Raja Chatila

Simeon Lacroix

Thierry Simeon
email: simon@laas.fr

Matthieu Herrb
email: matthieu@laas.fr

Planetary Exploration by a Mobile Robot: Mission Teleprogramming and Autonomous Navigation

Keywords: mobile robots, mission teleprogramming, autonomous navigation

Sending mobile robots to accomplish planet exploration missions is scientifically promising and technologically challenging. We present in this paper a complete approach that encompasses the major aspects involved in the design of a robotic system for planetary exploration. It includes mission teleprogramming and supervision at a ground station, and autonomous mission execution by the remote mobile robot. We have partially implemented and validated these concepts. Experimental results illustrate the approach and the results.

Introduction and Overview

Several aspects make planet exploration a demanding and difficult problem for robotics:

• The robot has to operate in a natural, unstructured and a priori unknown environment. • In the case of aremote planet (e.g., Mars), there is no possibility of continuous interaction with the robot because of important delays in communications and low bandwidth. • The information on the robot and the environment is mostly acquired through the robot's own sensors.

Little and rather poor a priori knowledge exist.

Because of time delays and low bandwidth, direct teleoperation is either impossible or very cumbersome. Telerobotics approaches [START_REF] Sheridan | Telerobotics[END_REF][START_REF] Hirzinger | Predictive and knowledge-based telerobotic control concepts[END_REF]Hirai & Sato, 1989) need a rather accurate model of the working space, and are therefore not applicable as such. The robot clearly needs important autonomous capacities.

It has been proposed [START_REF] Angle | Small planetary rovers[END_REF][START_REF] Miller | Experiments with a small behaviour controlled planetary rover[END_REF] to send one or more "simple" and completely autonomous robots, without any control from a ground station. Such robots, using a behaviorbased control scheme [START_REF] Brooks | A robust layered control system for a mobile robot[END_REF], would achieve an imaging, measurement or sample collection mission. However, it is not possible in this scheme to interact with the robot in order to designate a precise site to which the robot has to navigate, or to send different missions. Even in this case, reaching a precise site needs capacities that such robots cannot be endowed with.

We present a different approach to meet the challenge of planet exploration by mobile robots [START_REF] Giralt | THE FRENCH PLANETARY ROVER VAP: Concept and current developments[END_REF]. It stems from the following considerations:

• The landing site may be remote from areas of interest to the scientists, mainly because it will be selected for its safety whereas the interesting areas are in general rather inadequate for landing [START_REF] Costard | A reference martian mission for a long range rover[END_REF]. Hence the robot has to travel some distance (tens of kilometers or more) from the lander to reach a specific region (not at random nor merely in a given direction). • The mission is not defined once and for all. According to returned data, the scientists on Earth should be able to decide for the exploration of such or such site, the analysis of such sample, etc. It is necessary then to he able to control the robot, i.e., send it new missions. It is therefore important to know what it is doing. In order to provide it with new objectives, it is also important to know where it is. • Because the environment is poorly known, the mission can only be defined at a task-level in general, and not in its every detail (except in very special cases such as picking up a rock at reach). Hence the robot must be able to interpret the mission according to its actual context during its autonomous execution. • The robot could fall into difficult situations wherein its perception, interpretation or decision making capacities are insufficient. Human intervention would then be necessary for troubleshooting (which could be at a very low-level of command). According to these arguments, we propose a global architecture for a robotic exploration system in two main parts (Fig. 1): a ground station for mission programming and supervision, and a remote robot able to interpret the mission and execute it autonomously.

The Ground Station

The Ground Station includes the necessary functions to allow a human to:

1. build a mission that can then be interpreted and executed by the robot. Such a mission is called an executable mission, as opposed to a higher level description of objectives as they may be expressed by planet scientists, and 2. supervise its execution, taking into account the delays and communication constraints.

The process of building an executable mission is decomposed into two phases which correspond to two different levels of abstractions and to different planning techniques:

1. a phase called "mission planning" which produces a "mission plan", i.e. a set of (partially) ordered steps with temporal constraints that will allow the robot to achieve a given goal. 2. a phase called "teleprogramming" that consists in refining a step in the mission in terms of tasks that can be interpreted and then executed by the robot. Depending on the nature of the mission and its difficulty, and on the amount of information available at planning time, an executable mission can be composed of a variable number of more or less detailed steps.

Mission Planning

Mission planning can be carried out with the help of a planning system able to take into account temporal and resource constraints as they can be foreseen at this stage. We have developed a temporal planning system called IxTeT [START_REF] Ghallab | Managing efficiently temporal relations through indexed spanning trees[END_REF][START_REF] Dousson | Situation recognition: Representation and algorithms[END_REF] which can reason on symbolic and numeric temporal relations between time instants. It produces a set of partially ordered tasks with temporal constraints. The explicit representation of time allows for a representation of planning operators that specify information concerning the duration of actions, the relative time when the consequences of an operator become true, the conditions which must remain true during action execution, joint effects with other operators executed in parallel, and the like. The descriptions of the world, the goals and the planning operators are given using symbolic and or numeric temporal relations between time instants or elementary temporal relations between intervals which can be transformed into relations between instants.

At the mission planning level, the operator describes the mission in terms of results to be achieved, goals to be reached, temporal relations and numerical constraints, and so forth. The planner produces a set of tasks according to that description. This is the nominal plan.

As an example, let us consider the mission: go from sitel to site2, there take a video panorama, send it to Earth, and finally proceed to site3, in order to be there before nightfall. Given the appropriate task models, the IxTeT planner will produce the plan shown in Fig. 2, provided the overall time constraint ("before nightfall") is not too tight. The numerical constraints between time instants are not represented here.

In this example, we have chosen to use very simple task models (consisting in two instants: begin and end) for the sake of demonstrativeness. According to these models, the two tasks CotoSite and SendData do not share the same resources, so the planner leaves them unordered. What this means is, they both occur after instant 12 (when GetPanorama is finished), and after instant 2 in the case of SendData ( Panorama, Site2 ) (when the communication with the Earth becomes possible). In the case of the planetary rover, the physical machine cannot execute both tasks at the same time,

7

~. 12 I0 Ge~(51te2) ! GotoS i t~ ( S I tmi, S | te2) 6otoSitalSitm2, S I t~3) because talking to the Earth means unfolding the antenna, pointing it, etc. But ordering these two tasks would be very constraining, considering that we do not know in advance which instant occurs first, 2 or 12.

Task-Level Teleprogramming

Depending on the nature of the task and on its difficulty with respect to environment conditions, and depending on the robot decisional and operational capacities, a task selected by the planner can be sent as it is to the robot or must be further refined at the ground station. We call this process the "tele-programming phase". It uses all the information and expertise available at the ground station which may help the robot in performing its task. The result of this phase can be a more or less detailed program together with a set of execution "modalities" which provide a convenient representation for a class of conditional plans. These execution modalities are expressed in terms of:

• constraints or directions to be used by the robot control system for executing the mission and each of its tasks; • a description of situations to monitor and the appropriate reactions to their occurrence; such reactions are immediate reflexes, "local" correcting actions (without questioning the mission), or requests for re-planning a task. The plan produced by IxTeT corresponds to the nominal path of each task. We have to introduce the necessary indications to the robot to take into account failures and non-nominal events. A specific procedure is used to interactively build the final plan by appending other tasks, are signalled to the operator. The operator can modify and/or append tasks sing a graphic display and tools for the verification of preconditions and resource consumption.

Figure 3 shows an example. Here, the operator decided that the robot proceed to Site3 should it fail to reach Site2; as well if it is short of time after completing the task GetPanoraraa. Of course, all events not made explicit should be handled by the robot itself.

At this point, the plan skeleton is complete, but the tasks need yet to be refined. For example, a motion task "GO-TO(site)" is replaced by a sequence of more robust global motions that guide the robot along a "good" route as it may be selected from data taken from orbit, and also relying on environment features or landmarks-if any [START_REF] Chatila | Integrated planning and execution control of autonomous robot actions[END_REF]. The robot will be still executing autonomously its navigation, but instead of using only its own data, it also takes advantage of other observations. In addition, execution modalities can be added to the task, to be used by the robot to take its own decisions. Such modalities include constraints and indications for selecting the adequate actions (e.g., decision to cross an uneven terrain, with respect to try to avoid it, at the price of a longer but easier trajectory). This teleprogramming phase ends up for the case of g]obal navigation in constructing navigation routes as shown in Fig. 4. Some task need also to be completely programmed if they are not already defined at the robot level. Then, the operator has to supply a program for that task. Here is a simplified example: !i:! i Ei !¸I¸I: : I :: • . . . . . . . . . ::ii!i!iliiii! ! il,i I ! set of tasks, defined with their arguments, temporal constraints (relative to the start and end point, as well as duration) and modalities, connected by transitions labelled with internal and external events.

Telesupervision

Telesupervision in this context has both a mission monitoring role and a troubleshooting role. Because of communication constraints (communication requires pointing the antenna and hence cannot be done continuously) specific supervision commands such as status reports and data on mission execution must be included in the mission itself. In case of a problem encountered during execution, the robot must take the decision to call for help, or to continue the mission according to the given modalities. Task GetPanorama (place) { do { exec check_robot_at_place(place); report RESULT; if (is_false(?RESULT) ) raise END("context_failure"); post point_camera(0.00) report STATUS; if (is_failed(?STATUS))

raise END(~hardware_failure"); loop { post get_picture(); post move_camera(30.00); exec check_camera_position(0.00) report RESULT; if (is_true(?RESULT) )

raise BREAK; } watching BREAK; raise END(~success") ; } watching END; } export END;

The robot's version of the mission program includes the final mission plan, the modalities, the description of new tasks, and all necessary pieces of data. The plan is expressed as a data structure, consisting in a 3 The Rover Because the robot is in a remote ill-known environment, and communications constraints prevent from a continuous exchange of data with it, it is not possible in general to plan its actions with all the details. Therefore, the robot control system should be able to interpret the tasks in terms of actions to be executed, taking into account the actual state of the system and of the environment [START_REF] Chatila | Integrated planning and execution control of autonomous robot actions[END_REF]. Mission execution is completely autonomous and controlled onboard, without any direct interaction with the station (except if planned). Exchange of data with the Ground Station takes place as planned in the mission or when necessary because of execution status, e.g., the failure of some tasks.

The robot control architecture is derived from the architecture for complete autonomy presented in [START_REF] Alami | Designing an intellingent control architecture for autonomous robots[END_REF], in which the mission planning component is deported on the operator station, having more powerful computers as well as computer-aided facilities and human expertise at its disposal. It is organized into three levels.

The higher level is composed of a mission supervisor which interacts with the operator station and the next level (viewed as a set of processes which exchange signals with it).

The second level is composed of a task refinement planner and a task supervisor.

The activity of the supervisors consists in monitoring plan execution at their level by performing situation detection and assessment and by taking appropriate decisions in real time. In order to achieve this, the supervisor makes use of deliberation algorithms which are guaranteed to be time-bounded and compatible with the dynamics of the controlled system. Indeed, all deliberation algorithms which do not verify this property are actually performed by the planner (on-board or at the Operator's Station) upon request of the supervisor.

Note that in this architecture, on-board planning is necessary only at the second level. It is essentially a "refinement" using domain-or task-specific knowledge. For this, we use C-PRS [START_REF] Ingrand | An architecture for real-time reasoning and system control[END_REF]. which provides a suitable framework for goal-driven as well as situation driven deliberation processes. Indeed, PRS implements script (called KA in PRS) selection and goal posting mechanisms. Planning can be performed through context-dependent goal decomposition; situation driven reaction can be performed by triggering procedures according to the environment model.

The lowest level includes the robot modules that perform perception and action execution. The response time of these modules that implement polynomial time algorithms is bounded. This level is managed and controlled by a central Executive in order to execute the actions requested by the task supervisor. The executive is a time-bounded system: its reactions to events are predetermined in a precompiled structure.

A module embeds primitive robot functions which share common data or resources. An internal control process called the "module manager" is responsible for receiving requests to perform these functions from the robot controller, and for otherwise managing the module. Each function being well defined, its activation or termination must respect certain conditions that the module manager verifies. Modules interact by message passing or by reading data exported by other modules, and by putting their own processing results into exported data structures (EDS). At a given time, a module can be executing several functions.

Such an architecture allows a level of robot autonomy which is essentially dependent upon the difficulty of the task and the state of the environment. The autonomy is determined by the procedures implemented on the refinement level, and the algorithms within the module functions.

Mission Execution

On-board plan supervision consists in sequencing the tasks according to expected events specified in the plan (begin and end events of the tasks, and timesynchronization events) as well as unspecified (for instance, task failure not addressed in the plan). In case of conflict between two tasks, the plan supervisor is responsible for deciding which task should be executed or interrupted and for enforcing that decision.

Each task in the plan corresponds to the execution of one or several procedures. According to the tasks and to the execution context, the procedures are either selected because they are explicitly designated in the task plan, and are then instanciated for execution, or are selected as a result of goal posting. In this case the selection of a procedure follows the general scheme of PRS and is based on some invocation conditions and on the context of execution as expressed in the data base. The choice of the best procedure, when several are possible candidates, is made by a meta-procedure that reasons on applicability criteria. Procedure selection is an iterative process.

The execution of a procedure may produce several outcomes. The plan explicitly provides the desired chaining between the tasks according to some of these outcomes. If this chaining is not explicit in the plan, default procedures are selected (or goals) and executed by the supervision system. Usually, such procedures will put the robot in a safe and stable situation, and try to communicate with the ground station.

As an example, we describe the procedure GotoSite which loops until the robot has reached the target site. Executing this procedure makes the system post new goals, and select new procedures that will eventually result in executing some actions (e.g., perception, trajectory planning, etc.) and so on: Here the robot starts by acquiring new data on the environment, and decides, on the basis of a first modelling of the terrain, which navigation mode should be selected. Two modes are possible: reactive and planned. The reactive mode is selected in case of a flat terrain almost free of obstacles. It makes the robot move toward the goal while trying to detect obstacles--without a full analysis of the terrain. In the planned mode, a navigation map is built, and a trajectory planner is selected to compute a collision free trajectory (either on flat or uneven terrain). The selection of subgoals for navigation depends on the modalities associated with the plan, such as the navigation routes and landmarks.

I Missiontmm Ground Stati on

The task supervisor then updates the execution modalities and posts the goal corresponding to the task. The task refinement level (see Fig. 5) selects the suitable procedures for achieving the goal with respect to the execution context and the modalities. When the goal is fulfilled or recognized as unreachable, the task supervisor generates the task-termination event.

Autonomous Navigation

This section presents an approach to autonomous robot navigation in an unknown planetary environment. It involves several levels of reasoning, several environment representation s , and three different motion modes. We emphasize here especially on the "navigation level" of the whole system, which is in charge of reaching a distant goal by selecting sub-goals to reach, navigation modes to apply, and perception tasks to execute for this purpose.

We first present our general adaptive and hierarchical approach to autonomous navigation, pointing out the importance of the navigation level. Then we describe how terrain representations required by this level are incrementally built on the basis of 3D range and video sensory data. The algorithms that perform the selection of sub-goals and perception tasks are described, and illustrated by experimental results with the robot ADAM 1 (see Fig. 6) that has performed a large number of runs using this system in two different test sites at LAAS and at the Geroms lunar site at the French space Agency CNES.

The problem of long range navigation in unknown outdoors environments is not very frequently addressed. Important achievements are Robbie [START_REF] Weisbin | Evolving directions in nasa's planetary rover requirements end technology[END_REF], Ambler [START_REF] Krotkov | ~ Stereo friving and position estimation for autonomous planetary rovers[END_REF] and the navigation of the UGV [START_REF] Hebert | Pixel-based range processing for autonomous driving[END_REF].

An Adaptative Approach. According to a general "economy of means" principle due to limitations of onboard processing capacities, memory and energy put on the system, and to achieve a time-efficient behavior, we favor an adaptive approach in which the robot adapts its behavior to the nature of the terrain (Chatila et al., 1993;[START_REF] Lacroix | Autonomous navigation in outdoor environment: Adaptarive approach and experiment[END_REF]. Hence, three motion modes are considered:

• A reflex navigation mode: on large flat and lightly cluttered zones, the robot locomotion commands are determined on the basis of a goal and informations provided by "obstacle detector" sensors; • A 2D planned navigation mode: it relies on the execution of a planned 2D trajectory, using a binary description of the environment in terms of

Crossable~on-Crossable areas;

• A 3D planned navigation mode: this mode requires a precise model of the terrain, on which a fine 3D trajectory is planned and executed;

A HierarchicaIApproach. We assume that the terrain on which the robot must fulfill a navigation task is initially unknown, or mapped with a very low resolution.

It is then only possible for an operator to specify a graph of routes, i.e., large corridors within which the robot has to move autonomously. To tackle this problem, we defined three layers of planning (Fig. 7): • route planning which chooses long-term paths to the goal on the basis of the initial informations. It selects a sub-goal for the path planning level;

Route

• path planning (or navigation) which reasons on a global qualitative representation of the terrain, built from the data acquired by the robot's sensors. It selects the next perception task to perform, the subgoal to reach and the motion mode to apply;

• Finallytrajectoryplanningwhichdeterminesthetrajectory to execute (in one of the above mentioned three motion modes to reach the goal defined by the path planning level.

The Main "Go-To" Loop. Our approach to determine which navigation mode can be applied is based on a quick analysis of the raw 3D data produced either by a Laser Range Finder (LRF) or by stereovision. This quick analysis provides a description of the terrain in terms of navigation classes. This representation is incrementally built as the robot moves and new perceptions are fused with it to maintain a global qualitative representation of the environment. All "strategic" decisions are taken on the basis of this global representation. They concern the determination of the intermediate goal positions, the choice of the navigation mode to apply to reach them, as well as the definition of the next perception task to execute (which sensor to use? with what operating modalities? how should the data be processed?). Such an approach involves the development of different perception and motion planning processes, and emphasizes the importance of the navigation planner, which is in charge of the strategic decisions.

Terrain Representations

During navigation, a terrain representation is required for various processes: navigation planning, trajectory planning and robot localization. Aiming at building a "universal" terrain model that contains all the necessary informations is extremely difficult, inefficient, and moreover not really useful. It is more direct and easier to build different representations adapted to their use: for navigation decisions, for motion planning on flat terrain, on uneven terrain, and for localisation. Coherence relationships between these representations are to be maintained when necessary. The model is then multi-layered and heterogeneous (Fig. 8). Several perception processes coexist in the system, each dedicated to the extraction of specific representations. Perception is multi-purpose.

I m "--

roL~o'ltl~s* Fig. 8. The various terrain representations used in the system. Arrows represent the constructive dependencies between them.

Incremental Terrain Modelling. For the purpose of navigation planning, a global representation that describes the terrain in terms of navigation classes is required. We focus in this section on the algorithms developed to build such a model from 3D data (produced either by a laser range finder or a correlation stereovision algorithm).

3D Data Classification. Applied each time 3D data are acquired, the classification process produces a description of the perceived areas in term in terrain classes. It relies on a specific discretization of the perceived area that respects the sensor resolution. The discretization defines "cells" on which different characteristics are determined: density (number of points contained in a cell compared with a nominal density defined by the discretization rates), mean altitude, variance on the altitude, mean normal vector and corresponding variances... A non-parametric bayesian classification procedure is used to label each cell: a learning phase based on prototypes classified by a human leads to the determination of probability density functions, and the classical bayesian approach is applied, which provides an estimate of the probability for each possible label. A decision function that privileges false alarms (i.e., labeling a flat area as obstacle or uneven) instead of the non-detections (i.e., the opposite: labeling an obstacle as a flat area) is used (Fig. 9).

Incremental Fusion. The partial probabilities of a cell to belong to a terrain class and the variance on their altitude allow to perform a fusion procedure of several classified images. The fusion procedure is performed on a bitmap, in the pixels of which are encoded all the cell attributes determined by the classification procedure (Fig. 10).

Model Structure and Management. For the purpose of navigation planning, the global bitmap model is structured into a region map, that defines a connection graph. Planning a path (as opposed to p!anning a trajectory) does not require a precise evaluation of the static and kinematic constraints on the robot: we simply consider a robot point model, and therefore perform an obstacle growing in the bitmap before segmenting it into regions (Fig. 11). The regions define a connection graph, whose nodes are on their borders, and whose arcs correspond to a region crossing. Only the area surrounding the robot is explicited as a

In order to satisfy memory constraints, the global model is represented as a bitmap only in the surroundings of the robot's current position, and the region model (much more compact) is kept in memory during the whole mission (Fig. 12).

Navigation Planning

Each time 3D data are acquired, classified and fused in the global model, the robot has to answer autonomously the following questions:

• Where to go? (sub-goal selection) • How to go there? (motion mode selection) • Where to perceive? (data acquisition control) • What to do with the acquired data? (perception task selection)

For that purpose, the navigation planner reasons on the robot capabilities (action models for perception and motion tasks) and the global terrain representation.

A straightforward fact is that motion and perception tasks are strongly interdependent: executing a motion requires to have formerly modeled the environment, and to acquire some specific data, a motion is often necessary to go the adequate observation position.

Finding paths in the connection graph that minimizes some criteria (time and energy) is easily solved by classical search techniques, using cost functions that express these criteria; but estimating the result (and the utility) of a perception task is much more difficult. We developed an error model of the classification procedure that allows to estimate the amount of information it can bring, and a model of the localisation task that predicts the precision on the robot position it can provide.

A direct and brute force approach to answer the former questions would be to perform a search in the connection graph, in which all the possible perception tasks would be predicted and evaluated at each node encountered during the search. Besides its drastic algorithmic complexity, this approach appeared unrealistic because the model of the classification task cannot not predict what will be effectively perceived: it is then difficult to estimate the interest of these tasks.

We therefore choose a different approach to tackle the problem: the perception task selection is subordinated to the motion task. A search algorithm provides an optimal path, that is analyzed afterwards to deduce the perceptions tasks to perform. The "optimality" criterion takes here a crucial importance: it is a linear combination of time and energy consumed, weighted by the terrain class to cross and the confidence of the terrain labeling. The introduction of the robot position uncertainty in the cost function allows to plan localisation tasks along the path.

Trajectory Planning

Depending on tile label of the regions produced by the navigation planner, the adequate trajectory planner (2D or 3D) is selected to compute the actual trajectory within these regions.

Flat Terrain. The trajectory is searched with a simplified and fast method, based on bitmap and potential fields techniques. In a natural environment, and given the uncertainties of motion, perception and modelling, we consider it sufficient to approximate the robot by a circle and its configuration space is hence two dimensional, corresponding to the robot's position in the horizontal plane. Path planning is done according the following procedure: • a binary bitmapfree/obstacle is first extracted from the global bitmap model over the region to be crossed; • a classical wavefront expansion algorithm then produces a distance map from which the skeleton of the free-space is computed (Fig. 13(a)); • the path reaching the sub-goal is obtained by propagating a potential through this skeleton. This path is finally transformed into a sequence of line segments and rotations (Fig. 13(b)).

Search time only depends on the bitmap discretization, and not on the complexity of the environment. The final trajectory is obtained within less than 2 seconds (on a Sparc 10) for a 256 x 256 bitmap.

Uneven Terrain. On uneven terrain, irregularities are important enough and the binary partition into free~obstacle areas is not anymore sufficient: the notion of obstacle clearly depends on the capacity of the locomotion system to overcome terrain irregularities and also on specific constraints acting on the placement of the robot over the terrain. The trajectory planner therefore requires a 3D description of the terrain, based on the elevation map, and a precise model of the robot geometry in order to produce collision-free trajectories that also guarantee vehicle stability and take into account its kinematic constraints.

This planner, described in (Sim6on & Dacre Wright, 1993), computes a motion verifying such constraints by exploring a three dimensional configuration space C S = (x, y, O) (the x-y position of the robot frame and its heading 0). The obstacles are defined in C S as the set of configurations which do not verify some of the constraints imposed to the placement of the robot (Fig. 14). The ADAM robot is modelled by a rigid body and six wheels linked to the chassis by passive suspensions. For a given configuration, its placement results from the interaction between the wheels and the terrain, and from the balance of the suspensions. The remaining parameters of the placement vector (the z coordinate, the roll and pitch angles 4), ~p), are obtained by minimizing an energy function. The planner builds incrementally a graph of discrete configurations that can be reached from the initial position by applying sequences of discrete controls during a short time interval. Typical controls consist in driving forward or backwards with a null or a maximal angular velocity. Each arc of the graph corresponds to a trajectory portion computed for a given control. Only the arcs verifying the placement constraints mentioned above are considered during the search. In order to limit the size of the graph, the configuration space is initially decomposed into an array of small cuboid cells. This array is used during the search to keep track of small CS-regions which have already been crossed by some trajectory. The configurations generated into a visited cell are discarded and therefore, one node is at most generated in each cell.

In the case of incremental exploration of the environment, an additional constraint must be considered: the existence of unknown areas on the terrain elevation map. Indeed, any terrain irregularity may hide part of the ground. When it is possible (this caution constraint can be more or less relaxed), the path must avoid such unknown areas. If not, it must search the best way through unknown areas, and provide the best perception point of view on the way to the goal. The avoidance of such areas is obtained by an adapted weight of the arc cost and also by computing for the heuristic guidance of the search, a potential bitmap which includes the diffÉculty of the terrain and the proportion of unknown areas around the terrain patches [START_REF] Nashashibi | 3D autonomous navigation in a natural terrain[END_REF].

The minimum-cost trajectory returned by the planner realizes a compromise between the distance crossed by the vehicle, the security along the path and a small number of maneuvers. Search time strongly depends on the difficulty of the terrain. The whole procedure takes between 40 seconds to a few minutes, on an Indigo R4000 Silicon Graphics workstation. Figure 15 shows a trajectory computed on a real terrain, where darker areas correspond to interpolated unknown terrain.

Conclusion

The presented approach is based on a generic architecture for intervention robots we are developing for several highly demanding applications, including planet exploration. It has been partially instanciated in the " E D E N " experiment carried out at L A A S with the mobile robot A D A M , especially the functions necessary for autonomous navigation in a natural environment, including perception, environment modeling, localization, path and trajectory planning and execution on flat or uneven terrain. The integration of the full system including the mission planning and teleprogramming phases is being currently achieved.

Notes

L ADAM is property of Framatome and Matra Marconi Space, currently lent to LAAS.

Fig. 1 .

 1 Fig. 1. Global architecture.

GotoSiteFig. 3 .

 3 Fig. 3. The final plan.

Fig. 4 .

 4 Fig. 4. Construction of a navigation route.

Fig. 5 .

 5 Fig. 5. On-board architecture.Fig. 6. ADAM in the geroms test site.

Fig. 6 .

 6 Fig. 5. On-board architecture.Fig. 6. ADAM in the geroms test site.

Fig. 7 .

 7 Fig. 7. Three levels of planning.

Fig. 9 .

 9 Fig. 9. Classificationofacorrelatedstereoimage: correlatedpixels (left) and reprojection of the result in the camera frame (right--from clear to dark: unknown, flat, uneven and obstacle).

Fig. 10 .

 10 Fig. 10. Fusion of 8 different classified laser images: terrain classes (left) and altitude (right).

Fig. 11 .

 11 Fig. 11. The model of Fig. 10 after obstacle growing (left) and the nodes defined by the region segmentation (right).

Fig

  Fig. 12. bitmap.

Fig. 13 .

 13 Fig. 13. The 2D planner: (a) distance to the obstacles and skeleton of the free space, (b) trajectories produced by the planner.

SFig. 14 .

 14 Fig. 14. The constraints considered by the 3D planner: (a) collision, (b) stability, (c) terrain irregularities, and (d) kinematic constraint.

Fig. 15 .

 15 Fig. 15. A 3D trajectory planned on a real elevation map.


Floriane Guillevic

Magali Rossi

Anne-Lise Develle

Lorenzo Spadini

Jean M F Martins

Fabien Arnaud

Jérôme Poulenard

Pb dispersion pathways in mountain soils contaminated by ancient mining and smelting activities

Keywords: Mining and smelting soils, Pb-bearing phases, Pb-bearing Mn (hydr-)oxides, Pb mobilisation

Over the last millennia, mining and smelting activities have produced large amounts of mine and metallurgical wastes that remain enriched in potentially toxic trace elements (PTE). A spatial distribution of Pb content was coupled to mineralogical observations and single extraction tests to characterise the Pb contamination legacy and Pb dispersion trajectories in an ancient mining and smelting site that has been abandoned for approximatively 200 years. In the Peisey-Nancroix Pb-Ag mine (Savoy, France), extreme anthropogenic Pb contamination is located close to the slag heaps and along ore and slag transport paths. The contamination gradient is restricted to a few hundred metres downhill, down to background Pb values. The Pb-bearing phases change along the contamination gradient. The most contaminated soils contain significant amounts of galena and slags that are more or less weathered into pyromorphite and cerussite. Pb-bearing Mn (hydr-)oxides are the most stable and ubiquitous forms of Pb, which proportions increase downgradient. Despite the presence of some stable Pbbearing phases (pyromorphite, Pb-bearing Mn (hydr-)oxides), extraction tests indicate that a small proportion of Pb may still be mobile over time.

Introduction

Since the beginning of metallurgy, the exploitation of geological resources has been one of the most significant human activities releasing metals into the environment. Over the last millennia, mining and smelting activities have produced large amounts of mine wastes (waste dumps and tailings) and metallurgical wastes (slags and fumes) that remain enriched in potentially toxic trace elements (PTE; e.g., Pb, Sb, As, Cd, Cu and Zn). These wastes are sources of contamination, from which PTE are dispersed into the environment through different mechanisms. Ore smelting activities produce atmospheric particles carrying PTE over several tens of kilometres [START_REF] Zdanowicz | Metal emissions from a Cu smelter, Rouyn-Noranda, Québec: characterization of particles sampled in air and snow[END_REF][START_REF] Navel | Combining microscopy with spectroscopic and chemical methods for tracing the origin of atmospheric fallouts from mining sites[END_REF] to thousands of kilometres [START_REF] Hong | Greenland Ice Evidence of Hemispheric Lead Pollution Two Millennia Ago by Greek and Roman Civilizations[END_REF][START_REF] Doucet | Atmospheric Pb isotopic composition and trace metal concentration as revealed by epiphytic lichens: an investigation related to two altitudinal sections in Eastern France[END_REF][START_REF] Cloquet | Atmospheric pollutant dispersion around an urban area using trace metal concentrations and Pb isotopic compositions in epiphytic lichens[END_REF], Cloquet et al. 2015). Old mining and metallurgical wastes are usually abandoned on soils without any protection and therefore are subjected to weathering. Particles of wastes can be transported by wind, gravity, runoff water or even by anthropogenic transport. Weathering of mining and metallurgical wastes may induce the transfer of PTE within runoff water and soils as free ions or complexes. Overall, these remobilisation processes lead to the release of PTE to the environment for centuries or even millennia after mining and smelting have ceased (e.g., Galuszka et al. 2015[START_REF] Hansson | Atmospheric and terrigenous metal accumulation over 3000 years in a French mountain catchment: Local vs distal influences[END_REF][START_REF] Camizuli | Trace metals dispersion from 1000 years of mining activity in the northern French Alps[END_REF], making the metal contamination legacy an environmental issue that requires attention in many places in the world [START_REF] Van Der Voet | Measurement of organic and inorganic carbon in dolomitecontaining samples[END_REF]). Among PTE, lead (Pb) is considered one of the most toxic elements in the environment [START_REF] Alloway | Heavy metals in soils: trace metals and metalloids in soils and their bioavailability[END_REF]). Its toxicity depends on its mobility and reactivity between abiotic compartments and biota (bioavailability). The soil is one of the environmental compartments most affected by mining and metallurgical wastes as it is the closest sink to the wastes. Very high metal contents in soils are often measured in the vicinity of former smelters and former mines [START_REF] Ettler | Soil contamination near non-ferrous metal smelters: A review[END_REF][START_REF] Cortada | Impact in soils caused by metal(loid)s in lead metallurgy. The case of La Cruz Smelter (Southern Spain)[END_REF][START_REF] Kříbek | Soil contamination near the Kabwe Pb-Zn smelter in Zambia: Environmental impacts and remediation measures proposal[END_REF]. Soil quality guidelines only consider metal content as a contamination criterion (e.g., Canadian Environmental Quality Guidelines (CEQGs) for soils: Pb = 70 mg.kg -1 ; United States Environmental Protection Agency (US EPA): Pb = 400 mg.kg - 1 ). However, metal speciation is the key parameter for assessing the mobility of metals and their biological harmfulness [START_REF] Lejon | Copper Dynamics and Impact on Microbial Communities in Soils of Variable Organic Status[END_REF][START_REF] Navel | Effect of long-term organic amendments and vegetation of vineyard soils on the microscale distribution and biogeochemistry of copper[END_REF][START_REF] Spadini | Soil aggregates: a scale to investigate the densities of metal and proton reactive sites of organic matter and clay phases in soil[END_REF]. Lead speciation is influenced by soil properties that tend to reduce its transfer [START_REF] Alloway | Heavy metals in soils: trace metals and metalloids in soils and their bioavailability[END_REF], therefore, Pb is generally considered immobile.

To better limit the environmental impacts of future mining activities, it appears necessary to understand the long-term behaviour of PTE (dispersion and persistence) in the environment by developing studies on mining sites that have been abandoned for several hundred years.

Thousands of ore deposits have been formed and are located in mountain ranges. In the French Alps, hundreds of small ore deposits and occurrences have been reported by the French Geological Survey (BRGM). Environmental contamination related to past mining activities has already been identified in the French Alps based on records of direct atmospheric fallout deposition from mining exploitation in lake sediments [START_REF] Arnaud | Pollution au plomb dans la Savoie antique (II-IIIe s. apr. J.-C.) en relation avec une installation métallurgique de la cité de Vienne[END_REF][START_REF] Elbaz-Poulichet | A 10,000-year record of trace metal and metalloid (Cu, Hg, Sb, Pb) deposition in a western Alpine lake (Lake Robert, France): Deciphering local and regional mining contamination[END_REF]) and remobilisation of abandoned mining and metallurgical wastes in river sediments [START_REF] Camizuli | Trace metals dispersion from 1000 years of mining activity in the northern French Alps[END_REF]. While recent studies showed the persistence of PTE contamination in former mining soils in the Vosges Mountains over hundreds of years [START_REF] Monna | Wild Brown Trout Affected by Historical Mining in the Cévennes National Park, France[END_REF][START_REF] Mariet | Lead Highly Available in Soils Centuries after Metallurgical Activities[END_REF], this contamination has never been studied in alpine soils.

PTE contamination studies have often relied only on geochemical data such as PTE contents, which are insufficient to encompass their behaviours. Nevertheless, a combination of geochemical, mineralogical and extraction tests has more widely been used in PTE contamination studies (Swed et al. 2022, Chopin and[START_REF] Chopin | Trace element partitioning and soil particle characterisation around mining and smelting areas at Tharsis, Ríotinto and Huelva, SW Spain[END_REF]. However, the spatialisation of these data has rarely been undertaken and could help to better characterise the PTE dispersion from the sources of contamination to sinks. This paper aims to characterise the environmental legacy of former mining and smelting activities in the soils of a mountain mining site abandoned for more than 150 years: the Pb-Ag mine of Peisey-Nancroix, Savoy, France. A spatial approach, coupling soil properties, geochemistry, mineralogical observations, and single extraction tests, allows us to discuss the mobility, transfer mechanisms and remobilisation of lead in soils for more than 150 years.

2.

The Pb-Ag mine of Peisey-Nancroix (Savoy, France)

The northern French Alps have been mined for millennia [START_REF] Judet | Exploitation, abandon et patrimonialisation des mines savoyardes de 1750 à nos jours. Une introduction à une histoire longue et contrastée[END_REF][START_REF] Peloux | L'histoire si curieuse des mines de Brandes[END_REF], with the 18 th and 19 th century being the apex of industrial ore extraction in terms of production and number of sites. Indeed, most of these mines closed between the 19 th and 20 th centuries [START_REF] Judet | Exploitation, abandon et patrimonialisation des mines savoyardes de 1750 à nos jours. Une introduction à une histoire longue et contrastée[END_REF]) leaving hundreds of uncontrolled contamination spots in the environment. Pb, as a byproduct of silver mining, was the most extracted nonferrous metal in France [START_REF] Garçon | Les métaux non ferreux en France aux XVIIIe et XIXe siècles : Ruptures, blocages, évolution au sein des systèmes techniques[END_REF], providing large amounts of mining and smelting wastes that were abandoned all over the territory. The Peisey-Nancroix mining site has a former regional importance, and no anthropization has been identified since mine closure. The mining site is located in the northern French Alps at 1500 m a.s.l. on the Vanoise Massif, on the left bank of the Ponturin River (Figure 1). The mean annual temperature at the site is 1.5 °C and snow covers the area from November to May. The prevailing wind direction trends from northeast to southwest flowing up the valley. The ore deposit is located along the Internal Briançonnais Fault (IBF), which allows thrusting of the Internal Briançonnais on the External Briançonnais. The External Briançonnais is essentially composed of Carboniferous schists that extend over a few kilometres downstream from the mine site, overlying the Variscan basement. In the study area, the Internal Briançonnais is composed of various Variscan crystalline rocks (metagabbros, metabasites, micaschists and gneisses) and Permian micaschists. Some marbles of unknown age are also present in the area.

The Pb-Ag deposit of Peisey-Nancroix is hosted in Permian schists and Triassic quartzites of the External Briançonnais unit, which are trapped within the Internal Briançonnais Fault. The IBF is evidenced by the presence of Triassic dolomites that were brecciated and partly dissolved during alpine thrusting, called cargneules. The ore consists mainly of galena (PbS) and pyrite (FeS) that are disseminated or concentrated in veinlets. Silver is hosted in As-rich tetrahedrite ([Cu,Fe]12Sb4S13) that occurs as small inclusions within galena. Bertauts et al. (2022) provide a thorough description of the ore mineralogy. Galena and Ag-As-rich tetrahedrite were mined industrially between 1734 and 1866 to produce 22000 t Pb and 52 t Ag [START_REF] Meloux | Alpes-Nord : Bilan synthétique de dix années de prospection[END_REF]. The ore was smelted on site for 90 years (1745( -1824[START_REF] Barbier | La Savoie industrielle. Deuxième partie : Mines et métaux. Chaux, ciments, plâtres, poteries et tuileries[END_REF]. The ore processing and metallurgical facilities were built on the edge of an alluvial cone that contains Variscan basement rocks and cargneules. A cargneule scree is intercalated in the alluvial cone on the western side of the mine site (Figure 1-B).

At the beginning of the exploitation, the ore was crushed, ground, and washed near the metallurgical and ore smelting site (O.S. site), immediately next to the mine entrance and the Arc stream (Figure 1-C). Soon, ore processing was moved further north to the ore-processing site (O.P. site) to take advantage of greater hydraulic power. A dewatering gallery allowed groundwater evacuation, aeration and ore transport directly to the O.P. site [START_REF] Barbier | La Savoie industrielle. Deuxième partie : Mines et métaux. Chaux, ciments, plâtres, poteries et tuileries[END_REF]). The crushed ore was then transported from the ore-processing site to the ore-smelting site by a pathway that is still visible on the site. Close to the O.S. site, thousands of tons of abandoned waste rocks and smelting residues (slags) were stored and are still visible (Figure 1-C).

Figure 1 should be inserted here

Material and methods

Contamination source materials

Slags (n = 3) and waste rocks (n = 3) were sampled randomly on the heaps. Polished thin sections were made to perform scanning electron microscopy (SEM) observations to identify Pb-bearing phases. Each sample was analysed for major and trace elements by inductively coupled plasma-optical-emission-spectrometry (ICP-OES) and inductively coupled plasma-mass-spectrometry (ICP-MS), respectively, at the Service d'Analyse des Roches et des Minéraux (France, Carignan et al. 2001).

Soil sampling

With the help of a manual auger, 117 topsoils (0-20 cm) were sampled on a 40x40 metre grid from the O.S site to the O.P site (Figure 2-B) to characterise the spatial distribution of the contamination. These soil samples were air-dried for several days, gently crushed and sieved to 2 mm. The coarse fraction (> 2 mm) was observed under a binocular microscope to study the translocation of ore (e.g., galena) and slag particles. The fine fraction (< 2 mm) was kept for further analysis as Pb-bearing phases tend to concentrate in the fine fraction. In addition, a distant topsoil from waste heaps was sampled 2 km upstream on the same alluvial cone (yellow pentagon on Figure 1-B).

Physical and chemical characterisation of soils

Soil properties play an important role in the mobility of Pb. Soil organic matter (SOM) and carbonate contents were assessed by loss-on-ignition (LOI) using a furnace for the whole soil dataset (n = 117). Weight loss after a 550 °C-first and 950 °C-second heating step corresponds to the SOM and carbonate (%) fractions, respectively [START_REF] Heiri | Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results[END_REF]. Detailed analyses were performed on 27 soil samples at the French national reference soil laboratory (INRAE, France)

including particle size distribution (5 fractions), pH (ISO 10390), cation exchange capacity (CEC), and exchangeable cation content (ISO 23470, cobaltihexamine method). The SOM550°C and Carbonates950°C fractions were compared to the measured equivalent CaCO3 total content (CaCO3T, ISO 10693, volumetric method), the C total content (CT, ISO 10694, dry combustion), and the N total content (NT, ISO 13878). The total organic carbon (TOC) and organic matter (OM) contents were calculated as follows :

(1) TOC = C T -(CaCO 3 𝑇 * 0.12)

(2) OM = TOC * 1.73

The calculation of an equivalent CaCO3T content by the volumetric method may be improper when dolomite is predominant (Vuong et al. 2016). However, a comparison of the LOI and dry combustion methods showed a good linear trend between Carbonates950°C and CaCO3T (R 2 = 0.83) and between SOM550°C and OM (R 2 = 0.95) assessments (Supplementary Material Table S1). The Carbonates950°C and SOM550°C content from the LOI measurements were then used in the following results as a good estimator for the whole soil dataset.

Quantitative analysis of soils by WDS-XRF

The total Pb content of the soils was assessed by measuring the chemical content with a Brucker S8 Tiger wavelength dispersive X-ray fluorescence spectrometer (WDS-XRF) equipped with a Rh anode X-ray tube (1 kW, 50 kV, and 170 mA). A mass of 7 g of the fine fraction of soil (< 2 mm) was crushed and pressed with 10 % Licowax C powder into 34-mm diameter pellets with a manual press (at 15 kN.m -3 ). Aliquot duplicates of 12 soil samples were prepared and added to the sample list (Table S2). A certified standard was introduced at regular interval in the unknown samples list. The WDS-XRF calibration method included 12 standard samples, with 8 certified standards and 4 internal standards for very high Pb content (Pb content > 1000 mg.kg -1 , Table S3). The soil samples were analysed under vacuum conditions. The acquisition time of each spectrum was approximately 30 min for 23 elements. Hereafter, major elements (Na2O, MgO, Al2O3, SiO2, P2O5, K2O, CaO, TiO2, MnO, and Fe2O3) are given in weighted percentages (wt. %), and minor and trace elements (V, Cr, Co, Ni, Cu, Zn, As, Br, Rb, Zr, Ba, Pb, and Sb) in mg.kg -1 . Details of the method are available in Table S4.

The Pb Enrichment factor (EFPb) and Pb geoaccumulation index (IgeoPb) helping to discriminate anthropogenic from natural geogenic contamination were calculated [START_REF] Chester | Pb in Particulates from the Lower Atmosphere of the Eastern Atlantic[END_REF][START_REF] Müller | Schwermetalle in den sediments des Rheins-Veranderungen seit 1971[END_REF]and Reimann and de Caritat 2005). The EFPb was calculated considering Ti as an immobile element with a content range close to Pb in contaminated soil [START_REF] Thiombane | Geogenic versus anthropogenic behaviour and geochemical footprint of Al, Na, K and P in the Campania region (Southern Italy) soils through compositional data analysis and enrichment factor[END_REF]):

(3) 𝐸𝐹 = S5). A common approach to estimate metal enrichment above background is to calculate the geoaccumulation index (Igeo) as proposed by [START_REF] Müller | Schwermetalle in den sediments des Rheins-Veranderungen seit 1971[END_REF]. This index is calculated as follows:

(4) 𝐼𝑔𝑒𝑜 = 𝑙𝑜𝑔2(𝑀_𝑥/(1.5 * 𝑀 𝑏𝑘𝑔 ))

where Mx is the concentration of the element in enriched samples, and Mbkg is the background or pristine concentration of the element considered. The Factor 1.5 is introduced to minimise the effect of possible variations in the background values which may be attributed to lithological variations [START_REF] Stoffers | Heavy metal pollution in Wellington Harbour[END_REF]. [START_REF] Müller | Schwermetalle in den sediments des Rheins-Veranderungen seit 1971[END_REF] proposed 7 descriptive classes to assess the degree of metal pollution for increasing Igeo values (Table S5).

Mineralogical characterisation

Quantitative analysis of minerals from 10 soil samples (< 2 mm) was performed in the X-ray Diffractometry Laboratory of the Institut des Sciences de la Terre of Grenoble (ISTerre, France). X-Ray Diffraction (XRD) patterns were collected with a Bruker D5000 X-ray diffractometer equipped with a Sol-XE Si (Li) detector operated at 40 kV and 40 mA (Baltic Scientific Instruments). The Rietveld refinements of diffractograms obtained from disoriented powders of the bulk samples, were carried out with Profex software [START_REF] Doebelin | Profex: a graphical user interface for the Rietveld refinement program BGMN[END_REF]. The clay fraction analysis was used to refine the phyllosilicate description, and the diffractograms obtained were fit with Sybilla software [START_REF] Aplin | Influence of mechanical compaction and clay mineral diagenesis on the microfabric and pore-scale properties of deep-water Gulf of Mexico mudstones[END_REF]).

The Pb-bearing phases were identified for 19 soils using scanning electron microscopy (SEM)

imaging and semiquantitative analyses at the ISTerre laboratory on an epoxy mounting pad and with free coated powders, with a Vega3 Tescan equipped with a 30 mm 2 X-Ray SDD detector (EDX). Detailed observations were carried out on a smaller scale (hundreds of nanometres to micrometres) using a SEM-field emission gun (FEG), JEOL IT500HR equipped with an energy dispersive X-ray spectrometer (EDX) at the Consortium des Moyens Technologiques Communs (CMTC Grenoble, France).

Single extraction tests

Single extraction tests are one of the few tools available to determine PTE mobilisation in soils related to metal speciation [START_REF] Rao | A review of the different methods applied in environmental geochemistry for Single and sequential extraction of trace elements in soils and related materials[END_REF]. Despite their inherent limitation, they permit us to generally evaluate the potential mobility (long-term) and the mobile fraction of Pb in soils [START_REF] Quevauviller | Operationally defined extraction procedures for soil and sediment analysis I[END_REF], Gupta et al. 1996). Such tests were carried out on 21 samples selected according to their Pb content and soil properties. Three different extractants with increasing extraction power were used: distilled water, humic acid solution and an ethylene-diamine-tetraacetic acid (EDTA) solution. Humic acids are used to mimic both degraded polymerized organic matter in soils (to which humic acids belong) and dissolved soil organic matter of soil, which are known to have a high density of reactivity sites similar to that of as humic acids (Causse et al. 2003).

A 2 g mass of soil (< 2 mm) mixed with 20 ml of extractant solution (solid:liquid ratio of 10) was agitated on a vibrating plate for 48 hours. Humic acid extraction was performed with a 0.1 g.L -1 humic acid solution (Agros organic 50-60 %) and EDTA extraction was performed with a 10 mmol.L -1 EDTA, 1 M Na-acetate solution yielding a buffering pH of 7 (AFNOR X31-120). Each extraction was duplicated. Extracts were filtered at 0.45 µm and stabilised with 2 % HNO3 before analysis by ICP-AES (Varian 720ES Atomic Emission Spectrometer, IGE, France). ICP-AES emission at 220,353 nm was used for determination of Pb. The limit of detection was 0.02 mg.L -1 (L.O.D. = mean of blanks + 3σ) and the limit of quantification was (5) 𝑃𝑎𝑟𝑡 𝑜𝑓 𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑒𝑑 𝑃𝑏 (%) = (𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑒𝑑 𝑃𝑏)/(𝑡𝑜𝑡𝑎𝑙 𝑃𝑏 𝑐𝑜𝑛𝑡𝑒𝑛𝑡) * 100

Analytical data treatment

Data analysis was carried out in R (open-source software, http://cran.r-project.org). Despite the constant sum problem of the compositional data of soil, basic statistics (minimum, percentiles, maximum, etc.) were calculated for an easier comparison with guidelines. Clr-transformation was then applied to the geochemical (major, traces and SOM content) dataset to perform statistical analysis of compositional data. Hierarchical classification following a principal component analysis (FactomineR) was performed to distinguish the different soil types in the study area.

All data (geochemistry, mineralogy, extraction tests, etc.) were reported on a GIS (ArcGiS) to develop a source-to-sink spatial analysis.

Results

Slags and waste rocks compositions

Table 1 provides geochemical compositions of some waste rocks and slags. The analysed waste rocks contain up to 7.1 wt. % for Pb, 125 mg.kg -1 for Zn and 137 mg.kg -1 for Sb. The PTE contents of slags were higher than those of the waste rocks: up to 10.8 wt. % Pb, 5276 mg.kg -1

Zn and 1638 mg.kg -1 Sb.

The Pb-bearing phases observed in the waste rocks are those found in the ore (Bertauts et al., 2022): galena is largely dominant, and bournonite is locally observed. Because of weathering of the wastes, galena may slightly be altered into cerussite. In slags, three different Pb-bearing phases embedded in a Si-Fe-Ca-Ba-Al-rich silicate matrix were evidenced by SEM observations: (i) Pb-oxides, with different advancement in weathering processes, which had an ovoid shape of one to several hundred micrometres with a porous rim (Figure 2 2 and Table S1) was twice as high as that in the CPS (min.-max.: 1-19 wt. %; median: 9 wt. %). Detailed analyses were performed on selected soil samples (n = 27, Table S6). A slightly higher pH was observed for the CRS (pH = 7.7) compared to the CPS (pH = 7.0), due to a higher CaCO3T content. The particle size distribution was similar for all soil samples. The clay fraction represented a minor fraction for all types of soils, with a content ranging from 5 to 16 %. The content of exchangeable cations was dominated by Ca and Mg (Ca = 11.3-32.7 cmol+.kg -1 , Mg = 0.6-6.7 cmol+.kg -1 ). According to XRD measurements carried out on the fine fraction (n = 10), the CRS was dominated by dolomite while the CPS was dominated by quartz, plagioclase, and clay minerals such as K-micas and expanding phyllosilicates (Table S7 and Figure S2). The only oxide identified was haematite, and its proportion contributed to less than 0.5 % to the total mineral content. With the exception of Sample P2, which was located on the right bank of the Nant

Fesson stream, all samples were abundant in amorphous phases ranging from 2 % to 30 % in the soils. This amorphous material most likely corresponds to slag fragments, organic matter, or coal. 3). The distant soil from the alluvial cone was selected as a reference, considering (i) that the comparison of rocks and soils may not be relevant, and (ii) that a deep-horizon soil near the mine site could be naturally contaminated by the presence of the ore deposit.

Table 3 should be inserted here.

Total Pb content of soils

Geochemical maps based on PTE content allow the identification of "hot spots" of contamination [START_REF] Rao | A review of the different methods applied in environmental geochemistry for Single and sequential extraction of trace elements in soils and related materials[END_REF]). Among the PTE analysed (Table 2), Pb had the highest values above the guidelines and references (Table 3). The Pb content varied from < 10 mg.kg -1 to 3.8 wt. % (median: 1173 mg.kg -1 ). The high contents of Cu, Zn and Sb were very localised to S8.

Pb association with major elements

Overall, the Pb content of the soil had a medium correlation with MnO (r 2 = 0.58, p < 0.001;

Table 4) and P2O5 (r 2 =0.57, p < 0.001). In detail, carbonate-rich soils (CRS) had a significantly higher correlation between Pb and MnO than highly contaminated and carbonate-poor soils (HCS and CPS, respectively). Nevertheless, the HCS and the CRS had a higher average correlation between Pb and P2O5 than CPS. These correlations suggest that Pb in the CRS was mainly associated with Mn first and P then, whereas it was mostly associated with P in the HCS.

In CPS, no strong correlation between Pb and any major element was observed. The distribution of Pb correlated well with the distribution of Sb (r 2 = 0.79, p < 0.001), especially for CRS and CPS, and with SOM (r 2 = 0.43, p < 0.001).

Table 4 should be inserted here

Pb-bearing phases in soils

The mineralogical nature of the Pb-bearing phases was investigated by (i) observation of the coarse fraction using a binocular microscope (> 2 mm, n = 117) to qualify the presence of slag or ore mineral particles (e.g., galena) and (ii) detailed observations on 19 fine fraction samples (free powder or pressed pellets) using SEM.

Coarse fraction (> 2 mm)

Qualitative binocular observations on the coarse fraction (small circles in Figure 5-A S7). Slag fragments were also often associated with cerussite at their edges.

In Due to SEM-EDX detection limits and the very small amount of Pb adsorbed, it was very difficult to identify sorbed phases using SEM. However, Pb associated with clays and organic matter could occasionally be identified (Figure 5-B), based on the presence of a fairly small Pb peak observed in the SEM-EDX spectra (Figure S3). Because of its very low content, Pb is likely adsorbed on these phases.

Pb single extraction tests

The amount of Pb extracted by distilled water, humic acid and EDTA versus the total Pb content of the soil measured by WDS-XRF is shown in Figure 6. The total Pb content of soils and Pbextracted by water, humic acid and EDTA showed a good linear trend (respectively r 2 = 0.93, r 2 = 0.75, and r 2 = 0.91, respectively). The higher the total Pb content of the soil was, the higher the amount of Pb extracted. Samples with a low Pb content extracted less Pb than highly contaminated samples in proportion to the total Pb content. This was visually observable because the three overall slopes established by the amount of Pb extracted from water, humic acid, and EDTA were steeper than the slope established by the total Pb content (Figure 6).

Therefore, the percentage of extracted Pb relative to the total Pb content (see Equation 5) is presented in Figure 7 to spatially visualise the distribution of extracted Pb fraction. Waterextracted Pb quantities from 5 samples and humic acid-extracted Pb quantities from 3 samples were below the detection limit (Table S9).

Figure 6 should be inserted here

Water extraction

The measurable water-extracted Pb quantities varied from 0.1 to 42 mg Pb kg -1 . The highly contaminated soil E3 had the highest extracted Pb content, followed by the highly contaminated soils B2A and D3 (downhill slag heap), which also presented very high water soluble Pb contents of 40 and 35 mg Pb kg -1 , respectively. The water-extracted Pb represented 0.02 to 0.25 % of the total Pb content of the soil samples (Figure 7)

Figure 7 should be inserted here.

Humic acid extraction

The measurable humic acid-extracted Pb quantities varied from 0.1 to 197 mg Pb kg -1 . The highly contaminated soil B2A had the highest Pb content of humic acid-extracted Pb. Humic acid-extracted Pb quantities were 2 to 5 times higher than water-extracted Pb quantities (Figure 6). Pb extracted by humic acid represented 0.02 to 1 % of the total Pb content of the soil samples (Figure 7).

EDTA extraction

EDTA-extracted Pb quantities were much higher, varying from 45 to 25 423 mg Pb kg -1 . They were equivalent to the total Pb content of most of the highly contaminated samples (Figure 6), with the exception of the most contaminated soil D3, which contains the most slag and coal particles and therefore less accessible Pb. Pb extracted by EDTA represented 49 to 120 % of the total Pb content of the soil samples (Table S9). EDTA extractant is known to often leach a higher Pb content than the total Pb content [START_REF] Sterckeman | Soil and waste analysis for environmental risk assessment in France[END_REF]. These samples were fixed at 100 % in Figure 7 (Samples G3, G5, L2 and O1).

Data comparison

The soil samples were divided into 3 groups according to the total Pb content, the amount of Pb extracted by water and EDTA and the distance to the slag heaps (Table 5). The Group 1 samples had no or low Pb contamination (blue circles in Figure 7). They were characterised by a nonquantifiable water extraction of Pb and a low EDTA extraction of Pb (< 60 %). These samples were disconnected from the waste heaps downslope (H11; K9; and G8) or upstream of the ore transport pathway (K1). The Group 2 samples were moderately contaminated with Pb and characterised by low water extraction of Pb and median EDTA extraction of Pb (yellow circle in Figure 7). These samples were far away from mining and metallurgical wastes. The Group 3 samples were highly contaminated and characterised by high Pb water extraction and high Pb EDTA extraction (red circle in Figure 7). These samples were close to or in the immediate vicinity of mining and metallurgical wastes.

Table 5 should be inserted here

Discussion

Geochemical analyses provide evidence of extreme Pb contamination in the soils that is restricted to the ancient mining and smelting site of Peisey-Nancroix. The most contaminated soils are localised along anthropogenic features, close to the slag heaps and along the transport pathway and dewatering gallery that connect the O.P. site to the O.S. site. Such a spatial distribution provides evidence of the anthropogenic origin of the contamination there.

Remobilisation and long-term mobility of Pb

Mobility of Pb

Water is considered to be a weak acid extractant that allows the determination of the watersoluble metal fraction, considered the most mobile fraction [START_REF] Rao | A review of the different methods applied in environmental geochemistry for Single and sequential extraction of trace elements in soils and related materials[END_REF]. No waterextractable Pb fraction was measured in the samples of extraction Group 1 (Figure 7), which corresponds to control samples due to their disconnection from the sources of contamination (slag heaps and transport pathways). Such a low Pb mobility suggests the absence of watersoluble phases, which corroborates the presence of only Pb-bearing Mn and Fe (hydr-)oxides in these samples (Figure 5-B). In contrast, the most contaminated soils in Group 3 samples had a high amount of water-extracted Pb, which still represents a small proportion of the total Pb content (Figure 7). Pb water-extracted quantities tended to decrease in soils downgradient and represented a smaller extracted fraction of the total Pb content (Group 2 samples).

The water-soluble fraction was generally defined as easily exchangeable Pb and bound to carbonates and/or organic matter [START_REF] Sahuquillo | Overview of the use of leaching/extraction tests for risk assessment of trace metals in contaminated soils and sediments[END_REF]. Cerussite was the most abundant Pbbearing mineral in the highly contaminated samples, with slag particles (by relative proportion and by preferential weathering phase of galena and PbO in slags, Figure 5). Cerussite is known to be insoluble in pure water at neutral to alkaline pH [START_REF] Keim | Weathering of galena: Mineralogical processes, hydrogeochemical fluid path modeling, and estimation of the growth rate of pyromorphite[END_REF]. However, one can consider the soil organic matter as a competitive ligand to cerussite conducting to Pb partial extraction in solution, under in-situ conditions. Water extraction tends also to leach the not easily observable Pb adsorbed phases, which is suggested by the good correlation between TOC and water Pb extracted (r = 0.63, p < 0.05, Table 6).

Table 6 should be inserted here.

The decrease in Pb mobility is associated with a decrease in Pb contamination in the soils, reflecting a redistribution of the Pb-bearing phases.

Potentially mobilisable Pb

EDTA is a strong complexing agent that acts as a metal extractant. It is often used to estimate the potentially mobilisable pool of metals [START_REF] Cappuyns | A Critical Evaluation of Single Extractions from the SMT Program to Determine Trace Element Mobility in Sediments[END_REF] bound to soil organic matter (SOM) and carbonate complexes. EDTA-extraction tests of Group 1 samples showed the smallest fraction of Pb extracted by EDTA of all samples tested. Group 1 samples were uncontaminated or minimally contaminated, with less than 100 mg.kg -1 Pb, which is insignificant in the longterm. In contrast, the samples in Group 3 had an EDTA-extracted Pb content between 80 to 100 % of the total Pb content. This result suggests that the Pb content of the Pb-bearing phases is mobilisable in the long-term and represents a potential source of Pb in soil solution. However, the EDTA-extractable Pb fraction decreased rapidly downgradient indicating a greater proportion of less mobilisable Pb-bearing minerals downgradient (Group 2 Samples M5 and K5; Figure 7). [START_REF] Ostergren | Quantitative Speciation of Lead in Selected Mine Tailings from Leadville[END_REF] showed that EDTA successfully dissolved strongly bound surface Pb complexes and EDTA-soluble phases as carbonates and poorly crystalline Fe (hydr-)oxides.

There was an evolution of the chemical form of Pb from waste heaps to downgradient: Pb water soluble forms (weakly bound) disappeared for the benefit of a higher proportion of more stable phases (Pb-bearing Mn (hydr-)oxides), leading to a less mobile Pb down the slope. However, EDTA extraction tests suggest that an important pool of Pb, stocked in the most stable phases, could be mobilised in the long-term.

Pb dispersion processes in soils

Two Pb dispersion processes were identified by combining mineralogical observations, geochemical contents and leaching tests: particulate translocation of the Pb-bearing primary contamination phases and Pb leaching of the primary contamination phases leading to reprecipitated or adsorbed Pb.

Translocation of particles

The most contaminated soils provided evidence of the presence of significant amounts of galena and slag particles, which are weathered in soils. A few dropped galena were identified in the fine fraction of highly contaminated soils and in soils along former transport paths. No coarse (> 2 mm) or fine (< 2 mm) galena particles were observed in soils down to the O.S. site. In contrast, slag particles were more widespread in the coarse and fine fractions of soils.

Nevertheless, qualitative mineralogical observations indicated their scarcer proportion downwards in both the fine fraction and coarse fractions.

The extensive dispersion of slags can be explained by the natural translocation of small slag particles, by the reuse of slags for roasting the ore and the reuse of slags for construction (path, roads, etc.). Particulate translocation of Pb-bearing slag fragments significantly contributed to the Pb contamination in the soils due to their high Pb content (several wt. %).

Leaching processes

Leaching-reprecipitation processes

The dispersion and weathering of Pb-bearing galena particles or slag phases in soils represents a source of Pb, which can be leached and reprecipitated. These primary Pb-bearing phases were transformed into secondary Pb-bearing reprecipitated phases: cerussite, pyromorphite and Pbbearing Mn (hydr-)oxides.

Cerussite I was mainly observed in the most contaminated samples, located along the transport path and the dewatering gallery, between the O.S and O.P. sites. Galena particles are directly altered into cerussite (cerussite I) in carbonate-rich alkaline environments [START_REF] Bao | A cross scale investigation of galena oxidation and controls on mobilization of lead in mine waste rock[END_REF], which is consistent with our observations. Cerussite I has a porous layer on its faces that accelerates galena dissolution and releases Pb 2+ into the pore waters (Lara et al. 2011). The released Pb 2+ is likely to be reprecipitated further into cerussite II.

The restricted presence of Ca-rich pyromorphite in highly contaminated soils supports the significant correlation between Pb and P in these soils (Table 4). Pyromorphite is commonly observed in Pb-contaminated soils [START_REF] Cotter-Howells | Sources and pathways of environmental lead to children in a Derbyshire mining village[END_REF]. It is considered a long-term host for Pb or a mature alteration product of Pb (Davies et al. 1993) and as the most insoluble secondary form of Pb in soils under a wide range of environmental conditions [START_REF] Morin | Mineralogy of lead in a soil developed on a Pb-mineralized sandstone (Largentière, France)[END_REF], Hettiarchchi et al. 2000[START_REF] Nriagu | Lead orthophosphates-IV Formation and stability in the environment[END_REF]. The substitution of Ca 2+ for Pb 2+

accentuates the insoluble character of pyromorphite (solid solution, Cotter-Howells 1994).

Therefore, the Ca-rich pyromorphite observed at the site is considered to be highly insoluble (Figure S2). The source of P must be very localised within the highly contaminated soils as no pyromorphite was observed in the hayfields despite fertiliser application. The presence of monazite, xenotime and apatite in the ore (Bertauts et al. 2022) may be the main source of phosphorus as well as the P-enriched slags (Table 1). It can be assumed that pyromorphite crystallises as long as Pb is leached out and P is available [START_REF] Buatier | TEM-EDX investigation on Zn-and Pb-contaminated soils[END_REF]).

Pb-bearing Mn (hydr-)oxides, based on mineralogical observations, were the most ubiquitous Pb-bearing phases observed in soils and the dominant Pb-bearing phase observed downgradient. Mineralogical observations tended to show a decrease in cerussite and pyromorphite downgradient in favour of a greater proportion of Pb-bearing Mn (hydr-)oxides.

It is widely known that Mn-(hydr-)oxides and Fe-(hydr-)oxides have a high capacity to retain PTE in the environment and are considered also as a mature alteration phase [START_REF] Davis | Micromineralogy of mine wastes in relation to lead bioavailability, Butte, Montana[END_REF].

The characteristics of the Pb-bearing Mn (hydr-)oxides suggest leaching of the Pb-bearing slag or galena particles, solute transport and reprecipitation.

Leaching-adsorption processes

Few Pb-adsorbed phases were observed knowing the limits of the SEM to identify such phases with a low to a very low Pb content using backscattered electrons. The observed spatial distribution of Pb-adsorbed on clays and organic matter (Figure 5-B) is likely not representative of their real distribution because of the high difficulty to identify these phases using SEM.

Despite this difficulty, these phases play an important role in the mobility of Pb, as they can represent up to 50 % of the Pb-bearing phases in mining and smelting areas (Brown et al. 2009).

The airborne portion of the Pb contamination

Pb-rich atmospheric fallout was most likely been deposited on site during smelting. However, no Pb enrichment was evidenced among the farthest samples from the O.S. and O.P. sites (Figure 4-A), suggesting that the part of airborne lead contamination was negligible.

Considering that smelter fumes can be transported over several kilometres to thousands of kilometres [START_REF] Hong | Greenland Ice Evidence of Hemispheric Lead Pollution Two Millennia Ago by Greek and Roman Civilizations[END_REF][START_REF] Doucet | Atmospheric Pb isotopic composition and trace metal concentration as revealed by epiphytic lichens: an investigation related to two altitudinal sections in Eastern France[END_REF][START_REF] Cloquet | Atmospheric pollutant dispersion around an urban area using trace metal concentrations and Pb isotopic compositions in epiphytic lichens[END_REF][START_REF] Zdanowicz | Metal emissions from a Cu smelter, Rouyn-Noranda, Québec: characterization of particles sampled in air and snow[END_REF]Cloquet et al. 2015), it is necessary to obtain samples from a few kilometres downwind to characterise airborne Pb contamination. Lake sediment cores were sampled in La Plagne Lake (7 km upstream of the mining site) together with soils from its watershed in order to quantify the contamination contribution of the atmospheric deposition to the total Pb contamination observed at the site in soils (Guillevic et al. in prep.).

Conclusion

This Figure 6: Graph of the amount of extracted Pb (mg.kg -1 ) using 3 extractants (distilled water, humic acid, and EDTA) as a function of the total soil Pb content (mg.kg -1 ) on a logarithmic scale.

7.

Figure captions

Figure 7: Spatial distribution of the fraction of extracted Pb (%) for each extractant: distilled water (in black circles), humic acid (in white circles) and EDTA (in grey circles). The 3 extraction groups were distinguished according to the amount of extracted Pb with distilled water and EDTA, the Pb contamination (EFPb) and the proximity of the slag heap (see text). Table 1 : Major and trace element contents of waste rocks and slags

Tables

  Tix are the concentrations of the element and Ti in the soil sample, while Mbkg and Tibkg are their concentrations in the reference soil sample chosen as the local pedogeochemical background. The enrichment factor was classified into 7 classes (Table

  0.04 mg.L -1 (L.O.Q. mean of blanks + 10σ). The mean of the Pb-extracted values for duplicates was calculated for each sample and used in the results. If a duplicate was below the L.O.Q, half of the L.O.D. was assigned to the sample. Samples were compared based on the percentage of Pb extracted (per extractant) as a function of the total Pb content, calculated for each sample:

  -B and Figure 2-C); (ii) millimetric Fe-sulphide containing lead (Figure 2-C); and (iii) prills that were micrometric to tens of micrometres (Figure 2-E). Trace amounts of Pb were also found in the vitreous silicate-rich matrix (Figure 2-B).

Figure 2

 2 Figure 2 should be inserted here

  median: 17 wt. %). Highly contaminated soils (HCS, cluster 1) were located at the O.P. site (Samples O1 and Q1), the O.S. site (e.g., Samples D1 and B1), along the former ore transport paths (Sample F3), and a potential waste material storage area (Sample H7; Figure3-B). Among these samples, sample D1, which was collected on a poorly vegetated slag heap, can be considered as a technosol essentially made of slags. Most of these HCS are chemically close to CRS. Hence, the hayfields exploited downwards from the waste heaps are divided into two chemically different soils: CRS to the west and CPS to the east of the site (Figure3-B).

Figure 3

 3 Figure 3 should be inserted here

4. 3 .

 3 Pb contamination of soils 4.3.1. Definition of the local pedo-geochemical soil background To define a reference of Pb in soil, several options were considered: i) an external reference (continental crust content), ii) the average Pb content of the rocks in the watershed (excluding mineralized rocks), iii) a deep-horizon soil (45-60 cm) sampled the farthest away from the O.S. site, near the Ponturin River (sampled between Samples K5 and L6; Figure 3-B), and iv) a distant soil (0-20 cm) located 2 km upwards on the same alluvial cone, which was sampled near the active torrent in order to have the youngest possible soil to avoid the presence of airborne Pb emitted during smelting. The two soils (deep-horizon soil and distant soil) had a Pb content one order of magnitude larger than that of the middle continental crust and the local lithologies (Table

  the O.S. and O.P. sites. Therefore, the following study focuses on the Pb distribution. The highest Pb content was measured in the soils from the O.S. site and along the edge of the forest and hayfield (Figure4-A). Downwards from the hayfield slope, the Pb content decreased down to the local pedo-geochemical background (blue points in Figure4-A). The spatial distribution of Pb content in soils indicated a clear gradient of anthropogenic contamination from the mine site downwards. Major element and other trace element contents are available in Supplementary Material Table

Figure 4

 4 Figure 4 should be inserted here.

  ) showed the presence of slag particles in the soils in the vicinity of the O.S. site and along the ore transport pathways. This observation was confirmed by the presence of slag particles in the fine fraction (large circles in Figure5-A). Fewer slag particles were observed downwards in the coarse fraction, suggesting a lower proportion or the absence of them in the fine fraction.

Figure 5

 5 Figure 5 should be inserted here

  addition to cerussite II, Ca-rich pyromorphite (Pb5(PO4)3(Cl, OH, F)) was observed at the O.S. site or along the former transport path (Figure 5-B), either as tens of micrometres-sized fibrous shapes or as micrometric rounded grains (Figure 2-J and Figure 2-K).The most ubiquitous Pb-bearing phases were the Pb-bearing Mn (hydr-)oxides (Figure5-B). Pb can either be adsorbed at the surface of the Mn (hydr-)oxides or included in the crystal lattice to form Pb-Mn (hydr-)oxides through Pb 2+ Mn 2+ substitution. SEM spectra and semiquantitative analysis (FigureS3) indicated that the Pb stoichiometric part in the total phases is commonly several tens of percents. Such high Pb content suggest the occurrence of Pb 2+ Mn 2+ substitution rather than Pb-adsorption. A significant consistent C peak was associated with Pb-bearing Mn (hydr-)oxides in EDX analyses, suggesting an association of these (hydr-)oxides with carbonates and/or organic matter. Downwards from the slope, mineralogical observations tended to indicate a higher occurrence of rounded micrometric to tens of micrometres-sized aggregates of Pb-bearing Mn (hydr-)oxides (Figure2-H and Figure2-I) at the expense of Pb-bearing slags and galena particles. A minor proportion of Pb-bearing Fe-Mn (hydr-)oxides and Fe (hydr-)oxides with traces of Pb were also observed. Such Fe-rich phases likely derived from the alteration of pyrite.

  study shows the persistence of a 200 years Pb contamination in the vicinity of the Peisey-Nancroix Pb-Ag mine (Savoy, France). Severe anthropogenic Pb contamination is localised in soils around the former mining and smelting sites: it is restricted to anthropogenic features (slag heaps, former transport path and dewatering gallery) and decreases rapidly, in a few hundreds of metres in soils downwards. Slag particles are most likely the main source of Pb contamination, especially particles dispersed by anthropogenic transport between the O.P and O.S sites.Coupling mineralogical observations and extraction tests suggests a rearrangement of Pbbearing phases from labile to more stable phases downgradient. The highest contaminated soils account for a higher proportion of water-soluble and less stable Pb-bearing phases, as Pbcarbonates and Pb-adsorbed phases tend to decrease downgradient for the benefit of a higher proportion of Pb-bearing Mn (hydr-)oxides which are more stable. A form of Pb stabilisation is set up by moving away from the sources of contamination. This study contributes to a better understanding of the long-term dispersion of Pb due to mining activities. Evaluation of the mining legacy in soils and its memory effects should involve mineralogical characterisation in addition to leaching tests, in order to assess the Pb mobility/stability. Such knowledge is necessary to establish mitigation strategies that limit PTE migration in the different environmental compartments.

Figure 1 :

 1 Figure1: A) Location map of Peisey-Nancroix in the northern French Alps; B) Geological map of the Peisey-Nancroix Pb-Ag mine and its surroundings; C) Organisation of the old mine site, and infrastructures still present today divided between the ore-processing site (O.P.) to the north and the ore-smelting (O.S.) site to the southeast, where waste rock heaps and slag heaps are located.

Figure 2 :

 2 Figure2: Reflected light (A) and SEM images (B-K) of primary and secondary Pb-bearing phases identified in the ore (A), slags (B-C) and soils (D-K). In Pb-bearing primary contamination phases: A) galena (Gn.)-, pyrite (Py.), and tetrahedrite (Ttr.) from the ore; B) rounded-shaped PbO with empty holes in the centre observed in slags; C) Fe-sulfides mixed with PbO phases in slags. In weathered Pb-bearing primary contamination phases in soils: D) galena particles altered into cerussite (cerussite I); E) weathered slag particles with micrometric to tens of micrometres-sized Pb prills in a Pb-enriched silicate matrix. In secondary reprecipitated Pb-bearing phases in soils: F) cerussite particles with relict galena (cerussite I); G) reprecipitated cerussite (cerussite II); H) rounded nanometric aggregate of Pb-bearing Mn (hydr-)oxides; I) aggregate of Pb-bearing Mn (hydr-)oxides; J) pyromorphite; K) rounded aggregates of pyromorphite.

Figure 3 :

 3 Figure3: A) Principal component analysis of the 117 samples based on major elements and soil organic matter (SOM) with Pb as an illustrative supplementary variable, allowing the characterisation of three soil types: carbonate-rich cambisols, carbonate-poor cambisols and highly contaminated soils; B) Distribution map of the three soil types.

Figure 4 :

 4 Figure 4: A) Spatial distribution of the total Pb content in soils indicating that Pb content decreases down to the local pedo-geochemical background (blue points); B) the Pb enrichment factor and; C) the Pb geoaccumulation index. Represented in A: waste rock heap (light grey), slag heap (dark grey), former mine and metallurgical buildings (black), underground dewatering gallery (wide dotted line) and footpath (small dotted line).

Figure 5 :

 5 Figure 5: Spatial distribution of the Pb-bearing phases based on mineralogical observations: Aprimary contamination phases (slags and ore particles) observed in soils based on binocular (> 2 mm, n = 117)) and SEM (< 2 mm, n = 19) observations. B-the Pb-bearing secondary phases observed in soils, based on SEM (< 2 mm) observations only (n = 19).

Figure 1 :

 1 Figure 1: A) Location map of Peisey-Nancroix in the northern French Alps; B) Geological map of the Peisey-Nancroix Pb-Ag mine and its surroundings; C) Organisation of the old mine site, and infrastructures still present today divided between the ore-processing site (O.P.) to the north and the ore-smelting (O.S.) site to the southeast, where waste rock heaps and slag heaps are located.

Figure 2 :

 2 Figure 2: Reflected light (A) and SEM images (B-K) of primary and secondary Pb-bearing phases identified in the ore (A), slags (B-C) and soils (D-K). In Pb-bearing primary contamination phases: A) galena (Gn.)-, pyrite (Py.), and tetrahedrite (Ttr.) from the ore; B) rounded-shaped PbO with empty holes in the centre observed in slags; C) Fe-sulfides mixed with PbO phases in slags. In weathered Pbbearing primary contamination phases in soils: D) galena particles altered into cerussite (cerussite I); E) weathered slag particles with micrometric to tens of micrometres-sized Pb prills in a Pb-enriched silicate matrix. In secondary reprecipitated Pb-bearing phases in soils: F) cerussite particles with relict galena (cerussite I); G) reprecipitated cerussite (cerussite II); H) rounded nanometric aggregate of Pbbearing Mn (hydr-)oxides; I) aggregate of Pb-bearing Mn (hydr-)oxides; J) pyromorphite; K) rounded aggregates of pyromorphite.

Figure 3 :

 3 Figure 3: A) Principal component analysis of the 117 samples based on major elements and soil organic matter (SOM) with Pb as an illustrative supplementary variable, allowing the characterisation of three soil types: carbonate-rich cambisols, carbonate-poor cambisols and highly contaminated soils; B) Distribution map of the three soil types.

Figure 4 :

 4 Figure 4: A) Spatial distribution of the total Pb content in soils indicating that Pb content decreases down to the local pedo-geochemical background (blue points); B) the Pb enrichment factor and; C) the Pb geoaccumulation index. Represented in A: waste rock heap (light grey), slag heap (dark grey), former mine and metallurgical buildings (black), underground dewatering gallery (wide dotted line) and footpath (small dotted line).

Figure 5 :

 5 Figure 5: Spatial distribution of the Pb-bearing phases based on mineralogical observations: A-primary contamination phases (slags and ore particles) observed in soils based on binocular (> 2 mm, n = 117)) and SEM (< 2 mm, n = 19) observations. B-the Pb-bearing secondary phases observed in soils, based on SEM (< 2 mm) observations only (n = 19).

Figure 6 :

 6 Figure6: Graph of the amount of extracted Pb (mg.kg -1 ) using 3 extractants (distilled water, humic acid, and EDTA) as a function of the total soil Pb content (mg.kg -1 ) on a logarithmic scale.

Figure 7 :

 7 Figure 7: Spatial distribution of the fraction of extracted Pb (%) for each extractant: distilled water (in black circles), humic acid (in white circles) and EDTA (in grey circles). The 3 extraction groups were distinguished according to the amount of extracted Pb with distilled water and EDTA, the Pb contamination (EF Pb ) and the proximity of the slag heap (see text).

Table 1

 1 were developed on the Nant-Fesson alluvial cone (dark grey in Figure1-B) and present a high SiO2 content (min.-max.: 42-70 wt. %; median: 53 wt. %) and a low CaO content (min.-max.: 0.3-12 wt. %; median: 2 wt. %). Carbonate-rich soils (CRS, cluster 2) were developed on top of cargneule screes and led to a higher CaO content (min.-max.: 11-26 wt. %;

	should be inserted here
	4.2. Soil properties
	4.2.1. Majors elements, carbonates, and soil organic matter content
	Based on a principal component analysis (PCA), hierarchical clustering (Figure S1) on principle
	components was performed on clr-transformed major element (Na2O, MgO, Al2O3, SiO2, P2O5,
	K2O, CaO, TiO2, MnO, and Fe2O3) and soil organic matter (SOM550°C) content datasets (Figure
	3-A). Pb was added as an additional illustrative variable to explain the variability. The PCA
	allowed the identification of 3 clusters: highly Pb-contaminated cambisols (Cluster 1),
	carbonate-rich less-contaminated cambisols (Cluster 2) and carbonate-poor less-contaminated
	cambisols (Cluster 3). Basic statistics (minimum, 10 th , 25 th , 50 th , 75 th , 90 th , IQR, and maximum)

for the 3 groups of soils are presented in Table

2

. This classification reflects the local geology of the study site, leading to contrasting soil bedrocks (Figure

3-B

). Carbonate-poor soils (CPS, cluster 3)

Table 2

 2

	should be inserted here
	4.2.2. Mineralogy of soils

Table 5 :

 5 Classification of samples in groups of Pb extraction variability.

		Slope	Distance from sources	Pb contamination	Pb mobility	Potential mobilisation	Samples
				EF Pb	Distilled water	Humic acid	EDTA
	Group 1	Off slope	Distal	EF <4	Non quantifiable	Non quantifiable to low (> 0.20 %)	Low (< 60 %)	G8, H11, K1 (EF Pb = 5), K9
	Group 2	Downslope	Distal	4 < EF < 40	Non quantifiable to low (< 0.10 %)	Low (< 0.20 %)	Median (60 to 80 %)	B4 (EF Pb = 2), K4, K5, M3, M5, P2
	Group 3	Downslope Proximal	EF > 40	High (> 0.10 %) High (> 0.20 %)	High (> 80 %)	AA1, B2A, D3, E3, G3, G5, H5, I3, L2, N4 (EF Pb = 10), O1

Table 6 :

 6 Spearman correlation coefficients between extracted Pb and soil properties (n = 20).pH TOC CEC CaCO 3T Mn ex Ca ex Pb total

	Pb total	0.12 0.79 0.7	0.49	0.12 0.62	1
	Pb distill.water -0.08 0.63 0.55	0.33	0.25 0.43 0.93
	Pb hum.acid -0.10 0.61 0.50	0.26	0.20 0.38 0.92
	Pb EDTA	0.08 0.74 0.64	0.45	0.11 0.53 0.98
	ex. exchangeable cation
	Statistically significant correlation at probability levels: p<0.05, p<0.01, and p<0.001

highly contaminated soil (n=27); carbonate-rich soil (n=20); and carbonate-poor soil (n=70)

Acknowledgement This work was supported by the French National Program EC2CO (Ecosphère Continentale et Côtière), by the University of Savoie Mont-Blanc and by the IRS Program of the University of Grenoble Alpes. Chemical analysis at the Air-O-Sol facility at IGE was made possible with the funding of some of the equipment by the Labex OSUG@2020 (ANR10 LABX56). We acknowledge the work of C. Voiron (IGE) regarding chemical analysis of extracting solutions and the work of N. Findling (ISTerre) regarding XRD patterns acquisition and treatment. We also thank the three anonymous reviewers and the editor for valuable comments which significantly help to improve the original version of the manuscript.

Appendix A -Supplementary material

Supplementary material is available at the following link