Gautier Vanson

Pascale Marange

Eric Levrat

A technical and systematic characterization of circular strategy processes

Keywords: Circular Economy, Circular strategy, Products regeneration, Holistic approach, Requirement, characterization

To deal with environmental, economic and social problems linked to high consumption and intense manufacturing, Europe, ecological associations propose scenarios for the implementation of the circular economy, without saying how to implement them. Several circular strategies (CS) (reuse, remanufacturing, recycling...) enable to regenerate a product and its components throughout its life cycle. Currently, these CS are not implemented in a systemic way, but in a punctual and individual way. The objective is to deepen the knowledge of the global implementation of several CS. To achieve this, the paper proposes to characterise each CS according to the requirements of the entering and leaving products. This technical characterisation allows us to analyse their complementarities and interactions. This characterisation will be illustrated by the example of remanufacturing and resynthesis. Then, an analysis of our proposal is carried out to show the contributions in order to have a holistic approach of the regeneration.

Introduction

Today, governments are urging more and more companies to adopt a circular economy (CE) through laws, or decrees. Indeed, current issues such as linear consumption through mass customization, fashion effects and obsolescence [START_REF] Slade | Made to break: Technology and obsolescence in America[END_REF] are not compatible with the objectives of sustainable development (SD). The literature shows that this consumption mode is a source of environmental problems such as the increase in waste, climate change [START_REF] Ghisellini | A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems[END_REF] and the depletion of natural resources [START_REF] Hazen | Remanufacturing for the circular economy: An examination of consumer switching behavior[END_REF]. In addition, pandemics and wars show how dependent some states are on certain primary resources. [START_REF] Roy | Economic impact of COVID-19 pandemic[END_REF].

The CE concept based on the pillars of SD is defined by [START_REF] Mac | Towards the circular economy[END_REF]: "A CE is an industrial system that is restorative or regenerative by intention and design. It replaces the 'end-of-life' concept with restoration, shifts towards the use of renewable energy, eliminates the use of toxic chemicals, which impair reuse, and aims for the elimination of waste through the superior design of materials, products, systems, and, within this, business models.". Through this definition, the consideration of a systemic vision with several regeneration cycles becomes essential to achieve the objectives of CE. The objective of our work over the last few years is to propose a holistic approach of product regeneration (i.e consider the interactions of different systems and stakeholders in a global view) . In Diez 2016, we defined the regeneration paradigm as [START_REF] Diez | Maintenance as a cornerstone for the application of regeneration paradigm in systems lifecycle[END_REF]: "set of actions, natural or technical, to restore a waste or its constituents to an acceptable state (functional and operational) allowing to extend its life cycle".

In the literature, many works deal with circular strategies (CS), eco-design but there are very few papers that integrate the multiple life cycles and the holistic approach. Thus, a CS standard characterization would help regeneration designers to define an adequate regeneration process for their products in a holistic approach. In order to achieve the SD objectives, a characterization considering environmental, economical and social aspects is necessary. For this first work, only the CS technical aspect is considered. Thus, this article proposes a technical and systematic characterization of CS with a formalization that allows to compare and analyze CS. The final objective is to give a better knowledge of CS to help industrial to adopt CE. This holistic vision will allow them to better apprehend the complexity of CE and the new CE laws implemented by states.

Circular strategies state of the art

In literature, the circular strategies (CS) enable to extend the product life and create loops for circular economy (CE) to recover value for a product, subassemblies/components or material that would otherwise be considered as waste [START_REF] Morseletto | Targets for a circular economy[END_REF]. A literature review enabled the identification of several CS: reuse, repurposing, upgrading, reconditioning, remanufacturing, resynthesis, recycling, energetic valorization and landfill. A systematic review was done for each CS. This complete work is not presented in this article, only few references are used by CS. Each selected reference is considered as the best to describe the CS in a holistic view. The objective of this section is to present the technical CS features identified in the literature. The following elements are analyzed:

-input: the expected level in the product breakdown structure, and the expected product quantity for carrying out a regeneration. -output: the expected level in the product breakdown structure and its nature: does it have the same purpose and the same composition as the incoming product (i.e. is it identical /different to the incoming product (identical finality and composition) or is it improved (identical finality and different composition by additions/subtractions/modifications)) -process: the CS activities and the level of the product breakdown structure that is regenerated. This listed information of the processes will not be developed in the rest of the article but considered as the activities that enable to regenerate an input product.

The literature review shows that CS are developed in a silo view because researchers optimize the CS process activities rather than the life cycle of the

CS Input Output Process Activities
Regeneration level Reuse [START_REF] Cooper | The environmental impacts of reuse: a review[END_REF], [START_REF] Bauer | Characterization of circular strategies to better design circular industrial systems[END_REF] The same input product diagnostic, cleaning and requalification Repurposing [START_REF] Scott | The Intersection of Sustainable Consumption and Anticonsumption: Repurposing to Extend Product Life Spans[END_REF], [START_REF] Bauer | Characterization of circular strategies to better design circular industrial systems[END_REF] The same input product with another finality Upgrading [START_REF] Ijomah | 8 -Refurbishment and reuse of WEEE[END_REF], [START_REF] Pialot | Upgradable PSS": Clarifying a new concept of sustainable consumption/production based on upgradablility[END_REF], [START_REF] Muztoba | Review on upgradability -A product lifetime extension strategy in the context of product service systems[END_REF] Product

The same input product but enhanced diagnostic, cleaning, requalification, replacement, disassembly and Re-Assembly Product Reconditioning [START_REF] Gaur | Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model[END_REF], [START_REF] Ijomah | 8 -Refurbishment and reuse of WEEE[END_REF] The same input product with few different components Remanufacturing [START_REF] Östlin | Product life-cycle implications for remanufacturing strategies[END_REF], [START_REF] James | Remanufactured products in closed-loop supply chains for consumer goods[END_REF], [START_REF] Hazen | Remanufacturing for the circular economy: An examination of consumer switching behavior[END_REF] Several products subassemblies and components product to be regenerated. Thus, their goal is to regenerate a product with a certain health state only once. Nowadays, CS need to be developed in a holistic vision integrating each other, explaining how to implement them, how to choose a regeneration trajectory between different possibilities and regenerate for several life cycles. In this way, the CE objectives will be achieved, i.e not lose value (recycle a product that could be reused) and preserve the product regeneration potential (regenerate by considering others CS), it's necessary to define a regeneration process in its entirety.

A
Tab. 1 shows some differences and similarities between CS. For example, several CS have common activities which could enable to pool activities and reduce the regeneration cost infrastructures. In addition, CS as reuse, repurposing, upgrading, and reconditioning expect the same input (a product) but have a different output: the same product regenerated for reuse, the same product with a different finality for repurposing etc. These features, which are sometimes close, show that the papers analyzed in literature are not sufficient to analyze CS and to choose the optimal regeneration for a product according to its health state. Indeed, how to choose a CS between these four CS, knowing that each one expects a product to be regenerated as input? What are the technical features that enable us to say whether a regenerated product is different in its finality and composition? A formalization is necessary to deepen the features identified in the literature, to determine which are the technical elements that allow to specify a regenerated product and especially to be able to position how much one CS is different from another by the formalization. A formalization based on the product requirements baseline is proposed. Indeed, it is according to the product's technical features, reflecting its health state, and the CS's capacity to regenerate a product, i.e if a product can access to a CS or not, to be regenerated.

CS characterization and comparison methodology

For regenerating an end-of-life product, a circular strategy (CS) will be chosen according to various economic, environmental, and social constraints, but mainly according to the product's health state. We must also consider the CS's capacity to regenerate the product in order to reach a desired state at the CS's output. So, the product's health state is used to categorize CS, it can be measured according to its initial product requirements.

A requirement is defined by the standard (ISO/IEC 26702:2007) as a "Statement that identifies a product or process operational, functional, or design feature or constraint, which is unambiguous, testable or measurable, and necessary for product or process acceptability". According to [START_REF] Sebok | Guide to the Systems Engineering Body of Knowledge[END_REF], a guide for systems engineering, there are several types of requirements: functional, performance...

It is interesting to choose the product requirements to characterize the CS because the requirements are built in the design phase and constitute a commune baseline for a product family. This baseline is then used in the manufacturing phase which uses this baseline to manufacture product instances. As it is illustrated in Fig. 1, when the products leave the factory, they are considered as new, and all their requirements are satisfied. During the use phase, the product's use will degrade the product's health state, and throughout time some requirements will no longer be satisfied, the product becomes a product to regenerate. Then, depending on the product requirements state, a CS is selected and a regenerated product is obtained. Throughout its life cycle, the product is defined by requirements sets that evolve. The literature has shown that some CS can regenerate a product at multiple levels, and the requirement baselines are different according to the product life phase. Thus, the formalization of a requirement baseline A l,k must be defined according to the product breakdown structure level and the product life phase with:

-The l index to define the level of the product's breakdown structure. The l index can therefore take the value in the interval [1; n], with n the level number in the product's breakdown structure (l = 1 the product level, for l ∈ [2; n -2] the different sub-assemblies levels, l = n -1 the component level and l = n the material level). -The k index, to specify the product's life phase: if the product comes from: manufacturing phase N (New), use phase r (to regenerate) or regeneration phase R (regenerated).

Each requirements set can be decomposed according to the requirement type t:

A l,k = {A l,k t } with t ={F (Functional), Q(Performance)}.
In this first work and to simplify, only the F and Q type are used. A requirement is defined as Req l,k j,t with j the requirement ID. A requirement has a textual definition that can have parameters. To illustrate, a new product A leaving the factory has a requirements baseline composed of a F and a Q requirement subset:

A l,k = {A l,k F , A l,k Q } with A l,k F = {Req 1,N
1,F :"The system must provide a rotation"} and A l,k Q = {Req 1,N 2,Q : "The nominal speed must be between 1000 and 1500 rpm"}

The requirements sets of a new product (A 1,N ) and regenerated product (A 1,R ) product are compared according to their definition and parameters. For that, The 3 operators are defined:

-≡ indicates that the 2 requirements have the same definition and the same parameters. Ex: Req 1,N 1,F ≡ Req 1,R 1,F : "The system must provide a rotation" -= indicates that the 2 requirements have the same definition but with different parameters. Ex: Req 1,N 2,Q = "The nominal speed must be between 1000 and 1500 rpm" compared with Req 1,R 2,Q = "The nominal speed must be between 800 and 1200 rpm" -̸ = indicates that the 2 requirements have different definitions. Ex: Req 1,N 1,F = "The system must provide a rotation" compared with Req 1,R 1,F = "The system must provide a translation"

To compare the requirements sets, augmented same operators are used with the same variables and the requirements number:

-≡ indicates that the 2 sets compared have the same requirements number, with the same definitions and parameters for each requirement. -= indicates that the 2 sets compared have the same requirements number, the same definitions but with different parameters for some requirements. -̸ = indicates that the 2 sets compared have different requirements number, and/or with different definitions. In this case, the operator ⊑ is added to specify whether the set, although different, has the common basic requirements of the product family. For example, the set

A 1,N F with A 1,N F = {Req 1,N 1,F } and A 1,R F = {Req 1,R 1,F , Req 1,R 2,F , Req 1,R 3,F } so, A 1,N F ̸ = A 1,R F because the product number is different but A 1,N F ⊑ A 1,R F because Req 1,N 1,F and Req 1,R 1,F
have the same definition.

To categorize CS, the following methodology uses the previous formalization:

-Step 1: The starting point of the analysis is to measure the gap between the regenerated product expected and the original product (new). So, the first step consists in comparing both requirements sets, respectively A l,R t and A l,N t for each requirement type t.

-Step 2: Consists in identifying the requirement type t that could be regenerated by the CS activities. -Step 3: Consists in comparing the requirements sets of a product to regenerated A l,r t to the regenerated product expected A l,R t for each requirement type t.

To illustrate this methodology, remanufacturing and resynthesis processes are categorized:

Step 1: the requirements set of a remanufactured product A 1,R and a resynthesized product B 1,R are compared with an original product A 1,N .

-For remanufacturing, the F requirements are identical to the original product (new

) (A 1,R F ≡ A 1,N F )
and the Q requirements have different parameters (worse performance than the original product

) (A 1,R Q = A 1,N Q ).
-For resynthesis, the requirements number and definitions are different because the product finality has changed (For t = {F, Q}:

B 1,R t ̸ = A 1,N t ).
Step 2: Both CS regenerate components and sub-assemblies and are able to recover F and Q requirements because they have the same activities. The difference is that resynthesis regenerates sub-assemblies and components from several other different products.

Step 3: Both CS receive some components and sub-assemblies, which may have requirements not satisfied, but with the CS activities satisfaction will be recovered for F and Q requirements (For t = {F, Q}: A l,r t ̸ = A l,R t and A l,r t ̸ = B l,R t ).

The following section analyzes the CS categorization and positions the CS.

Discussion

The characterization made it possible to clarify the differences and complementarities between circular strategies (CS). Indeed, by comparing the sets of F and Q requirements of a CS output product, a more relevant positioning is proposed. In addition, the CS characterization confirms that all CS do not enable a complete regeneration of all the product levels in a sustainable way. The next subsection shows the positioning.

Gap between regenerated product compared to an original product

The CS characterization showed that no CS can achieve the equivalent of an original product but with inferior performance. So the more a regenerated product has different requirements from the original product, the more it is distant.

Therefore, the CS of this regenerated product is more distant from the manufacturing process of the original (new) product. In addition, the more a regenerated product is close to an original product, the higher its health state, and the more likely it would go through a regeneration cycle again. Thus, the shortest gap for a product between an original and regenerated product will be preferred when choosing a CS.

Reuse, reconditioning, remanufacturing and recycling allow to get closer to the original requirements with the difference that the Q requirements have parameters representing their performance intervals lower than the original ones

(A l R Q = A l N Q ).
Thus, to decide which of these four CS used, it is necessary to look at the regeneration activities. It is more advantageous to reuse a product because it requires fewer activities and the product level (l) is the highest (1). However, to be reused, the incoming product must be at product level and all its functional requirements must be satisfied.

For upgrading, the objective is to improve the product by adding, deleting or improving the requirements. Thus, an updated product has different requirements set than the original one, but with the initial functional requirements common to the original product (A

1 N F ⊑ A 1 R F ).
Other CS such as repurposing and resynthesis completely change the product's finality, which further differentiates the requirements of these regenerated products from the original product (B 1 R F ̸ = A 1 N F ). Finally, energy recovery and landfill are even further away, as the output is energy or waste.

An analysis of holistic approach

To implement a complete circular economy (CE) it is necessary to regenerate a product at all its levels. From a sustainable development point of view it is obvious that favoring short regeneration loops with few activities with the highest product level like reuse is more advantageous. On the contrary, recycling a product that still has functional and reusable sub-assemblies is a significant loss.

The analysis of all circular strategies (CS) input shows that it is possible that a product does not fulfill any condition to access a CS. For example, if there is a product with a requirement set that does not have the right requirements satisfied to access product-level CS, or sub-assembly-level CS then the product will be regenerated for its material whereas probably several sub-assemblies and components are still functional. A need for a holistic approach in the design phase becomes important in order to plan the different regeneration and avoid skipping regeneration levels.

Thanks to the CS characterization and the expected input requirements (image of the product health state to regenerate) it is possible to position CS by specifying supply chains for the product flow to be regenerated. For example, to avoid switching from reuse to recycling without skipping intermediate CS. Four groupings are proposed:

-Product from use phase: The product can be sent to reuse, upgrading and reconditioning. -Product, sub-assemblies and components from reconditioning: The product can be sent to repurposing and sub-assemblies/components to remanufacturing or resynthesis. -Sub-assemblies and components from remanufacturing: The subassemblies and components are either sent to other supplier regeneration cycles that can regenerate them or they are sent to recycling. -Material from recycling: The material considered as waste is used as an energy source (energetic valorization) or landfilled if this is not possible.

Fig. 3 illustrates these explanations by positioning CS in a holistic approach. To simplify the figure, external cycles of different products that supply some CS with elements to regenerate have not been added. In addition, fig. 3 could be instantiated for each element disassembled. Indeed, sub-assemblies are potentially the finished product of a sub-supplier. By defining the access conditions of each CS in adequacy with the CS regeneration capacities and the expected result, it is possible to constrain the regeneration paths to avoid losing value and preserve the regeneration potential of a product throughout its life cycle.

Conclusion

According to the need to adopt a circular economy (CE) and the problems highlighted in literature, circular strategies (CS) are implemented in a punctual/individual way and the processes are mostly artisanal, this paper proposes to use a holistic vision to define the regeneration process which enables to support the CE. However, in this assumption, it would be necessary to analyze CS to study their differences and complementarities. So technical CS features from review are identified in section 2 and section 3 proposes a formalization to complete the CS characterisation to specify the CS more precisely, to be able in section 4, to position CS according to their technical features. Finally, a possible technical regeneration path is proposed to avoid losing value and preserving the regeneration potential of a product throughout its life cycle. So, this first characterization work raised several questions and perspectives: This first technical and systematic characterization of CS is a beginning. Indeed, in order to get a CS holistic approach, complementary characterizations from an environmental, economic and social point of view should complete this work. By integrating these elements into the CS categorization it will be possible to choose the optimal CS for a product to be regenerated, with a multi-criteria decision-making system. This system will need to be fed with complementary data (product, market and CS features, ...) [START_REF] Vanson | End-of-Life Decision making in circular economy using generalized colored stochastic Petri nets[END_REF].

This paper promote the need of a holistic approach to define a regeneration process and implement multiple CS. We therefore propose in the design phase to develop, in addition to the product, a regeneration system that will support the product family throughout the product life cycle. Thus, a product, its manufacturing system and its regeneration system must be co-designed to consider their interactions. So, the CS characterization in Section 3 can be used to determine the outputs, activities, and input conditions of the CS to build the regeneration system. Through this co-engineering, it would therefore be possible to avoid skipping regeneration loops and implement a realistic CE.

Fig. 1 .

 1 Fig. 1. Origin of the baseline requirements and the formalization method illustration.

Fig. 2

 2 Fig. 2 illustrates the above explanations by positioning CS according to the comparison gap between a regenerated product and an equivalent new product. In addition, CS are positioned according to what the CS activities can regenerate.

Fig. 2 .

 2 Fig. 2. CS positioning according to the comparison gap between a regenerated product with an equivalent new product and the regeneration level process.

Fig. 3 .

 3 Fig. 3. CS positioning synthesis to avoid value loss and preserve the regeneration potential of a product throughout its life cycle.

Table 1 .

 1 CS technical features in the literature

			new product composed	diagnostic,	cleaning,
			with different components	requalification, replace-
				ment,	disassembly,
				Re-Assembly	and
				reworking
	Resynthesis	Several sub-assemblies	A new product but now for				Sub-assemblies	/
	[8], [9]	and components from	another finality and com-				Components
		different product fami-	posed with different compo-
		lies	nents from different product
			families
	Recycling [5],	Several products mate-	Recycled material	diagnostic,	Sort	and	Material
	[6], [16], [3]	rial		Separate
	Energetic Val.		Energy	Combustion or Metha-	Wastes
	[17]			nization
	Landfill [24]		Wastes	Stock			No


Durrieu Gaël
email: gael.durrieu@univ-tln.fr

Layglon Nicolas
email: nicolas.layglon@unige.ch

D ' Onofrio Sébastien

Oursel Benjamin
email: benjamin.oursel@mio.osupytheas.fr

Omanović Dario
email: omanovic@irb.hr

Garnier Cédric
email: cgarnier@univ-tln.fr

Mounier Stéphane
email: stephane.mounier@univ-tln.fr

Onofrio D'

Oursel Sébastien

Omanović Benjamin

Garnier Dario

Mounier Cédric

Stéphane

Extreme hydrological regimes of a small urban river: impact on trace element partitioning, enrichment and fluxes

Keywords: small river, trace metals, urban impact, Extreme event

The input of trace elements from a small urban river (Las River, Toulon, France) located on the northern Mediterranean coast was studied during both base flow and flood events. A two-year monitoring period of water flow and suspended particulate matter (SPM) showed a typical Mediterranean hydrological regime: a strong increase in water flow and SPM during short flood periods. During the flood event, an up to 2-fold increase in dissolved trace element (D TM) concentrations and particulate trace element content in SPM (PTM) was observed compared to the baseline discharge.

The enrichment factor of elements in the SPM ranges from low or moderate for Co, Ni and Cr (1.0 -4.7) to extremely high for Cd (157). However, the enrichment factors decrease from base flow to flood, indicating a dilution effect with a large yield of weathering particles with higher particle size. The most significant total trace element loading occurred during flood, ranging from 78 % for As and Ni to 91 % for Pb, while PTM loading during flood ranged from 35 % for As to 77 % for Pb. The specific dissolved fluxes during the flood are significantly higher for Pb, Cu and Zn than in the surrounding rivers, indicating specificity in the catchment (lithology). This study shows the importance of monitoring the transport of pollutants through small urban rivers and their potential impact on the coastal region, especially when they enter small and closed bays, as a receiving pool.

Introduction

Rivers are known to be an important transport route for pollutants from the continent to coastal areas [START_REF] Viers | Chemical composition of suspended sediments in World Rivers: New insights from a new database[END_REF]. Overall, river runoff is the main source of metals and metalloids entering the waters of the continental shelf [START_REF] Olías | Evaluation of the dissolved contaminant load transported by the Tinto and Odiel rivers (South West Spain)[END_REF][START_REF] Viers | Chemical composition of suspended sediments in World Rivers: New insights from a new database[END_REF] and therefore the transport of most contaminants depends on the runoff, resulting from the precipitation regime in the river basin. The meteorological regime of the Mediterranean area is characterised by long dry summers and mild winters. Long periods without rain (with accumulation of contaminants on the surfaces of the catchment areas) are very often interrupted by short but intense rainfalls [START_REF] Bernal | Hydrological extremes modulate nutrient dynamics in mediterranean climate streams across different spatial scales[END_REF][START_REF] Cowling | Rainfall reliability, a neglected factor in explaining convergence and divergence of plant traits in fire-prone mediterraneanclimate ecosystems[END_REF][START_REF] Miller | Canopy Structure of Mediterranean-Type Shrubs in Relation to Heat and Moisture[END_REF] during which urban runoff, erosion and sediment resuspension occur. Consequently, water quality is known to be affected by elevated trace metal concentrations (Cobelo-García et al., 2004;[START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF]Oursel et al., 2014). Another characteristic of flash flooding in Mediterranean regions is that it brings with it a considerable amount of suspended matter of natural or anthropogenic origin, which serves as a vector for trace metals , [START_REF] Dumas | Riverine transfer of anthropogenic and natural trace metals to the Gulf of Lions (NW Mediterranean Sea)[END_REF][START_REF] Meybeck | River sediment transport and quality: From space and time variability to management[END_REF][START_REF] Pont | Medium-term Changes in Suspended Sediment Delivery to the Ocean: Consequences of Catchment Heterogeneity and River Management (Rhône River, France)[END_REF]. This particular system requires an adapted sampling protocol to take into account the actual pollutant load. The large fluctuations in precipitation lead to extreme variations in runoff and thus in the fluxes of chemical elements. As a result, high-frequency sampling is required during flood events (intraday frequency), while regular sampling (weekly or monthly) is sufficient during baseflow. Furthermore, understanding the relationships between catchment characteristics (bedrock and lithology), anthropogenic activities (land use in the catchment) and river flow (dam discharges and precipitation) is crucial for developing spatial models for trace metals in a temperate continental shelf such as the Toulon Bay (France) [START_REF] González-Ortegón | Trace metal characterization and fluxes from the Guadiana, Tinto-Odiel and Guadalquivir estuaries to the Gulf of Cadiz[END_REF]. Moreover, small rivers play an important role in the coastal zone of the Mediterranean because of their number [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF][START_REF] Roussiez | Fate of metals in coastal sediments of a Mediterranean flood-dominated system: An approach based on total and labile fractions[END_REF]. Therefore, it is particularly important to ensure a good assessment of metal fluxes in urbanised coastal areas, as they contribute significantly to the total amount of trace metals in the environment. Furthermore, when inputs occur in a semi-enclosed bay, metal inputs can lead to a contamination gradient due to low tides and low water turnover. In Toulon Bay (France), for example, there is a strong gradient of metal contamination in the sediments [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF] for which it was found to affects benthic prokaryotic diversity [START_REF] Misson | Chemical multicontamination drives benthic prokaryotic diversity in the anthropized Toulon Bay[END_REF] and has implications for the quality of mussels farmed in the bay [START_REF] Dang | Evidencing the Impact of Coastal Contaminated Sediments on Mussels Through Pb Stable Isotopes Composition[END_REF]. Sediment resuspension has been shown to influence the chemical and biological quality of Toulon Bay [START_REF] Layglon | Long-term monitoring emphasizes impacts of the dredging on dissolved Cu and Pb contamination along with ultraplankton distribution and structure in Toulon Bay (NW Mediterranean Sea, France)[END_REF]. In the same bay, a high gradient of dissolved trace metals in the water column was found to impact bacterioplanktonic and phytoplanktonic communities [START_REF] Coclet | Trace metal contamination as a toxic and structuring factor impacting ultraphytoplankton communities in a multicontaminated Mediterranean coastal area[END_REF][START_REF] Coclet | Changes in Bacterioplankton Communities Resulting From Direct and Indirect Interactions With Trace Metal Gradients in an Urbanized Marine Coastal Area[END_REF][START_REF] Coclet | Impacts of copper and lead exposure on prokaryotic communities from contaminated contrasted coastal seawaters: The influence of previous metal exposure[END_REF][START_REF] Layglon | Long-term monitoring emphasizes impacts of the dredging on dissolved Cu and Pb contamination along with ultraplankton distribution and structure in Toulon Bay (NW Mediterranean Sea, France)[END_REF]. This gradient could be also due to the river input like the Las river which is first rural and then becomes more urbanized along its crossing [START_REF] Dufresne | Compréhension et analyse des processus hydro-sédimentaires de la Baie de Toulon[END_REF]. Since the watershed is not much industrialized and the municipalities crossed fairly well cleaned up the quality of the river water should be good even though not much information are available concerning this river. That's why, until now, it is unclear what is the most important driver in bay contamination: river inputs, sediment resuspension, aerosol or river inputs.

The annual fluxes of contaminants to the coastal region by rivers are commonly estimated based on average level of contaminants concentration and average river discharge. However, the dynamics of the fluxes, i.e. base flow vs. flood events, was not always considered due to the logistical problems. Hence, the Las River (Toulon, France) was used as a model of a small Mediterranean urban river characterised by extreme hydrological regimes due to the episodic heavy rain events. This work aimed to (i) Characterise the inputs of trace metals during base flow and flood events, to (ii)estimate the contribution of these inputs to the bay.

Materials and methods

Site description

The Las River is an 8 km long urban river located in south-eastern France near the city of Toulon on the north-western coast of the Mediterranean Sea. Its catchment is located in a predominantly calcareous area [START_REF] Baudement | Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)[END_REF]. In the upper part it is mainly composed of forest, small agricultural zones and two stone quarries and in the lower part it is urbanised. The area of the catchment is estimated at 60 km², but due to the karst type, water from another aquifer can enter in the watershed [START_REF] Dufresne | Compréhension et analyse des processus hydro-sédimentaires de la Baie de Toulon[END_REF][START_REF] Lamarque | Établissement d'une courbe de tarage des débits du cours d'eau du Las réalisée d'août à décembre[END_REF]. It starts at an altitude of 100 m after the Dardennes dam (43°10'29.23" N; 5°55'49.13" E) which is used for drinking water supply, but also causes karst flash floods downstream in the urban area [START_REF] Baudement | Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)[END_REF]. The bed of the river consists in coarse gravel and crushed stone [START_REF] Dufresne | Karst and urban flood-induced solid discharges in Mediterranean coastal rivers: The case study of Las River (SE France)[END_REF]. In the middle course, the Las River is channelised with concrete and covered over a length of about 2 km. The river flows into the sea in the little bay of Toulon (43°6'58.11" N;5°53'27.81" E) within a military zone. This little bay is a semi-enclosed bay of about 9.1 km² characterized by an average depth of 10 m and separated from the large bay by a dyke.

The rainfall regime of the region is Mediterranean and is subject to high (inter)annual variability. For example, precipitation in Toulon averaged 670 mm in 2013-2018, with a minimum of 270 mm in 2017 and a maximum of 1120 mm in 2014 (Météo France, La Mitre station), and most rain occurred from October to April.

Sampling

To consider the most important part of the river, the sampling point (43°7 '22.44" N; 5°53'44.20" E) is located 900 m before the confluence with the sea (Fig. 1). To our knowledge, there are no further water inflows after this point.

The sampling strategy consisted in sampling during base flow and flood events, using the passive and manual sampling of suspended particulate matter and water. Sensus Ultra (ReefNet Inc.) loggers were used to monitor the water column pressure (depth) and temperature (at 10 min intervals) in the period from March 2017 to March 2019, while a multi parameters probe (600-OMS-V2, YSI) was additionally used to monitor turbidity, conductivity, depth and temperature in the period from January 2018 to March 2019.

Before sampling, all FEP (Fluoro Ethylene Propylene) and HDPE (High Density Polyethylene) sampling bottles (Nalgene) were cleaned with 10 % v/v HNO3 (Fisher scientific, Analytical Reagent grade), rinsed 3 times with Milli-Q water (resistivity 18.2 MΩ; Milli-Q Direct 8, Millipore) and filled with Milli-Q water acidified with 0.1 % HCl (Carl Roth, Rotipuran supra) until sampling. Glass bottles (Wheaton 24 mL) and a glass filtration system were cleaned with 10 % v/v HCl (Fisher scientific 37 %, Analytical Reagent grade), rinsed 3 times with Milli-Q water before being combusted for 6 h at 450 °C. Glass fibre filters (Whatman GFF, 0.7 µm) were combusted for 6 h at 450 °C, placed in an oven (60 °C) until constant weight was measured. The strategy of sampling needed to combine a long-term monitoring of the river during the base flow and punctual sampling of flood events. For that purpose, during base flow samples were taken every month to cover the seasonal and temporal variability. The detail sampling of the major flood event monitored on 10/10/2018 is described below.

Sampling during the base flow

In total, 24 monthly sampling campaigns were conducted under base flow conditions from 20/2/2017 to 20/2/2019. For each campaign, 4 L of water was taken directly in the stream (after rinsing the sampling bottle 3 times with the stream water) for dissolved and particulate fraction analysis. In addition, using two deployed loggers and a YSI probe, the main physico-chemical parameters (temperature, specific conductivity, redox, pH, chlorophyll-a), were punctually measured each time using the Hydrolab DS5 multi-probe.

Sampling during the flood event

The strong rainy event (94 mm rain in 24 h, Météo France, La Mitre) occurred on 10/10/2018 was selected as a representative flood event. Samples were collected in a period from 11 h UTC to 24 h UTC. A precleaned HDPE bucket with a rope was used to collect river water from the bridge (43°7 '22.44" N; 5°53'44.20" E). An integrative sampling strategy was used: depending on river discharge, estimated by water height, every 10 min during 1 h or every 20 min during 2 h, an aliquot of (1) 150 mL of bulk water was pooled in a 1 L HDPE bottle for further analysis of particulate material and (2) a 60 mL of sample was filtered using a 0.2 µm cellulose acetate (CA) syringe filter (Minisart, Sartorius) and pooled in a 0.5 L FEP bottle for analysis of dissolved trace elements. In this way, a total of 11 composite samples of (1) bulk (unfiltered) water and (2) filtered water were collected during the whole flood event.

Time-Integrated Suspended Particulate Matter (SPM TI ) sampling A sediment trap [START_REF] Phillips | Time-integrated sampling of fluvial suspended sediment: a simple methodology for small catchments[END_REF] made of a stainless-steel tube of 1 m length and 98 mm internal diameter (Fig. SI 1, in Supplementary Information) was used to continuously collect suspended particulate matter (SPMTI). The details about the sample and principle of the work are provided by [START_REF] Phillips | Time-integrated sampling of fluvial suspended sediment: a simple methodology for small catchments[END_REF]. In short, water entered into the sampler through a 4 mm hole facing towards the water stream. Due to the increase of the internal diameter of the tube, an internal flow of the water was suddenly slowed down, allowing settlement of the particles inside of the tube. The sediment trap is designed to collect SPMTI at small streams. The period of deployment was adjusted depending on meteorological conditions (from some days during flood to 1.5 month during base flow) to finally get a set of SPMTI corresponding to contrasted flow periods (12 samples under base flow and 5 samples under flood). The whole quantity of water and SPMTI in the trap was transferred in a 10 L HDPE bottle. After one day of sedimentation in a cold place, supernatant was removed and SPMTI was placed in a 150 mL HDPE bottle, frozen and freeze-dried thereafter.

Calculation of river flow

The determination of the flow is a key parameter when studying river inputs. In order to precisely determine the water height of the river, two devices were used: a limnometer and a pressure sensor. The first device gives the official water height certified by authorities (HLimn) and the second one gives a high frequency measurement of water pressure (Psensor).

Water pressure from the sensor was measured every 10 min and was corrected by the daily average atmospheric pressure from Météo France services and transformed into water height (HSensor). By using the certified measurement, a linear regression (R 2 =0.98, N=12) was done between HLimn and HSensor and used to transform all the Hsensor into HLimn'.

From this extended HLimn' data set, the rating curve established by [START_REF] Lamarque | Établissement d'une courbe de tarage des débits du cours d'eau du Las réalisée d'août à décembre[END_REF]) was used to obtain the high frequency river discharge. This rating curve has been validated for limnometer heights between 0.35 m to 1.85 m which corresponds to the heights measured during our monitoring. In accordance with previous study from [START_REF] Dufresne | Karst and urban flood-induced solid discharges in Mediterranean coastal rivers: The case study of Las River (SE France)[END_REF], the threshold of 1 m 3 s -1 was defined as the limit between base flow and flood. Table SI 2

High frequency suspended particulate matter (SPM HF ) determination

Another key parameter when studying river inputs is the SPM concentration. As shown previously, this parameter is highly correlated to the turbidity [START_REF] Dufresne | Compréhension et analyse des processus hydro-sédimentaires de la Baie de Toulon[END_REF][START_REF] Dufresne | Karst and urban flood-induced solid discharges in Mediterranean coastal rivers: The case study of Las River (SE France)[END_REF]. This property is used to estimate SPM from high frequency measurement of turbidity probe, calibrated by using discrete SPM measurement from GFF filtration (SPMGF). First, the data outliers due to sensor clogging were replaced using a specific filter described in Fig. SI 3.

Secondly, turbidity > 1 NTU was transformed in SPMHF by using the linear relation between SPMGF values and corresponding turbidity measurement (R 2 =0.98, N=20). This concerns 25 % of the data set. Thirdly, for low turbidity, < 1 NTU or "nd" or data associated to flow < 1 m 3 s -1 , the average of all measured SPMGF concentration during base flow was applied (SPMHF =avg(SPMGF) = 1.13 +/-0.34 mg L -1 ). This concerns 69 % of data set. Finally, for turbidity < 1 NTU or "nd" associated to a flow > 1 m 3 s -1 , as it is not base flow measurement, a specific linear relation (R²=0.81, N=16) between SPMGF and flow was used to avoid underestimation of SPMHF. This concerns 6 % of data set. The final data contains N = 103,282 SPMHF data between 2017 and 2019.

Filtration, treatment and preservation of samples

Samples for dissolved organic carbon (DOC) analysis were filtered at the laboratory using a 25 mm glass fibre filter (Whatman GFF, 0.7 µm) during the base flow, whereas during the flood an in-line 0.2 µm cellulose acetate syringe filter (Minisart, Sartorius) was used for on-site samples filtration. Before taking the final sample, the syringe filter was rinsed several times with the ambient water (washed in this way, the blanks of DOC in Milli-Q were negligible). The filtrates were collected in 24 mL pre-combusted glass tubes (Wheaton), preserved with 0.2 % HCl (Carl Roth 37 % Rotipuran supra) and stored at 4 °C before analysis. The GFF filters were used to measure particulate organic carbon (POC) and SPMGF concentrations. Filters were dried overnight in an oven at 60 °C and thereafter stored at room temperature in a closed box with a drying agent before weighting for SPMGF content. For POC analysis, the GFF filters were exposed to HCl fumes during 4 h in a glass desiccator to remove inorganic carbon, and after that stored in a fume hood during 3 h and overnight in an oven at 60 °C before analysis [START_REF] Lorrain | Decarbonation and preservation method for the analysis of organic C and N contents and stable isotope ratios of low-carbonated suspended particulate material[END_REF].

For analysis of dissolved trace metals (DTM), samples were filtered at the laboratory by using cellulose acetate filters (47 mm, 0.2 µm, Sartorius) during the base flow. Before filtration, the filters were cleaned with 100 mL of 10 % v/v HNO3 (Fisher scientific, Analytical Reagent grade), then with 1 L Milli-Q water acidified with 0.1 % HCl (Carl Roth 37 %, Rotipuran supra) and finally rinsed with Milli-Q water. Then, the filtrate was collected in an 8 mL HDPE bottle and preserved with 0.5 % HNO3 (Carl Roth 69 %, Rotipuran supra) for further ICP-MS measurement of DTM. During periods of flooding, samples for dissolved fractions were filtered on-site by using in-line 0.2 µm cellulose acetate syringe filters (Minisart, Sartorius). In-line syringe filters were cleaned by filtering 2 x 60 mL of 0.1 % v/v HNO3 (Fisher scientific, Analytical Reagent grade), and then 2 x 60 mL of river water. After filtration in the field, the filtrate was split for DTM and major analysis. For analysis of particulate trace metals (PTM) and SPM concentrations, water was filtered at the laboratory using cellulose acetate filters (47 mm, 0.2 µm, Sartorius).

All filters from base flow and flood samples filtration were placed overnight in an oven at 60 °C and then placed 1 h in an oven at room temperature with a drying agent before weighing. Both GFF and cellulose acetate filters were used to determine SPM concentration (mg L -1 ) in discrete samples (further denoted as SPMGF).

Cellulose acetate filters (47 mm, 0.2 µm, Sartorius) and SPMTI (see section 2.3) were mineralised by microwave digestion (Milestone, UltraWAVE ECR) for the determination of trace element concentrations in particulate and solid samples. Filter or 100 mg of SPMTI were placed in a 15 mL teflon tube with aqua regia (mixture of 7.5 mL HCl and 2.5 mL of HNO3 (Carl Roth, Rotipuran supra) and mineralized (temperature range from ambient to 240 °C in 20 min and hold during 20 min, while pressure ranges from 30 bar to around 70 bar). After digestion the whole volume of digestate was transferred in a 30 mL HDPE bottle and diluted to a final volume of 25 mL for further ICP-MS measurement of particulate trace metals (PTM). The PTM was then expressed in trace metal content in µg g -1 of SPM using SPMGF or SPMTI.

Analysis of parameters

DOC

DOC was determined by high temperature combustion at 720 °C using a TOC-V Analyser (Shimadzu®), calibrated using potassium hydrogen phthalate standard. The limit of quantification is 0.1 mgC L -1 with a good linearity from 0.1 to 50 mgC L -1 . Quality control (QC) of measurements was checked every run by the determination of element concentration in "a Lake Water Reference Material" (SUPER-05, Environment and Climate Change Canada). Certified values for DOC is 1.28 mgC L -1 . Obtained values for the whole data set agreed with certified values within 2 %.

POC

POC was determined using a Flash 2000 NC Soil Analyser (Thermo Scientific®). Carbon was measured by flash combustion at 930 °C in tin capsules. The limit of detection was 5 µg, and the calibration curve ranges respectively from 5 to 1100 µg. Quality control (QC) of measurements was checked by the determination of element concentration in "NC Soil" (Thermo Fisher Scientific). Certified values for POC is 2.29 % C. Obtained values for the whole data set agreed with certified values within 1 %. In the following text, POC concentration refers to mass of POC per volume of water and POC content refers to mass of POC per mass of SPM.

Trace elements

DTM and PTM (Al, As, Cd, Co, Cr, Cu, Ni, Pb and Zn) were determined by High Resolution Inductively Coupled Plasma Mass Spectrometer (HR ICP-MS, Element 2, Thermo Finnigan, Bremen, Germany). The samples for the analyses were prepared in pre-cleaned polypropylene tubes (Sarstedt). Freshwater samples were analysed undiluted (acidified to 2 % v/v HNO3, ROTIPURAN Supra, Carl Roth), whereas an appropriate dilution (5-10×) for digested SPMGF or SPMTI samples was used. Indium ( 115 In) was used as an internal standard. Quality control (QC) was checked by the determination of element concentration in "River Water Reference Material for Trace Metals" (SLRS-5, National Research Council Canada) and PACS-2 for sediment samples.

Calculation of parameters

Load of TM

For the dissolved fraction, the calculation of the load (DLTM in g) is defined as:

D L TM = ∑ i=1 n (V i × D TM ,i ×10 -3 ) equation 1
where DLTM is the dissolved load of a given element (g) during observation 1 to n, DTM,i is the dissolved concentration of a given trace metal (µg L -1 ) and Vi is the volume of river water (m 3 ) between two observations i and i+1. We distinguished two conditions for the load calculation. During the base flow (flow < of 1 m 3 s -1 ) DTM,i concentration corresponds to the concentration measured from the date of sampling (observation i) until the next sampling (observation i+1). For unsampled flood events (flow > of 1 m 3 s -1 ), DTM,i concentration was estimated from the relationship between DLTM and Q during the flood sampling on 10 th October 2018. For the 8 studied elements the R² coefficient varied between 0.86 and 0.98, depending on the element (SI 4).

The particulate fraction calculation of the load (PLTM) was defined as:

PL TM = ∑ i=1 n (SPM Mass ,i × P TM , i × 10 -6 ) equation 2
where PLTM is the particulate load of a given trace metal (g) during observation 1 to n, PTM,i is the content of a given trace metal during observation to i+1 (µg g -1 ) in SPMTI, SPMMass,i is the mass of SPMHF (g) during observation i to i+1.

Enrichment factor (EF)

To distinguish the lithogenic from an anthropogenic origin of trace metals in particles, enrichment factors were calculated. For that purpose, aluminium is assumed as a normalizer element and the concentration of the upper continental crust (UCC) proposed by [START_REF] Rudnick | Composition of the Continental Crust[END_REF] as the lithogenic background. The enrichment factor is calculated as follows:

EF TM ,i = P TM ,i P Al , i P TM ,UCC P Al ,UCC (equation 3)
where PTM,i is the particulate content of a given element in SPM (µg g -1 ) at observation i, PAl,i the aluminium content of the considered sample at observation i, PTM,UCC and PAl,UCC the element and aluminium content (µg g -1 ) respectively in the UCC. To compare the degree of enrichment the classification defined by [START_REF] Sutherland | Bed sediment-associated trace metals in an urban stream, Oahu, Hawaii[END_REF] was used. EF < 2: deficiency to low enrichment; EF 2-5: moderate enrichment; EF 5-20: significant enrichment; EF 20-40: very high enrichment; EF > 40: extremely high enrichment. In the present work for an element, EF TM will represent the mean of EFflood and EFbase flow if no distinction is given.

Distribution coefficient (K D )

To study the repartition of metals between the dissolved and the particulate fraction the distribution coefficient was calculated by the following equation:

K DTM , i = P TM ,i D TM ,i ×10 -3 (equation 4)
where KD TM,i is the distribution coefficient (L kg -1 ), PTM,i is the particulate content of a given element in SPMGF (µg g -1 ), as it is a punctual measurement, DTM,i is the dissolved concentration of the element (µg L -1 ) at observation i. For each TM, an optimised logKD during a flood or base flow is calculated using all PTM,i and DTM,i available from measured data using Excel Solver.

Statistical analysis

Microsoft Excel® XLSTAT add-on was used for statistical analyses. These tests were used to compare the data set for base flow versus for flood for each parameter. First, Grubbs' test was applied to remove extreme values (outliers). Then the Shapiro-Wilk test was applied to test the normality of each distribution. As all the distributions were not normally distributed, the non-parametric test of Mann-Whitney (with a p<0.05) was applied to determine differences between the base flow and the flood data set.

Results and discussion

Main physico-chemical parameters

The average values of the main physico-chemical parameters (SPM, river flow, temperature, conductivity, dissolved oxygen and chlorophyll-a) obtained for the base flow and flood events are presented in Table SI 5, along with data from other similar water systems. A clear difference between the base flow and the flood was observed for SPM and the river flow. The average increase by a factor 34 and 20 during the flood event was evidenced for SPM GF and the flow, respectively. Compared to other Mediterranean rivers (Table SI 5), the increase of SPM is slightly higher, regardless of the watershed size, likely due to the Las River geology being composed of karstic rocks [START_REF] Baudement | Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)[END_REF].

Moreover, it should be highlighted that in these two years of study the flood occurred "only" 20 % of the time, but it accounts for 69 % of the total water discharge and 78 % of the solid material yield. These results are close to ones previously reported by [START_REF] Dufresne | Compréhension et analyse des processus hydro-sédimentaires de la Baie de Toulon[END_REF][START_REF] Dufresne | Karst and urban flood-induced solid discharges in Mediterranean coastal rivers: The case study of Las River (SE France)[END_REF] for the period October 2012 to January 2014 (flood 30 % of the time, 85 % of the water discharge and 85 % of the solid material yield). Temperature, conductivity, dissolved oxygen and pH remain stable regardless of the water regime. Chlorophyll-a is the only parameter that increases from base flow to flood. This indicates an increase of phytoplankton abundance, however there is also a high probability that the increase is related to the measurement artefact caused by high turbidity, which was often seen when the probe touches the sediment.

Dissolved and particulate carbon concentrations

Average concentrations of organic carbon in dissolved and particulate phases are presented in Table 2. DOC concentration is in the same range of other Mediterranean rivers from the same region, with a similar, 3-fold increase during the flood over the base flow. POC concentrations are slightly smaller than other surrounding rivers mainly because of a smaller SPM concentration (Table SI 5). The POC fraction (POC/(DOC+POC)) increased from 12 % during the base flow to 47 % during the flood. Nevertheless, in terms of OC content in SPM, the values obtained in the Las River are in the same range as the Huveaune, Jarret and Eygoutier Rivers, but higher than the Rhône River. For all rivers OC content in SPM is 2-fold higher during the base flow compared to flood (Table 2). This trend is attributed to a dilution of POC by addition of mineral particles resulting from erosion processes (Oursel et al., 2014).

Table 2. DOC (in mgC L -1 ), POC (in mgC L -1 and mgC g -1 ) in Las River during base flow and flood, Rhône River [START_REF] Sempere | Carbon inputs of the Rhône River to the Mediterranean Sea: Biogeochemical implications Carbon inputs of the Rhône River to the Mediterranean Sea: Biogeochemical implications[END_REF], Huveaune and Jarret Rivers [START_REF] Oursel | Dynamics and fates of trace metals chronically input in a Mediterranean coastal zone impacted by a large urban area[END_REF]Oursel et al., 2014), Eygoutier River [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF]. For Las River, " §" refers to average and sd without extremes values, "*" refers to min-max values including extremes values.

Dissolved and particulate trace metal concentrations

The average and variation range of trace metal concentrations during the base flow and flood for the Las River compared to the rivers from the same part of Mediterranean coast (Rhône, Huveaune, Jarret, and Eygoutier Rivers), and to the world average and upper continental crust are provided in Table 3 for dissolved TM and in Table SI 5 for particulate TM content.

Dissolved trace metal concentrations (D TM )

For most of the DTM in the Las River, the values are in the same range of concentrations during the base flow and the flood, except for Cr, Co and Zn, for which the two regimes are statistically different (p < 0.05, Mann-Whitney) with an increase by a factor 2. This is also the case for Al with an increase by a factor 3. An hypothesis to explain this increase could be the presence of colloids of aluminium oxids from clays minerals weathering and their association with Cr, Co and Zn. Although concentrations of Pb between the base flow and the flood are not statistically different (due to high variability), it should be highlighted that average Pb concentrations are by factor 2 higher during the flood. Despite being an urban river, according to DTM, the Las River could be characterised by a non-polluted karstic river. Indeed, all mean concentrations are below the European Quality Standards (EQS) except for Cu under flood regime (Table 3).

Compared to the world's river averages, DTM concentrations are higher for Zn, equivalent for Pb and lower for all other metals.

Table 3. Dissolved concentration of trace elements (in µg L -1 ) in Las River during base flow and flood, Rhône River [START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF], Huveaune and Jarret Rivers [START_REF] Oursel | Dynamics and fates of trace metals chronically input in a Mediterranean coastal zone impacted by a large urban area[END_REF]Oursel et al., 2014), Eygoutier River [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF], European Quality Standards (EQS), world river average [START_REF] Gaillardet | Trace Elements in River Waters[END_REF][START_REF] Viers | Chemical composition of suspended sediments in World Rivers: New insights from a new database[END_REF]. For Las River, " §" refers to average and sd without extremes values, "*" refers to min-max values including extremes values.

Particulate trace metal content in SPM (P TM )

Particulate trace metal content (PTM) observed in the Las River (Table SI 5 For any of the considered metals, no regularity could be extracted for the base flow and the flood events, between different rivers and the world averages. A short description of PTM tendencies is provided in Table SI 6.

Lastly, it stands that all metal contents in SPM are above the UCC average whatever the period except Co. Moreover Cd, Cu, Zn and Pb are over or in the range of the world's river average content. So an enrichment factor of these elements in Las River SPM calculation will give more information concerning possible anthropogenic inputs.

Enrichment Factor (EF)

Average enrichment factors for measured elements for the base flow, the flood event and for SPM collected by discrete (SPMGF) and time integrative (SPMTI) sampling are presented in Fig. 2. Among the eight studied elements Co showed the lowest EF (EF < 2) indicating the absence of the anthropogenic contribution, while the highest EF was obtained for Cd (EF > 150; for SPMGF). Therefore, high EF of Cd indicates a potential strong anthropogenic influence or a different composition of the weathered rocks/soils compared to UCC composition. Assuming that the carbonate background of the watershed is composed mainly of limestone and dolomite [START_REF] Durozoy | Ministère de l'industrie[END_REF][START_REF] El Houssainy | Apports et géochimie sédimentaire des éléments traces métalliques dans deux zones côtières méditerranéennes urbanisées : Beyrouth (Liban) et Toulon[END_REF], there is high probability that dolomites are enriched in Cd, as it was already found for other karstic carbonate regions [START_REF] Cuculić | Natural and anthropogenic sources of Hg, Cd, Pb, Cu and Zn in seawater and sediment of Mljet National Park, Croatia[END_REF][START_REF] Vukosav | Heavy metal contents in water, sediment and fish in a karst aquatic ecosystem of the Plitvice Lakes National Park (Croatia)[END_REF]. Enrichment factors for all metals are higher in samples collected during the base flow. This trend has already been observed in other rivers [START_REF] Benoit | Partitioning of Cu, Pb, Ag, Zn, Fe, Al, and Mn between filter-retained particles, colloids, and solution in six Texas estuaries[END_REF][START_REF] Miller | Baseflow and stormflow metal fluxes from two small agricultural catchments in the Coastal Plain of the Chesapeake Bay Basin, United States[END_REF]. This indicates that during flood the particles are less enriched than during the base flow. This could be linked to the weathering of more crustal material containing less metals (Cobelo-García & Prego, 2004;[START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF]. This is supported by an increase of Al content during flood (Table SI 6 EF observed for the Las River are higher than those observed in the Rhône River [START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF] due to an higher urban surface in Las River watershed (about 30% for Las River against 3.8% for Rhône River). In the Rhône River only Pb, Cd and Zn were considered as enriched (EF higher than 3) whereas Cu, Ni, Co and Cr were around 1.5. Using average data from Table SI 6, enrichment factors were calculated for trace metals in Las, Huveaune, Jarret, Eygoutier and Rhône Rivers during base flow and flood and compared to the average world river SPM (Table SI 7). For Cd, Pb, Cu, Zn and As in Huveaune River and Cd, Cu and Zn in Jarret River we observed a very high enrichment factor and an extremely high enrichment of Pb in the Jarret River which is the most urbanised watershed (about 50%). In general, during floods EF is less important in the Las River than in the Huveaune and Jarret, but higher than in Rhône River which is the less urbanised catchment.

Fig. 2 also points out the differences between SPMGF and SPMTI. For all metals, the EFs during the flood were higher for particles collected using time-integrated passive sampler (SPMTI) than for grab samples (SPMGF). Nevertheless, this difference is only significant for Co, Ni and Zn (Mann-Whitney, p<0.05). This difference was attributed to the difference of sampling method and possible variability in the SPM composition [START_REF] Lučić | Sedimentological and geochemical characterization of river suspended particulate matter (SPM) sampled by time-integrated mass flux sampler (TIMS) in the Sava River (Croatia)[END_REF][START_REF] Lučić | Appraisal of geochemical composition and hydrodynamic sorting of the river suspended material: Application of time-integrated suspended sediment sampler in a medium-sized river (the Sava River catchment)[END_REF]. This could also be related to the particles size, as in average the lower grain size with the higher specific surface is collected using integrative sampler. During base flow, mean EF are similar whatever the way particles were collected, for all metals except Cd, Cr and Co.

Partitioning between particulate and dissolved fraction

The partitioning of trace metals based on the calculation of the distribution coefficient (KD) was studied to estimate Cobelo-García et al. ( 2004) described a negative relation between KD of trace metals and SPM concentrations explained by an organic rich SPM predominant during base flow and a detrital SPM, poor in metals and increasing with flow. [START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF]) also presented this relation with a negative trend for some metals (Ni and Cu) and not significant for Zn and Pb. This negative trend could also be related to the effect of the particle concentration on the trace metal partition between the water and particles, named "particle concentration effect" as discussed by [START_REF] Benoit | The influence of size distribution on the particle concentration effect and trace metal partitioning in rivers[END_REF], with a various of causes. In our case, a negative trend is observed for Cd, Cu and Zn.

The optimised logKD for Cu, Pb, Cd and Zn are consistent with literature (Cobelo-García et al., 2004;[START_REF] Deycard | Contributions and potential impacts of seven priority substances (As, Cd, Cu, Cr, Ni, Pb, and Zn) to a major European Estuary (Gironde Estuary, France) from urban wastewater[END_REF][START_REF] Miller | Baseflow and stormflow metal fluxes from two small agricultural catchments in the Coastal Plain of the Chesapeake Bay Basin, United States[END_REF][START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF]Oursel et al., 2014). Copper is known to have a great affinity for organic matter. POC content being higher during base flow in the Las River but also in other rivers (Table 2), this could explain the higher logKD of Cu during base flow compared to flood (Fig. 3-B).

The optimised logKD for Co are consistent with the values from [START_REF] Miller | Baseflow and stormflow metal fluxes from two small agricultural catchments in the Coastal Plain of the Chesapeake Bay Basin, United States[END_REF] under base flow (5.0) but slightly higher than those observed during the flood compared to the Huveaune and Jarret rivers (Oursel et al., 2014).

Concerning Ni and Cr, the logKD are significantly higher than the one observed in previous works and seem not to be influenced by the hydrologic regime [START_REF] Miller | Baseflow and stormflow metal fluxes from two small agricultural catchments in the Coastal Plain of the Chesapeake Bay Basin, United States[END_REF]Oursel et al., 2014).

Finally, logKD for As is the lowest in this study and it is consistent with value of Oursel et al. (2014) in Huveaune and Jarret rivers (3.9) and of [START_REF] Miller | Baseflow and stormflow metal fluxes from two small agricultural catchments in the Coastal Plain of the Chesapeake Bay Basin, United States[END_REF] in Chesterville Branch (4.4).

From Fig. 3 it can be noted that the percentage of particulate metal increases with increasing SPM concentration following the optimised logKD of each metal. So, according to the optimised logKD calculated under flood, particulate metals become prevailing over the dissolved ones at SPM concentration of above 20, 15, 3, 1 mg L -1 , for As, Cu, Cr and Pb, respectively. It is therefore clear that during the flood Cr and Pb load is dominated by the particulate fraction. 4). The rainfall for the second period (785 mm) was twice the former one (356 mm). As a results, the volume of water and the SPM load delivered by the Las River due to floods are different during the two periods. Between periods 1 and 2, the water and SPM load are 6 and 4 times higher, respectively (Table 4). On the contrary under baseflow conditions, the volume of water is quite similar during the two annual periods, while the SPM load is 3 times higher during the period 2 compared to the period 1 (Table 4). The values of SPM and flow are consistent with those found by [START_REF] Dufresne | Karst and urban flood-induced solid discharges in Mediterranean coastal rivers: The case study of Las River (SE France)[END_REF] for a year in 2013 (SPM: 707 t y -1 and flow: 58 Mm 3 y -1 ). [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF][START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF][START_REF] Oursel | Dynamics and fates of trace metals chronically input in a Mediterranean coastal zone impacted by a large urban area[END_REF]. Empty forms represent base flow data (BF) and full forms represent flood (F).

The specific fluxes, meaning annual load divided by the watershed surface [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF][START_REF] Ollivier | Major and trace element partition and fluxes in the Rhône River[END_REF], allowed us to compare rivers of different watersheds. Contrasting patterns were obtained for dissolved metals under base flow (Fig. 5). Specific cadmium flux in the Las River is equivalent to Jarret River (both are urban rivers), but it is significantly higher than the flux of the Eygoutier River (less urban river and less calcareous area than Las River). For Pb all specific fluxes are in the same range, highlighting nodifference in terms of sources of contamination between these catchments. For Co, Ni and As, the Las River is less contaminated than other surrounding watersheds. In the Las River, Cu and Zn fluxes are relatively equal to those found in the Eygoutier and Huveaune Rivers, but clearly lower than in the Jarret and Rhone Rivers. During flood comparison with the Rhone River changes. Contamination by Pb, Cu and Zn became predominant in the Las River whereas for Ni and As, the Rhône River is predominant (Fig. 5).

For all particulate metals under the base flow specific fluxes are in the same range of values as for the Eygoutier and Huveaune Rivers, but significantly lower than in the Jarret and Rhône Rivers (Fig. 5). A comparison with the Rhône River during the flood indicates a greater load of trace metals per km² related to the 10 times higher specific SPM flux of the Rhône River (Table SI 7). So, an extrapolation of our results to other Mediterranean rivers should be conducted with care as, the SPM can play an important role.

Contribution to the bay

From these particulate and dissolved fluxes, an estimation of contribution of the Las River trace metal inputs is calculated. These values are compared to the stock of trace metals in the upper (0-5 cm) sediment estimated in the little Bay of Toulon Bay [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF] for the particulate fraction. For the dissolved fraction these values are compared to an estimation stock of dissolved trace metals in the little bay, from concentrations measured in 2017 in surface (unpublished data) as described by [START_REF] Coclet | Trace metal contamination as a toxic and structuring factor impacting ultraphytoplankton communities in a multicontaminated Mediterranean coastal area[END_REF] and extrapolated to the whole volume. As a result, the annual particulate contribution of the Las River is less than 0.2 % for Cu, Pb, Zn (Table SI 9), so Las River is not the main contributor to the sediment contamination in the little bay. The annual dissolved contribution of the Las River varies among trace metals. For Cd, Pb, Cr, Ni, Cu and Zn it is between 21 and 48 %, around 4 % for As and 115 % for Co (Table SI 9). In these conditions the contribution of the Las River appears as not negligeable, compared to the water column stock.

Conclusions

This work highlights the importance of sampling strategy for small river studies. First, high-frequency monitoring of flow and turbidity as a proxy of suspended particulate matter is necessary to correctly account for these two key parameters. For chemical measurements monthly sampling during base flow was sufficient to obtain a correct annual load. However, it was important to consider flood differently than base flow (focus on flood). For floods, a relation between flux and flow can be used that allows extrapolation to unsampled flood events. The use of time-integrated SPM sampler allowed periodic collection of representative particles.

The results point out that for small Mediterranean rivers the flood represents the main regime for trace metal load (from 78 % for As to 91 % for Pb) even if it occurs only 20 % of the time. Moreover, the impact of the flood was mainly dependent on the SPM flux and on the flow intensity. Indeed, a 2-fold increase in precipitation leads to an increase in volume and SPM discharge by a factor of 4 to 6 and consequently to a corresponding increase in TM load depending on its main affinity for dissolved fractions (e.g. As increase for the same volume increase) or particulate fractions (e.g Pb increase for the same SPM increase). It was also found that the yield of As, Cu, Co, Zn, Cd and Ni during base flow was mainly in the dissolved phase and for Pb in the particulate phase. During flood, the yield of As was mainly in the dissolved phase, while the yield of Cd, Ni, Cr and Pb was in the particulate phase. A decrease in the enrichment factor for all trace metals was observed from base flow to flood probably due to more neutral particles coming from the watershed erosion. Compared to other watersheds, we conclude that the specific dissolved fluxes for some metals could be higher in small rivers, but for the specific particulate fluxes the importance of SPM concentrations should be considered. Extrapolation of results from one catchment to a larger zone should therefore be considered with caution. In terms of contribution to the small bay, particulate trace metals annual yield is low compared to the high contamination of the sediment while dissolved trace metals annual input represents, for Cd, Pb, Cr, Ni, Cu and Zn 20 to 50 % of the dissolved stock.

Figure 1 .

 1 Figure 1. The Las River catchment area (green) and sampling station (red point). LiB= little Bay, LaB = Large Bay

  summarizes the flows during the different sampling campaigns.

  ) presents a small range of variation (0.4-fold for Cd and Cu to 1.8-fold for Co and 2.5-fold for Al) between the base flow and the flood. Nevertheless, for Cd, Cr, Co, Ni, Cu, As and Al the two periods are statistically different (p < 0.05, Mann-Whitney). For Cd and Cu, this difference consists of a decrease by a factor 2.5 of content during the flood, whereas it corresponds to a relative increase for Cr, Co, Ni, As and Al. Thus, the particles brought to the sea by the river during a flood are richer in Cr, Co, Ni, Zn and As, increasing the net mass contribution. This contribution could be associated with the average urban particle signature taking into account these five elements(Kaonga et al. 2021).

  ) and the statistical test of difference (Mann-Whitney test) conducted between the average EF of SPMGF, indeed for all TM a statistical difference is observed between flood and base flow regime (p < 0.05) except for As.

Figure 2 .

 2 Figure 2. Average Enrichment Factors (EF) of measured elements relative to Al content and UCC composition (Rudnick & Gao, 2014). EF is plotted in log scale during baseflow as a function of EF in log scale during flood for punctual SPMGF particles (blue) and integrated SPMTI (orange). Dotted line represents equivalent distribution. Colour scale of the EF legend is described on the left and corresponds to the colour of the axes. Error bars represent one standard deviation.

  whether the composition of particles is changing upon the different flow regimes. The percentages of particulate fractions as a function of SPMGF, along with the theoretical lines representing the different distribution coefficients are plotted in Fig. 3 and Fig. SI 8.From a general point of view, elements can be grouped depending on their different logKD. Arsenic presents a logKD around 4.6 (Fig.3-A), Zn, Cu, Ni, Co, and Cd have a logKD around 5 (Fig.3-B, example of Cu), Cr around 5.5 (Fig.3-C) and Pb around 6 (Fig.3-D).The optimised logKD are similar for the flood and the base flow for Cr, Co and Zn but different for Cd, Cu, As, Ni and Pb. This indicates different interaction properties of particles with respect to these trace metals. Cd and Cu have a higher KD during the base flow than during the flood, whereas it is the opposite for Pb, As and Ni (Fig.3and Fig. SI 7).

Figure 3 .

 3 Figure 3. Selected Particulate TM concentration in % as a function of SPMGF concentration (mg L -1 ) in log scale. Empty square represents base flow data and black disc represents flood. Black lines represent theoretical lines for logKD, blue line represents optimised logKD during flood and orange line represents optimised logKD during base flow. The Quadrant B for Cu is representative of Zn, Ni, Co, and Cd patterns.

Figure 4 .Figure 5 .

 45 Figure 4. Annual TM load in kg y -1 during two periods March 2017 to March 2018 (P1) and March 2018 to March 2019 (P2) for selected TM (As, Cu, Cr and Pb). For each period load is separated into flood and baseflow. On flood (F) histogram dark grey represents particulate load and wavy plot represents dissolved load. On the base flow (BF) histogram grey represents particulate load and white represents dissolved load. Errors bars represent 5 % of the value for dissolved fraction and 7 % of the value for particulate fraction. Value (in %) above each histogram refers to the particulate % in the histogram.

Table 4 .

 4 Hydrological conditions during the two studied periods. The annual load of each studied TM for the two separate periods are represented in Fig. 4, distinguishing base flow and flood on separate histograms and indicating on each histogram the proportion of particulate and dissolved load. For period 1 (3/17 to 3/18), the flood inputs are dominant and represents from 50 % to 87 %, for As to Pb, respectively. It seems consistent because As is predominantly delivered in a dissolved form irrespective of the hydrologic regime and Pb is predominantly delivered under particulate form for any hydrologic regime. During period 2 (3/18 to 3/19), the flood inputs are also dominant representing from 87 % to 92 %, from As to Pb, respectively. Taking into account the mean of the 2 years of the study, during the base flow period, Cd, Co, Ni, Cu, Zn and As are predominantly loaded under dissolved form (from 70 % for Ni to 93 % for As). Only Pb and Cr are predominantly delivered in particulate form with only 21 and 46 % under dissolved form respectively. These results are in accordance with the KD and the lower concentration of SPM under base flow regime. During flood, Cd, Pb, Cr and Ni prevailed under particulate form (respectively 62, 77, 65 and 62 %), Co and Zn are equally distributed (respectively 50 and 52 %) and lastly Cu and As prevailed in dissolved form (respectively 38 and 35 %). For Pb, Cr and As these findings are consistent with the optimised logKD determined. For metals like Cu (logKD around 5) the correlation between KD and percentage in particulate form is probably subjected to large uncertainty hiding the theoretical trend.

		3/2017-3/2018 (period 1) 3/2018-3/2019 (period 2)
		Base flow	Flood	Base flow	Flood
	volume (×10 6 m 3 )	8.1	4.9	7.9	30
	SPM (×10 6 g)	15	185	54	777
	Rain (mm)		356		785

Funding

This study was part of the METFLUX research project funded by the French water agency "Agence de l'Eau Rhône Méditerranée Corse" (convention n°2016-1364).

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

Data availability

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.