (Medtherm TCS-244-KU(KU-156)-72-11340) is amplified by a custom electronic card (Analog device AD595 with 10-kHz low-pass filter) whose output is recorded with an oscilloscope (Lecroy Waverunner 610Zi). Before differentiation, the temperature trace is smoothed using a Tikhonov regularization, which is more adapted to temperature-to-flux reconstruction problems than linear low-pass filtering, [START_REF] Hendricks | Estimation of surface heat flux in IC engines using temperature measurements: processing code effects[END_REF] using a ready-made MATLAB script. [START_REF] Chartrand | Numerical differentiation of noisy, nonsmooth data[END_REF] Precision on the final flux measurement is estimated to be better than 0.1 MW/m 2 based on the noise obtained on the heat flux measurement during the precombustion event.

The response time of the whole processing chain (thermocouple, amplifier, recording and processing code) has been measured using a laser heating setup similar to that of previous literature. [START_REF] Burgess | Transient thermal response of plasma-sprayed zirconia measured with thin-film thermocouples[END_REF] Imposing a step of heat flux (rise time \ 1 ms, duration 8 ms) on the thermocouple junction causes a non-instantaneous increase in the reconstructed heat flux, whose rise time gives an estimation of the time resolution of the whole processing chain. The response time of the whole setup was measured to be 0.08-0.1 ms, which is compatible with an engine target of 1 °CA at 1200 r/min.

General shape and statistical processing

Figure 2 shows the general shape of the results obtained for three repetitions of the reference point (P inj = 1500 bar, d = 45 mm, T a = 850 K). Time is counted starting from the electronic command of injection.

Defining the start of heat flux as the timing at which the flux value is above 0.5 MW/m 2 , the jet impinges on the wall with a delay of about 1.5 ms after the start of injection. This delay is attributed to the hydraulic delay of the injector (about 0.3 ms) and to the travel time between the nozzle and the obstacle. The heat flux then increases in less than 0.5 ms up to values of the order of 5 MW/m 2 . Finally, it decreases back to zero in a few milliseconds.

The steep initial gradient in heat flux is reproducible for each shot: both the timing of the start of heat flux and the rise time (duration between the start of heat flux and 63% of heat flux maximum) exhibit standard deviations of about 0.06 ms. However, these curves exhibit shot to shot variations in later stages. Peaks and valleys of about 2 MW/m 2 amplitude are observed. Those are attributed to physical changes in the heat flux due to statistical variations in the jet/ wall interaction. To obtain quantitative measurements, such random deviations are filtered by pointby-point averaging of repetitions of the same operating condition. Figure 2 shows the resulting mean as a continuous line and the standard deviation as the shaded area surrounding it.

Results and discussion

Radiative heat flux estimation

Testing radiative heat transfer. In this study, convective and radiative transfers are considered predominant to describe heat transfer to the wall. Therefore, conduction will not be further discussed. These two modes of heat transfer tend to happen simultaneously because they are both correlated with jet impingement: convective transfer happens only if hot gases are close to the wall, and radiative transfer is maximal when soot are close to the wall. According to literature, [START_REF] Benajes | In-cylinder soot radiation heat transfer in direct-injection diesel engines[END_REF] soot in diesel flames can emit more than 1 MW/m 2 of blackbody radiation heat flux. Therefore, a specific experiment was designed to evaluate the contribution of the radiative component to the overall heat flux transmitted to the wall. As shown in Figure 3, the reference test case (left) was compared to a case where the wall is 45 mm from the flame (right). In this configuration, the wall only sees radiation from soot, and heat from convection or conduction is considered negligible. Schlieren imaging presented in Figure 3 clearly shows the incandescent soot radiation at the tip of the jet.

Results of that test are shown in Figure 4. For the non-impinging case, heat flux in the 10 ms following the injection command is inferior to 0.05 MW/m 2 , below the estimated precision limit of 0.1 MW/m 2 . There is no statistically significant difference between heat flux traces during that time and in the 10 ms immediately preceding injection either. Therefore, the maximum radiative heat flux will be considered to be 0.1 MW/m 2 .

Estimation of the maximum radiative heat flux inside the flame. In the previous experimental test case, radiating soot particles are far away from the sensor, which reduces the incident radiative heat flux compared to the reference case where soot is very close (impinging jet). That geometrical effect can be evaluated by an elementary solid angle calculation. Soot emission is modeled as a disk of radius R whose surface area emits uniform and isotropic radiation from a distance d of the sensor. It is furthermore assumed that there is no optical absorption in the transmitting medium. Under those assumptions, the radiative heat flux received at the sensor location is found to be proportional to the geometrical factor

G = 1 À 1 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi 1 + R d À Á 2 q ð2Þ
When the sensor is close to the emitting area (d \ \ R), the received radiation is equal to the emission (G = 1); further away, it is only a fraction of the emission. In the previous test case, d = 45 mm is taken from the distance between the injection axis and the sensor. The image from Figure 3, right allows us to evaluate R = 20 6 10 mm based on the glowing area, where the large uncertainty takes into account that soot radiation is out of focus for Schlieren imaging; that estimate of soot cloud size is compatible with data from previous experimental studies using formaldehyde laser-induced fluorescence or soot extinction diagnostics. [START_REF] Bruneaux | Combustion structure of free and wallimpinging diesel jets by simultaneous laser-induced fluorescence of formaldehyde, poly-aromatic hydrocarbons, and hydroxides[END_REF][START_REF] Lind | Mechanisms of post-injection sootreduction revealed by visible and diffused backillumination soot extinction imaging[END_REF] The corresponding G is therefore estimated between 0.09 and 0.25.

This calculation leads to the estimation of a maximum radiative heat transfer component of 0.6 MW/m 2 . That value is about 10% of the observed peak of heat flux during jet impingement. Convective effects are then the dominant effect of heat transfer in the present experiments and will be the focus of the following analysis.

Ambient gas temperature variation

The ambient gas temperature at which the injection is performed can be adjusted by changing the timing of injection. Figure 5 shows the effect of that variation on the measured heat flux for three temperatures: 966, 850 and 780 K.

As the ambient gas temperature is increased, the heat flux peaks sooner: the delay between injection and heat flux peak increases from 1.36 to 1.63 ms (jitter is of the order of 0.05 ms, i.e. negligible). This is due to earlier spray impingement, as combustion causes gas expansion which increases spray tip speed. That effect increases with higher temperature. [START_REF] Payri | A study on diesel spray tip penetration and radial expansion under reacting conditions[END_REF] With increasing ambient temperature, an increase in heat flux is observed as well, as the peak value varies from 4.4 6 1.0 to 6.4 6 0.4 MW/m 2 .

In order to analyze that increase, recall Newton's law of convection

Q = h T g À T w À Á ð3Þ
where Q is the local heat flux in W/m 2 ; h is the convection coefficient in W/m 2 /K; T g , T w are, respectively, the gas and wall temperature in K.

The following analysis aims to determine estimates of the unknown quantities (h, T g ) in Newton's law (cf. equation ( 3)) using the experimental determination of wall temperature T w (by thermocouple measurements), heat flux Q (cf. equation ( 1)), and the ambient gas temperature T a (computed from pressure sensor data).

While ambient gas temperature does have an effect on spray tip speed due to autoignition delay effects, when the spray tip penetration reaches 45 mm, spray tip speed is the same for every temperature. [START_REF] Payri | A study on diesel spray tip penetration and radial expansion under reacting conditions[END_REF] Therefore, turbulence inside the center line of the jet is assumed to be identical after jet impingement for the different ambient temperatures. If so, the convection coefficient h is constant with ambient gas temperature, although it may vary with time. T w is measured and shows very low variations in time, within 5 K, compared to gas temperature exhibiting variations in the order of 200 K. As a result, the observed increase in heat flux must be linked with an increase in T g .

Let dT = T g À T a be the difference in temperature between gases next to the sensor and those in the bulk of the CV chamber. Assuming as a first-order approximation that dT is independent of the ambient gas temperature, it follows that

Q = h T a + dT À T w ð Þ ð 4Þ
where Q, T a , T w are known experimentally and h, dT do not vary as T a is varied. Under those hypotheses, the values of h, dT can be recovered by fitting the experimental data, as shown in Figure 6. A least-square fit weighted by the inverse of standard deviations observed on the experimental data was applied on values from the peak of heat flux and yields h = 10 kW/m 2 /K and dT = 140 K. The fitting uncertainty on these values is estimated to be about 10%-15%.

The convection coefficient value of h;10 kW/m 2 /K is two to five times higher than those obtained by previous experimental [START_REF] Enomoto | Heat transfer coefficient on the combustion chamber wall surfaces in a naturally aspirated direct-injection diesel engine[END_REF] or correlation-based [START_REF] Tanov | Influence of the number of injections on piston heat rejection under low temperature combustion conditions in an optical compression-ignition engine[END_REF] studies. Most likely that is due to differences in the experimental setup (engine instead of CV chamber cases). In particular, a global pressure increase in the chamber during combustion, as observed in engines, might have an effect on turbulence and hence the convection coefficient, whereas in this study, no such increase occurs (due to the very small global air/fuel ratio) and the combustion occurs at constant pressure. Furthermore, correlationbased studies involve considerable spatial averaging (as heat coefficient correlations were calibrated from cylinder-averaged data), and previous experimental studies have usually lower bandwidths (either because of acquisition chain or post-processing effects) than the 10 kHz effective acquisition frequency reported here. That causes heat flux peaks to be underestimated in those previous studies and explains lower values of h.

The temperature increase of 140 K can be compared with non-impinging jet data. A reactive spray model from the literature 40 yields an fuel/air ratio = 3.75 in the center line of a non-impinging dodecane jet at a distance of 45 mm. Assuming adiabatic constant-pressure complete reactions, such an air-fuel ratio would cause an increase in temperature of about 600 K. [START_REF] Dahms | Understanding the ignition mechanism of high-pressure spray flames[END_REF] The discrepancy between that value and the observed 140 K can be explained by a higher fuel/air ratio in the impinging jet case than for a non-impinging jet or by non-complete reactions.

Injection pressure variation

Figure 7 shows the effect of varying the injection pressure. At higher injection pressure, the jet is faster and hence impinges sooner on the wall (delay between injection and heat flux start goes from 1.5 to 2.1 ms between 1500 and 500 bar of injection pressure). Heat flux is also higher: it peaks from 5.7 6 0.7 MW/m 2 at 1500 bar versus 4.0 6 0.4 MW/m 2 at 500 bar.

Jet speed and therefore entrained air turbulence increase as the injection pressure increases, and it is expected that this causes a significant change in the convection coefficient. Assuming that effect is the main reason for the heat flux increase observed in Figure 7 as injection pressure increases, the variation in gas temperature close to the sensor is neglected. Using the value of dT = 140K obtained above, convection coefficients can be computed for every injection pressure.

The results are shown in Figure 8. The convection coefficient increases by about 50% between the extremes of injection (from 500 to 1500 bar). The impingement speed of the jet can be estimated from the literature model used previously [START_REF] Desantes | A 1D model for the description of mixing-controlled reacting diesel sprays[END_REF] ; the velocity at 45 mm of the nozzle on the center line of a steady-state free (non-impinging) jet is 52 m/s at 500 bar and 94 m/s at 1500 bar, an increase by 80%.

Distance variation

The distance between the injector nozzle and the obstacle was varied between 45 and 80 mm (cf. Table 1). Figure 9 shows the results obtained measuring the Fit coefficient values are given with more digits than physically significant (uncertainty estimated to be 10%-15%). heat flux in those different conditions. When that distance is higher, jet impingement occurs later which explains the later arrival timing (up to 3.1 ms for the larger distance) and some jitter (flux peak arrival has 0.15 ms of standard deviation, leading to a slower slope in the averaged curve) for the larger distance d = 80 mm. A change in distance between the injector and the obstacle has two effects on the physics of the impingement process. On one hand, turbulence is lower further away from the nozzle, hence the convection coefficient is expected to be lower further downstream. On the other hand, higher mixing with fresh gases means the fuel/air ratio is lower, hence closer to stoichiometry, and gas temperature might be increased due to a higher release of energy by rich combustion reactions.

To deal with the gas temperature change, it can be assumed as a first-order approximation that the actual temperature increase dT for a given case of wall/injector distance is proportional to the temperature increase computed for a homogeneous, adiabatic, constant-pressure, complete reaction with the fuel/air ratio for a free jet. The reacting-jet model cited previously [START_REF] Payri | A study on diesel spray tip penetration and radial expansion under reacting conditions[END_REF] predicts equivalence ratios of u = 3.75 at 45 mm and u = 2.01 at 80 mm for a free jet. The actual temperature increase in the 45 mm case is known from the aforementioned analysis of ambient temperature variations.

The convection coefficient can then be recovered by a similar procedure as previously and are shown versus the obstacle impact velocity in Figure 10. The convection coefficient decreases when the wall/injector distance is increased, from 11.5 to 6.5 kW/m 2 /K.

The previously cited reactive spray model from the literature [START_REF] Desantes | A 1D model for the description of mixing-controlled reacting diesel sprays[END_REF] yields a velocity of 94 m/s at mm and 54 m/s at 80 mm of the nozzle (on the center line of a steady-state free jet). Spray velocity is very similar in the (1500 bar, 80 mm) case as in the (500 bar, 45 mm) case (54 vs 52 m/s); nonetheless, the convection coefficient is lower in the higher-distance case (6.5 vs 8 kW/ m 2 /K). Assuming that the estimation of the impingement velocity from a steady-state free jet model is roughly correct, this shows that the impingement velocity is not an adequate representation of the aerodynamic phenomena at hand. Indeed, the convection coefficient is driven by small-scale turbulence, whose intensity is not well correlated with that of large-scale advection motion.

Conclusion

Transient heat flux transfer by an impinging diesel jet was measured in the reference conditions of the ECN spray A, with variations in ambient gas temperature, injection pressure and distance between the injection and the obstacle it impinges on.

The high temporal resolution of the acquisition chain allows us to observe variations in the heat flux during the injection process. Reaching time resolutions better than the symbolic target of 1 °CA at 1200 r/min (0.15 ms) constitutes an improvement over previous studies of CI engines. It is nonetheless likely that the rise in heat flux is not fully resolved, and further improvements in temporal resolution would be desirable: data show rise times of about 0.3 ms, close to the temporal resolution.

Under simple assumptions of gas temperature next to the sensor location, convection coefficient values can be recovered and range from 6 to 12 kW/m 2 /K as the jet interacts with the wall. Values of heat flux peaks and associated convection coefficients are somewhat higher than previous studies for diesel jets, which can be attributed to sharper heat flux determination thanks to the better measurement resolution. Such values are also one order of magnitude higher than observed in SI engines, due to the high turbulence induced by spray injection.

In future work, simultaneous and near-wall gas temperature and flux measurements would remove the need for first-order interpretation hypotheses about nearwall gas temperature. Characterizing turbulence levels next to the wall under the same parametric variations would allow us to link microscopic turbulence processes to the macroscopically observed convection coefficient. Non-reactive jets might also be used in order to decouple induced turbulence effects and temperature effects.

Figure 1 .

 1 Figure 1. CV chamber with obstacle and thermocouple schematics.

Figure 2 .

 2 Figure 2. Result post-processing for reference case (T a = 850 K, P inj = 1500 bar, d = 45 mm). Left: heat flux traces for three typical repetitions of the experiment. Right: point-by-point average and standard deviation of all (N = 7) repetitions.

Figure 3 .

 3 Figure 3. Schlieren imaging of the combustion. Left: jet impingement at a distance of 45 mm. Right: radiation test: the obstacle and heat flux sensor are placed away from the jet, and there is no impingement.

Figure 4 .

 4 Figure 4. Heat flux for impinging and non-impinging case.

Figure 5 .

 5 Figure 5. Heat fluxes measured for three different ambient gas temperatures (P inj = 1500 bar, d = 45 mm in all cases).

Figure 6 .

 6 Figure 6. Flux versus temperature difference for the temperature variation.Experimental data show the peak of flux. Convection coefficient and increase in temperature are extracted from a weighted mean squares fit. Fit coefficient values are given with more digits than physically significant (uncertainty estimated to be 10%-15%).

Figure 7 .Figure 8 .

 78 Figure 7. Injection pressure variation (T a = 850 K, d = 45 mm in all cases).

Figure 9 .

 9 Figure 9. Nozzle-obstacle distance variation (T a = 850 K, P inj = 1500 bar in all cases).

Figure 10 .

 10 Figure 10. Convection coefficient variation with wall/injector distance.

Table 1 .

 1 Operating conditions through parametric variations.

		Ambient gas temperature T a , K	Injection pressure P inj , bar	Wall/injector distance d, mm
	Reference condition	850 6 10	1500 6 10	45 6 0.5
	Temperature variation	966 6 10	1500 6 10	45 6 0.5
		780 6 10	1500 6 10	45 6 0.5
	Injection pressure variation	850 6 10	1000 6 10	45 6 0.5
		850 6 10	500 6 10	45 6 0.5
	Distance variation	850 6 10	1500 6 10	60 6 0.5
		850 6 10	1500 6 10	80 6 0.5
	Gas composition and density before injection are always the same (15% O 2 + 75.2% N 2 + 6.2% CO 2 + 3.6% H 2 O, 23.5 6 0.3 kg/m 3 ).

Acknowledgements

The author(s) acknowledge the assistance of Cle´ment Bramoulle and Thomas Collazo for data collection.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.


Anne-Catherine Pierson-Wickmann
email: anne-catherine.pierson-wickmann@univ-rennes1.fr

Mélanie Davranche
email: melanie.davranche@univ-rennes1.fr

Julien Kerloc'h
email: j35.kerloch@gmail.com

Charlotte Catrouillet
email: charlotte.catrouillet@univ-rennes1.fr

Elaheh Lotfi-Kalahroodi
email: elaheh.lotfi-kalahroodi@protonmail.com

Malgorzata Grybos

Jesus Martinez-Frias

Monitoring the Organic Matter Quality Highlights the Ways in Which Organic Matter Is Removed from Wetland Soil

Keywords: wetland, redox fluctuations, carbon isotopic composition

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

Introduction

The organic matter (OM) cycle cannot be dissociated from that of Fe in different environmental systems such as soils, sediments, surface waters and permafrosts (in response to thawing), or peatlands and wetlands. Several studies have demonstrated that the stabilization of OM is related to the presence of ferric species [1][2][3]. More specifically in wetlands, ferric species enhance the biodecomposition of natural organic matter (NOM) by acting as terminal acceptor electrons during soil waterlogging periods. In contrast, in response to the water level decrease in wetland soils, in the presence of high amounts of OM, Fe(III) precipitates with DOM, forming aggregates of Fe and OM nanoparticles expected to stabilize OM [4]. Herndon et al. [START_REF] Herndon | Influence of iron redox cycling on organo-mineral associations in Arctic tundra soil[END_REF] showed that, by complexing low-molecular-weight OM, i.e., the most labile and bioavailable carbon, ferric species inhibit the microbial degradation of OM. Through 14 C analysis, Hall et al. [START_REF] Hall | Order from disorder: Do soil organic matter composition and turnover co-vary with iron phase crystallinity?[END_REF] demonstrated that the C residence time in humid soil is positively correlated with the crystallinity of the Fe(III) oxyhydroxides. Chen et al. [START_REF] Chen | Iron-mediated organic matter decomposition in humid soils can counteract protection[END_REF] also demonstrated that the alternation of redox conditions results in decreased C degradation and increased crystallinity of the ferric species. They suggest that repeated redox cycles induce the loss of dissolved organic matter (DOM), which is coprecipitated as Fe-OM aggregates, but that part of the DOM bound to Fe-minerals is preserved from the degradation involved via the reducing conditions. However, many of these processes depend on the variations in the quality and composition of the OM water during the redox cycles. Organic matter coating and binding processes with minerals depend on their binding sites, site density, molecular weight, and/or physicochemical structure (molecular vs. colloidal). However, in many studies dedicated to the impact of redox variations on OM degradation, DOM is considered whole and is only monitored by measuring the dissolved organic carbon (DOC) concentration. However, all of these processes are theoretically accompanied by transformations of the DOM quality and source variations.

Despite our understanding of the impact of the Fe cycle on DOM degradation or protection, few data are available on the variation in DOM quality within a redox cycle. The whole DOM quality and source variations can be specifically followed and studied using simple spectroscopic methods (UV-Vis absorbance, 3D fluorescence) and the C and N isotopic composition (δ 13 C and δ 15 N) [START_REF] Henneberry | Structural stability of coprecipitated natural organic matter and ferric iron under reducing conditions[END_REF][START_REF] Lambert | DOC sources and DOC transport pathways in a small headwater catchment as revealed by carbon isotope fluctuation during storm events[END_REF][START_REF] Riedel | Iron traps terrestrially derived dissolved organic matter at redox interfaces[END_REF]. For this purpose, we performed a series of successive reduction/oxidation incubations using natural wetland soil. The C and N isotopic compositions were measured over time and combined with measurements of the DOM quality evolution with time and redox-alternating conditions. Element solution chemistry and thermodynamic modeling approach were also used.

Materials and Methods

All of the chemicals used were of analytical grade. The solutions were prepared with deionized water (Milli-Q system, Millipore). The containers used were (i) soaked in 10% ultrapure HNO 3 for 48 h at 60 • C to remove all possible contaminant sources, (ii) soaked in and then rinsed with Milli-Q water for 24 h at 60 • C, and (iii) finally dried at 30 • C.

Soil Sampling and Soil Characteristics

The soil sample was collected in a riparian wetland, the so-called Mercy wetland, located in the Kervidy-Naizin catchment (Brittany, north-western France), belonging to the French network of long-term Environmental Research Observatories (ORE Agrhys). Numerous hydrological and biogeochemical studies [START_REF] Curmi | Hydromorphic soils, hydrology and water quality: Spatial distribution and functional modelling at different scales[END_REF][START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF][START_REF] Lambert | Hydrologically driven seasonal changes in the sources and production mechanisms of dissolved organic carbon in a small lowland catchment[END_REF][START_REF] Merot | Four-component hydrograph separation using isotopic and chemical determinations in an agricultural catchment in western France[END_REF] provided good information about the water sources and pathways throughout the hydrological periods.

The Mercy wetland regularly undergoes periodic fluctuations in the water level, leading to the establishment of redox cycles involving Fe [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF][START_REF] Lambert | Hydrologically driven seasonal changes in the sources and production mechanisms of dissolved organic carbon in a small lowland catchment[END_REF][START_REF] Pédrot | Interactions between natural organic matter, sulfur, arsenic and iron oxides in re-oxidation compounds within riparian wetlands: NanoSIMS and X-ray adsorption spectroscopy evidences[END_REF][START_REF] Dia | The distribution of rare earth elements in groundwaters: Assessing the role of source-rock composition, redox changes and colloidal particles[END_REF][START_REF] Gruau | Controls on the distribution of rare earth elements in shallow groundwaters[END_REF].

The soil sample corresponds to an aliquot of the upper organo-mineral horizon (Ah) from a Planosol (according to the WRB classification), developed on Proterozoic schists. This schist is mainly composed of quartz, muscovite, chlorite, K-Felspar, and plagioclase [18]. The soil horizons comprise a large number of secondary minerals, including illite, smectite, kaolinite, various Fe-oxyhydroxides, such as hematite and goethite, and Mn oxides [START_REF] Curmi | Hydromorphic soils, hydrology and water quality: Spatial distribution and functional modelling at different scales[END_REF].

The soil sample was collected in February 2013 during the water table rise. The soil was air-dried for five days and sieved to 2 mm [START_REF] Afnor | Evaluation De La Qualité des Sols. Méthodes D'analyse Chimique[END_REF].

Experimental Setup

The experimental procedure was based on a two-stage experiment using a soil suspension, settled under reducing and then under oxidizing conditions. The soil suspension was prepared at a 1:20 ratio of dry soil/solution by mixing 50 g of soil with a solution containing 30 mg L -1 of Cl -, 30 mg L -1 of NO 3 -, and 10 mg L -1 of SO 4 2-to mimic the anion composition of the soil solution in the Mercy wetland during the rise of the water table.

The suspension was placed in an air-tight, 1 L batch reactor (Guerin, Biolafite) at 30 • C (Figure A1 of Appendix A). Prior to the start of the experiment, the soil suspension was gently stirred under aerobic conditions for the first two days until the pH and DOC concentrations stabilized. The suspension was continuously and gently stirred, with a stream of N 2 continuously supplied via an autogas injection system at 2 L min -1 for the first 5 h and then at 0.2 L min -1 . The Eh and pH of the suspension were monitored with combination electrodes (405-DPAS-SC-K8S/225 Mettler Toledo (Greifensee, Switzerland) for the pH and Pt4805-DPAS-SC-K8S/225 Mettler Toledo (Greifensee, Switzerland) for the Eh). Approximately 30 mL of the soil suspension was drawn off daily with a sterile syringe (under N 2 gas in the anaerobic treatments), centrifuged for 10 min at 1950 g, and directly filtered through a 0.2 µm cellulose acetate membrane filter (Millipore, Burlington, MA, USA). The experiments were carried out in duplicate, and the errors bars reported in each figure represent the analysis standard errors. On the collected soil solutions, the DOC, Fe(II), cation, and anion concentrations were determined, as well as the SUVA and 3D fluorescence of the soil solutions and δ 13 C and δ 15 N values for both the soil solutions.

Analytical Procedures

Elemental Concentrations

After fusion of the whole-rock sample with LiBO 2 flux and acidic dissolution with HNO 3 , the major and trace element composition was determined at the CNRS Analytical Research Facility (SARM, CNRS, France) by ICP-OES and ICP-MS (Table A1 of Appendix B). The soil organic carbon content was determined using a carbon-sulfur analyzer (Leco SC144 DRPC) (Table A1). The soil sample contained 1.40 wt % of Fe and 6.64 wt % of organic carbon.

For the soil solutions, the major and trace element concentrations were determined using an Agilent Technologies HP 7100 inductively coupled plasma-mass spectrometry (ICP-MS) system in the Geosciences Laboratory at Rennes University (Rennes, France). Briefly, each soil solution was acid-digested two times with 14 N HNO 3 at 90 • C in a clean Savillex ® (Eden Prairie, MN, USA) digestion vessel and evaporated to complete dryness. In the case of a high DOC concentration, 20 drops of ultrapure hydrogen peroxide (H 2 O 2 , of ultrapure grade) were added to the samples in order to ensure the total oxidation of the organic matter, and then the vessel was closed and heated on a hot plate (80 • C) for 24 h. Afterwards, the solution was evaporated. The samples were then dissolved in 0.37 N HNO 3 and analyzed. International geostandard SLRS-4 (riverine water reference) was used to check the validity and reproducibility of the analyses. The typical rates of uncertainty (including all error sources) are <5% for all of the trace elements, whereas for major anions, the uncertainty lies between 2% and 5%, depending on the concentration levels.

The dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentrations of the soil solutions were analyzed with a Total Organic Carbon (TOC) analyzer (Shimadzu TOC-V-CSH). The accuracy of the DOC measurements was estimated at ±5% for all of the samples using a standard solution of potassium hydrogen phthalate. Ion chromatography measurements were performed on a Dionex DX-120 system. Respectively, the detection and quantification limits are 0.27 and 0.89 mg L -1 for NO 3 -, 0.32 and 1.06 mg L -1 for Cl -, and 0.38 and 1.25 mg L -1 for SO 4 2-, with an estimated accuracy of ±5%.

The concentrations of Fe(II) in the soil solutions were determined with the 1.10 phenanthroline colorimetric method (AFNOR NF T90-017 (AFNOR, 1997)) at 510 nm using a UV-Vis spectrophotometer (UVIKON XS, Bio-Tek Instruments, Saint Quentin Yvelines, France).

Stable Carbon and Nitrogen Isotopic Compositions

The carbon and nitrogen isotopic compositions of the soil solutions (δ 13 C solution , δ 15 N solution ) and soil (δ 13 C soil , δ 15 N soil ) values were determined at the Stable Isotope Laboratory of the PEGASE Joint Research Unit of the INRA in Saint-Gilles, France. Each soil solution aliquot was filtrated through a previously washed 0.2 µm acetate filter and then acidified by adding 1 mL of 1 N HCl to remove all traces of inorganic carbon. The solution samples were then frozen and freeze-dried before analysis. Each soil sample was also acidified by adding 1 N HCl and then rinsed with Milli-Q water in order to remove any trace of inorganic carbon. Each soil sample was frozen and freeze-dried before analysis.

The δ 13 C and δ 15 N of both soil and soil solutions were determined using an elemental analyzer (Vario Micro Cube, Elementar) interfaced with an isotope ratio mass spectrometer (IRMS) (VG Isoprime). Tin capsules were used for sample loading. The δ 13 C or δ 15 N values are expressed as relative to the international standard Vienna Pee Dee Belemnite (V-PDB) or atmospheric N 2 , as follows:

δ 13 C or δ 15 N (‰) = [(R sample /R standard ) -1] × 1000 (1)
where R standard and R sample are the ratios of 13 C/ 12 C or 15 N/ 14 N in the standard and sample.

International standards were also measured for the analysis period: (i) USGS 24 (δ 13 C = -16.0 ± 0.1‰ (n = 8)), (ii) ANU sucrose (δ 13 C = -10.5 ± 0.1‰ (n = 8)), (iii) Glutamine (δ 13 C = -14.5 ± 0.1‰; δ 15 N = 0.9 ± 0.1‰ (n = 8)), (iv) urea (δ 13 C -38.1 ± 0.1‰; δ 15 N = 0.0 ± 0.1‰ (n = 8)), and (v) Glutamic acid (δ 13 C = -27.6 ± 0.1‰; δ 15 N = 3.8 ± 0.1‰ (n = 8)). The accuracy of the measured δ 13 C values is better than ±0.2‰, based on repeated measurements of the samples and standards.

Spectroscopic Analyses

The dissolved organic matter was characterized using UV-Vis absorbance and fluorescence. The absorption spectra (UV-Vis) of the soil solutions were determined with a Perkin-Elmer Lambda 20 spectrophotometer in a 1 cm quartz cuvette, with a wavelength ranging from 200 to 600 nm with 0.5 nm increments. The specific UV absorbance measured at 254 nm (SUVA) characterizes the absorption in the mass units following this equation: SUVA (L mgC -1 m -1 ) = A 254 (m -1 )/[DOC] (mgC L -1 ). SUVA is often used as a proxy for DOM aromaticity (aromaticity = 6.52 SUVA + 3.63) [START_REF] Weishaar | Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and reactivity of dissolved organic carbon[END_REF]. The absorption properties measured at 280 and 287 nm are correlated with both the apparent molecular weight and aromaticity of the aquatic natural organic matter [START_REF] Chin | Molecular weight, polydispersity, and spectroscopic properties of aquatic humic substances[END_REF][START_REF] Leenheer | Characterizing aquatic dissolved organic matter[END_REF]. Distilled water was used as a blank. Possible interference due to Fe(III) absorbance at A 254 nm was taken into account (<5%) based on repeated measurements of the soil water extracts with variable levels of Fe(III) enrichment, and the SUVA values were corrected for the presence of iron.

All of the soil solutions were analyzed using a Perkin-Elmer LS 55 spectrofluorometer in a 10 mm quartz cuvette. The soil solutions were diluted with deionized water until A 254 was below 0.10 to minimize the inner filter effect [START_REF] Ohno | Fluorescence inner-filtering correction for determining the humification index of dissolved organic matter[END_REF] and were subsequently analyzed using a 3D-fluorescence excitation-emission matrix (3D-FEEM). The three-dimensional excitation-emission fluorescence spectra were obtained by collecting individual emission spectra (250-600 nm) over a range of excitation wavelengths (200-420 nm), with a 0.5 nm increment and a scan speed of 1500 nm min -1 , and then by merging the data together into a single three-dimensional data file. Instrument stability was determined using the Raman peak of deionized water excited at 350 nm, with the emission monitored at 395 nm as suggested by Lawaetz and Stedmon [START_REF] Lawaetz | Fluorescence intensity calibration using the Raman scatter peak of water[END_REF]. Raman scattering was mitigated by subtracting a blank EEM spectrum collected on deionized (18.2 MΩ) water from each corrected EEM. The FI, BIX, and HIX values were determined using data from the corrected EEM spectra.

Speciation Modeling

Modeling calculations were performed with PHREEQC/Model VI [START_REF] Marsac | An improved description of the interactions between rare earth elements and humic acids by modeling: PHREEQC-Model VI coupling[END_REF]. The model was used to calculate the speciation (saturation index, redox, sorption, etc.) in organic-rich solutions. This model assumes that the complexation of ions by humic substances occurs through eight discrete sites: four weak sites (carboxylic groups) and four strong sites (phenolic groups). The "minteq.v4" database was completed by both (i) the solubility constants of the reduced soil phases that were possibly encountered in this soil from [START_REF] Rickard | Chemistry of iron sulfides[END_REF], such as green rusts (GR1(Cl -) with log K = 28.3; GR2(SO 4 2-) with log K = 3.9) and hydroxylgreen rusts (hydroGR2 with log K = 25.4), and (ii) model VI specific binding parameters corresponding to the complexation of Ca, Mg, Al(III), Fe(II), and Fe(III) with the organic matter. Specific binding parameters for Ca and Mg are from Tipping [START_REF] Tipping | Humic ion-binding model VI: An improved description of the interactions of protons and metal ions with humic substances[END_REF], those for Al(III) and Fe(III) are from Marsac et al. [START_REF] Marsac | Aluminium competitive effect on rare earth elements binding to humic acid[END_REF], and those for Fe(II) are from Catrouillet et al. [START_REF] Catrouillet | Geochemical modeling of Fe(II) binding to humic and fulvic acids[END_REF].

The speciation was calculated from the chemical composition of the experimental soil solutions at each sampling point.

Results

Evolution of the Soil Solution Chemistry

The evolution of the elemental composition of the wetland soil with the anoxic and oxic periods is consistent with the establishment of reducing and oxidizing conditions [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF][START_REF] Ponnamperuma | The Chemistry of submerged soils[END_REF][START_REF] Thompson | Colloid mobilization during soil iron redox oscillations[END_REF][START_REF] Lotfi-Kalahroodi | Iron isotope fractionation in iron-organic matter associations: Experimental evidence using filtration and ultrafiltration[END_REF].

During the reducing period (0-497 h), pH increased from 6.3 ± 0.2 to 7.5 ± 0.3 in response to the consumption of H + by the reduction reactions. The Eh progressively decreased from 519 to -8.2 mV, reflecting the establishment of moderate reducing conditions (Figure 1a).

such as green rusts (GR1(Cl -) with log K = 28.3; GR2(SO4 2-) with log K = 3.9) and hydroxylgreen rusts (hydroGR2 with log K = 25.4), and (ii) model VI specific binding parameters corresponding to the complexation of Ca, Mg, Al(III), Fe(II), and Fe(III) with the organic matter. Specific binding parameters for Ca and Mg are from Tipping [START_REF] Tipping | Humic ion-binding model VI: An improved description of the interactions of protons and metal ions with humic substances[END_REF], those for Al(III) and Fe(III) are from Marsac et al. [START_REF] Marsac | Aluminium competitive effect on rare earth elements binding to humic acid[END_REF], and those for Fe(II) are from Catrouillet et al. [START_REF] Catrouillet | Geochemical modeling of Fe(II) binding to humic and fulvic acids[END_REF]. The speciation was calculated from the chemical composition of the experimental soil solutions at each sampling point.

Results

Evolution of the Soil Solution Chemistry

The evolution of the elemental composition of the wetland soil with the anoxic and oxic periods is consistent with the establishment of reducing and oxidizing conditions [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF][START_REF] Ponnamperuma | The Chemistry of submerged soils[END_REF][START_REF] Thompson | Colloid mobilization during soil iron redox oscillations[END_REF][START_REF] Lotfi-Kalahroodi | Iron isotope fractionation in iron-organic matter associations: Experimental evidence using filtration and ultrafiltration[END_REF].

During the reducing period (0-497 h), pH increased from 6.3 ± 0.2 to 7.5 ± 0.3 in response to the consumption of H + by the reduction reactions. The Eh progressively decreased from 519 to -8.2 mV, reflecting the establishment of moderate reducing conditions (Figure 1a). Iron(II) and acetate, a by-product of the consumption of OC by bacteria, were produced as soon as the solution was free of NO3 (< quantification limit 0.5 mg L -1 ) at t = 160-184 h (Figures 1b and2). The iron(II) and total Fe (Fetot) concentrations were similar, suggesting that the released Fe corresponded to Fe(II) (Figure 2). The maximum Fe(II) concentrations reached 14.4 ± 1.4 mg L -1 at t = 425 h, along with the maximum acetate concentration of 174.5 mg L -1 , which represented 49% of the produced DOC at the end of the reduction period. This indicates the onset of Fe-oxyhydroxides reductive biodissolution. Iron(II) and acetate, a by-product of the consumption of OC by bacteria, were produced as soon as the solution was free of NO 3 (< quantification limit 0.5 mg L -1 ) at t = 160-184 h (Figures 1b and2). The iron(II) and total Fe (Fe tot ) concentrations were similar, suggesting that the released Fe corresponded to Fe(II) (Figure 2). The maximum Fe(II) concentrations reached 14.4 ± 1.4 mg L -1 at t = 425 h, along with the maximum acetate concentration of 174.5 mg L -1 , which represented 49% of the produced DOC at the end of the reduction period. This indicates the onset of Fe-oxyhydroxides reductive biodissolution. Released Fe(II) mainly occurs as Fe(II)-organic complexes (90-100%), as shown by the modeling calculations (Figure 3). Released Fe(II) mainly occurs as Fe(II)-organic complexes (90-100%), as shown by the modeling calculations (Figure 3). In the early reduction period, the DOC concentration slowly increased from 80.1 ± 13.3 to 99.3 ± 2.8 mg L -1 after 39.5 h and reached 356.7 ± 33.3 mg L -1 , i.e., nearly 4.5 times the initial DOC concentration, at the end of the reduction period (Figure 1). The DIC concentrations also increased from 1.9 ± 0.2 to 24.9 ± 2.0 mg L -1 at the end of the reduction period, combined with the production of acetate. Note that the reduction experiment was performed under constant N2 flux preventing large CO2 solubilization.

During the oxidation (497-654 h), the pH rapidly decreased from 7.3 ± 0.2 to 5.4 ± 0.2 after 2 h of oxidation and then increased to 6.0 at the end of the oxidation. Meanwhile, the Eh rapidly increased from -8.2 to 300 mV after 2 h and then slowly to 362 mV (Figure 1a). Released Fe(II) mainly occurs as Fe(II)-organic complexes (90-100%), as shown by the modeling calculations (Figure 3). In the early reduction period, the DOC concentration slowly increased from 80.1 ± 13.3 to 99.3 ± 2.8 mg L -1 after 39.5 h and reached 356.7 ± 33.3 mg L -1 , i.e., nearly 4.5 times the initial DOC concentration, at the end of the reduction period (Figure 1). The DIC concentrations also increased from 1.9 ± 0.2 to 24.9 ± 2.0 mg L -1 at the end of the reduction period, combined with the production of acetate. Note that the reduction experiment was performed under constant N2 flux preventing large CO2 solubilization.

During the oxidation (497-654 h), the pH rapidly decreased from 7.3 ± 0.2 to 5.4 ± 0.2 after 2 h of oxidation and then increased to 6.0 at the end of the oxidation. Meanwhile, the Eh rapidly increased from -8.2 to 300 mV after 2 h and then slowly to 362 mV (Figure 1a). In the early reduction period, the DOC concentration slowly increased from 80.1 ± 13.3 to 99.3 ± 2.8 mg L -1 after 39.5 h and reached 356.7 ± 33.3 mg L -1 , i.e., nearly 4.5 times the initial DOC concentration, at the end of the reduction period (Figure 1). The DIC concentrations also increased from 1.9 ± 0.2 to 24.9 ± 2.0 mg L -1 at the end of the reduction period, combined with the production of acetate. Note that the reduction experiment was performed under constant N 2 flux preventing large CO 2 solubilization.

During the oxidation (497-654 h), the pH rapidly decreased from 7.3 ± 0.2 to 5.4 ± 0.2 after 2 h of oxidation and then increased to 6.0 at the end of the oxidation. Meanwhile, the Eh rapidly increased from -8.2 to 300 mV after 2 h and then slowly to 362 mV (Figure 1a). The dissolved organic carbon decreased from 356.7 ± 33.3 mg L -1 at the end of the reduction to 219.8 ± 2.5 mg L -1 in the early stage of the oxidation. Then, the DOC slightly increased to reach 230.4 ± 21.7 mg L -1 at this end of the oxidation period. Acetate was still present after 2 h, reaching 170 mg L -1 , and then it completely disappeared. The DIC also significantly decreased to approximately 2.0 mg L -1 ; this value is close to the one obtained at the beginning of the redox cycle. The abiotic oxidation of Fe(II) by O 2 also produces CO 2 [START_REF] Wood | Pathways for production of Fenton's reagent by wood-rotting fungi[END_REF][START_REF] Hammel | Reactive oxygen species as agents of wood decay by fungi[END_REF][START_REF] Hall | Iron oxidation stimulates organic matter decomposition in humid tropical forest soils[END_REF]; however, the venting of the reactor to produce oxic conditions involved significant CO 2 degassing. After this significant decrease, DIC progressively increased to reach 3.7 ± 0.4 mg L -1 at the end of the experiment. This concentration is approximately 100 times higher than the DIC concentration expected due to atmospheric CO 2 solubilization. This DIC concentration combined with the weak increase in DOC suggests a possible OM degradation. Iron(II) (from 15.4 ± 1.5 mg L -1 to 2.2 ± 0.4 mg L -1 ) and Fe tot (14.4 ± 1.4 mg L -1 to approximately 3.1 ± 0.2 mg L -1 ) decreased rapidly in response to the O 2 increase and subsequent Fe oxidation and precipitation (Figures 1b and2). However, both Fe(II) and Fe tot stabilized rapidly (since t = 19.5 h) at about 3.1 and 4.7 mg L -1 , respectively, indicating that approximately 65% of the dissolved Fe is present as Fe(II). Moreover, this final Fe(II) concentration remains larger than that at the beginning of the redox cycle.

PHREEQC-Model VI Modeling

PHREEQC-Model VI modeling was used to determine the Fe speciation and saturation indexes of the potential Fe(II)/Fe(III) newly formed minerals that could precipitate under reducing and oxidizing periods (Figure 3). The results showed that from 0 to 39.5 h, nearly 100% of the Fe in solution was present as Fe(III), as Fe(III)-organic complexes. From 39.6 to 160.5 h, roughly 7-10% of the Fe occurred as Fe(II) complexed to organic ligands (Figure 4). From 184.5 to 500 h, Fe(II)-organic complexes were the dominant Fe species in solution, even at the beginning of the oxidizing period. After 519.5 h, the Fe(II)-organic complexes were less present, down to 24.5% at the end of the experiment, while the Fe(III)-organic complexes represented the dominant Fe species. Both at the beginning of the reducing period and at the end of the oxidizing period, when Fe was mainly bound to DOM, the solution was saturated with respect to ferrihydrite (-0.5 < saturation index (SI) < +0.5).

Geosciences 2021, 11, x FOR PEER REVIEW 7 of 14

The dissolved organic carbon decreased from 356.7 ± 33.3 mg L -1 at the end of the reduction to 219.8 ± 2.5 mg L -1 in the early stage of the oxidation. Then, the DOC slightly increased to reach 230.4 ± 21.7 mg L -1 at this end of the oxidation period. Acetate was still present after 2 h, reaching 170 mg L -1 , and then it completely disappeared. The DIC also significantly decreased to approximately 2.0 mg L -1 ; this value is close to the one obtained at the beginning of the redox cycle. The abiotic oxidation of Fe(II) by O2 also produces CO2 [START_REF] Wood | Pathways for production of Fenton's reagent by wood-rotting fungi[END_REF][START_REF] Hammel | Reactive oxygen species as agents of wood decay by fungi[END_REF][START_REF] Hall | Iron oxidation stimulates organic matter decomposition in humid tropical forest soils[END_REF]; however, the venting of the reactor to produce oxic conditions involved significant CO2 degassing. After this significant decrease, DIC progressively increased to reach 3.7 ± 0.4 mg L -1 at the end of the experiment. This concentration is approximately 100 times higher than the DIC concentration expected due to atmospheric CO2 solubilization. This DIC concentration combined with the weak increase in DOC suggests a possible OM degradation. Iron(II) (from 15.4 ± 1.5 mg L -1 to 2.2 ± 0.4 mg L -1 ) and Fetot (14.4 ± 1.4 mg L -1 to approximately 3.1 ± 0.2 mg L -1 ) decreased rapidly in response to the O2 increase and subsequent Fe oxidation and precipitation (Figures 1b and2). However, both Fe(II) and Fetot stabilized rapidly (since t = 19.5 h) at about 3.1 and 4.7 mg L -1 , respectively, indicating that approximately 65% of the dissolved Fe is present as Fe(II). Moreover, this final Fe(II) concentration remains larger than that at the beginning of the redox cycle.

PHREEQC-Model VI Modeling

PHREEQC-Model VI modeling was used to determine the Fe speciation and saturation indexes of the potential Fe(II)/Fe(III) newly formed minerals that could precipitate under reducing and oxidizing periods (Figure 3). The results showed that from 0 to 39.5 h, nearly 100% of the Fe in solution was present as Fe(III), as Fe(III)-organic complexes. From 39.6 to 160.5 h, roughly 7-10% of the Fe occurred as Fe(II) complexed to organic ligands (Figure 4). From 184.5 to 500 h, Fe(II)-organic complexes were the dominant Fe species in solution, even at the beginning of the oxidizing period. After 519.5 h, the Fe(II)organic complexes were less present, down to 24.5% at the end of the experiment, while the Fe(III)-organic complexes represented the dominant Fe species. Both at the beginning of the reducing period and at the end of the oxidizing period, when Fe was mainly bound to DOM, the solution was saturated with respect to ferrihydrite (-0.5 < saturation index (SI) < +0.5).

Spectroscopic Properties of Bulk DOM

At the early stage of the reducing period, SUVA and HIX increased from 3.19 to 4.48 and from 56 to 77.7, respectively (Figure 5), suggesting that DOM was composed of aromatic molecules (humic-like DOM). Then, SUVA and HIX decreased continuously to reach 3.19 and 23, respectively, indicating a decreasing DOM aromaticity. reach 3.19 and 23, respectively, indicating a decreasing DOM aromaticity.

At the beginning of the oxidation, all of the fluorescence indices significantly decreased concomitantly with the DOC, DIC, acetate, and Fe concentrations in response to the precipitation of Fe as Fe(III)-OM nanoaggregates and their subsequent sedimentation [4,[START_REF] Riedel | Iron traps terrestrially derived dissolved organic matter at redox interfaces[END_REF][START_REF] Cismasu | Composition et propriétés structurales des ferrihydrites naturelles[END_REF][START_REF] Guénet | Highlighting the wide variability in arsenic speciation in wetlands: A new insight into the control of the behavior of arsenic[END_REF][START_REF] Keiluweit | Mineral protection of soil carbon counteracted by root exudates[END_REF]. However, BIX and FI rapidly increased to reach their highest values at 0.41 and 1.6, respectively, indicating that DOM was mainly constituted of microbial-derived DOM [START_REF] Gabor | Fluorescence indices and their interpretation[END_REF]. After 19.5 h of oxidation, BIX and FI decreased, whereas SUVA and HIX increased, which is consistent with the release of aromatic DOM in the solution. This release seems to dominate the DOM composition, since BIX and FI increased once again after 19.5 h, whereas SUVA and HIX remained constant.

Carbon Isotopic Composition of DOC during the Experiment

The δ 13 Csolution values displayed a narrow range, averaging -29.2 ± 0.2‰ (from -28.9 to -29.4‰) and -28.9 ± 0.1‰ during both the reduction and oxidation periods, respectively. These values are typical of C3 plants and in the same range as those already observed in both soil and soil solutions at the same site [START_REF] Lambert | Hydrologically driven seasonal changes in the sources and production mechanisms of dissolved organic carbon in a small lowland catchment[END_REF][START_REF] Lambert | Carbon isotopes as tracers of dissolved organic carbon sources and water pathways in headwater catchments[END_REF]. For information, the soil OM (SOM) remained constant all throughout the experiment, and within the same range as the soil solution, with a δ 13 Csoil of -29.2 ± 0.2‰. During the reduction period, between 39.5 and 63.5 h, even if the δ 13 Csolution range remains narrow, the small but significant variation indicates an enrichment in 12 C by 0.5‰ in the soil solution.

From 63.5 to 160.5 h, the δ 13 Csolution slowly increased (to -29.1‰) but never reached its initial value (Figure 6). This period corresponds to an increase in pH (from 6.9 to 7.2) and to the release of aromatic organic molecules in the solution, as indicated by the concomitant SUVA and DOC increase. However, here, this significant release does not entirely mask the signal of the 13 C-enriched microbial metabolites.

With regard to oxidation, δ 13 C increased from -29.4 to -28.8‰ and became enriched in 13 C. At the beginning of the oxidation, all of the fluorescence indices significantly decreased concomitantly with the DOC, DIC, acetate, and Fe concentrations in response to the precipitation of Fe as Fe(III)-OM nanoaggregates and their subsequent sedimentation [4,[START_REF] Riedel | Iron traps terrestrially derived dissolved organic matter at redox interfaces[END_REF][START_REF] Cismasu | Composition et propriétés structurales des ferrihydrites naturelles[END_REF][START_REF] Guénet | Highlighting the wide variability in arsenic speciation in wetlands: A new insight into the control of the behavior of arsenic[END_REF][START_REF] Keiluweit | Mineral protection of soil carbon counteracted by root exudates[END_REF]. However, BIX and FI rapidly increased to reach their highest values at 0.41 and 1.6, respectively, indicating that DOM was mainly constituted of microbial-derived DOM [START_REF] Gabor | Fluorescence indices and their interpretation[END_REF]. After 19.5 h of oxidation, BIX and FI decreased, whereas SUVA and HIX increased, which is consistent with the release of aromatic DOM in the solution. This release seems to dominate the DOM composition, since BIX and FI increased once again after 19.5 h, whereas SUVA and HIX remained constant.

Carbon Isotopic Composition of DOC during the Experiment

The δ 13 C solution values displayed a narrow range, averaging -29.2 ± 0.2‰ (from -28.9 to -29.4‰) and -28.9 ± 0.1‰ during both the reduction and oxidation periods, respectively. These values are typical of C3 plants and in the same range as those already observed in both soil and soil solutions at the same site [START_REF] Lambert | Hydrologically driven seasonal changes in the sources and production mechanisms of dissolved organic carbon in a small lowland catchment[END_REF][START_REF] Lambert | Carbon isotopes as tracers of dissolved organic carbon sources and water pathways in headwater catchments[END_REF]. For information, the soil OM (SOM) remained constant all throughout the experiment, and within the same range as the soil solution, with a δ 13 C soil of -29.2 ± 0.2‰. During the reduction period, between 39.5 and 63.5 h, even if the δ 13 C solution range remains narrow, the small but significant variation indicates an enrichment in 12 C by 0.5‰ in the soil solution.

From 63.5 to 160.5 h, the δ 13 C solution slowly increased (to -29.1‰) but never reached its initial value (Figure 6). This period corresponds to an increase in pH (from 6.9 to 7.2) and to the release of aromatic organic molecules in the solution, as indicated by the concomitant SUVA and DOC increase. However, here, this significant release does not entirely mask the signal of the 13 C-enriched microbial metabolites.

With regard to oxidation, δ 13 C increased from -29.4 to -28.8‰ and became enriched in 13 C.

During the first 100 h of the reducing period, the δ 15 N solution remained stable at close to 8‰, equivalent to the constant δ 15 N soil (+7.9 ± 0.2‰) and then regularly increased to reach 10‰. Under the oxidizing period, after a decrease of the initial value to 8‰, the δ 15 N solution increased once again to reach 10‰.

During the first 100 h of the reducing period, the δ 15 Nsolution remained stable at close to 8‰, equivalent to the constant δ 15 Nsoil (+7.9 ± 0.2‰) and then regularly increased to reach 10‰. Under the oxidizing period, after a decrease of the initial value to 8‰, the δ 15 Nsolution increased once again to reach 10‰.

Discussion

Evolution of the DOM Quality during the Redox Cycle

During the redox cycle, DOM is released through both anoxic and oxic mineralization mediated by microorganisms and desorption from soil components. Specifically during reduction, the DOM release was produced by the desorption of DOM from the soil in response to the increase of pH, as suggested by Grybos et al. [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF]. During the early stage of the reduction period, DOM was bound to Fe, as Fe(III), and then as Fe(II) when the reducing conditions were completely established (Figure 4). The DOC concentrations reached very high values (up to 352 mg L -1 ). In addition, the DIC release, associated with acetate production, and as highlighted by the evolution of the SUVA, HIX, BIX, and FI indices, indicating the production of nonaromatic organic molecules, suggests that OM was first solubilized as aromatic organic molecules and, in a second step, as nonaromatic metabolites such as acetate and other small organic molecules from OM degradation [START_REF] Lipson | Reduction of iron (III) and humic substances plays a major role in anaerobic respiration in an Arctic peat soil[END_REF][START_REF] Lovley | Availability of ferric iron for microbial reduction in bottom sediments of the freshwater tidal Potomac River[END_REF][START_REF] Roden | Kinetics of microbial Fe(III) oxide reduction in freshwater wetland sediments[END_REF]. This is also highlighted by the concomitant release of 13 C-enriched DOC from microbial metabolites. After 160.5 h, a small and significant decrease in δ 13 C, concomitant with the strong acetate increase and SUVA decrease, was consistent with the higher activity of the microorganisms.

When Fe(II) dominated as Fe(II) bound to DOC (Figure 3), its adsorption onto soil minerals or still-not dissolved Fe-oxyhydroxides and its subsequent precipitation as secondary minerals (such as siderite, magnetite, or green rust) were thus prevented [START_REF] Davranche | Organic matter control on the reactivity of Fe(III)-oxyhydroxides and associated As in wetland soils: A kinetic modeling study[END_REF]. All these results suggest that the increase in the DOC concentration in the solution was produced by both desorption from Fe-oxyhydroxides and OM mineralization. They are consistent with increasing microorganism metabolic activity that results in the production of metabolites in response to the biodissolution of reducing Fe-oxyhydroxides in the soil [START_REF] Dia | Bacteria-mediated reduction of As(V)-doped lepidocrocite in a flooded soil sample[END_REF]. This production of metabolites is also corroborated by the evolution of slowly decreasing BIX and increasing FI, suggesting the production and release of a low C/N ratio During the redox cycle, DOM is released through both anoxic and oxic mineralization mediated by microorganisms and desorption from soil components. Specifically during reduction, the DOM release was produced by the desorption of DOM from the soil in response to the increase of pH, as suggested by Grybos et al. [START_REF] Grybos | Is trace metal release in wetland soils controlled by organic matter mobility or Fe-oxyhydroxides reduction?[END_REF]. During the early stage of the reduction period, DOM was bound to Fe, as Fe(III), and then as Fe(II) when the reducing conditions were completely established (Figure 4). The DOC concentrations reached very high values (up to 352 mg L -1 ). In addition, the DIC release, associated with acetate production, and as highlighted by the evolution of the SUVA, HIX, BIX, and FI indices, indicating the production of nonaromatic organic molecules, suggests that OM was first solubilized as aromatic organic molecules and, in a second step, as nonaromatic metabolites such as acetate and other small organic molecules from OM degradation [START_REF] Lipson | Reduction of iron (III) and humic substances plays a major role in anaerobic respiration in an Arctic peat soil[END_REF][START_REF] Lovley | Availability of ferric iron for microbial reduction in bottom sediments of the freshwater tidal Potomac River[END_REF][START_REF] Roden | Kinetics of microbial Fe(III) oxide reduction in freshwater wetland sediments[END_REF]. This is also highlighted by the concomitant release of 13 C-enriched DOC from microbial metabolites. After 160.5 h, a small and significant decrease in δ 13 C, concomitant with the strong acetate increase and SUVA decrease, was consistent with the higher activity of the microorganisms.

When Fe(II) dominated as Fe(II) bound to DOC (Figure 3), its adsorption onto soil minerals or still-not dissolved Fe-oxyhydroxides and its subsequent precipitation as secondary minerals (such as siderite, magnetite, or green rust) were thus prevented [START_REF] Davranche | Organic matter control on the reactivity of Fe(III)-oxyhydroxides and associated As in wetland soils: A kinetic modeling study[END_REF]. All these results suggest that the increase in the DOC concentration in the solution was produced by both desorption from Fe-oxyhydroxides and OM mineralization. They are consistent with increasing microorganism metabolic activity that results in the production of metabolites in response to the biodissolution of reducing Fe-oxyhydroxides in the soil [START_REF] Dia | Bacteria-mediated reduction of As(V)-doped lepidocrocite in a flooded soil sample[END_REF]. This production of metabolites is also corroborated by the evolution of slowly decreasing BIX and increasing FI, suggesting the production and release of a low C/N ratio OM and indicating the production of DOM from microbiological activity [START_REF] Gabor | Fluorescence indices and their interpretation[END_REF]. This time period corresponds to the establishment of reducing conditions and therefore to the exponential growth of the microorganisms involved in the soil Fe-oxyhydroxides bioreduction, which preferentially consumed 12 C. However, the release of 12 C-enriched organic carbon, typical of the humic-like substances encountered in these soil solutions, as indicated by the high SUVA values [START_REF] Lambert | DOC sources and DOC transport pathways in a small headwater catchment as revealed by carbon isotope fluctuation during storm events[END_REF][START_REF] Lambert | Carbon isotopes as tracers of dissolved organic carbon sources and water pathways in headwater catchments[END_REF], seems to mask the 12 C consumption via the metabolic activity of the microorganisms.

During oxidation, when O 2 was reintroduced in the system, close to 70% of the DOC disappeared from the solution and Fe(II) was oxidized as Fe(III), hydrolyzed, and partially precipitated as newly formed amorphous nano ferric oxides with colloidal DOM as previously demonstrated by Guenet et al. [4,[START_REF] Guénet | Highlighting the wide variability in arsenic speciation in wetlands: A new insight into the control of the behavior of arsenic[END_REF] and Beauvois et al. [START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF] (Figure 4). This decrease in DOC results in an instantaneous decrease in all of the DOM quality indexes. After that, BIX and FI increased once again, thereby suggesting that fresh DOM was produced in response to the lysis of reducing bacterial cells, as also highlighted by the remaining DOM in the soil solutions enriched in 13 C relative to the reduced solution (+0.6‰), corresponding to released 13 C-enriched microbial DOM. The precipitation of Fe-oxyhydroxides seems to preferentially adsorb 12 C-enriched DOM following microbial cell lysis. The relative increase in δ 15 N solution observed during the reducing conditions followed by the oxidizing conditions can be explained either by the preferential gain of nitrogen enriched in 15 N or the loss of a fraction depleted in 15 N. In some bacterial cultures, the total proteins within a cell have been found to be enriched in 15 N relative to the bulk nitrogen [START_REF] Macko | Isotopic fractionation of nitrogen and carbon in the synthesis of amino acids by microorganisms[END_REF]. The increase in the δ 15 N values with the degradation of OM could partly reflect the selective gain in proteins. The activity of the microorganisms may modify the δ 15 N value through the consumption and fractionation of the soil N organic matter content but also via the increase in the bacterial biomass [START_REF] Lehmann | Preservation of organic matter and alteration of its carbon and nitrogen isotope composition during simulated and in situ early sedimentary diagenesis[END_REF][START_REF] Kohzu | Direct evidence for nitrogen isotope discrimination during sedimentation and early diagenesis in Lake Kasumigaura, Japan[END_REF].

After this first oxidative step, aromatic molecules were progressively released in the solution, concomitantly with a slight increase in Fe(III), indicating the abiotic oxidation/precipitation of Fe involves the precipitation/sedimentation of Fe-OM aggregates and the release of Fe-OM colloids. This release may be due to the continuous stirring of the suspension and the subsequent disaggregation of a part of the freshly formed Fe-OM aggregates. This disaggregation is also expected in natural systems in response to the establishment of the water flow. This release represents approximately 22% of the previously sedimented DOM. This result highlights the binding of Fe with the most aromatic molecules during its precipitation. Several studies have demonstrated that Fe nano-oxides are bound to DOM via inner spheres formed between Fe and C in bidentate complexes [4,[START_REF] Beauvois | How does calcium drive the structural organization of iron-organic matter aggregates? A multiscale investigation[END_REF][START_REF] Guénet | Characterization of iron-organic matter nano-aggregate networks through a combination of SAXS/SANS and XAS analyses: Impact on As binding[END_REF]. These complexes are preferentially formed with molecules that have high binding site densities such as aromatic humic molecules. However, a small part of Fe is maintained as Fe(II) due to its binding with DOM. These results may be explained by (i) the preferential retention of small nonaromatic organic molecules in the solution in response to the preferential binding of aromatic organic molecules with the newly formed Fe(III) nano-oxides [START_REF] Adhikari | Selective stabilization of aliphatic organic carbon by iron oxide[END_REF] or (ii) the production of small organic molecules due to the lysis of reducing bacterial cells under oxidizing conditions.

Impact on Soil OM Degradation and Preservation

In soil, the stabilization of OM through its binding to minerals has long been considered to prevent OM degradation by microorganisms [1,[START_REF] Mikutta | Stabilization of soil organic matter: Association with minerals or chemical recalcitrance?[END_REF][START_REF] Kögel-Knabner | Organo-mineral associations in temperate soils: Integrating biology, mineralogy, and organic matter chemistry[END_REF]. Generally, it is admitted that ferric oxyhydroxides preserve, via their binding, SOM from degradation. Several mechanisms have been evoked for the stabilization of OM by ferric species, such as the coprecipitation of DOM with ferric oxide particles or nano-oxides, sorption to highly crystallized Fe oxides, or inhibition of the consumption of labile C by microorganisms due to their binding to ferric species [START_REF] Eusterhues | Biodegradation of ferrihydrite-associated organic matter[END_REF].

In the present study, the evolution of the DOM quality relative to the redox conditions, combined with recent studies on the structure of the Fe-OM associations, shed new light on these hypotheses. Under reducing conditions, OM degradation occurs by producing and releasing CO 2 as well as metabolites in sufficient amounts that are able to modify the quality indexes of the terrestrial aromatic molecules. These organic molecules act as electron donors for a microbial consortium, as previously shown by Dia et al. [START_REF] Dia | Bacteria-mediated reduction of As(V)-doped lepidocrocite in a flooded soil sample[END_REF]. They are also bound to Fe as ferrous species. This strong binding allows the preservation of a significant amount of Fe(II) even under oxidizing conditions. Here, it may represent approximately 25% of the Fe(II) present under reducing conditions (Figure 2). When oxidizing conditions are established, the abiotic precipitation of Fe as Fe(III) nano-oxides involves the coprecipitation of DOM as Fe-OM aggregates, but also promotes the lysis of reducing bacterial cells as small nonaromatic molecules, as indicated by the evolution of the BIX and FI indexes. This lysis is supported by the release of 13 C-enriched DOM under oxidizing conditions. Therefore, it is fundamental to take into account the lysis of the bacterial cells involved by considering the alternating reducing and oxidizing conditions in temporarily waterlogged soils. As microorganisms grow at the expense of SOM, the cell lysis represents a second way of SOM degradation. Moreover, these results show that the newly formed Fe-OM aggregates are not stable with regard to the stirring constraints. As a result, the Fe(III)-OM aggregates produced under the oxidation period may be more unstable than expected. When there are enough physical constraints, e.g., in response to the water flux, to involve their disaggregation, smaller and more mobile Fe-OM aggregates are produced, involving the removal of DOM and all of the associated elements.

Conclusions

With the context of climate change likely being responsible for the increase in the frequency of soil flooding or drying, it is crucial to understand how nano-and microscale environmental conditions affect organomineral interactions and hence the stability of SOM [START_REF] Newcomb | Developing a molecular picture of soil organic matter-mineral interactions by quantifying organo-mineral binding[END_REF]. It has long been considered that the binding of DOM with ferric species preserves DOM from degradation by microorganisms. Soils that are temporarily waterlogged are perfect targets to study these processes since Fe is alternatively soluble and insoluble under high water level periods (reducing conditions) and low water level periods (oxidizing conditions), respectively. In this study, we tested the impact of a redox cycle on the solubilization of OM. Under reducing conditions, DOM is released from both OM mineralization and desorption from soil minerals in response to the increase in pH. These processes involve changes in the DOM quality from an aromatic OM corresponding to soil terrestrial material to less-aromatic OM due to the production of metabolites in response to the dissimilatory reductive dissolution of Fe-oxyhydroxides in the soil. When oxidizing conditions are re-established, the precipitation of aromatic OM with Fe and the lysis of reducing bacterial cells involve a release of nonaromatic and very labile organic molecules in the solution. This process is rapidly followed by the release of more aromatic OM in the solution. This secondary solubilization occurs in response to the disaggregation of the newly formed Fe-OM aggregates due to the physical constraints applied due to the stirring under our experimental conditions, but which can be compared to the physical constraints of the water flow under natural conditions. These results shed new light on the stabilization/preservation of OM by ferric phases; here, we demonstrate that bacterial cell lysis can be a significant way to solubilize OM from soil during the redox cycle and that the fresh Fe-OM aggregates formed under oxidizing conditions relative to the physical constraints to which they are submitted could release smaller entities that are rich in colloidal OM and able to disseminate in the environment.

Figure 1 .

 1 Figure 1. Temporal evolution of the (a) pH and Eh of the soil solutions; (b) nitrate, acetate, dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentrations (mg L -1 ) relative to time (in hours).

1 )Figure 1 .

 11 Figure 1. Temporal evolution of the (a) pH and Eh of the soil solutions; (b) nitrate, acetate, dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentrations (mg L -1 ) relative to time (in hours).

  iences 2021, 11, x FOR PEER REVIEW 6 of 14

Figure 2 .

 2 Figure 2. Temporal evolution of the DOC concentration and total Fe and Fe(II) concentrations (mg L -1 ).

Figure 3 .

 3 Figure 3. Fe speciation throughout the experiment.

Figure 2 .

 2 Figure 2. Temporal evolution of the DOC concentration and total Fe and Fe(II) concentrations (mg L -1 ).

Figure 2 .

 2 Figure 2. Temporal evolution of the DOC concentration and total Fe and Fe(II) concentrations (mg L -1 ).

Figure 3 .

 3 Figure 3. Fe speciation throughout the experiment.

Figure 3 .

 3 Figure 3. Fe speciation throughout the experiment.

Figure 4 .

 4 Figure 4. Saturation indices for the hydroxy green rusts: [Fe III 2Fe II (OH)8] and [Fe II Fe III (OH)5], goethite and ferrihydrite versus time for the incubation experiment modeled with PHREEQC/Model VI [25].

Figure 4 .

 4 Figure 4. Saturation indices for the hydroxy green rusts: [Fe III 2 Fe II (OH) 8 ] and [Fe II Fe III (OH) 5 ], goethite and ferrihydrite versus time for the incubation experiment modeled with PHREEQC/Model VI [25].

Figure 5 .

 5 Figure 5. Evolution of the fluorescence and UV indexes during and between the reducing and oxidizing periods.

Figure 5 .

 5 Figure 5. Evolution of the fluorescence and UV indexes during and between the reducing and oxidizing periods.

Figure 6 .

 6 Figure 6. Evolution of the δ 13 CDOC and δ 15 N variations both during and between the reducing and oxidizing periods in the soil solution.

Figure 6 .

 6 Figure 6. Evolution of the δ 13 C DOC and δ 15 N variations both during and between the reducing and oxidizing periods in the soil solution.

4 . Discussion 4 . 1 .

 441 Evolution of the DOM Quality during the Redox Cycle

Figure A1 .

 A1 Figure A1. Experimental setup for the soil experiment.Appendix B

Table A1 .

 A1 Chemical composition of soil sample.

	SiO 2 (wt. %)	Al 2 O 3 (wt. %)	Fe 2 O 3 (wt. %)	MnO (wt. %)	MgO (wt. %)	CaO (wt. %)	Na 2 O (wt. %)	K 2 O (wt. %)	TiO 2 (wt. %)	P 2 O 5 (wt. %)	PF (wt. %)	Total	Organic Car-bon (%)
	58.39	11.51	2.85	0.01	0.44	0.25	0.37	1.98	0.71	0.12	22.56	99.19	6.64
	As
	(ppm)

Cd (ppm) Co (ppm) Cr (ppm) Cu (ppm) Ni (ppm) Pb (ppm) Zn (ppm)

									U (ppm)	-	-	-	-
	7.64	7.65	4.80	74.88	10.51	21.26	25.13	40.96	2.34	-	-	-	-

Geosciences 2021, 11, 134. https://doi.org/10.3390/geosciences11030134 https://www.mdpi.com/journal/geosciences

Acknowledgments: We thank J.N. Thibault from PEGASE INRA unit for his assistance with C isotopic analyses. This research was partly funded by the CNRS-INSU Program EC2CO via the "PRO-DYNAMOS" project allocated to AC Pierson-Wickmann. Sara Mullin post-edited the English style.

Acknowledgments: We thank J.N. Thibault from PEGASE INRA unit for his assistance with C isotopic analyses. This research was partly funded by the CNRS-INSU Program EC2CO via the "PRO-DYNAMOS" project allocated to AC Pierson-Wickmann. Sara Mullin post-edited the English style.

Conflicts of Interest:

The authors declare no conflict of interest.