Guillaume Fumery

Hugo Mérienne

Vincent Fourcassié

Pierre Moretto
email: pierre.moretto@univ-tlse3.fr

Locomotor pattern and mechanical exchanges during collective load transport

Introduction

Load carriage is part of the routine of everyday life in humans and the effect of load carriage (load on top of the head: [START_REF] Heglund | Energysaving gait mechanics with head-supported loads[END_REF] on the shoulders: [START_REF] Castillo | Effects of pole compliance and step frequency on the biomechanics and economy of pole carrying during human walking[END_REF]; on the back: [START_REF] Ackerman | A model of human walking energetics with an elastically-suspended load[END_REF][START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF] on the locomotor behavior of single individuals is relatively well documented in the literature. However, humans are also endowed with the capacity to transport objects collectively and hitherto there are to our knowledge no studies on the biomechanics of individual locomotion during collective transport in humans. Our study fills this gap with an analysis of individual locomotor pattern and mechanical exchanges during a collective transport task. This task is part of our everyday life experience, e.g. when we move a heavy of voluminous object with the help of another person. It is also a task that is performed routinely by humans working in factories when they 2 have to move heavy loads together or in clinical environments when caretakers have to move a patient. Therefore, a better understanding of the biomechanics of collective load carriage could have potential applications in the field of ergonomics.

Finally, collective load carriage is one of the exercises regularly performed by athletes in sports. For example, the CrossFit program (i.e. CrossFit daily training or CrossFit events, [START_REF] Feito | A 4-year analysis of the incidence of injuries among CrossFit-trained participants[END_REF] needs to move loads by team regularly. [START_REF] Cavagna | External work in walking[END_REF][START_REF] Cavagna | Mechanical work basic mechanisms in terrestrial locomotion: two basic mechanisms for minimizing energy expenditure[END_REF] were the first to propose the inverted pendulum system (IPS) model to explain the economy of gait in humans. In this model the oscillations of the center of mass of the body (CoM) during stable walking in the sagittal plane is represented as a wave with constant amplitude and period [START_REF] Cavagna | Mechanical work basic mechanisms in terrestrial locomotion: two basic mechanisms for minimizing energy expenditure[END_REF][START_REF] Kuo | The six determinants of gait and the inverted pendulum analogy: A dynamic walking perspective[END_REF]. For an ideal pendulum this undulation can be represented by a sine wave as a function of time. It has been shown that the displacement of the CoM in humans is not an ideal sine function but is very close to it [START_REF] Saunders | The major determinant sin normal and pathological gait[END_REF][START_REF] Ackerman | A model of human walking energetics with an elastically-suspended load[END_REF]. The oscillations of the CoM allow the transfer of potential energy into kinetic energy and vice versa on each gait cycle, explaining the major part of the mechanical economy of walking [START_REF] Cavagna | The role of gravity in human walking: pendular energy exchange, external work and optimal speed[END_REF][START_REF] Lee | Determinants of the center of mass trajectory in human walking and running[END_REF]. Although there are also during walking some oscillations of the CoM in the frontal plane due to the movement of the pelvis [START_REF] Blickhan | Intelligence by mechanics[END_REF][START_REF] Kuo | Stabilization of lateral motion in passive dynamic walking[END_REF][START_REF] Mahaudens | Effects of short-term brace wearing on the pendulum-like mechanism of walking in healthy subjects[END_REF] and the stabilization of lateral motion [START_REF] Kuo | Stabilization of lateral motion in passive dynamic walking[END_REF], they actually contribute for a very weak part of the overall changes in mechanical energy [START_REF] Cavagna | External work in walking[END_REF][START_REF] Tesio | The 3-D motion of the centre of gravity of the human body during level walking. I. Normal subjects at low and intermediate walking speeds[END_REF]. The question we ask in this paper is whether individuals are able to walk as economically when they are transporting collectively an object as when they are walking alone and unloaded.

Representing the body by its CoM allows to understand a good part of the biomechanics of locomotion. However, it neglects some important information, namely the variations of kinetic energies at the level of each body segment. Yet, the study of the mechanical exchanges due to the body segments during collective carriage could complement the global analysis of the CoM and highlight the regulation of walking economy. High resolution 3D tracking and reconstruction techniques [START_REF] Tesio | The 3-D motion of the centre of gravity of the human body during level walking. I. Normal subjects at low and intermediate walking speeds[END_REF] allow to take this into account by using a Poly-Articulated Model (PAM) [START_REF] Moretto | Elastic energy in locomotion: spring mass vs. poly-articulated models[END_REF][START_REF] Zatsiorsky | The mass and inertia characteristics of the main segments of the human body[END_REF], i.e. a poly-articulated system of multiple rigid segments, where each segment i is characterized by a center of mass CoMi and a mass mi. In this paper, we used this method to test the general hypothesis that when two individuals are transporting an object collectively their locomotor pattern (i.e. amplitude and pendulum-like behavior of the CoM displacement) and their mechanical exchanges (i.e. percentage of energy recovered, internal, external and total works), are similar to that of an unloaded individual walking alone.

Materials & methods

Participants

Ten pairs of healthy male volunteers, whose characteristics are presented in The volunteers had no orthopedic disabilities, no dysfunctions of the locomotor system, no neurological or vestibular diseases, no visual deficits and no proprioceptive disorders or dementia. Informed consent was obtained from all participants. The research was non-invasive and respected a level of activity practiced daily by the individuals, in accordance with the definition of a noninterventional study given by the CNRS bioethical office.

Procedures

The volunteers were tested successively in two experimental conditions: one in which they walked by pairs but separately (condition Walking Separately: WS) and the other in which they walked with a box they carry together by two lateral handles (condition Collective Transport: CT). The mass of the box was 13.41 kg and its size was 0.40x0.40x0.28 m (Length x Width x Height). A single trial was performed in the WS condition and three trials in the CT condition (i.e. CT1, CT2, CT3). During each trial, the volunteers had to walk at spontaneous speed along a 13m-long walkway.

Data acquisition

Thirteen optoelectronic (11 MX3 and 2 TS40) video cameras (Vicon©, Oxford) were used to acquire the kinematic data. Forty-two markers were placed on bony landmarks and on the navel of each volunteer, according to [START_REF] Wu | ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion-part i: ankle, hip, and spine[END_REF][START_REF] Wu | ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion-part ii: shoulder, elbow, wrist and hand[END_REF]. Following [START_REF] Ackerman | A model of human walking energetics with an elastically-suspended load[END_REF], in order to compare the locomotor pattern of individuals walking loaded and unloaded, we analyzed the kinematic data of the two individuals and the load separately, i.e. we considered three separate systems.

The calibrated volume (30 m 3 ) was set in the middle of the walkway in order to record the walking patterns at a stable state walking (i.e. to exclude the acceleration and deceleration phases at the beginning and at the end of each trial). To allow the kinematic analysis, the volunteers and the box were reconstructed with the software Nexus© 1.8.5 (Fig. 1). ****Figure 1 (1)

The difference between the vertical displacement of the CoM and the adjusted sinusoidal function was assessed by the Root Mean Square Error (RMSE). The RMSE was normalized by the amplitude (RMSE/A), so that we only considered the error due to the alterations of the periodic signal.

External work:

We computed the kinetic and potential energies, as well as the external works on the antero-posterior, medio-lateral and vertical axis.

Wkf is the positive work to accelerate the CoM forwards, calculated as the sum of the increments of the forward kinetic energy (Ekf, computed on the anteroposterior axis) along the time curve with:

Ekf = m ! """# (t) 2 /R (2)
where m is the mass of the individual and ! """# (t)/R is the linear forward velocity of the CoM in the Galilean reference frame (R).

Wkh is the positive work to accelerate the CoM on the medio-lateral and antero-posterior axis, calculated as the sum of the increments of the horizontal kinetic energy (i.e. the medio-lateral kinetic energy Ekml, computed on the mediolateral axis, plus the forward kinetic energy Ekf,) along the time curve with:

Ekml = m $ """"""# (t) 2 /R
(3) where $ """"""# (t)/R is the linear medio-lateral velocity of the CoM in the Galilean reference frame (R).

Wv is the positive work to move the CoM against gravity, calculated as the sum of the increments of the vertical kinetic energy (Ekv, computed on the vertical axis) plus the potential energy (Epot, computed on the vertical axis) along the time curve with:

Ekv = m % """# (t) 2 /R (4)
and

Epot = mgh/R (5)
where % """# (t)/R is the linear vertical velocity of the CoM in R, g=9.81 m.s -2 the module of the acceleration vector due to gravity and h/R the vertical height of the CoM position in R.

Wext(sagittal) and Wext(3D) are the positive external work to raise and accelerate the CoM in the sagittal plane and in the three directions of the space (i.e.

mediolateral, anteroposterior and vertical axis), respectively. They are computed as the sum of the increments of the external mechanical energy (Eext(sagittal) and Eext(3D))

along the time curve [START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF][START_REF] Burdett | Comparison of mechanical work and metabolic energy consumption during normal gait[END_REF] with:

Eext(sagittal) = Epot + Ekv + Ekf (6) Eext(3D) = Eext(sagittal) + Ekml (7)
We also computed the energy recovered through the pendulum-like oscillations of the CoM (RR, called recovery rate in [START_REF] Fumery | Walking pattern efficiency during collective load transport[END_REF]. This metric has been proposed by [START_REF] Cavagna | Sources of external work in level walking and running[END_REF] as an indicator of the amount of energy transferred between the potential and the kinetic energy of the CoM due to its pendulum-like behavior: the closer the value of RR to 100%, the more consistent the locomotor pattern is with the IPS model [START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF][START_REF] Cavagna | External work in walking[END_REF][START_REF] Fumery | Walking pattern efficiency during collective load transport[END_REF][START_REF] Gomenuka | Adaptations to changing speed, load and gradient in human walking: Cost of transport, optimal speed, and pendulum[END_REF][START_REF] Willems | External, internal and total work in human locomotion[END_REF].

For the sake of comparison with the data of the literature, we first computed a value of the energy recovered for the sagittal plane only (RRs, Eq. 8) and then, since we had the positions of the markers in 3D, for the three dimensions of the space (RR3D, Eq. 9).

RRs

= 100 &'()&* &+ , -./011.2 &'()&* (8) RR3D = 100 &'3)&* &+ , 45 &'3)&* (9)
Here, we assumed that the friction forces at the joints and at the ground contacts can be neglected. In this condition, the system is submitted only to conservative forces and thus the variation of the external mechanical energy is null and the system is conservative. In this case, the system could have a 100% recovery and all potential energy would be converted into kinetic energy.

Internal work

In order to take into account the coordination between all body segments we determined the internal work by considering each individual as a poly-articulated system consisting of 16 segments.

Following the assumption of a conservative PAM, the internal work (Wint) was computed in 3D as the sum of the increments of the Eint,k along the time curve with:

Eint,k = ∑ 7 89 : 8 ; ""# (t) 2 /R* + mi< 8 ² × = " "# 8 ²/ R*) ( 10
)
where mi is the mass of the i th segment, ; ""# (t)/R* the linear velocity of this i th segment CoM in the barycentric reference frame (R*, Fig. 1), Ki the radius of gyration around this i th segment CoM and = " "# 8 ²/R* its angular velocity in the R* reference frame [START_REF] Duboy | Mécanique humaine[END_REF].

Total work

The total mechanical energy of the PAM (Etot) was computed as follows in 3D in the R reference frame [START_REF] Leboeuf | Construction et illustration des différentes formulations biomécaniques du coût énergétique d'un geste sportif[END_REF][START_REF] Moretto | Elastic energy in locomotion: spring mass vs. poly-articulated models[END_REF].

Etot = Epot + Ekv + Ekf + Ekml + Eint,k (11)
Finally, since the cycle duration was longer in the CT than in the WS condition, in order to compare the two conditions we assessed the quantity of energy expanded by the volunteers and we normalized it per unit of distance. Each work (internal, external and total) was thus divided by the distance walked by the volunteers during one gait cycle.

Data analysis

The data were analyzed with Matlab R2016b© and R 3.4.3©. After checking for normality, a paired Student t-test was used to compare the parameters assessed in the WS condition and in the first trial of the CT condition. The changes in the three successive trials in the CT conditions (CT1, CT2 and CT3) were tested with a linear mixed model (GLMM) with trial number entered as a fixed factor and volunteer identity as a random variable. The threshold of statistical significance was set at 0.05.

Results

Center of Mass trajectory

The CoM velocity (mean±s.d.) was 1.25±0.12 m.s -1 in the WS condition and 1.28±0.17, 1.36±0.13 and 1.40±0.14 m.s -1 (CT1, CT2 and CT3 respectively) in the CT condition. There was no significant difference between WS and CT1 (Student and CT3 (t=-2.61, p=0.01). No significant difference in the RMSE was found between CT1 and CT3 (t=0.87, p=0.39).

Inverted Pendulum System

The energy recovered in the sagittal plane (RRs: Fig. 3C) increased from 58.74% in WS to 65.95% in CT1 (Student t test: t=2.44, p=0.02). However, there was no significant difference between the three trials in the CT condition (GLMM:

F2,40=1.99, p=0.15).

The energy recovered in 3D (RR3D: Fig. 3D) also increased and raised from 58.45% in WS to 65.91% in CT1 (Student t test: t=2.50, p=0.02). In the same way as the RRs, there was no significant difference in the RR3D between the three trials in the CT condition (GLMM: F2,40=1.83, p=0.17).

Total mechanical

Discussion

The aim of our study was to test the hypothesis that the locomotor pattern of an individual walking while carrying a load with another individual remains as pendular and economical as when he is walking alone. This hypothesis was tested by using the IPS model associated with a PAM to assess the economy of the locomotor pattern. The IPS represents the ideal situation of a pendulum displacement of the CoM and is considered as a model of energy saving during walking [START_REF] Donelan | Simultaneous positive and negative external mechanical work in human walking[END_REF]. The PAM allowed us to compute the position of the CoM and to take into account the internal work [START_REF] Moretto | Elastic energy in locomotion: spring mass vs. poly-articulated models[END_REF][START_REF] Zatsiorsky | The mass and inertia characteristics of the main segments of the human body[END_REF]). To our knowledge, it is the first time that the economy of gait during collective load carriage in humans is investigated. Our work explores first the immediate adaptation of the individuals to load transport (WS vs CT1), then the adaptation to the task due to its repetition (CT1, CT2 and CT3).

When the RMSE and the amplitude of the vertical displacement of the CoM were compared between WS and CT1, no significant differences were found. The vertical displacement of the CoM of the individuals as a function of time in the two conditions thus followed the same sinusoidal pattern. These results are consistent with those of [START_REF] Holt | Increased musculoskeletal stiffness during load carriage at increasing walking speeds maintains constant vertical excursion of the body center of mass[END_REF] who found no significant difference in the amplitude of the CoM displacement for isolated individuals walking loaded (wearing a backpack) or unloaded.

To assess the consistency of the walking pattern with the IPS model, we computed the energy recovered according to [START_REF] Cavagna | Mechanical work basic mechanisms in terrestrial locomotion: two basic mechanisms for minimizing energy expenditure[END_REF], i.e. in the sagittal plane only, and the energy recovered in the three dimensions of the space, RR3D, to take into account the fact that the potential energy can be transferred in forward as well as in transverse kinetic energy.

The value of RRs we found in the WS condition (59%) is close to that found by [START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF] in unloaded Nepalese porters and untrained individuals, i.e.

61% for individuals walking at 1.4 m.s -1 . Because the value of RRs increases in the CT condition compared to the trial in the WS condition, one can say that the walking pattern of the individuals was closer to a pendulum-like behavior when they were performing the collective load transport task than when they were walking separately. This result can be compared to that found by [START_REF] Heglund | Energysaving gait mechanics with head-supported loads[END_REF] in African women of the Luo tribe carrying loads on top of their heads. These authors found a RRs of 65% for unloaded women and a RRs of 68% for women carrying a load representing 10% of their body-mass (BM).

The values of RR3D we found are very close to that found for RRs. Thus, one can conclude that the pendular behavior of the CoM is low in the frontal plane. Since this is observed in both the WS and CT conditions, one can assume that the walking pattern is not disturbed by the collective transport task, despite the physical link established between the two individuals. Finally, one should note that both RRs and RR3D increase between WS and CT1, suggesting an adjustment of the individuals to the load carriage task. Thus, it seems that the additional efforts linked to the coordination between individuals in the frontal plane do not disturb the energy recovered by each individual.

When the individuals are considered as a poly-articulated system and the contribution of each body segment can be assessed, the total mechanical work can be computed. Our results show that the mechanical work (whether internal, external or total) did not change in CT1 compared to WS. Although [START_REF] Heglund | Energysaving gait mechanics with head-supported loads[END_REF] calculated mechanical work only in the sagittal plane, the values they found are comparable to ours for African women carrying loads of up to 20% of their body mass on top of their head. Our results are also close to those of [START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF] on individual Nepalese porters in which the changes in mechanical energy due to the lateral movements of the CoM were also neglected. In agreement with our findings these authors found that for individuals walking at a speed of 1.1 m.s -1 the massspecific total work is independent of the load carried, although it decreases with increasing loads for higher speeds (Wext is stable but Wint decreases) [START_REF] Bastien | The mechanics of head-supported load carriage by Nepalese porters[END_REF].

When comparing the three successive trials in the CT condition we observed an increase in the speed of the CoM, which could be considered a result of immediate adaptation to the collective task. Indeed, this could correspond to a better motor control of the task, i.e. for the same economy in mechanical output, individuals performed the carriage task faster during the first ones trials of collective carriage. As in [START_REF] Holt | Increased musculoskeletal stiffness during load carriage at increasing walking speeds maintains constant vertical excursion of the body center of mass[END_REF], this increase was accompanied by an increase of the CoM amplitude. There was also a trend to increase for both the RRs and RR3D (Fig. 3). The movements of the lower limbs could contribute to increase the pendulum like behavior of the overall CoM, and thus lead to a higher economy level.

Our study shows that the displacement of the CoM of an individual during the collective transport of an object follows the same sinusoidal pattern as that of an individual walking alone and unloaded. Moreover, during collective transport the pendular behavior of the CoM of the individuals increases, so that their locomotor pattern was more consistent with the IPS model. In parallel, we noted an increase in the speed and in the CoM amplitude during successive trials, which seems an immediate adaptation to the collective transport situation. It could be also interesting to complete this analyze with more trials, to observe a possible effect of training.

Finally, when the external and internal work are considered in 3D, we found that, despite the physical link between individuals, the total mechanical cost of locomotion did not change when walking alone and when walking while transporting an object with another individual. Our results are in accordance with the literature on load transport by single individuals and demonstrate the stability and economy of the locomotor pattern during load transport in general. As a caveat however, one should note that the object carried by the individuals in our experiment was relatively light and that one does not know whether the same results would be observed with heavier objects. In addition, a study of the metabolic cost and efficiency [START_REF] Minetti | Himalayan porter's specialization: Metabolic power, economy, efficiency and skill[END_REF] associated with collective load carriage could be helpful to complement the mechanical analysis presented here.

Today, carriage tasks are increasingly appearing as training exercises to improve physical capacities, e.g. in CrossFit training by team. Our study provides a better understanding of the effects of collective load carriage between two humans on locomotion and could be useful for improving the design of this type of training exercises. Our results could also be used for the conception of robots especially designed to assist humans (Cobot) in achieving difficult and strenuous tasks. The sampling frequency was set at 200 Hz (filtered by a 4 th order Butterworth filter and a 5 Hz cut frequency). The precision of the optoelectronic system was 1 mm for 1 m. The points correspond to the locations of the markers placed on the body according to De Leva's model [START_REF] De Leva | Adjustments to Zatsiorsky-Seluyanov's segment inertia parameters[END_REF]. The R* referential (segments coordinate system) is represented in blue and the R referential (external coordinate system) in purple. The left side of the body is represented in red, the right side in green, the head, trunk and pelvis in orange and the box in yellow.

  near here**** 2.4. Computed parameters 2.4.1. Inverted Pendulum System and external work The Inverted Pendulum System (IPS) model allows us to evaluate the pendulum-like behavior of the CoM of each volunteer in the WS and CT conditions. The De Leva's anthropometric tables (1996) allowed us to estimate the mass, the center of mass position CoMi and the radius of gyration of each segment. The global CoM of each volunteer was then computed from the CoMi of their segments. Sine wave: To record at least one gait cycle for each individual, a walking cycle was defined as the interval between two heel strikes of the same leg. One gait cycle thus consisted of two steps. Following Ackerman et al. (2014), we modeled the vertical motion of the CoM along time in the sagittal plane as a sine function. The amplitude (A = ; in meter), angular frequency (ω = in rad.s -1 , with T the period) and phase shift ( = * in radian, with τ the time shift) of the vertical displacement of the CoM allowed us to determine the function (see Castillo et al. 2014): t = sin ωt +

  t test: t=-1.15, p=0.26). However, the CoM velocity was significantly different between the three trials in the CT condition (GLMM: F2,40=29.27, p<0.01). It increased by 6.25% between CT1 and CT2 (t=5.03, p<0.01), by 9.38% between CT1 and CT3 (t=7.51, p<0.01) and by 2.94% between CT2 and CT3 (t=2.47, p=0.02). ****Figure 2 near here**** Whether in the WS or CT condition, the vertical displacement of the CoM of the two individuals was sinusoidal (Fig. 2). ****Figure 3 near here****The amplitude of the CoM increased by 9.12% between the trial in the WS condition and the first trial in the CT condition (Fig.3A, Student t test: t=2.07, p=0.05). Overall there was a significant increase of the amplitude of the CoM over the three trials in the CT condition (GLMM: F2,40=4.20, p=0.02). The amplitude increased by 9.16% between CT1 and CT2 (t=2.82, p<0.01), but did not differ significantly between CT1 and CT3 (t=1.99, p=0.05), and CT2 and CT3 (t =-0.83, p=0.41).The RMSE was not significantly different between the trial in the WS condition and the first trial in the CT condition (Fig.3B, Student t test: t=-0.43, p=0.67). However, it was significantly different between the three trials in the CT condition (GLMM: F2,40=6.57, p<0.01). The RMSE first increased by 63.5% between CT1 and CT2 (t=3.48, p<0.01) and then decreased by 29.2% between CT2

  work ****Figure 4 near here**** The internal, external and total mechanical work, computed for the two polyarticulated systems, were not different between WS and CT1 (Fig. 4, Student t test:t=-1.81, t=1.09 and t=0.42 for Wint, Wext and WmecaTot, respectively, p>0.05 in all cases). Overall, there was also no significant difference between the three trials in the CT condition for Wint (GLMM: F1,40=1.07, p=0.31), Wext (GLMM: F1,60=0.24, p=0.63), and WTot (GLMM: F1,40=0.01, p=0.91).

Figure 1 :

 1 Figure 1: Example of a reconstruction of the participants and the box they carry on Nexus.

Figure 2 :

 2 Figure 2: (A) Example of the vertical displacement of the CoM over a walking cycle for a pair of participants carrying a box of 13.41 kg while walking at a speed of 1.29 m.s -1 . The continuous

Figure 3 :

 3 Figure 3: Mean ± s.d. of (A) the amplitude of the vertical displacement of the CoM, (B) of the

Figure 4 :

 4 Figure 4: Mean ± s.d. of the total, internal and external mechanical work divided by the distance

Table 1 ,

 1 took part in the experiment.

	****Table 1 near here****

Table 1 :

 1 Characteristics of the subjects: mean (standard deviation).

		Age (yr)	Size (m)	Mass (kg)
	Subject 1 (S1)	25.40 (4.72)	1.77 (0.07)	74.78 (9.00)
	Subject 2 (S2)	25.30 (2.71)	1.77 (0.05)	74.54 (12.38)

Acknowledgements

Financial support was provided by the ANRT (CIFRE 2015/1321) and the MAS Marquiol for G.F. PhD grant.

The authors do not have to disclose any financial or personal relationships with other people or organizations that could inappropriately influence (bias) their work.

Conflict of interest


Khaoula Hamdi

Patrick Martin

Mathieu Etienne

Marc Hébrant

Rapid and reversible adsorption of BTX on mesoporous silica thin films for their real time spectrophotometric detection in air at ppm levels

Keywords: VOC, benzene, toluene, xylene, BTX, mesoporous silica, UV absorption

Benzene, toluene and xylenes (BTX) are among the most toxic volatile organic compounds that can be emitted into the environment of different workplaces. Regulations to protect workers continue to strengthen permissible exposure limit (PEL), and short-term exposure limit (STEL) for any 15-minutes period are defined for BTX that should be controlled with rapid, selective and sensitive on-site sensors. For that purpose, a real-time analysis of BTX is described here, using the UV spectrometric determination of instantaneously concentrated pollutants in a thin film of mesoporous and transparent silica deposited onto quartz plates. A new optical cell has been designed to achieve the lowest detection limits, up to the ppm level in air for benzene, toluene and p-xylene. The sensor was equipped with an air dryer to detect BTX in the presence of humidity and major interfering volatile organic compounds (acetone, ethanol, butanone and cyclohexane). The sensor has detection limits below defined PEL and STEL for benzene, toluene and xylenes. The adsorption properties of BTX on the sensor surface were quantitatively analyzed using the Freundlich equation, showing the singular behavior of benzene adsorption on the surface of silica relative to toluene and p-xylene.

Introduction

Benzene, toluene and xylenes (BTX) are among the most toxic volatile organic compounds (VOCs) that are widely found in industrial environments. A large number of manufacturing processes and uses involving petrol and fuels, varnishes, paints, rubber, solvents, chemicals can be sources of these volatile compounds. The first regulation dealing with work places air quality appeared more than three decades ago. Nowadays, the legislation defined permissible exposure limit (PEL) and short-term exposure limit (STEL) for benzene, toluene and xylenes (see Table S1, the limits defined by the Occupational Safety & Health Administration -USA and European Union).

STEL imposes a rapid detection whereas the low permissive levels at long time exposure impose a sensitive detection (down to 1 part per million of air for benzene). Methods and techniques allowing detection at very low levels are described in the literature, most of them are based on active or passive adsorption/pre-concentration on sorbent material followed by thermal or solvent desorption and chromatographic analysis [START_REF] Kim | Ultimate detectability of volatile organic compounds: How much further can we reduce their ambient air sample volumes for analysis?[END_REF][START_REF] Wang | Automated gas chromatography with cryogenic/sorbent trap for the measurement of volatile organic compounds in the atmosphere[END_REF][START_REF] Zhang | Determination of BTEX Compounds in Solid-Liquid Mixing Paint Using the Combination of Solid Phase Extraction, Thermal Desorption and GC-FID[END_REF]. In most cases, the analysis is not taking place in situ and the delays necessary to deliver the results are typically ranging from a couple of hours to days, even when short sampling times are used.

The development of portable devices allowing on-site detection is thus the subject of many studies. Sensors based on metal oxides semiconductor properties variation during adsorption of BTX gave rise to recent works [START_REF] Dutta | An efficient BTX sensor based on p-type nanoporous titania thin films[END_REF][START_REF] Acharyya | An efficient BTX sensor based on ZnO nanoflowers grown by CBD method[END_REF]. Semiconductor sensor based on Cr-doped NiO hierarchical nanostructures [START_REF] Kim | Ultraselective and sensitive detection of xylene and toluene for monitoring indoor air pollution using Crdoped NiO hierarchical nanostructures[END_REF] allowed to detect 5 ppm xylenes or toluene without significant cross response of 5ppm benzene, formaldehyde, ethanol, hydrogen, and carbon monoxide, respectively. However, the detection of benzene in the presence of other aromatic molecules is not shown. Quartz crystal microbalance (QCM) sensors based on adsorption on pentacene was recently proposed to reach the sensitivity criteria and to allow to distinguish the responses of the separated analytes [START_REF] Bearzotti | A study of a QCM sensor based on pentacene for the detection of BTX vapors in air[END_REF]. Functionalized SBA-15 mesoporous silica functionalized with 4,4′-diaminodiphenyl sulfone-based was deposited on a QCM sensor, allowing the detection of toluene down to 20 ppb [START_REF] Qian | 4,4′-Diaminodiphenyl sulfone functionalized SBA-15: Toluene sensing properties and improved proton conductivity[END_REF]. Cavitand molecules were also designed as selective adsorbent and were implemented in a micro-electro-mechanical system (MEMS) coupled to a photoionization detector (PID) detection. It allowed very sensitive detection in a short time but no selectivity was experimentally demonstrated [START_REF] Trzciński | In search of the ultimate benzene sensor: The EtQxBox solution[END_REF]. Differential ion mobility spectrometry (DMS) is also capable of detecting very low amounts of BTX, pattern recognition for benzene, toluene or xylene in filtered air containing various amount of water vapor have been recently published [START_REF] Maziejuk | Determination of benzene, toluene and xylene concentration in humid air using differential ion mobility spectrometry and partial least squares regression[END_REF][START_REF] Szczurek | BTX compounds recognition in humid air using differential ion mobility spectrometry combined with a classifier[END_REF]. Excellent sensitivities are often demonstrated, but the efficiency in the presence of humid air is often diminished and the selectivity of the detection of BTX in the presence of other pollutants is not always demonstrated. Moreover the ability to determine one of the BTX in the presence of another BTX is not reported.

The experimental strategy we adopted to reach sensitivity, selectivity and reversibility is to concentrate the pollutant by adsorption on a transparent solid and to detect it simultaneously by in situ UV spectrometric determination (i.e., there is no desorption step). The principle of such experiment has been described before [START_REF] Lamotte | Direct optical spectroscopic detection and analysis of organic micro-pollutants adsorbed on solid phases. Performances and perspectives[END_REF] and was initially developed for BTX detection using a transparent mesoporous silica monolith (∼2 mm thick) as sorbent. This approach allowed the detection of very low BTX concentrations, however, the pollutant adsorption was found to be non-reversible over a short time scale (less than 3 minutes), making this approach unsuitable for real time sensing [START_REF] Calvo-Muñoz | Chemical sensors of monocyclic aromatic hydrocarbons based on sol-gel materials: kinetics of trapping of the pollutants and sensitivity of the sensor[END_REF]. A reversible detection of BTX was later reported, using mesoporous silica thin disks displaying bigger pores [START_REF] Tran-Thi | Optical chemical sensors based on hybrid organic-inorganic sol-gel nanoreactors[END_REF]. In a previous study, we considered films made of mesoporous silica nanoparticles [START_REF] Hamdi | Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes)[END_REF]. The low thickness, less than 4 µm, and the high inter and intra-particle porosities of the film allowed to obtain rapid responses and the sensor was regenerated in less than 30 s. Cyclohexane had no effect on the BTX detection while polar organic molecules (ethanol, butanone, and acetone) increased the signal. Removing humidity using an air drier was shown to allow the detection of toluene in air initially humid.

The aim of the present report is to demonstrate that real time analysis can be achieved with this approach (preconcentration in porous silica and UV spectrometric determination), even in the presence of interfering pollutants, and to estimate the detection limits that can be achieved. We have considered mesoporous silica thin film (150-250 nm thickness) deposited on quartz plates to concentrate instantaneously and reversibly the BTX molecules. A new optical cell was designed and built in order to improve the sensitivity of the sensor.

Adsorption properties of BTX in the mesoporous silica were analyzed quantitatively.

Experimental section

Chemicals

Tetraethoxysilane (TEOS, 98%), cetyltrimethylammonium bromide (CTAB ≥98%), hydrogen chloride (37%), anhydrous pure toluene (99.8%), benzene (99.8%), p-xylene(99%), cyclohexane (99.5%), butanone (≥99%), anhydrous ethanol (≥99.8%) and acetone (≥99.9%) have been used as received from Sigma Aldrich-France.

Thin film elaboration

The experimental protocol to obtain the thin films is based on a previously reported protocol from Grosso et al [START_REF] Etienne | Molecular transport into mesostructured silica thin films: Electrochemical monitoring and comparison between p6m , P63/mmc , and Pm3n structures[END_REF]. Briefly a sol is prepared by mixing TEOS:CTAB:ETOH:H2O:HCl (mol to mol ratio 1:0.14:20:5:0.004, respectively) and allowed to age for 4 days under stirring.

The resulting sol has been dip-coated on 8x9x1 mm quartz plates with 2 mm s -1 withdrawal speed maintaining the relative ambient humidity at 50%. Quartz plates have been cleaned with ethanol and treated with sodium hydroxide and dried at 130°C prior the deposition.

Curing for 2 days at 130°C is followed by a calcination for 4 hours at 450°C. The film was characterized by TEM (Figure S1) which revealed a well-defined mesostructure. The film thickness determined by profilometry was between 150-250 nm. 78-90% of transmittance was observed for one modified plate (i.e., two films, one on each side, Figure S2, curve b) in the wavelength range 190-400 nm and more than 15% in the same wavelength range for 5 plates (i.e. 10 films, Figure S2,curve c).

BTX detection

The setup allowing BTX detection is illustrated in Figure 1 (left). The films were continuously exposed to UV light emitted from the D2000 Oceanoptics source. The signal intensity was followed by the Oceanoptics QE65000 spectrometer every 25 ms and an average spectrum was saved every 5 s. Two chambers (42.5 L and 5.8 L) were used for the generation of the synthetic air with controlled amount of BTX. The flow circuit was built with Teflon® tubes. During the analysis, the pump was delivering a flow rate of 0.1 L min -1 , and the flow was adjusted to 4.7 L min -1 for the regeneration of the adsorbent with a second circuit.

Two measuring cells have been used. The first one, which had already been described in a preceding paper [START_REF] Hamdi | Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes)[END_REF] was composed of two brass blocks in which a slot was incised in order to introduce the quartz plate, the second one, designed and built for this study holds at the same time 5 plates spaced by 1 mm (Figure 1B). In both cases, the zero absorbance value is the one obtained with the plate(s) coated with the thin film before any exposure to BTX. Calibrated SnO2 detectors at the input and output of the measuring cell allow to control the accuracy of the amounts of pollutant flowing in the measurement cell and to ensure that it was the same as the one generated (controlled by a PID detector in the generation chamber).

A portable air dryer (PDseries-50 tubing-and 30 cm length, Perma Pure LLC, USA) has been added in the setup between the generation chamber and the measurement cell in order to remove the humidity from the air to be analyzed before it enters the measurement cell.

Results and discussion

Validation of the sensor for toluene detection in humid air

The BTX sensor is described with a simplified scheme in Figure 1A. A quartz plate modified with mesoporous silica allowing BTX adsorption was introduced in a cell that was designed for allowing at the same time the flow of the air to be analyzed and the measurement of UV light absorption by chemical species adsorbed in the mesoporous silica. First, experimental evaluation was done with a cell allowing analysis with a single quartz plate modified with mesoporous silica. Another cell allowing the use of five plates (Figure 1B) was later used for improving the analytical performances of the sensor.

Due to its low toxicity and its simplicity (no isomers) toluene was considered all along this work as a BTX model. Once optimized, the experimental setup and methods were tested for their ability to determine benzene and xylene.

Detection of BTX at ppm level is not that difficult in the absence of any interfering molecule, and this can be achieved with SnO2 sensors that were introduced in the setup for controlling the accuracy of the concentrations of pollutants. However, in the working environments where BTX are potentially present, water is always present in a relatively large amount compared to the BTX. Indeed, 50% of relative humidity under atmospheric pressure corresponds to 11700 ppm of water at 20°C, i.e. four to five order of magnitude higher than the concentration of BTX. Thus, a great attention was first paid on the effect of water on toluene detection.

The principle of the sensor that is evaluated here is to concentrate rapidly the pollutant by reversible adsorption on the mesoporous silica surface and, simultaneously, to detect it by absorption spectroscopy. Figure S3A shows the typical spectrum that can be obtained by the sensor in the presence of 20 ppm toluene, in dry air. An absorption signal is observed between 230 and 280 nm when toluene molecules are adsorbed on the mesoporous silica layer. The signal to noise ratio may appear poor as shown in Figure S3A. Indeed, the complete spectrum was acquired for the need of the demonstration, but this is not necessary for the application of the sensor for which the acquisition can be limited to several wavelengths with a longer spectrophotometric acquisition time, that allows reducing the noise. The influence of water on toluene detection is shown in Figure S3B. The sensor was exposed to 20 ppm toluene in a synthetic air with 50 % relative humidity. A signal is still discernable, but its intensity was decreased dramatically, at a level that makes impossible the quantification of toluene. A strategy that has been successfully used before implies the removal of water by an air dryer before it comes in contact with the sensor [START_REF] Hamdi | Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes)[END_REF]. Figure S3C shows the application of the air dryer on the toluene detection. Air with toluene and water was flowing through the air dryer before to enter the detection cell of the sensor (as it is shown in Figure 1A). An absorption peak is observed between 230 and 280 nm, which indicates that the detection of toluene is well recovered when air is pretreated with the air dryer. In the next steps of this study, air dryer is always applied for pre-treating the air that is analyzed. We compared the repeatability of the sensor response to 20 ppm toluene by preparing two batches of sensors and testing them 1) in dry air and 2) in humid air with an air dryer. The standard deviation is found similar, close to 10 % of the sensor response, for the two batches of sensors and no significant difference is observed between the two conditions of measurement (Figure S4).

Validation of the sensor for toluene detection in the presence of other VOCs

Other volatile species may also be found in the workplace, that can interfere with the detection of BTX [START_REF] Triolet | Panorama de l'utilisation des solvants[END_REF][START_REF] Bertrand | Panorama des expositions professionnelles organiques volatils entre 2003 et 2010[END_REF]. In this work we limited the interference study to the VOC likely found together with BTX in real situations, i.e. ethanol, acetone, butanone and cyclohexane.

First, we evaluated the influence of the air dryer on the removal of polar (ethanol, acetone and butanone) and non-polar molecules (cyclohexane). The sensor response to successive exposure of the to 20 ppm toluene, and 40 ppm of ethanol, acetone, butanone and cyclohexane is shown Figure 2. The setup was also equipped with SnO2 sensors that are very sensitive sensors but lack selectivity. When UV and SnO2 sensors are exposed three times to toluene, this BTX is detected on both sensors, with an absorbance increasing from 0 to 0.01 with UV detection at 267 nm, and the response of SnO2 sensor increasing by 0.9 V in the presence of toluene. On the contrary, no signal was detected when the sensors were exposed to air containing 40 ppm of ethanol, acetone and butanone. These three molecules give a signal with SnO2 or UV detection (see Figure S5 for an illustration of their UV detection). In fact, the air-dryer used to eliminate water, is also eliminating very efficiently these polar molecules from the air while toluene is kept at the same concentration. Cyclohexane is a nonpolar molecule that cannot be eliminated by the air-dryer. For this reason, it is easily detected at 40 ppm by the SnO2 sensor. This molecule is thus a major interfering species of SnO2 detection. At the opposite, since cyclohexane does not absorb light in the UV range, it does not interfere with the detection of toluene.

To finalize this evaluation, the spectroscopic detection of 20 ppm toluene was performed in the presence of 40 ppm of ethanol, acetone, butanone and cyclohexane using the air dryer. Figure S6 depicts the relative sensor response to toluene and toluene with other VOC. The variability observed between the different experiments is included in the experimental error observed for each experiment, demonstrating that toluene detection is not significantly affected by the presence of ethanol, acetone, butanone and cyclohexane, when the air dryer is used to pre-treat the air before it is analyzed.

Sensor LOD and LOQ

Initial attempts to detect BTX were performed with a single quartz plate led to limit of detection of 2 ppm, 10 ppm and 1 ppm for toluene, benzene and p-xylene, respectively. While these values are sufficient for reaching PEL and STEL reported in Table S1 for toluene (50 to 300 ppm) and p-xylene (50 to 100 ppm), it is still far from the benzene concentrations that have to be monitored (1 ppm for PEL and 5 ppm for STEL). In order to increase the sensitivity of the sensor, we built a detection cell with 5 quartz plates, covered on both sides by mesoporous silica. Figure 3 reports the continuous detection of toluene from 1.1 to 196 ppm. The spectra show clearly the presence of toluene (Figure 3A) and continuous measurement of absorbance allows to build a calibration curve over a wide range of concentration (Figure 3B). The same experiment was performed with p-xylene (Figure S7) and benzene (Figure S8 andS9). The detection limits were evaluated using 267 nm for toluene detection, 274 nm for p-xylene detection and 252 or 190 nm for the detection of benzene. In these conditions, the detection limits reached 1 ppm for all three molecules (Figure S9).

Time response of the sensor

The sensor response is very rapid. Figure S10 shows the comparison in time response of a SnO2 sensor and the spectroscopic sensor developed here, when the concentration of toluene was changed from 0 to 1.3 ppm, from 16 to 22 ppm and from 187 to 237 ppm. For these three ranges of concentrations, the time response of the SnO2 sensor and of the spectroscopic sensor is comparable. These series of experiments show that the response of the spectroscopic sensor is not limited by adsorption phenomenon in the mesoporous layer, and that the temporal dynamic of the sensor is mainly governed by the mass transport of the pollutant in the fluidic from the source of pollution (that is here generated by us) to the sensor. 90 % of the response is reached in 40 s, whatever the concentration range (Figure S11) and should be easily reduced by reduction of the tubing length between the pint of air collection and the measurement cell. The sensor allows thus a continuous monitoring of BTX in complex environments.

Non-linearity of the sensor

We further analyzed the sensor response. Each plateau of the incremental curves given in the Figures 3, S7 and S8 gives the absorbance value at a given concentration. These values are plotted in Figure 4 as a function of the concentration. The molar extinction coefficient of the adsorbed species are not known, which means that the adsorption isotherms cannot be rigorously established. Nevertheless, we can assume that the Beer-Lambert law is valid, and that the reported values are proportional to the number of mole adsorbed. We can see that the sensor does not give a linear response as a function of the BTX concentration. Fitting these curves is not possible with a straight line or a Langmuir equation, and the equation derived from the Freundlich model must be considered. Only the α may be discussed since, in this equation, K is a function of the molar absorption coefficient which is depending on the species.

(equation 1)

α value coming out from the nonlinear least square analysis is higher than 1 for benzene, indicating a cooperative adsorption, and lower than 1 for toluene and p-xylene (isotherms shown in Figure 6). Thus, the adsorption of benzene differs from the adsorption of toluene or p-xylene. In a previous report, in which the adsorbing layer was a self-assembled film of mesoporous nanoparticles displaying both intra-particle and inter-particle porosities, this phenomenon was attributed to a heterogeneity in the adsorption sites energy. Here, the adsorbing material is very well defined and its porosity is unique, so this interpretation must be discarded. In fact, adsorption of benzene is very limited on silica surface, and the observed heterogeneity comes from a higher interaction of benzene with benzene than with silica.

Conclusion

The selective and sensitive detection of BTX in air was investigated. The use of thin transparent films of mesoporous silica supported on quartz as adsorbing material, together with an online air drier and a multi-plate detection cell allowed to determine BTX in real time at levels as low as 1 ppm, suitable for STEL monitoring according to the existing legislation.

No significant interference of polar (water, acetone, ethanol, butanone) and non-polar (cyclohexane) molecules was observed. The next steps in this development is a miniaturization of the all device and a detailed study of complex mixture of BTX with chemometric approaches before field application. S2). All measurements have been performed with the same multi-plate sensor. Benzene content

Figure captions Figure 1 .

 captions1 Figure captions

Figure 2 .

 2 Figure 2. (Top) Absorbance and (Bottom) SnO2 sensor response measured in the presence of

Figure 3 .

 3 Figure 3. (A) UV spectra recorded in the presence of toluene at 1.1 ; 2.2 ;3.3 ; 4.4 ; 5.5 ; 6.6;

Figure 4 .

 4 Figure 4. Influence of the concentration of (a) benzene, (b) toluene and (c) p-xylene on the

  Figure 1

Acknowledgements

J. Ghanbaja (Institut Jean Lamour, Nancy, France) for the TEM analysis. G. Paquot (LCPME) for the building the 5 plates cell. These works were funded by the National Institute for research and safety INRS-France.


Jocelyne Caparros
email: jocelyne.caparros@obs-banyuls.fr

Camila I Fernandez
email: fernandez@obs-banyuls.fr

Angel Rain-Franco

Marcus Sobarzo
email: msobarz@udec.cl

Variability of chromophoric dissolved organic matter in three freshwater-influenced systems along central-southern Chile

Keywords: CDOM, DOC, central Chile, northern Patagonia, southern Patagonia

Introduction

Chromophoric dissolved organic matter (CDOM), the fraction of dissolved organic matter (DOM) that interacts with solar radiation and absorbs ultraviolet and visible radiation [START_REF] Bricaud | Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains[END_REF], is an ubiquitous compound in the marine water column [START_REF] Nelson | The global distribution and dynamics of chromophoric dissolved organic matter[END_REF]. It is produced by the microbial degradation of biologically produced dissolved organic carbon (DOC) [START_REF] Nelson | Seasonal dynamics of colored dissolved material in the Sargasso Sea[END_REF]. Experimental evidence shows that zooplankton [START_REF] Steinberg | Production of chromophoric dissolved organic matter (CDOM) in the open ocean by zooplankton and the colonial cyanobacterium Trichodesmium spp[END_REF] and macroalgae [START_REF] Hulatt | Exudation and decomposition of chromophoric dissolved organic matter (CDOM) from some temperate macroalgae[END_REF] can release significant amounts of CDOM. In coastal environments, CDOM has primarily terrestrial origins and shows a rapid decline across the continental shelves [START_REF] Vodacek | Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial inputs and photooxidation[END_REF] primarily via the photochemical alteration or photobleaching of CDOM. This process is dependent on incident solar radiation and water column stratification [START_REF] Vodacek | Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial inputs and photooxidation[END_REF][START_REF] Del Vecchio | Spatial and seasonal distribution of chromophoric dissolved organic matter and dissolved organic carbon in the Middle Atlantic Bight[END_REF].

Several optical approaches, including absorbance and fluorescence, have been used to describe the dynamics relationship between DOC and CDOM because its optical properties, especially those based on the absorption spectra, help identifying the origins of CDOM in aquatic ecosystems [START_REF] Helms | Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter[END_REF][START_REF] Hansen | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF]. Some studies have used absorption spectra to predict potential changes in coastal DOC concentrations [START_REF] Fichot | A novel method to estimate DOC concentrations from CDOM absorption coefficients in coastal waters[END_REF], revealing the importance of CDOM river discharges into the coastal ocean and the seasonal significance of photochemical degradation [START_REF] Mannino | Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the U.S. Middle Atlantic Bight[END_REF].

The coastal area off central Chile is characterized by seasonally variable rates of biological production and chlorophyll concentration, with maximum levels related to wind-driven upwelling in spring-summer [START_REF] Yuras | On the annual cycle of coastal and open ocean satellite chlorophyll off Chile (18°-40°S)[END_REF] and minimum levels dominated by freshwater inputs (mainly riverine) in winter [START_REF] Escribano | The structure and functioning of the coastal upwelling system off central/southern Chile[END_REF]. The strong discharge of the Biobío River [START_REF] Saldías | Seasonal variability of turbid river plumes off central Chile based on high-resolution MODIS imagery[END_REF] represents over 40% of the region's marine DOC in winter and spring in this area [START_REF] Vargas | Bacterial production along a river-to-ocean continuum in central Chile: implications for organic matter cycling[END_REF]Fig. 1A) which produces strong physical and chemical gradients in the water column on short spatial scales [START_REF] Vargas | Bacterial production along a river-to-ocean continuum in central Chile: implications for organic matter cycling[END_REF].

Northern and southern Patagonia (41-55ºS) comprise geographically complex channels, fjords, and bays where freshwater continental waters (coming from rivers, precipitation and snow/glacier melting) interact with marine waters (Iriarte et al., 2014). Primary production shows a southward latitudinal gradient, going from 0.089-0.372 gC m -2 d -1 (North) to 0.114-0.120gC m -2 d -1 (South). Because of the high correlation between photosynthetically active radiation (PAR) and primary productivity throughout Patagonia, some authors have recognized the importance of CDOM in the attenuation of PAR (Jacob et al., 2014) and even UV radiation in the area (Houvinen et al., 2016).

Using these three contrasting study areas, this study aims to evaluate the contribution of terrestrial-derived CDOM as a function of freshwater inputs and stratification levels and to analyze the variability of CDOM using its optical parameters.

Materials and methods

Study area and sampling strategy

Three oceanographic cruises were carried out at contrasting study areas: 1) at the mouth of the Biobio River, in the coastal upwelling area off central Chile (36.8°S; November 2013), 2) the Puyuhuapi Fjord in northern Patagonia (44.6°S; August 2016) and 3) the Beagle Channel in southern Patagonia (subantarctic region; 54.9°S; July 2017; Fig. 1).

The Biobio station was visited for 27 hours, with samplings scheduled every 3 and then every 6 hours (six profiles total; Fig. 1A). Four stations were sampled along a transect from Jacaf Channel to the southern mouth of Puyuhuapi Channel in Puyhuapi ford (Fig. 1B). This area is characterized by a seasonal stratification. Inside the fjord, the winter input of marine water comes strongly from the north via the Jacaf Channel while freshwater comes from the Cisnes River, in the central part of the Puyuhuapi Channel. This creates a wellmixed water column (Fig. 1B). However, in spring-summer, the water column is highly stratified, driven by freshwater discharges in the northern part of Puyuhuapi fjord [START_REF] Schneider | On the hydrography of Puyuhuapi Channel, Chilean Patagonia[END_REF]. In the Beagle Channel we concentrated in two subantarctic fjords: Yendegaia and Pia (Fig. 1C). Yendegaia shows a retreated glacier separated from the fjord by ~12 km, whereas Pia Fjord receives freshwater inputs directly from a glacier. In each fjord three stations were sampled on a transect going from the head to the mouth of each fjord (Table 1).

The physico-chemical variability of the study areas was assessed with CTD profiles (SeaBird®). Seawater samples were collected using Niskin bottles. Surface sampling (1 m) was carried out by closing the Niskin bottle immediately below the surface (Table 1).

The mean daily river discharge data were obtained from the Dirección General de Aguas (www.dga.cl). Data was used between January 2007 and December 2012 for the Biobio River (Central Chile) and between January 2007 and December 2014 the Cisnes River in the Puyuhuapi Fjord (Northern Patagonia). There is not data available for the Beagle Channel.

We estimated the degree of stratification of the water column for each profile using the stratification parameter, ns, defined by [START_REF] Haralambidou | Salt-wedge propagation in a Mediterranean micro-tidal river mouth[END_REF] and applied previously by [START_REF] Schneider | On the hydrography of Puyuhuapi Channel, Chilean Patagonia[END_REF] for Puyuhuapi as shown in equation 1:

ns = S50m-Ssurface / ½ (S50m+Ssurface) (1)
Where Ssurface and S50m are defined as the salinity at surface m and 50 m, respectively.

Surface salinity for Biobío corresponds to values at 1m, for Puyuhuapi at 2m and for Beagle at 0.5 m depth. The stratification parameter varies from values lower than 0.1 (representing a well-mixed water column), between 0.1-1 (partially mixed) and higher than 1 (highly stratified water column).

Bacterioplankton abundances (including archaea and bacteria) were estimated by flow cytometry [START_REF] Marie | Flow cytometry analysis of marine picoplankton[END_REF] using a FACSCalibur flow cytometer at Universidad de Concepcion. Samples were taken in duplicate using sterile cryovials (1350 µL), fixed with glutaraldehyde (0.1% final concentration), and stored at -80°C until laboratory analysis.

For DOC samples, water was filtered using GF/F filters (0.7 µm, combusted at 450°C, 6 h) and sterile syringes. Samples were stored in glass vials (previously combusted at 450°C, 6 h) and acidified immediately with H3PO4 (25%; 90µL/15mL) to pH 2. DOC concentrations were determined by chromatography using a Shimadzu TOC-5000 carbon analyzer [START_REF] Benner | A critical evaluation of the analytical blank associated with DOC measurements by high-temperature catalytic oxidation[END_REF] at the laboratory of microbial oceanography (CNRS, France).

Samples for nitrate (NO3 -) and nitrite (NO2 -) determination were taken in duplicate (10 mL) and stored at -20°C awaiting colorimetric analysis with a Brann Luebbe® autoanalyzer [START_REF] Aminot | Dosage automatique des nutriments dans les eaux marines[END_REF]. Total chlorophyll-a (Chl-a) was estimated using a Turner Design fluorometer [START_REF] Holm-Hansen | Fluorometric Determination of Chlorophyll[END_REF]. CDOM was sampled in duplicate (50 mL)

and slowly filtered through precombusted GF/F filters (0.7 µm 450°C, 6 h). Samples were then stored in dark conditions at -20°C until absorption analysis.

Absorbance for CDOM determination was measured in an Agilent 8453 UV-Visible spectrophotometer (single beam spectrophotometer). CDOM concentrations were determined using the absorption spectra at 325 nm as a proxy [START_REF] Nelson | Hydrography of chromophoric dissolved organic matter in the North Atlantic[END_REF][START_REF] Swan | Biogeochemical and hydrographic controls on chromophoric dissolved organic matter distribution in the Pacific Ocean[END_REF]. Ultrapure water was used as a blank. The absorption coefficient was according to equation 1 [START_REF] Bricaud | Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains[END_REF]:

αCDOM(λ) = 2.303 A(λ) / L (2)
where αCDOM is the absorption coefficient (m -1 ), A is the absorption of the sample (325 nm), and L is the optic length path (0.05 m). A baseline correction was applied by subtracting the absorption at 700 nm.

The spectral slope (SCDOM in nm -1 ) was estimated at intervals of 300 to 700 nm of absorption spectra through a simple exponential function fitted using a non-linear regression [START_REF] Twardowski | Modeling the spectral shape of absorption by chromophoric dissolved organic matter[END_REF] according to equation 3:

α(λ) = α(λRef) * exp (-S*(λ -λref)) (3)
where α is the absorption coefficient (m -1 ), λ is the wavelength (nm), and λref is the reference wavelength (300 nm). Additionally, we calculated the slope ratio (SR) between spectral slopes at 275-295 nm (S275-295) and 350-400 (S350-400) using a linear regression to the natural log-transformed spectra [START_REF] Helms | Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter[END_REF].

Statistical analyses

Principal component analysis (PCA) was performed using environmental variables (temperature, salinity, nitrate, bacterioplankton and Synechoccocus sp abundances, Chl-a)

in order to reduce dimensionality and then compare with a325 values by area. We did several linear regressions between the first and second principal component scores and a325. The significance of each regression was tested using the lm function. Several Spearman correlation tests were calculated to assess potential relationships among a325 and DOC in each study zone. Finally, a Wilcoxon pairwise comparison was used (R-package lattice) to test significant differences of DOC concentrations, a325, SCDOM, and SR by zone and layers.

The statistical analyses were performed with the software R (https://www.r-project.org/).

Results

Oceanographic conditions

In central Chile, monthly averages of freshwater discharge of the Biobío River show variable outflow though the year, reaching maxima in the spring months (1494 ±853 m 3 s -1 during August), while minima were observed during early autumn (320 ± 172 m 3 s -1 in April). Monthly average for November was 989 ± 430 m 3 s -1 (Fig. 2A). Consequently, the water column was stratified in the first 5 m, presenting surface (1 m) temperatures of 16.75 ± 1.05 °C and salinity of 21.36 ± 2.55 psu. Below this surface layer, salinity remained constant (~35 psu), whereas temperature decreased slowly with depth (Fig. 3A). Average surface Chl-a was 1.00 ± 0.47 mg m -3 and at 5 m this variable was highest (1.72 ± 0.69 mg m -3 ). Below the subsurface maximum, chlorophyll decreased to 0.47 ± 0.29 mg m -3 at 45 m.

Like chlorophyll, bacterioplankton increased from the surface (248 ± 73 10 3 cell mL -1 ) to 5 m depth (557 ± 293 10 3 cell mL -1 ), then decreased with depth (Fig. 3E). Nitrate concentrations increased strongly with deep from 8.02 ± 2.3 µmol L -1 in surface waters to 25.77 ± 3.11 µmol L -1 at 45 m. The analyses of water masses show warmer and saltier water compared to the fjord areas (Fig. 2C). An important freshwater-influenced layer (< 5m) is present followed by Equatorial subsurface water (ESSW) in deeper layers.

In northern Patagonia (Puyuhuapi Fjord), freshwater inputs are characterized by the outflow of Cisnes River (Fig. 2B), the maximum month average were registered in spring (272 ± 152 m 3 s -1 ) and the minimums in February (127 ± 108 m 3 s -1 in February). River discharge during sampling period (August) usually has shown intermediate levels of discharge with a monthly average of 193 ± 209 m 3 s -1 . The average salinity in surface waters showed high variability along the channel (Fig. 3B). Averages were 29.9 ± 1.14 psu at northern stations but 17.88 ± 1.08 psu in the south; however, in deep layers, salinity profiles were constant (~33 psu). Surface temperatures were similar in the south (9.49 ± 0.30 °C) and north Patagonia (9.08 ± 0.77 °C) and remained stable with depth. Chl-a was highest in surface waters in the south (1.50 ± 0.36 mg m -3 ) while northern maxima were observed at 10 m depth (0.75 ± 0.23 mg m -3 ). In both zones, Chl-a and bacterioplankton abundances decreased with depth following the same pattern. Nitrate concentrations in the south of the channel peaked at depths of 50 m (25 µmol L -1 ) and 150 m (15.28 µmol L -1 ), but deepwater nitrate concentrations in the north were low compared to values in the south (Fig. 3F). Puyuhuapi Fjord was influenced by estuarine water in surface (<30 m). Below 30 m, modified subantarctic waters (MSAAW) were dominant, with temperatures around 10°C.

The Pia Fjord had the lowest average surface temperature (4.43 ± 0.88 °C), increasing slightly down to 100 m, where it reached an average of 6.92 ± 1.69 °C. Salinity profiles showed lower values and more variable at the surface (28.37 ± 2.62 psu), followed by an increment to 30.39 ± 0.077 psu at 5 m and to 31.54 ± 1.02 psu at 100 m (Fig. 3C). Chl-a ranged from 0.03 to 0.28 mg m -3 at the surface and decreased slightly with depth.

Bacterioplankton abundances were highest in surface waters (147 ± 54 x10 3 cell mL -1 ) and decreased with depth (48 ± 34 x10 3 cell mL -1 ). Finally, the observed nitrate concentrations were around 11.56 ± 1.57 µmol L -1 at the surface and increased slowly to 15.06 ± 0.43 µmol L -1 at 100 m depth (Fig. 3G).

Temperature and salinity in the Yendegaia Fjord increased with depth (Fig. 3D). In this fjord, Chl-a decreased following the same trend observed for Pia fjord. Bacterioplankton abundances were highest at the surface (214 ± 70 x10 3 cell mL -1 ) and remained stable below 5 m (175 ± 68 x10 3 cell mL -1 ). The same trend was observed for nitrate (Fig. 3H).

CDOM and DOC distribution in the water column

In the Biobio River, dissolved organic carbon ranged from 47.70 to 162.10 µmol L -1 , with maximum concentrations in surface waters. In Puyuhuapi, DOC varied from 69.73 µmol L - 1 to 119.12 µmol L -1 , with maximum concentrations in intermediate waters. SCDOM values were highest in the deep waters of the Puyuhuapi Fjord (0.304 nm -1 ), followed by 0.020 nm -1 in Beagle Channel and 0.014 nm-1 in Biobio River (Fig. 4C). On the other hand, values of SR in Biobio River varied from 1.065 to 2.592, whereas in Puyuhuapi they ranged from 0.480 to 1.477. In the Beagle Channel values of SR varied from 0.922 to 1.842. In Biobio, the highest SR was estimated for intermediate waters as well as in Puyuhuapi fjord, but for Beagle Channel, the highest SR values were located in the deepest waters (Fig. 4D). No significant differences were found along the water column within each study area (p>0.050). However, we observed significant differences between study areas. Significant changes in SR at the surface and intermediate layers were found between the Beagle Channel and Puyuhuapi Fjord (p<0.05). SR values of surface waters in Biobio were significantly different from deep and surface Puyuhuapi waters (p=0.018 and 0.029, respectively).

The principal component analysis showed differences between zones (Fig. 5). The first principal component represented 43.8% of the variance of environmental parameters (temperature, Chl-a, microbial abundances; Table 2). This principal axis revealed geographical variability in the case of Puyuhuapi fjord and temporal variability for the Biobio River. In contrast, Pia and Yendegaia fjords were less variable and grouped together. The second principal component (PC2), which explained 25.4% of the remaining variability, represented salinity and nitrate changes (Table 2).

Linear regression between the PC1 (biological variables and temperature) the PC2 scores (representing changes in salinity) and the a325 values indicated significant relationships for Biobío River (p-value=0.010 and p-value<0.001, respectively) explaining the 28 and 46%

of their respective variability. Linear relationships between PC2 scores and Puyuhuapi

Fjord were significant (p-value=0.048, n=12) and explained 34% of the variability.

However, no significant relationships were found between the PC2 scores and a325 for the Beagle Channel (Table 3). Spearman correlations between DOC and a325 by area revealed non-significant correlations, except for the Biobio River (rho=0.637, p-value=0.001, n=21).

However, a high positive but non-significant correlation was found at the southern Puyuhuapi stations (rho=0.714, p-value=0.088, n=7). In the case of the Beagle Channel, important correlations were found only for Pia Fjord (rho=0.462, p-value=0.072, n=16;

Table 3).

Overall, the stratification parameter varied from 0.02 to 0.78, going from the lowest estimated values (0.02-0.19) at the Beagle channel to intermediate values at Biobio (0.37-0.62) and the highest at Puyuhuapi Fjord (0.78). Particularly heterogeneous conditions were observed in Puyuhuapi with maximum values observed in the southern stations, which contrasted with the northern channel. Surface a325 presented a positive and exponential relationship with stratification (0.002+exp (1.453*ns), n=16) explaining the 63% surface CDOM variability (Fig. 6A). Average SR (considering all the sampling points per profile) varied along with water column stratification in all study areas. Significant differences were found among zones of study (One-way ANOVA, p=0.007). Average SR in Puyuhuapi (0.99 ± 0.07) was significantly low compared to the Beagle channel (1.43 ± 0.04) and Biobio

(1.17 ± 0.20). No differences were found between average SR between Beagle and Biobio.

Discussion

The study of CDOM dynamics is an emergent field of research off the Chilean coast. Other than a recent study on CDOM distribution off central Chile [START_REF] Vargas | Bacterial production along a river-to-ocean continuum in central Chile: implications for organic matter cycling[END_REF] this study is the first report of CDOM variability from the perspective of its optical properties (a325, SCDOM, SR) covering productive conditions in central Chile to subantarctic waters.

The importance of terrestrial sources of CDOM in our study area is reflected by the significant relationship between CDOM and PC2 scores (which represents river influence)

for Biobio River and, less importantly for the Puyuhuapi Fjord (Fig. 5). However, PC2 and CDOM did not correlate in the Beagle Channel.

The strong relationship between surface CDOM absorption and DOC in Biobio suggests that chromophoric molecules represent an important fraction of total DOC from terrestrial origins, as previously seen over other continental shelves [START_REF] Mannino | Algorithm development and validation for satellite-derived distributions of DOC and CDOM in the U.S. Middle Atlantic Bight[END_REF][START_REF] Shank | Distribution and photoreactivity of chromophoric dissolved organic matter in northern Gulf of Mexico shelf waters[END_REF]. This was confirmed by the response of the magnitude CDOM to the stratification caused by salinity (Fig. 6A). However, there is no conclusive evidence on the importance of river runoff on the CDOM distribution over the entire water column in this study. Indeed, the highest CDOM concentrations were registered in Puyuhuapi although the river discharge of the Cisnes River was less intense (7-fold in winter season) than the Biobío River (Fig. 3). Second, mean CDOM seems to be independent of the water column stability.

Even if no significant differences occurred in surface DOC concentrations among our study areas, the optical parameters of CDOM (a325, SCDOM, SR) allowed us to identify differences in CDOM between and within zones (Fig. 4). First, Biobio stations presented high levels of DOC, a325, and SCDOM at the surface compared with deeper layers. High SCDOM has been associated with photobleached CDOM [START_REF] Vodacek | Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial inputs and photooxidation[END_REF][START_REF] Moran | Carbon loss and optical property changes during long-term photochemical and biological degradation of estuarine dissolved organic matter[END_REF][START_REF] Stedmon | The optics of chromophoric dissolved organic matter (CDOM) in the Greenland Sea: An algorithm for differentiation between marine and terrestrially derived organic matter[END_REF]. Also, low SR values were related to the low salinities found in surface waters which were associated with compounds of terrestrial origin (high molecular weight), in accordance with estuarine values reported in previous literature [START_REF] Das | Chromophoric dissolved organic matter (CDOM) variability over the continental shelf of the northern Bay of Bengal[END_REF][START_REF] Helms | Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter[END_REF]. Sampling sites in Puyuhuapi Fjord showed the highest a325 values in CDOM but the same was not true for DOC concentrations. SR values were lower in Puyuhuapi for all depths compared to BioBio, suggesting a system strongly influenced by terrestrial organic matter in the water column (even independent of the particular oceanographic conditions during the sampling time) in contrast with the fjords of the Beagle Channel, which were associated to in situ produced DOM (SR around 1.5) in subsurface depth layers.

The southern Channel in Puyuhuapi presented the expected CDOM distribution for an estuarine system: CDOM was high at the surface but tended to increase in deep waters in the northern channel. Interestingly, high a325 was observed along with a nitrate peak in intermediate layers (Fig. 3B) with higher SR, suggesting potential local production of CDOM decoupled from freshwater input in the southern channel of the Puyuhuapi Fjord.

The stations in Pia and Yendegaia fjords (Beagle Channel) showed the lowest chlorophyll levels (Fig. 2G,H) and less stratified water column of our study. However DOC concentrations, varied in the same order as Biobio River and Puyuhuapi Fjord (Fig. 4A).

The stations in Beagle Channel presented higher DOC and a325 concentrations at 10 m compared to surface and deep layers which were unrelated to salinity changes. However, we observed relatively high and stable SR (~1.5) values through the water column compared to the Puyuhuapi Fjord. These findings suggest these fjords to be well-mixed dominated by DOM of low molecular weight and in situ biological production (such as zooplankton excretion) as reported by [START_REF] Steinberg | Production of chromophoric dissolved organic matter (CDOM) in the open ocean by zooplankton and the colonial cyanobacterium Trichodesmium spp[END_REF] for copepods, euphausiids, amphipods, and salps. However, we do not have enough evidence to draw conclusions about the importance of the zooplankton community and the magnitude of their excreted compounds in these systems.

These optical parameters (especially a325 and SR) are simple but useful tools for describing the photochemical/biological processes affecting CDOM. Further experiments using fluorometric methods such as the excitation emission spectra [START_REF] Hansen | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF] and focusing on key species are needed in order to assess the residence time and fingerprinting of chromophoric components in relation to the dynamics of CDOM, its sources, and its sinks in coastal waters.

Conclusion

This study aimed to estimate the impact of terrestrial DOM on the characterization of CDOM in three study areas. SR concentrations along with a325 and SCDOM showed marked differences between the three regions. .Freshwater was mostly responsible for surface CDOM changes and the principal source of chromophoric material input to in Biobio River and Puyuhuapi Fjord, when systems are highly stratified Surface terrigeneous organic matter dominated the dissolved organic pool in Puyuhuapi and was strongly correlated with its colored component. Changes in the average spectral ratio were observed independent of the condition of the water column in Beagle Channel and Puyhuapi suggesting the distribution of CDOM is potentially dominated by biological in situ production below the surface freshwater-influenced layer. We conclude that in stratified systems freshwater inputs determine the distribution of surface CDOM, but in well-mixed systems the in situ production of CDOM dominates.

  For the Beagle Channel, DOC fluctuated between 60.02 and 104.3 µmol L -1 . Overall, the median concentrations were 67.2, 78.8, and 72.5 µmol L -1 for Biobio, Puyuhuapi, and Beagle, respectively (Fig 4A). The only significant differences detected by analyzing DOC concentrations were between the Beagle Channel (surface and intermediate layers) and the Biobio River (intermediate depths) (p-value=0.030 and 0.025, respectively).For CDOM parameters, values of a325 were highest in the deep waters of the Puyuhuapi Fjord (3.865 m -1 ), followed by the intermediate layer of Beagle Channel (1.729 m -1 ).Significant differences were detected in Biobio River between the intermediate layer and surface (p-value=0.040). Also, differences occurred between Biobio River and Beagle Channel at the surface (p-value=0.005) and in intermediate layers (p-value=0.001) and Puyuhuapi Fjord at the surface (p-value=0.031) and in the deep layer (p-value=0.036). In the Puyuhuapi and Beagle channels, non-significant differences were found for a325 among depths.

Figure 1 .

 1 Figure 1. Location of oceanographic stations in the three study areas. A) Biobio River, B)

Figure 2 .

 2 Figure 2. River discharge and T-S diagram for the study sites. A) Annual variability of

Figure 3 .Figure 4 .

 34 Figure 3. Oceanographic conditions in the three study areas during sampling. Average

Figure 5 .

 5 Figure 5. Biplot of principal components analyses (PCA) for environmental variables,

Figure 6 .

 6 Figure 6. Relationship between stratification and CDOM properties. A) Exponential

Acknowledgements

We thank Claudia Muñoz and Maria Lorena Gonzalez for support in fieldwork. This study was partially funded by LIA MORFUN, Fondecyt grants 1150891 and 1180954, COPAS Sur-Austral CONICYT PIA APOYO CCTE AFB170006, INCAR (FONDAP-CONICYT No15110027), and IDEAL (FONDAP-CONICYT No15150003).

Location

Station Date Longitude (ºW)

Latitude (ºS)

Sampling depth (m) Biobío River Biobío river 12-11-201373.226 36.829 0, 5, 20, 45 Biobío River Biobío river 12-11-201373.226 36.829 0, 5, 20, 45 Biobío River Biobío river 12-11-201373.226 36.829 0, 5, 20, 45 Biobío River Biobío river 12-11-2013 73.226 36.829 0, 5, 20, 45 Biobío River