Rouaa Wannous
email: rwannous@univ-lr.fr

Jamal Malki
email: jmalki@univ-lr.fr

Alain Bouju
email: abouju@univ-lr.fr

Cécile Vincent
email: cvincent@univ-lr.fr

Modelling Mobile Object Activities Based on Trajectory Ontology Rules Considering Spatial Relationship Rules

Keywords: Trajectory data modelling, Modelling activities, Ontology rules, Spatial data modelling

Several applications use devices and capture systems to record trajectories of mobile objects. To exploit these raw trajectories, we need to enhance them with semantic information. Temporal, spatial and domain related information are fundamental sources used to upgrade trajectories. The objective of semantic trajectories is to help users validating and acquiring more knowledge about mobile objects. In particular, temporal and spatial analysis of semantic trajectories is very important to understand the mobile object behaviour. This article proposes an ontology based modelling approach for semantic trajectories. This approach considers dierent and independent sources of knowledge represented by domain and spatial ontologies. The domain ontology represents mobile object activities as a set of rules. The spatial ontology represents spatial relationships as a set of rules. To achieve this approach, we need an integration between trajectory and spatial ontologies.

Introduction

Over the last few years, there has been a huge collection of real-time data on mobile objects. These data are obtained by many kind of systems like GNSS 3(GPS 4 or ARGOS 5 ), phone location or RFID 6 . This opens new perspectives for developing applications, such as bird migration monitoring [START_REF] Spaccapietra | A conceptual view on trajectories[END_REF], daily trips of employees [START_REF] Yan | A hybrid model and computing platform for spatio-semantic trajectories[END_REF], military application [START_REF] Perry | A Framework to Support Spatial, Temporal and Thematic Analytics Over Semantic Web Data[END_REF] and marine mammal tracking [START_REF] Malki | Temporal reasoning in trajectories using an ontological modelling approach[END_REF]. The raw data captured, commonly called trajectories, traces moving objects from a departure point to a destination point as sequences of pairs (sample points captured, time of the capture). In [START_REF] Spaccapietra | A conceptual view on trajectories[END_REF], the authors give a general denition of a trajectory: A trajectory is the user dened record of the evolution of the position (perceived as a point) of an object that is moving in space during a given time interval in order to achieve a given goal. Raw trajectories contain neither contextual information about the displacement of a moving object nor its accomplished activities [START_REF] Baglioni | An ontology-based approach for the semantic modelling and reasoning on trajectories[END_REF]. Semantic trajectories can be seen as a high-level data layer on raw trajectories [START_REF] Yan | A hybrid model and computing platform for spatio-semantic trajectories[END_REF]. Furthermore, it becomes necessary to provide mechanisms for storage, modelling, ecient analysis and knowledge extraction from these data to enable interoperability between systems and services. Ontologies have been proposed as a solution for modelling data with their semantic information. To exploit raw trajectories, we need other data sources. Temporal, spatial and domain related information are fundamental sources. In the continuation of our previous work [START_REF] Malki | Temporal reasoning in trajectories using an ontological modelling approach[END_REF], a domain ontology was constructed to model semantic trajectory concepts and domain rules. We focused on semantic annotations for seal trajectories activities. We discussed the temporal data dimension of trajectories. This approach takes into account the temporal data features from low-level to high-level trajectory modelling. We give an evaluation of our approach on generated and real data. In this work, we are interested in modelling mobile object activities while considering the spatial relationships.

Raw trajectories can be captured as sample points given by their coordinates with the time of capture. So, a trajectory can be considered as spatio-temporal data. From this point of view, we can consider spatio-temporal data models to represent trajectory data. Nevertheless, these models do not propose specic support for a trajectory as a whole entity [START_REF] Huang | STOQL: An ODMG-based spatio-temporal object model and query language[END_REF][START_REF] Parent | Spatio-temporal conceptual models: Data structures + space + time[END_REF]. Trajectory can also be considered from the point of view of the moving object. Moving object data models have been dened to represent trajectories [START_REF] Macedo | Trajectory data models[END_REF]. Our approach models a trajectory by an RDF graph combining features from domain application and both spatio-temporal and moving objects data models. In this paper, we illustrate our proposal to integrate these three data models.

This paper is organized as follows. Section 2 summarizes some recent related work on semantic trajectories. Section 3 represents the domain application considered in this work. Section 4 details independently the ontological modelling approach: domain seal trajectory and spatial ontologies. Section 5 introduces the domain and spatial rules. Section 6 illustrates the integration between seal trajectory and spatial ontologies. Finally, Sect. 7 concludes this paper and presents some future prospects.

Related work

Data management techniques including modelling, indexing, inferencing and querying large spatio-temporal data have been actively investigated during the last decade [START_REF] Yan | SeMiTri: A framework for semantic annotation of heterogeneous trajectories[END_REF][START_REF] Matthew | A framework to support spatial, temporal and thematic analytics over semantic web data[END_REF][START_REF] Malki | An ontological approach modeling and reasoning on trajectories. taking into account thematic, temporal and spatial rules[END_REF]. Most of these techniques are only interested in raw trajectories [START_REF] Yan | A hybrid model and computing platform for spatio-semantic trajectories[END_REF][START_REF] Wannous | Time integration in semantic trajectories using an ontological modelling approach[END_REF][START_REF] Baglioni | An ontology-based approach for the semantic modelling and reasoning on trajectories[END_REF]. The objective is to represent and query moving object trajectories. In [START_REF] Macedo | Trajectory data models[END_REF], authors notice two data modelling points of view for trajectories: the conceptual modelling view and the moving objects view. Both need spatio-temporal data modelling and reasoning.

Projects like GeoPKDD [START_REF] Geopkdd | Geographic privacy-aware knowledge discovery and delivery[END_REF] and MODAP [START_REF] Modap | Mobility, data mining and privacy[END_REF] emphasized the need to address and to use semantic data about moving objects for ecient trajectory analysis. For example, in [START_REF] Spaccapietra | A conceptual view on trajectories[END_REF], bird migration monitoring was analysed to get better understanding of bird behaviour. Scientists tried to answer queries such as: where, why and how long birds stop on their travels, the activities they engage during their stops, and which weather conditions the birds face during their ight. Considering these new requirements, new research has emerged oering data models that can be easily expanded taking into account semantic data. Thereby, a trajectory is seen as a user dened time-space function from a temporal interval to a space interval. To consider semantic trajectories, a conceptual view was dened by three main concepts: stops, moves, and begin-end of a trajectory [START_REF] Spaccapietra | A conceptual view on trajectories[END_REF]. Each part contains a set of semantic data. Based on this conceptual model of trajectories, several studies have been proposed such as [START_REF] Baglioni | An ontology-based approach for the semantic modelling and reasoning on trajectories[END_REF][START_REF] Bogorny | A conceptual data model for trajectory data mining[END_REF]. Moreover, in [START_REF] Yan | A hybrid model and computing platform for spatio-semantic trajectories[END_REF], authors designed a conceptual model of trajectories from low-level real-life GNSS data to dierent semantically abstracted levels. Their application concerned daily trips of employees from home to work and back.

Using ontologies as a model for semantic spatio-temporal data is a recent research eld. In [START_REF] Wannous | Time integration in semantic trajectories using an ontological modelling approach[END_REF], authors worked on marine mammal tracking with the objective of understanding the behaviour of the animal by studying its activities. To model semantic trajectories, an ontological approach was dened to represent trajectory concepts. The ontologies constructed are formalised in RDF and OWL languages. This approach takes into account thematic and temporal rules [START_REF] Malki | Temporal reasoning in trajectories using an ontological modelling approach[END_REF]. In consequence, the inference mechanism was based on domain rules in addition to temporal and spatial rules dened as entailments. Moreover, in [START_REF] Matthew | A framework to support spatial, temporal and thematic analytics over semantic web data[END_REF], authors worked on a military application domain with complex queries that require sophisticated inference methods. For this application, they presented an upper-level ontology dening a general hierarchy of thematic and spatial entity classes and associating relationships to connect these entity classes. They intended for application-specic domain ontologies in the thematic dimension to be integrated into the upper-level ontology through subclassing of appropriate classes and relationships. Consequently, the inference mechanism was based on several domain specic table functions and used only RDFS rules indexes.

Correspondingly, an integration between application domain ontology and spatial ontology led to the discovery of more semantics on trajectories. Furthermore, an ontological framework was produced in [START_REF] Yan | Trajectory ontologies and queries[END_REF], composed of a modular ontology and its three component modules. The three following ontologies were integrated into a unique ontology by setting up rules between them to get more semantics:

1. Geometric trajectory ontology is a generic ontology that describes in particular the spatio-temporal features of a trajectory; 2. Geographic ontology describes the geographic objects; 3. The domain application ontology describes the thematic objects of the application.

Domain application

Our modelling approach considers trajectories of seals. The data comes from the LIENSs 7 (CNRS/University of La Rochelle) in collaboration with SMRU 8 . The captured spatio-temporal data of seal trajectories can be classied into three main states: haulout, cruise and dive [START_REF] Wannous | Time integration in semantic trajectories using an ontological modelling approach[END_REF]. In every state, there is a specic activity: resting, travelling and foraging, respectively. Based on these activities, we aim at answering queries, such as:

Example 1. seals foraging in a specic area Analysing this query highlights the necessary of dening seal activities, such as foraging. Nevertheless, the spatial concepts representing area and the spatial relationship contains must be dened. Table 1 analyses the example query and illustrates the domain and spatial requirements. The need of a spatial model and its relationships clearly appears from Table 1.

In this section, we consider independently trajectory and spatial data models. -seqHasActivity is an object property between an activity and a sequence; -startPosition, endPosition are object properties between a position and a geosequence. They represent start and end captured position of a geosequence; long, lat are data properties for the position of a captured point; -dive_dur, sur_dur and max_depth are dive duration, surface duration and maximum depth of a dive, respectively; -TAD is Time Allocation at Depth which denes the shape of a seal's dive [START_REF] Fedak | Two approaches to compressing and interpreting time-depth information as collected by time-depth recorders and satellitelinked data recorders[END_REF].

-a is-a is-a is-a is-a is-a is-a is-a isS eq Of

Spatial ontology model

To model the spatial data dimension of a trajectory, we introduce a spatial ontology. In our approach, we choose owlOGCSpatial ontology developed by Malki [7]. This ontology is obtained by a model transformation. The input of this transformation is the spatial model represented by a UML class diagram proposed by Open Geospatial Consortium (OGC) [START_REF] Werner | Open GIS consortium, inc, openGIS simple features specication for SQL[END_REF]. An extract of the declarative part of this ontology is shown in Fig. 2.

Rule denition in the trajectory ontology

Table 1 highlights the need of rules dened between ontology concepts: domain rules which are seal activities as well as spatial relationship rules. LineRing

is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a is-a
is-a is-a exterior Fig. 2. A view of owlOGCSpatial ontology trajectory: travelling, resting, foraging and travelling-foraging. Figure 3 shows the declarative part of these activities. We implement them as an object relationship seqHasActivity between the sequence and activity concepts. The implementation of these rules is based on Table 2. This decision table shows the classication of seal activities based on parameters and considerations established by the domain expert. We use Oracle Semantic Data Store to implement these rules. We create the rule base sealActivities_rb to hold this implementation. Code 1.1 shows the implementation of foraging_rule: where maximum dive depth is more than 3 meters, TAD is bigger than 0.9 and less than 1 and nally, surface duration divided by dive duration is smaller than 0.5.

3 > 0 & < 0.7 < 0.5 F oraging > 3 > 0.9 & < 1 < 0.5 T ravelling_F oraging > 3 > 0.7 & < 0.9 < 0.5 1 EXECUTE SEM_APIS.CREATE_RULEBASE('sealActivities_rb'); 2 INSERT INTO mdsys.semr_sealActivities_rb 3 VALUES( 'foraging_rule', 4
'(?diveObject rdf:type s:Dive)(?diveObject s:max_depth ?maxDepth) 5 (?diveObject s:tad ?tad) (?diveObject s:dive_dur ?diveDur) 6 (?diveObject s:surf_dur ?surfaceDur)', 7 '(maxDepth > 3) and (tad > 0.9) and (surfaceDur/diveDur < 0.5)', 8 '(?diveObject s:seqHasActivity ?activityProberty) 9 (?activityProberty rdf:type s:Foraging)', 10 SEM_ALIASES(SEM_ALIAS('s','http://l3i.univ-larochelle.fr/owlSealTrajectory#'))); This function connects the spatial rules with the corresponding Oracle spatial operators, as shown in Fig. 4. Spatial Data Option SDO_ is the prex for the implementations of Oracle spatial operators [START_REF] Oracle | Oracle spatial developer's guide 11g release 2[END_REF]. Figure 6 illustrates the algorithm for calculating an inference for two spatial objects. For every two spatial objects, the inference procedure calls the spatial rules. The evalSpatialRules function calls the corresponding Oracle spatial operator. The result is returned to the spatial rule to specify if there is a relationships between the two spatial objects. When calculating a new relationship, a new inference triple is generated and saved in an entailment. The need of a semantic integration is fundamental while considering dierent and independent sources of information. For this integration, we are based on Position and GeoSequence concepts in seal trajectory ontology as mentioned in Sect. 4.1. The integration process of owlOGCSpatial ontology with seal trajectory ontology follows these steps, as shown in Fig. 5 Trajectories are usually available as raw data. Indeed, raw trajectories, collected by sensors, do not embed any kind of information about the travel of the moving object or about a possible interpretation of this travel. So, trajectory lacks semantics which is fundamental importance for its ecient use. In this work, Fig. 6. Calculate the inference for two spatial objects we present an ontological approach for modelling semantic trajectories. This approach considers the spatial characteristics of semantic trajectories. Based on the principle of reusing existing ontologies and considering dierent and independent sources of knowledge, we dene an ontological integration approach to connect the domain and spatial ontologies. Throughout the dened ontologies, we implement the domain rules and spatial relationship rules.

In our future work, we will evaluate this approach on real data and we will compare results with other approaches. Moreover, we are highly interested in dening new notions of semantic trajectories and the of data mining algorithms with ontological rules.

Fig. 1 .

 1 Fig. 1. An extract of owlSealTrajectory ontology

5 . 1

 51 Domain seal tra jectory rulesThroughout the rules associated with the domain seal trajectory, we focus on seal activities. With our domain expert, we dene four seal activities during their

Fig. 4 .

 4 Fig. 4. Connect spatial rules with Oracle spatial operators

Fig. 5 .

 5 Fig. 5. Integrating owlSealTrajectory and owlOGCSpatial ontologies

Table 1 .

 1 Domain, spatial concepts and rules needed for answering the example query

	Concepts and rules	Description
	Concepts	Domain Dive Spatial Polygon/Region spatial concept for area specic part of the seal trajectory
	Rules	Domain Foraging Spatial Contains	seal activity spatial relationship between the domain
			and spatial concepts
	4 Ontology based modelling of trajectory

  The seal trajectory ontology, called owlSealTrajectory, is a result of a model transformation like in model-driven engineering approaches. The input of this transformation is the semantic seal trajectory model represented by a UML class diagram. Figure1presents an extract of this ontology, where:-Seal is a mobile object. It represents the animal equipped with a tag; -Sequence is captured in the form of temporal intervals.-Trajectory is a logical form to represent a set of sequences; -Activity is the semantic part representing seal activities for a sequence; -GeoSequence is the spatial part in seal trajectory ontology and can be Haulout, Cruise or Dive; -Position is a point location of a geosequence.

			Activity	Summary	CTD
		is	Tag	is-a		is-a	xsd:time	xsd:time
	Thing	Trajectory Zone	Sequence is-a	Dive dive_ dure is-a	max_depth surf_ dur	xsd:double
			Position	GeoSequence	is-a	Haulout	tad	xsd:double
			Deployment	long	xsd:double	Cruise
			Seal	lat	xsd:double
	4.1	Tra jectory ontology model

Table 2 .

 2 Decision table associated with seal activities

	Rules	Max dive	Dive shape	Surface ratio =
		depth (meter) or TAD	surface dur / dive dur
	Resting	< 10	all	> 0.5
	T ravelling	>

  Code 1.1. Implementation of foraging rule Within, and Contains. We use Oracle Semantic Data Store to implement these relationships. For each spatial relationship, we associate an ontology rule in the rule base owlSpatialOnto_rb. For example, Code 1.2 presents the implementation of the imperative part of Contains_rule. In line 6, the property wkt represents the coordinate of the spatial objects. While we consider these ontology rules based on Oracle spatial layer, we implement a PL-SQL function called evalSpatialRules.

			Thing Thing
			is a
			Trajectory Trajectory
			isSeqOf
			Sequence
			seqHasActivity
			Activity
		is a	is a	is a	is a
		Resting	Travelling	Foraging	Travelling-Foraging
			Fig. 3. Declarative part of seal activities
	5.2	Spatial relationship rules
	Spatial relationships are usually classied as topological, directional, and metric
	relationships. In this paper, we consider the topological relationships: Equals,
	Disjoint, Intersects, Touches, Crosses, Overlaps, AnyInteract,

  Code 1.2. Implementation of Contains spatial rule

	1 EXECUTE SEM_APIS.CREATE_RULEBASE('owlSpatialOnto_rb');
	2 INSERT INTO mdsys.semr_owlSpatialOnto_rb VALUES(
	3 'contains_rule',
	4 '(?spObj1	rdf:type	os:Geometry)	(?spObj2	rdf:type	os:Geometry)
	5 (?spObj1	os:srid	?sridSpObj1)	(?spObj2	os:srid	?sridSpObj2)
	6 (?spObj1	os:wkt	?strSpObj1)	(?spObj2	os:wkt	?strSpObj2)',
	7 '(evalSpatialRules(spObj1,strSpObj1,spObj2,strSpObj2,sridSpObj2,
	8	''CONTAINS'')=1)',
	9 '(?spObj1	os:contains ?spObj2)',
	10 SEM_ALIASES(SEM_ALIAS('os','http://l3i.univ-larochelle.fr/owlOGCSpatial#')));

: 1 .

 1 owlSealTrajectory:Position is mapped by the OWL statement owl:equivalentClass to owlOGCSpatial:Point. 2. owlSealTrajectory:GeoSequence is mapped by OWL statement owl:equivalentClass to owlOGCSpatial:Line.

			rdfs:subClass
		GeoSequence	Sequence
	geoHasPositions = points	owl:equivalentClass
	Position	Line
	owl:equivalentClass	points	wkt
		wkt
		Point	xsd:string

GNSS : Global Navigation Satellite System

GPS: Global Positioning System

ARGOS: Advanced Research and Global Observation Satellite

RFID: Radio Frequency IDentication

http://lienss.univ-larochelle.fr

SMRU: Sea Mammal Research Unit-http://www.smru.st-and.ac.uk


Y Benlatreche

C Nouveau
email: nouveau@cluny.ensam.fr

R Marchal

J.-P Ferreira Martins

H Aknouche

Applications of CrAlN ternary system in wood machining of medium density fibreboard (MDF)

Keywords:

Nowadays, medium density fibreboard (MDF) composite wood is more and more used in the furniture industry to replace bulk wood such as oak, beech, etc. Indeed, this material presents good mechanical properties, is easy to machine, homogeneous, exists in different dimensions (thickness, etc.), is cheaper than bulk wood and finally can be covered by an adhesive decorative coat.

Nevertheless, even if this material is homogeneous, it is abrasive enough to tend to the breakdown of the conventional carbide tools employed during its routing process. That is why it is necessary to improve the wear resistance of these tools. One solution is to protect them with a hard coating.

The present study deals with the development of ternary CrAlN hard layers obtained by PVD method on carbide tools employed in second transformation of wood. CrAlN coatings have been optimized and then applied on carbide tools in routing of three types of MDF: standard, waterproof and fireproof. The aim of these wood machining tests was first to define the ability to be machined of the three kinds of MDF and second to compare the effectiveness of CrAlN coatings during the routing tests of these materials.

Introduction

The MDF is a panel of medium density fibreboard; known also as the medium, this panel is made from wood fibres and a synthetic binder. The use of MDF panels is increasing because of its good mechanical qualities, the easiness to be machined and its ability to receive numerous finishes. Moreover, the MDF is a recent industrial material which has many advantages; it is a homogeneous panel in three dimensions, aesthetic because of its fine texture, cheaper than bulk wood and it is available in various thicknesses.

The MDF panels qualities allow many and varied applications in three areas: the interior design as acoustic elements, flooring laminates, various skins, mouldings, friezes and baseboards; the furniture industry: kitchen, bathroom, libraries, cupboards and small furniture; and finally the arrangement of: offices, shops or reception areas.

However, MDF panels are abrasive, resulting in substantial tools wear of tungsten carbide. Indeed, when machining these materials, high friction forces are generated at the interface tool/MDF. As a consequence, the WC grains become detached from the edge causing the wear of the cutting tool.

Several studies have been carried out in order to first understand the different mechanisms contributing to cutting edge wear of tungsten carbide tools during MDF machining [START_REF] Darmawan | Performance of coated carbide tools in turning wood-based materials: effect of cutting speeds and coating materials on the wear characteristics of coated carbide tools in turning woodchip cement board[END_REF][START_REF] Darmawan | Performance of coated carbide tools when grooving wood-based materials: effect of work materials and coating materials on the wear resistance of coated carbide tools[END_REF], second to improve tool life using hard coatings [START_REF] Morita | On the cutting performance of diamond-coated cemented carbide tools pretreated with Murakami/H2O2-H2SO4 solution[END_REF][START_REF] Sheikh-Ahmad | Tool coatings for wood machining: problems and prospects[END_REF], cryogenic treatment [START_REF] Stewart | Cryogenic treatment of tungsten carbide reduces tool wear when machining medium density fibreboard[END_REF] or different kinds of tungsten carbide [START_REF] Sheikh-Ahmad | The wear characteristics of some cemented tungsten carbides in machining particleboard[END_REF]. Nevertheless, no study has been conducted to define the machining ability of different types of MDF. Actually, according to the application, the MDF can be standard (E) (used in dry environments), waterproof (H) (used in humid environment) or fireproof (M) (intended for the use in dry environments subjected to regulatory fire safety).

The aim of this work was first to define the machining ability of these three types of MDF, second, hard coatings of CrAlN have been optimized by magnetron sputtering and then applied on carbide inserts employed in routing of MDF, to try to improve their service life.

Experimental

MDF machining tests

The experiments were performed using a three-axis industrial RECORD1 SCM S.p.A CNC router. Fig. 1 represents the tool-holder, the cutting procedure and the WC-Co tool geometry used in this work.

The MDF plates were 600 mm long, 200 mm width and 19 mm thick. For each machining test, the cutting conditions were 2 mm radial engagement and 5 mm axial engagement along the plate length. These conditions give 170 m of linear cutting distance. Wear measurements were made at the end of each cutting test. The final distance of MDF cutting was 1530 m, which requires nine tests. The cutting rate was 38 m/s, the rotation rate was 18,000 rpm and the feed rate was 15 m/s.

The cutting tools used in this study were cemented tungsten carbide inserts (WC-2% Co) 50 mm long, 12 mm width and 1.5 mm thick. The cutting edge angle was 55 • . The evaluation of wear was made by measuring the nose width (NW) using an optical microscope as shown in Fig. 2. This method has been used in different studies [START_REF] Sheikh-Ahmad | Failure characteristics of diamondcoated carbides in machining wood-based composites[END_REF][START_REF] Gottloeber | Determination of wear on cutting edges[END_REF]. Several measurements were made along the cutting edge and an average value was calculated.

Coatings deposition and characterizations

The deposition of the CrAlN coatings, with different Al atomic percent, was carried out by a dual RF magnetron sputtering system (NORDIKO type 3500-13.56 MHz). A pure Cr and a pure Al target were used. To vary the Al content in the CrAlN films, we first fixed the Cr applied voltage at -900 V and we made a variation of the Al one (-300, -500, -700 and -900 V), then we fixed the Al applied voltage at -900 V and we made a variation of the Cr one (-500 and -700 V). The working pressure was about 4 bar, the plasma discharge contained 80% of Ar and 20% of N 2 and the deposition time was 90 min. In addition to carbide inserts, different kinds of substrates were employed: silicon 10 mm × 10 mm (for internal stress and thickness measurements), SiO 2 10 mm × 10 mm (for nanoindentation: NHT from CSM Instruments with a Berkovitch indenter, sinusoidal mode employed (1 Hz of frequency and 1 mN of amplitude), max load 10 mN, load and unload rate 5 mN/min)) and 90CrMoV8 steel (La Forézienne-MFLS, France TM ) samples frequently used for tools in wood machining 20 mm × 20 mm to conduct pin-on-disk tests with an applied load of 5 N, a 100Cr6 ball of 5 mm diameter with an alternative friction each 8 s and a tests duration of 10 min to determine and compare the friction coefficient of the layers. Before deposition all the substrates were ultrasonically cleaned in ethanol. The Cr and Al targets and the samples were then etched 5 min in Ar plasma by RF and DC (-1000 V) discharges, respectively. The carbide tools were CrAlNcoated on both sides. The morphology and the composition of MDF samples and CrAlN coatings were determined by scanning electron microscopic (SEM) observations and EDS microanalyses (Jeol JSM-5900 LV).

Results and discussion

CrAlN deposition and characterization

Table 1 gives the different properties of the synthesized CrAlN coatings. The Al content contained in CrAlN films varies between 5 and 51 at.%. We can note that in the CrAlN deposited films, the hardness varies between 15 and 36 GPa which is more than the conventional Cr-N system [START_REF] Barshilia | A comparative study of reactive direct current magnetron sputtered CrAlN and CrN coatings[END_REF] or the WC-Co substrate (16 GPa) [START_REF] Pirso | Friction and wear behaviour of cemented carbides[END_REF]. Besides, a high Young modulus (which varies between 331 and 520 GPa) has been calculated (same results were obtained by Kim and Lee [START_REF] Kim | Microstructure and mechanical properties of AlCrN films deposited by CFUBMS[END_REF]), which is good for an application of these layers on WC-Co substrates which have a Young modulus of 640 GPa [START_REF] Pawlowski | Dépôts Physiques, Techniques Microstructures et Propriétés[END_REF]. Furthermore, the CrAlN layers present a high coefficient of friction (0.6-0.75) as observed in a previous study [START_REF] Ding | Structural, mechanical and tribological properties of CrAlN coatings deposited by reactive unbalanced magnetron sputtering[END_REF]. Brizuela et al. [START_REF] Brizuela | Magnetron sputtering of Cr(Al)N coatings: mechanical and tribological study[END_REF] showed that the friction coefficient of CrAlN coatings varied between 0.42 and 0.55 during pin-on-disc tests applying a load of 0.98 N to an AISI 52100 steel ball of 10 mm diameter, at a constant sliding speed of 0.1 m/s under controlled humidity of 50%. However the coefficient of friction stays below the substrate one of 1.0 which was determined with pin-on-disk on a sample with a high roughness (Rt close to 1 m). As a consequence, the cutting forces during the routing process with coated tools will be lower than the ones with an unmodified tool. Low residual stresses (between -1.1 and -3.58 GPa) as obtained by Reiter et al. [START_REF] Reiter | Investigation of the properties of Al1-xCrxN coatings prepared by cathodic arc evaporation[END_REF] were determined, which promotes good adhesion of the CrAlN layers. In addition, these low values of residual stresses will enable us to deposit thick films. Finally, the CrAlN films thickness varied between 2 and 3.6 m which avoids rounding the cutting edge and leads to good mechanical and tribological properties.

Machining of MDF

CrAlN-coated carbide tools with different Al content were tested in standard MDF routing (Fig. 3). We can observe that the CrAlN-Fig. 4. The nose width vs the cutting length after the routing of the three types of MDF with conventional tools. coated carbide insert with 5 at.% of Al performed the best which means that this layer protects the tool more than the others. In fact with increasing of Al, the nose width value increases. According to Bobzin et al. [START_REF] Bobzin | Wear behaviour of Cr1-xAlxN PVD-coatings in dry running conditions[END_REF] this can be explained because the aluminium nitride films have a higher friction coefficient than the chromium nitride ones. So, it seems that the aluminium nitride content in CrAlN films increases with the Al content. Consequently, the cutting forces increase which explains the variation of the nose width of the carbide coated inserts. After these tests, we chose CrAlN films with 5 at.% of Al content to be applied on carbide inserts dedicated to the machining of waterproof and fireproof MDF.

Fig. 4 shows the tool nose width as a function of the cutting length during the routing of the three types of MDF. We clearly see that the fireproof MDF (M) is much more abrasive than the others, the standard (E) and waterproof (H) ones. Indeed, after 1530 m of cutting, the nose width is about 188 m for the fireproof MDF (M) while it is around 45 and 30 m for the standard (E) and waterproof (H) ones respectively. In the milling of MDF, Sheikh-Ahmad et al. [START_REF] Sheikh-Ahmad | Failure characteristics of diamondcoated carbides in machining wood-based composites[END_REF] obtained 170 m of nose width after 1525 m of cutting while Bai et al. [START_REF] Bai | Research and development of polycrystalline diamond woodworking tools[END_REF] obtained a value of 70 m after 1500 m of cutting. However, we do not know which type of MDF was used in their studies. It is worthy of note that after 1530 m of cutting, we are always in the steady wear phase for both standard and waterproof MDF, in the contrary, we move on to the severe wear phase only after 850 m of cutting of fireproof MDF, which shows that this material is very abrasive.

Fig. 5 represents the EDS composition microanalysis of different MDF studied. The overall analysis gives the same composition for the three types of MDF. Unlike, the local analysis shows the presence in addition to fibreboards, of foreign elements such as calcium, metals, silicon and phosphorus, which explains the abrasive behaviour of MDF panels.

In addition to the composition analysis, a comparison between the SEM morphological images from the different types of MDF were obtained (Fig. 6). We observed that the standard and waterproof MDF have the same morphology, while the fireproof one shows a higher degree of impurities. One can suppose that this difference in the degree of impurities is the reason for the high value of the nose width obtained when machining this wood composite material.

To improve the wear resistance of tungsten carbide tools during the routing of MDF, the above mentioned CrAlN coatings (5 at.% of Al) have been applied on them. Fig. 7 shows the results obtained during routing of the three types of MDF using unmodified and modified carbide tools. We can observe that the CrAlN films reduced the nose width during the fireproof and standard MDF machining.

Indeed, after 1530 m of cutting, the value of the nose width decreases from 45 to 26 m for the standard MDF and from 188 to 148 m for fireproof MDF. We can conclude that for the routing of the fireproof MDF, the tool was well protected by the CrAlN layer and more wear resistant. As a matter of fact, we can see that we machine around 1.5 times more than with a conventional tool in this case. Even if the effectiveness of the CrAlN layer was obvious as in the case of the standard MDF, we cannot conclude on its protection against wear because as this material is not abrasive enough, we should cut enough meters to be after the steady wear phase of the tool, such experiments are in progress today. Indeed, as the CrAlN-coated tool is more wear resistant than the unmodified one during its lapping we can expect that it would be also the case after 5000 or 10,000 m of cutting. It is worthy of note that we are always in the steady wear phase for the standard and waterproof MDF as opposed to the fireproof MDF where we passed the severe wear phase in both cases, with or without CrAlN film. As far as the waterproof MDF is concerned, no improvement of the wear resistance was observed: the nose width was in the order of 35 m in both cases. We can suppose that as this material is not very abrasive, like the standard one, the difference in behaviour comes from the difference of composition of these two MDF. EDS microanalyses revealed that the waterproof MDF presents Ti or Pb elements while the standard one presents in some places Si element. This difference of composition could be the reason why the CrAlN coating was effective in the case of the routing of the standard MDF but not in the case of the waterproof one.

Fig. 8 shows SEM micrographs and EDS analysis of CrAlN WC-Co coated tool tested during routing of waterproof MDF. The EDS analysis confirms the presence of W and Co on the tool edge (Fig. 8a), of Cr and Al in the coating and of all of these elements in addition to C and O in a zone between WC-Co and CrAlN coating. However, it is not possible to know whether there was formation of new materials (oxides or carbides, etc.) during routing of MDF.

Based on the SEM images we suppose that during cutting process, the first contact occurs between the coating, which protects well the cutting edge, and the MDF plate. The good adhesion of the layer on the carbide inserts permits to decrease the detachment of WC grains from the tool edge and as a consequence the wear resistance increased.

Conclusion

In this study three kinds of MDF were studied in order to define the machining ability of each one. In addition, CrAlN films with different Al content have been applied to try to improve the wear resistance of the tungsten carbide used in the routing of MDF. Based on the results presented above, the following conclusions were reached:

1. The increase of Al content in CrAlN films decreases the wear resistance of the coated-carbide inserts. Indeed, the carbide insert CrAlN-coated with 5 at.% of Al gives the smallest value of nose width. 2. The fireproof MDF is more abrasive than the standard and the waterproof ones. Actually, after 1530 m of cutting, the nose width is about 188 m for the fireproof MDF while it is approximately 45 and 30 m for the standard and waterproof ones respectively. 3. When compare the standard, the waterproof and the fireproof MDF, this last one has the highest degree of impurities and we suppose that it can be the reason of the abrasive behaviour of this material. 4. The use of CrAlN film with 5 at.% of Al improves the wear resistance of carbide inserts during the routing of standard and fireproof MDF but not in the case of the waterproof one.

Fig. 1 .

 1 Fig. 1. (a) The tool-holder and the MDF cutting procedure and (b) the WC-Co tool geometry.

Fig. 2 .

 2 Fig. 2. Evaluation of the wear of the tool's edge by measuring the nose width (NW).

Fig. 3 .

 3 Fig. 3. Variation of the nose width as a function of the cutting length of standard MDF for tungsten carbide inserts coated with different CrAlN films.

Fig. 5 .

 5 Fig. 5. EDS analysis of: (a) standard, (b) waterproof and (c) fireproof MDF.

Fig. 6 .

 6 Fig. 6. SEM morphological images of the three types of MDF.

Fig. 7 .

 7 Fig. 7. Comparison of the obtained results during routing of the three types of MDF with unmodified and modified carbide tools.

Fig. 8 .

 8 Fig. 8. SEM micrographs and EDS analysis of CrAlN WC-Co coated tool and tested during routing of waterproof MDF: (a) of the cutting edge, (b) of the CrAlN film and (c) in a zone between WC-Co and CrAlN coating.

Table 1

 1 Properties of CrAlN deposited films.

	Al applied	Cr applied voltage (-V)	Al content (at.%)	Thickness (m)	Hardness (GPa)	Young's modulus (GPa)	Friction coefficient	Residual stress (GPa)
	voltage (-V)
	CrAlN
	300		5	2.1	26	410	0.6	1.1
	500 700	900	13 28	2.5 2.7	26 23	410 380	0.65 0.7	1.52 1.43
			30	3	35	460	0.65	3.58
	900	700	44	2	15	331	-	1.13
		500	51	2.14	36	520	-	1.62

Acknowledgements

The authors want to thank especially Mr. Ferreira Martins from ISOROY of St-Dizier (France) for his advice and collaboration during this work. We also appreciated the contribution of Mr. Hamid Aknouche, PhD student in our laboratory.


Guérin Cyrielle

Binet Renaud

Pierrot-Deseilligny Marc

DSM GENERATION FROM STEREOSCOPIC IMAGERY FOR DAMAGE MAPPING, APPLICATION ON THE TOHOKU TSUNAMI

INTRODUCTION

Change detection methods from remote sensing are largely investigated, especially for damage mapping after a disaster such as tsunami, earthquake, flood or landslide. In this context, a fast evaluation and localization of the inferred damages is essential for the rescue teams and the authorities [START_REF] Brunner | Change detection for earthquake damage assessment in built-up areas using very high resolution optical and sar imagery[END_REF], [START_REF] Gokon | Mapping Of Building Damage Of The 2011 Tohoku Earthquake Tsunami In Myagi Prefecture[END_REF], [START_REF] Chesnel | Object oriented assessment of damage due to natural disaster using very high resolution images[END_REF], an automatic method is then particularly adapted. Today, most of the automatic or semi-automatic change detection methods are based on radiometric changes [START_REF] Gokon | Mapping Of Building Damage Of The 2011 Tohoku Earthquake Tsunami In Myagi Prefecture[END_REF] but a significant amount these changes are irrelevant. An alternative is a change detection method involving objects elevation [START_REF] Tian | Multitemporal 3d change detection in urban areas using stereo information from different sensors[END_REF]. The advantage of using this information is that most of the indexed changes are of interest, especially in an urban context.

A previously submitted article describes the fully automatic and generic processing flow we developed for the production of change detection maps from stereoscopic images. This flow consists in the generation of accurate Digital Surface Model (DSM) with an improved image-space based matching technique followed by the detection of real changes from the DSM difference through a classification method with a spatial regularization constraint.

In this article, we present the application of this methodology on a real application case, the 2011 earthquake and tsunami occurred on the Tohoku region, in Japan.

STUDY AREA

The study area is situated on the north-eastern coast of Japan (Tohoku region) nearby the city of Sendai. On March 11, 2011, a magnitude 9.0 earthquake occurred 130 km away from the coast and generated a tsunami which caused the death of 15,781 people, 4,086 are still missing. It also caused catastrophic damages on buildings, infrastructures and forests localized in the area [START_REF] Gokon | Mapping Of Building Damage Of The 2011 Tohoku Earthquake Tsunami In Myagi Prefecture[END_REF].

The data set we processed consists of two stereoscopic couples acquire over Sendai coast on December 11, 2010 and August 13, 2011, both by the Ikonos sensor and resample at 1m spatial resolution. According to the panchromatic images (Figure 1), radiometric changes of the area are particularly important and would raise numerous alarms of changes with a radiometric-based change detection method, especially over agricultural areas.

METHOD

DSM Generation

The comparison of the objects elevation (buildings, infrastructures or forest) before and after the crisis allows an accurate evaluation of the inferred damages. This difference of elevation is obtained through the generation of two DSM from the stereoscopic images acquired at each date of interest.

The method developed for the DSM generation is based on a semi global matching [START_REF] Hirschmuller | Accurate and efficient stereo processing by semi-global matching and mutual information[END_REF] and consists in a matching from the image space [START_REF] Pierrot-Deseilligny | Paparoditis. 3d building facade reconstruction under mesh form from multiple wide angle views[END_REF]. In order to process the images symmetrically, the matching is performed twice and the outcomes DSMs are fusioned by an optimized process with a spatial regularization constraint (not described in this article). The objective of this fusion is to choose, for each pixel of the final DSM, the value of one of the computed DSM or a value corresponding to occlusions areas.

The advantages of this technique are, first, a better consideration of the occlusions areas from both images, the edges of the structures are thus better handled, and the computation of a more robust DSM to correlation errors (Figure 2(b)). Indeed, the production of accurate DSMs at each date is essential for their comparison.

Change Detection method

The differential DSM is obtained by a pixel to pixel difference. However, because of the remains of numerous miscorrelation errors in the DSMs due to various sources such as vegetation, vehicles or homogeneous features, a naïve threshold on the DSM difference would generate a very high false alarm rate on the change detection map.. The relevant changes are then highlighted through an original classification method based on an optimization function with a spatial regularization. This function depends on the elevation difference as an agreement function and on the labels variation (positive, negative or no change) between two consecutives pixels as a spatial regularization. This classification is based on the fact that the label of a pixel is likely to be the same than the label of the neighbor pixel, theory close to the Markov Random Fields [START_REF] Bruzzone | Automatic analysis of the difference image for unsupervised change detection[END_REF].

Eventually, the balance between the elevation difference, computed on a pixel, and the labels variation is adapted according to the researched changes. A low regularization will lead to a high detection sensibility to the finest changes but also to a high false alarm rate. In return, a high regularization will remove most of the false alarms but the sensibility will then be lower.

EXPERIMENTATION AND RESULTS

The methodology has been tested over the Tohoku region. Over this coastal area, most of the anthropogenic structures correspond to low buildings and pavilions, often close to each others. Consequently, the regularization is defined with a low value so that most of the buildings are considered and intact buildings among destroyed once are not missed and vice versa. Yet, the coastal region also includes large vegetation areas severely damaged.

In order to separate vegetation and buildings damages, a multi spectral images from Ikonos sensor, acquired before the crisis on August 4, 2010, has also been processed and a vegetation mask, derived from the NDVI (Normalized Vegetation Index) has been computed. Finally, the generated change detection map allows observing the bounds of this damaged area (Figure 3(a) and (b)). The result shows that most of the buildings situated on the coast have been destroyed and only a few were preserved while debris have been stacked on certain places of the sinister area (Figure 3(c)). Besides, the whole forest situated along the coast has been removed by the wave. However, it appears that the damages are much lower in the North West, areas furthest from the coast.

CONCLUSION

We described a new approach of change detection from remote sensing based on the elevation changes. The advantage of using this information rather than the radiometry, like in many other studies, is the high relevance of the detected changes, essential for fast damage estimation in a crisis context. Besides, we showed, on a submitted article, that more than 75% of the usual buildings changes of a stable urban environment are detected. The presented methodology is completely automatic and generic to process any high resolution sensors, which makes it particularly adapted for a fast mapping of the damages inferred by natural disaster.

Figure 1 :

 1 Figure 1 : Ikonos panchromatic images of the most affected region of Tohoku before (left) and after the tsunami (right).

Figure 2 :

 2 Figure 2: (a) Image crop of an Ikonos stereoscopic couple from the 11/12/2010. (b) Fusioned DSM.

Figure 3 :

 3 Figure 3: (a) Ikonos Multi-spectral image from the 11/12/2010. (b) Change detection maps obtained by the processing flow with a low regularization. (c) Zoom on the damaged area before and after the tsunami.


Optimization of pressurized liquid extraction using a multivariate chemometric approach and comparison of solid-phase extraction cleanup steps for the determination of polycyclic aromatic hydrocarbons in masses

Keywords:

A factorial design was used to optimize the extraction ofpolycyclic aromatic hydrocarbons (PAHs) from mosses, plants used as biomonitors of air pollution. The analytical procedure consists of pressurized liquid extraction (PLE) followed by solid-phase extraction (SPE) cleanup, in association with analysis by high performance liquid chromatography coupled with fluorescence detection (HPLC-FLD). For method development, homogeneous samples were prepared with large quantities of the mosses Isothedum myosuroides Brid. and Hypnum cupressiforme Hedw., collected from a Spanish Nature Reserve. A factorial design was used to identify the optimal PLE operational conditions: 2 static cycles of 5 min at sooc. The analytical procedure performed with PLE showed similar recoveries H セ W P E I @ and total PAH concentrations ( セ R P P @ ng g-1 ) as found using Soxtec extraction, with the ad van tage of reducing solvent consumption by 3 (30 mL against 100 mL per sample ), and taking a fifth of the time (24 samples extracted automatically in 8 h against 2 samples in 3.5 h). The performance of SPE normal phases {NH2, Florisi!®, silica and activated aluminium) generally used for organic matrix cleanup was also compared. FlorisiJ® appeared to be the most selective phase and ensured the highest PAH recoveries. The optimal analytical procedure was validated with a reference material and applied to moss samples from a remote Spanish site in order to determine spatial and inter-species variability.

Introduction

Polycyclic aromatic hydrocarbons (PAHs) are products of thermal decomposition, formed during incomplete combustion of organic materials and geochemical formation of fossil fuels. The main anthropogenic sources are power plants, domestic heating, waste incineration, industrial processes and, most importantly, motor vehicle exhaust emissions [START_REF] Bjiirseth | Sources and Emissions of PAH[END_REF][START_REF] Lh | [END_REF][3]. PAHs are considered to be persistent organic pollutants (POPs) due to their slow rates of degradation, toxicity and potential for both long-range transport and bioaccumulation in living organisms [4] . Carcinogenic, mutagenie and immunotoxic effects of PAHs, detrimental to human health, have frequently been reported [START_REF] Bjiirseth | Sources and Emissions of PAH[END_REF][START_REF] Nauss | Diesel Exhaust: A Critical Analysis of Emissions, Exposure and Health Effects, Health Effects lnstitute (HEl) Special Report, Health Effects lnstitute[END_REF]. Regulation of PAH emissions and reliable monitoring of PAH concentrations in ambient air is thus ofparamount importance for public health.

Atmospheric PAH levels are monitored by collecting atmospheric particles and gases with high or low volume sam piers, and PAH deposition is evaluated by sampling bulk deposition and/or wet deposition in collectors [ 4,6, 7]. However, the sampling deviees have severa! drawbacks such as low sample representativeness, analytical difficulties (trace levels), cost and maintenance of equipment. Conversely, monitoring using biological samples appears to be a low cost alternative that can be easily developed globally. For this reason, plants are widely used as airborne pollution biomonitors in urban and rural environments [START_REF] Carree | Biosurveillance végétale de la qualité de l'air -Concepts, méthodes et applications (Air Quality Biomonitoring with Plants -Concepts, Methods and Applications)[END_REF] . The most common are herbaceous species [START_REF] Klumpp | [END_REF] , deciduous tree leaves [10], persistent tree leaves [11], coniferous needles [4,12], tree bark [13] ,lichens [14,15] and mosses [4,15,16].

Bryophytes in particular have been used over the past decade as biomonitors for the assessment of airborne pollutant deposition: heavy metals [17] , radionuclides [18], nitrogen [19], natural abundance of C, N and S isotopes [20,21] and POPs [16,[22][23][24]. As they do not have any root system or cuticle, mosses obtain most oftheir nutrients from the atmosphere. Moreover, their high cationic exchange capacity and surface to volume ratio favours the accumulation of large amounts of pollutants [25]. The International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (!CP-Vegetation), established under the United Nations Economie Commission for Europe (UNECE) Convention on Long-Range Transboundary Air Pollution (LRTAP), has monitored heavy metal deposition in Europe with masses since 1990 [17]. A pilot study was initiated by !CP-Vegetation in 2010 to monitor POPs, particularly PAHs, at a European scale. Therefore, development of a fast and efficient analytical procedure for determining PAHs in masses is necessary.

PAH determination in masses is currently undertaken by sol vent extraction followed by a cleanup step, associated with chromatographie analysis. Traditional extraction procedures using Soxhlet [26][27][28] or Soxtec apparatus [15,29] do not provide enough energy to release the analytes rapidly and therefore require long extraction times (3.5-24h) and large amounts of organic solvents (100-200mL). Thus, sonication extraction [25,30], microwaveassisted sol vent extraction [ 31] and pressurized liquid extraction (PLE) [32][33][34], have been proposed as alternatives, with extraction taking on average 30 min with 20-30 mL of solvent. However, sonication extraction has the drawback of not being automated and, even though the microwave apparatus extracts 40 samples simultaneously, an extra filtration step is necessary to separate the matrix residues from the solvent. By comparison, PLE can perform 24 sequential extractions, with no further treatment.

With PLE -also called accelerated solvent extraction (ASE)extractions can be performed at high temperatures, since the solvents remain in a liquid state under the high pressures applied, ensuring high analyte recoveries [35]. Static extraction temperature, time and number of cycles appear to be critical experimental parameters [36][START_REF] Dionex | Methods Optimization in Accelerated Solvent Extraction (ASE[END_REF][38]. Indeed, temperature hasan effect on the solventviscosity and thereby its ability to wet the matrix and solubilise the target analytes, and certain sample matrices can retain analytes within pores or other structures, thus increasing extraction time allows these compounds to diffuse into the extraction solvent. Finally, the use of static cycles was developed to introduce fresh solvent during the extraction process, which helps maintain favourable extraction equilibrium, without diluting the sample (sin ce the flush volume is the same whatever the number of cycles). The effect of pressure is to main tain the solvents as liquids above their atmospheric boiling point, and the pressures used in PLE are weil above the thresholds required to main tain the solvents in the liquid phase. Changing the pressure has very little impact on analyte recovery, so it seems unnecessary to optimize this parameter.

Severa! optimization procedures for PAH extraction by PLE on plantbiomonitors such as masses [34] and pine needles [39,40] are available in the literature, and the univariate approach was used in the se studies: one parameter was optimized while the others were set at a convenient value. However, operational parameters may interact, making it necessary to use a multivariate chemometric approach for developing the analytical method.

Selectivity is a necessary condition for obtaining reliable chromatographie results [41] . Therefore, solid-phase extraction (SPE) cleanup is usually employed to separate co-extracted matrix compounds from the target analytes as they may interfere during final determination [40,42]. Moreover, the isolation of target compounds from plant co-extracts, appears to be highly important when analyzing PAHs by high performance liquid chromatography coupled to fluorescence detection {HPLC-FLD) [39]. To date, no study covering comparison of SPE cleanup steps of moss extracts has been published.

In arder to facilita te the use of masses as bioindicators of organic airborne pollution, this study offers a fast, law solvent consuming and effective analytical procedure for PAH determination in these plants. PLE operating conditions were optimized with a factorial design and PAH recoveries were compared with those obtained by Soxtec extraction, whose efficiency was demonstrated in a previous study [29]. Moss extracts obtained under optimal PLE conditions were subsequently submitted to severa! normal phase SPE, in arder to reveal the most efficient cleanup, i.e. the one offering the highest recoveries and the best selectivity. Finally, after verifying the accuracy of the optimal analytical procedure using reference material, the method was applied to moss sam pies from a mountainous area in Spain to determine spatial and inter-species variability on the site.

Experimental

Materials and reagents

Moss samples

To develop the analytical procedure, Pleurocarpous masses Isothedum myosuroides Brid. and Hypnum cupressiforme Hedw. were collected in the Bertiz Nature Reserve (Navarra, Spain) between 2008 and 201 O. The former was used for optimizing the extraction procedure and the latter for finding the most efficient cleanup. Two different species were used, because large amounts of material were needed to develop the analytical procedure, and the Nature Reserve authorities limit the quantity of masses sampled, for conservation reasons. Ali analyses were performed on homogeneous material (cf. Section 2.2 ) prepared with composite samples. Approximately 0.5 m 2 of each species was collected, giving 50 and 25 g (dry weight) of 1. myosuroides Brid. and H. cupressiforme Hedw. respectively.

After validation, the optimal parameters were applied to moss samples collected in june 2010 from a law-alpine site in the Aralar Range {Navarra, Spain). The aim of the study was to validate the use orthe moss species Hylocomium splendens (Hedw.) Schimp. for monitoring atmospheric deposition ofPAHs in a rural environment. Initially, spatial variability in sampling was evaluated by collecting 9 samples from the same site H セ P N P R ュ R @ per sample), and the PAH levels were compared with those of H. cupressiforme Hedw., because the latter had been used in a previous study for monitoring atmospheric deposition of PAHs in Navarra [29] . To this end, samples of H. cupressiforme H セ P N P T ュ R @ per sample) were taken at the same site as H. splendens. Masses were collected under the surveillance of the Navarra authorities, and due to its scarcity in the Aralar Range, a maximum of only 3 sam pies of H. cupressiforme was allowed. A reference material IAEA-140-0C (35 g) {ANALAB, Bischheim, France), consisting of a common brown seaweed (Fucus sp.) and characterized for the mass fractions of certain organic contaminants, was used to evalua te the accuracy of the analytical method. The International Atomic Energy Agency supplies reference values for organochlorine pesticides, PCB congeners, petroleum hydrocarbons and PAHs for this material, based on an international inter-laboratory comparison [START_REF] Villeneuve | World-wide and Regionallntercomparison for the Determination of Organochlorine Compounds and Petroleum Hydrocarbons in Fucus Sample IAEA-140,1ntemational Atomic Energy Agency[END_REF].

Ali solvents were HPLC grade: acetonitrile, cyclohexane, dichloromethane (DCM) and n-hexane were provided by Scharlau (Sentmenat, Spain) and Milli-Q water by Millipore (Billerica, MA, USA).

HPLCIFLD analysis

Sample preparation

Any litterfan (dead leaves, twigs ... ) attached to the moss sampies was removed with stainless steel tweezers. The green and green-brown shoots from the last three years growth were withdrawn using stainless steel tweezers and scissors. Brown parts were not included in the samples, even if the remaining green parts represented Jess than three years of growth.

The unwashed samples were freeze-dried -recommended to minimize Joss of volatile compounds during preparation [START_REF] Markert | [END_REF]45] with an Alpha 2-4 LD apparatus for 24 h {Martin Christ, Osterode am Harz, Germany). To obtain homogeneous samples, the lyophilized mosses were ground to a fine powder in a stainless steel mill (particle size < 0.5 mm).

Solvent extraction and SPE cleanup

First, PLE was optimized and compared with previously validated Soxtec extraction [29]. Then, during a second phase, different sorbent phases were compared for the SPE cleanup. The analytical procedure is shown in Fig. 1.

Pressurized liquid extraction

PLE extractions were performed with an ASE 200 apparatus (DIONEX, Sunnyvale, CA, USA). Homogenized moss sam pies of 1.5 g were extracted in 11 mL stainless steel cens with O. 75 g of anhydrous sodium sulfate and 0.75g ofFlorisiJ® (activated magnesium silicate) from U.S. Si! ica Company (Berkeley Springs, USA). The sorbents were layered at the out! et of the extraction cens. Anhydrous sodium sulfate was used to ensure total dryness ofthe cen content to avoid problems of water immiscibility with non polar solvents. FlorisiJ® was used to retain co-extracted polar compounds which could interfere with PAHs during analysis. In-line selective removal of interferences avoids drastic post-extraction cleanup steps [46]. Each sam pie was spiked with 50 ng of surrogate standards ANT d 10 and B(a)P d 12 , chosen to estimate the recoveries of the light PAH fraction (ACE to PYR) and heavy PAH fraction (B(a)A to B(ghi)P), respectively.

Extractions were carried out with n-hexane at a pressure of 150 bar. The cens were preheated for 5 min to reach thermal equilibrium, then were submitted to one or severa! static extraction cycles. After each cycle, the cens were flushed with a volume offresh solvent corresponding to 100% of the cen volume divided by the number of cycles. Finany, at the end of the extraction process, the cens were purged with purified nitrogen for 120 s. The solvent and fixed operational parameters were chosen in the light of a previous study [34] that demonstrated their efficiency for PLE extraction of PAHs from mosses.

Nonpolarfpolar solvent mixtures such as DCM/acetone or nhexanefacetone have shown high PAH recoveries in previous PLE studies performed on environmental samples [39,47]. However, high co-extraction of matrix polar compounds such as pigments and lipids was also observed. Hence, with polar solvents, a more drastic cleanup procedure is necessary to ensure interference free chromatographie analysis. Th us the choice of a non-polar solvent, such as n-hexane, for PLE extraction seems preferable to obtain lighter extracts containing low matrix residue content. This solvent also has the advantage ofbeing highly volatile, ensuring a fast concentration step, and is compatible with the normal cleanup phases. The PLE experimental design was developed to identify the optimal values of static extraction temperature, static time and number of static cycles. Severa! studies concerning PLE applied to bioindicators for PAH determination use operating temperatures from 80 to 140°C, static extraction times of 5-15min and a maximum of 3 cycles [33,34,39]. These limits were assigned to each variable for the experimental design (Table 1 ).

Before SPE cleanup, the extracts were concentrated to 1 mL with purified N 2 (Alpha 1, Air Liquide, Paris, France) in a Turbovap II apparatus (Caliper Life Sciences, Hopkinton, MA, USA).

Soxtec extraction

The extractions were performed with a Soxtec System HT2 (Tecator, France). 1.5 g moss samples spiked with 50 ng of surrogate standards were extracted in cellulose thimbles with O. 75 g of anhydrous sodium sulfate and 0.75 g of Florisil® (U.S. Silica Company, Berkeley Springs, USA).

Extractions were carried out with 100 mL ofn-hexane. The thimbles were first immersed in the boiling solvent for 2 h and then raised above the solvent to be rinsed for 1 h by the condensing solvent.

Before SPE cleanup, the extracts were concentrated to 1 mL with purified N 2 (Alpha 1, Air Liquide, Paris, France) in a Turbovap II apparatus (Caliper Life Sciences, Hopkinton, MA, USA).

SPE cleanup procedure

During the PLE optimization and validation, cleanup was performed with Florisil® SPE cartridges (Supelclean LC-Florisil SPE 1 g/6 mL from Su peleo Analytical, Sigma-Aldrich, St. Louis, MO, USA). The use of these cartridges and their elution protocol has been validated previously [29].

During the second stage of the study, cleanup using severa! normal phase SPE cartridges was tested: Supelclean LC-Florisil SPE 1 gf6mL and Supelclean LC-Si SPE 1 gf6mL from Supelco Analytical (Sigma-Aldrich, St. Louis, MO, USA); Strata NH 2 1 g/6 mL and Strata Alumina-N 120 J..Lm, 120A, 1 g/6 mL from Phenomenex (Le Pecq, France). Cartridges of the same volume were chosen, with equal sorbent mass.

The SPE was performed using a Supelco manifold (Sigma-Aldrich, St. Louis, MO, USA). The LC-Florisil, LC-Si and N-Alumina cartridges were conditioned with 10 mL of n-hexane, the NH 2 cartridges with 2x 20 mL of n-hexane. After sample deposition, PAH elution was performed with 8 mL of cyclohexane/DCM (60: 40, vfv) for the first three cartridges containing polar adsorption media and with 6 mLofn-hexane/DCM (65: 35, vfv) forthe NH 2 bonded cartridges. The elution protocols were based on previous studies ofSPE cleanups on pine needles, lichens and moss extracts for PAH analysis [29,40,48], which systematically used a mixture of nonpolar solvent, n-hexane or cyclohexane, and a slightly polar solvent, dichloromethane. The polarity of these mixtures ensures efficient PAH elution, as polar co-extracted matrix compounds stay adsorbed on the normal phase sorbents. For example, Blasco et al. carried out lichen extract cleanup with NH 2 bonded cartridges and measured 95% of PAH recovery and 98% of matrix compounds elimination with n-hexane/DCM elution [48].

The extracts were concentrated to 0.1 mL under a gentle stream of nitrogen (Alpha 1, Air Liquide, Paris, France), then 1 mL of acetonitrile was added. Finally, extracts were fil te red with PTFE syringe filters (I.D. 13 mm, 45 J..Lm) (Xilab, Atlanticlabo-ICS, Bruges, France), and 80 ng ofinternal standard FTN d 10 was added. The extracts were stored at -20 oc.

HPLC-FLD analysis

The PAH analyses were performed with a high-performance liquid chromatography system consisting of a P680 HPLC pump and an RF 2000 fluorescence detector (Dionex, Sunnyvale, CA, USA). An 8125 low dispersion injector (Rheodyne, Rohnert Park, CA, USA) was fitted with a 20 f..LL loop. The system was equipped with a 250mmx4.6mm I.D. SupelcosillM LC-PAH C18 column (particle size 5 J..Lm) and a 20 mm x 4.6 mm I.D. precolumn (particle size 5 J..Lm) (Supelco Analytical, Sigma-Aldrich, St. Louis, MO, USA). Their temperatures were controlled with an Ultimate 3000 column compartment (Dionex, Sunnyvale, CA, USA). Chromeleon 6.80 Chromatography Data System (SR10 Build 2818 (166959)) was used for data acquisition (Dionex, Sunnyvale, CA, USA).

Elution was carried out with a binary solvent gradient ofwater and acetonitrile (ACN) at a flow rate of 1.5 mLmin-1 • The gradient elution program was as follows: initial conditions with 60% ACN maintained for 5 min, followed by a 25 min linear ramp to 1 00% ACN and finally a 10min plateau at 100% ACN. The column temperature was set at 30 oc. Detection was performed with selected fluorescence wavelengths to obtain the best sensitivity and minimal interference. The excitation/emission wavelength pairs (nm) are given in Table 2.

Quality assurance (QA) and quality control (QC)

Detection (LOD) and quantification (LOQ) limits were determined by studying the chromatogram obtained with a 2ngmL-1 standard solution. The LOD was calculated as equal to three times the background (S/N=3) and the LOQas 10 times the background (S/N = 10) [START_REF] Tranchant | Manuel pratique de chromatographie en phase gazeuse (Practical Handbook of Gas Chromatography[END_REF]. Quantification limits are given in Table 2.

Calibration curves were prepared for six levels (0, 2, 5, 10, 50, 150 ng mL -1 ) and each calibration leve! was injected in triplicate. The linearity range for the PAH analysis extended from LOQ to 150 ng mL -1 with regression coefficients from 0.9993 (FLR) to 0.9999 (PHE, ANT, FTN, B(a)A, CHR, B(b)F, B(k)F, D(ah)A).

Repeatability was satisfactory since the uncertainty (as defined in (1) [START_REF] Konieczka | [END_REF]) of 10 replicate analyses orthe 2 ngmL -1 standard solution ranged from 1 to 10%.

. tx SD

Uncertamty = .Jij ( 1
)
where t is the Student's t-value, SD is the standard deviation, and n is the number of injections. The optimal analytical procedure showed average surrogate recoveries of 70% forANT d 10 and 68% B(a)P d12. Reproducibility (n=6) ranged from 1 to 22% (for PYR and ANT respectively) (cf. TableZ Analytical parameters for PAH analysis by HPLC-FI.D. Excitation (Exc. À) and emission {Em. À) wavelengths were chosen as a function of the compounds analyzed. The limits of quantification (I.OQ) are expressed in mass of injected compound (pg). As a rough guide, equivalent concentrations in mosses (ngg-1 dry weight) have been calculated (for 1.5 g of moss sample treated, and with satisfactory PAH recoveries of 70%). Section 3.1 ). The accuracy was also verified with the reference material (cf. Section 3.4).

Experimental design approach

To understand the way in which PLE operating variables affect PAH extraction, individual operating variables must be considered along with interaction terms. The operating variables, temperature [START_REF] Bjiirseth | Sources and Emissions of PAH[END_REF], static extraction time ( ts) and numberof cycles (N), were studied using a factorial design (Nemrodw, LPRAI, Marseille, France). Each of the variables was set at 3 coded levels: -1, 0 and + 1, requiring 18 experiments in total (Table 1 ).

The results from the factorial design can be assessed using multilinear regression (Nemrodw, LPRAI, Marseille, France), with an equation of the form:

Y = bo + bt T + b2ts + b3N + bt2 Tts + b131N + b23tsN
where Y is the extraction recovery and b 0 the intercept. This first degree mode! was validated using a Fischer test. Each regression coefficient was tested using a Student's t test with a corresponding p-value. The factors whose p-values were less than 0.05 were considered as, Nstatistically significant".

Results and discussion

Optimization of the PLE method

The factorial design revealed recoveries of 56-75% forANT d 10 (surrogate for ACE to PYR) and from 58 to 71% for B(a)P d 10 (surrogate for B(a)A to B(glù)P) (Fig. 2 ), in agreement with the results obtained in the literature with n-hexane over the same extraction temperature ranges, static extraction time and number of cycles Variance analysis of the factorial design with a Fischer test validated the choice of a first degree model.Indeed, a variance coefficient ofF= 2, strictly inferior to the Fischer coefficient fAscher = 6, showed that the variability of the central point was significantly lower than the variability over the facto rial design.

Multilinear regression was applied to the light and heavy PAH recoveries obtained with the central factorial design. Statistical treatment of the results is shown in Table 3. At the 95% confidence level (p-value < 0.05 ), the PLE operational parameters studied in the factorial design bad an insignificant effect on light and heavy PAH recoveries, except for extraction temperature which bad a significant effect on heavy PAH recoveries (99% confidence levet, p-value<O.Ol). This parameter is therefore the key to PLE optimization. The interaction between the terms corresponding to the extraction temperature and the number of static cycles was particularly important as it appeared to have a significant effect on heavy PAH recoveries at the 95% confidence levet (p-value < 0.05 ).

The response surface representing heavy PAH fraction recoveries showed that optimal conditions were reached with a minimum temperature of 80 oc and a maximal extraction ti me of 45 min (3 cycles of 15min) (Fig. 3). However, at the optimal temperature of "'

. . The extracts obtained with n-hexane were pale yellow, green or brown, depending on the operatiollill parameters (Fig. 4 ). At 80 oc environmental samples such as soi!, sediments and partirulate matter: generally 1-2 cycles of 5 min at 100 oc [36,38].

The optimal conditions were tested using 6 repetitions of the analytical procedure. The extracts obtained were bright yellow and did not contain any visible matrix residues. Moreover, the extracts showed average recoveries of 70% and 68% for light and heavy PAHs respectively. These results were satisfactory as they tallied with the highest quartiles oflight and heavy PAH recoveries obtained with the factorial design (shown in Fig. 2). Average total PAH concentrations of233±6ngg-1 were measured for 13 PAHs in I. myosuroides Brid. (Table 4). FLR, PHE, FTN and PYR appeared as the major compounds. These levels were within the ranges of concentrations measured in 2006-2007 in four other pleurocarpous moss species sampled from the same site [29]. These results also valida te the reprodudbility of the method as the relative standard deviation of the total concentrations was 2% and of the individual concentrations of 1-22% (for PYR and ANT respectively).

Comparison with Soxtec extraction

Soxtec extraction provided similar yellow extracts to those obtained with optimal PLE, as weil as equivalent surrogate recoveries: 77% for light PAHs (ACE to PYR) and 67% for heavy PAHs (B(a)A to B(ghi )P). Moreover, the individual PAH concentrations measured after PLE and Soxtec extraction were within the same range, except for ACE and FLR (Table 4). During analysis, these two-ring aromatic compounds sometimes interfered with matrix compounds, Ieading to diffirult quantification, and as they are volatile, !osses may have occurred during Soxtec extraction. These observations confirm the necessity for evaluating the accuracy of the PLE method with a reference material. Average total concentrations measured with the two methods showed a low relative difference of 6%. Saxtee ensured 2 parallel extractions with 200 mL of solvent in 3.5 h ( .-...0.6 extractions per hour), whereas optimal PLE conditions (2 static cycles of 5 min) led to 3 extractions per hour with 30 mL of solvent per sample. Therefore, optimal PLE conditions were as efficient as Soxtec for PAH extraction from masses, with the advantage of being five times faster and of consuming three times less solvent

3.3. Oeanup procedure l i '"' r - '"' '"' '"' '"' -- """ '"' '"' '"' "' J r l 1 r-r- l c セ ッ イ ィ ゥ ゥ ャ @ + r-r- L C.SI 1 1 ッ l ゥ セ ィ ャ @ P.I. H$ ACE -PYR OHtaYyPAHs B(a)A -B(ghl lf"
Strata NH 2 cartridges were immediately eliminated during preliminary tests because quantification with HPLC/FW analysis was impossible due to the presence of high quantities of interfering compounds on the chromatograms. Conversely, analysis of the purified extracts obtained with Strata Alumina-N, Supelclean LC -Florisil and Supeldean LC -Si SPE cartridges was possible. Recoveries of light and heavy PAHs were determined for each type of sorbent H ョ セ s I @ (Fig. 5). Alumina-N recoveries were significantly lower than the 2 other sorbents. For these cartridges, average recoveries of 51% and 59% were observed for light and heavy PAHs respectively, compared to 71% for bath fractions with LC-Fiorisil and 67% and 75% for light and heavy PAHs respectively with LC-Si cartridges. LC-Fiorisil and LC-Si cartridges gave equivalent cleanup PAH recoveries. However, light PAH recoveries were much more variable with LC-Si than with LC-Fiorisil cartridges (RSD of 20% compared to 8%). Therefore, LC -Fiorisil cartridges appeared to be the most appropriate for moss extract cleanup after PLE extraction, as they were the only type of SPE tested that ensured recoveries higher than 60% for aU PAHs. These cartridges also appeared to give the extracts with the least coextracts.

As cleanup of moss extracts with Florisi1 111 ensured the highest PAH selectivity and recoveries, Supelclean LC-Florisil (1 g/6 mL) cartridges were chosen and used in subsequent experiments. Fig. 6 shows a chromatogram obtained with the optimal analytical procedure combining optimal PLE conditions (80°C, 2nùn x Smin) and Florisi1 111 deanup. The chromatogram of a standard solution is also included to show the law interfering compound content in the moss extract chromatogram.

Validation of the analytical procedure

The accuracy of the optimal analytical procedure was verified by applying PLE extraction three times, under the optimal conditions (2 min x 5 min at 80°C) followed by deanup with Supeldean LC-Florisil (1 g/6 mL) cartridges, to a reference material (IAEA-140-0C Fucus (35 g) from ANAIAB) containing the 13 target PAHs.

The International Atomic Energy Agency (IAEA) supply reference material with recommended values for 9 target PAHs (ANT, PHE, FIN, PYR, B(a)A, CHR, B(k)F, B(a)P, B(ghi)P), establishedon the basis of 8-28 statistically valid results submitted during an international Iaboratory inter-comparison exercise [START_REF] Villeneuve | World-wide and Regionallntercomparison for the Determination of Organochlorine Compounds and Petroleum Hydrocarbons in Fucus Sample IAEA-140,1ntemational Atomic Energy Agency[END_REF]. As shawn in Fig. 7, concentrations of 8 target PAHs measured (ANf, PHE, FTN, PYR, CHR, B(k)F, B(a)P, B{ghi)P) were included in the recommended value ranges (95% confidence intervals). Only B(a)A was slightly overestimated, due to the presence of chromatographie interfering peaks, because the reference mate rial con tains numerous other organic compounds such as polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs).

The IAEA also supply information values for ACE, FI.R, B(b )F and D( ah)A( established with 3-7 accepted labo ra tory results ). The concentrations measured with optimal PI.E and SPE conditions were within the information value 95% confidence intervals. :z:

<1: IL B(gh i)P b H 。 I p セ セ M M \ @ セ M M M M M \ @ B(k)F ANT y= x >-------;1 PHE / / 1 セ @ z= PYR ^ M M M M M M J セ @ 0 セ M M セ M M M セ M M セ M M M セ M M セ M M M M T @ 0

Study of spatial and inter-spedes variability at a rural site

Using the optimal analytical procedure, the 13 target PAHs were quantified in the moss samples collected from the remote site in the Aralar Range Iocated in Navarra, Spain (Table 5). Average total concentrations of 133±5 and 130±5ngg-1 (dry weight) were measured in the H. splendens (Hedw.) Schimp. and H. cupressiforme Hedw. samples, respectively. The levels were of the same arder of magnitude as those measured in the H. in the Bertiz Nature Reserve, located 35 km from the Aralar Range sampling site, also showed average totallevels for the 13 PAHs of approximately 1 00 ng g-1 (dry weight) in the moss H. cupressifonne [29] . Average individual concentrations ranged from 1.3 ± 0.2 to 30±3 ngg-1 (dryweight) forANT and FLRrespectively inH. splendens and from 1.2 ± 0.1 to 32 ± 3 ng g-1 (dry weight) for ANT and PYR respectively in H. cupressifonne. The major compounds in both species were FLR, PHE, FTN and PYR, with concentrations over lOngg-1 (dry weight), as previously found in the Bertiz Nature Reserve [29].

The nine sam pies of H. splendens were sampled from soi! at severa! points over 200 rn, at the limit between grassland and forest, where local conditions varied slightly (light intensity, throughfall precipitation ... ) in function of the canopy cover. The analysis of the se sam pies revealed relative standard deviations lower than 20% for ali target PAHs, of the same order as the reproducibility previously determined in this study with a homogenous composite sample. The low variability showed that the local environmental conditions had a negligible influence on bioaccumulation of PAHs by the mosses.

Individual concentrations of FLR, B(a)A, B(b)F, B(k)F, B(a)P, D(ah)A, B(ghi)P were significantly lower in H. cupressifonne than in H. splendens samples. PYR concentrations were significantly higher in H. cupressifonne. The quantity of PAHs bioaccumulated was therefore specifie to the moss species, as shown previously by Galuszka [32] who observed higher PAH accumulation in H. splendens than in Pleurozium schreberi mosses. The variability of bioaccumulation between species can be explained by their different morphologies and/or their growth conditions. H. splendens is a weft moss with feathery fronds, whereas H. cupressifonne has prostrate, creeping stems which form smooth, dense mats [START_REF] Goffinet | Bryophyte Biology[END_REF]. Moreover, H. cupressifonne was growing on tree stumps and dead branches under forest cover, whereas H. splendens was collected from soi! at the Iimit between the forest and grassland. Therefore, to biomonitor atmospheric deposition of PAHs with severa! moss species, preliminary inter-species calibration is necessary.

Conclusions

PAH extraction from the moss 1. myosuroides Brid., using Soxtec with n-hexane showed average PAH recoveries of 67-77% and concentrations of approximately 200 ngg-1 (dry weight). To increase the extraction turnover and reduce solvent consumption, PLE was tested. The PLE factorial design revealed the optimal extraction conditions: 80 oc for 2 cycles of 5 min, giving maximum recoveries and ensuring good selectivity for moss PAH determination at trace levels. Under optimal PLE conditions, satisfactory average recoveries of 68-70% were obtained and concentrations similar to tho se for the Soxtec extraction procedure were measured, whereas solvent volume was divided by 3 and total extraction time by 5. Severa! normal phase SPE cleanup steps were tested. Supelclean LC-Florisil (1 g/6 mL) cartridges appeared to be the most efficient since the purified extracts contained the !east interfering compounds and the highest PAH concentrations. The accuracy of the optimal analytical procedure, combining the optimal PLE conditions with cleanup by FlorisiJ® SPE, was verified on a reference material.

Finally, the optimal analytical procedure was applied to sampies of H. splendens (Hedw.) Schimp. and H. cupressifonne Hedw. collected at a remote site in Navarra (Spain) in june 2010. The target PAHs were quantifiable and showed similar levels to those of previous studies carried out in Europe and locally in Navarra. The study revealed negligible on-site spatial variability for the PAH levels in the H. splendens samples, but significant differences between the levels in the two species, due to their morphology and growth conditions.

2. 1 . 2 .

 12 Chemicals and standards A standard mix containing acenaphthene {ACE), fluorene {FLR), phenanthrene {PHE), anthracene {ANT), fluoranthene (FTN), pyrene {PYR), benz(a)anthracene (B(a)A), chrysene {CHR), benzo(b)fluoranthene (B(b)F), benzo(k)fluoranthene (B(k)F), benzo(a)pyrene (B(a)P), dibenz(a,h)anthracene (D(ah)A), and benzo(ghi)perylene (B(ghi)P) at 101J.gmL-1 of acetonitrile, was used for calibration {Mix 16 HAP, LGC Standards, Teddington, UK). Deuterated PAHs were used as surrogate standards (anthracene d 10 and benzo(a)pyrene d 12 at 101J.gmL-1 in acetonitrile) and as internai standard (fluoranthene d 10 at 100 1-Lg mL -1 in acetonitrile) {LGC Standards, Teddington, UK).

1. 5 g-

 5 of homogenized freeze-dried moss sample PLE Static extraction time (5-15 min) -Preheating time: 5 min -Number of static cycles (1-3) 1 h ''rinsing mode" -Flush: 100"/o, 120 s -30 mL of raw extract containing P AHs plus interferences (pigments .•• ) SPE clean-up Supeclean® LC-Florisil, LC-Si, Strata® N-Alumina -Conditionning: 10 mL of n-hexane. -Sample deposition -Elution: 8 mL cyclohexane/DCM (60:40) 8 mL of purified extract 100 mL ofraw extract 1 mL of concentrated raw extract Strata®NH2 -Conditionning: 2*20 mL of n-hexane. -Sarnple deposition -Elution: 6 mL n-hexane/DCM (65:35)

Fig. 1 .

 1 Fig. 1. Diagram illustrating ali operations of the analytical procedure to optimize PAH determination in masses.

  TablelCentral factorial design used for the PLE optimization ofPAH extraction from masses.

Fig. 2 .

 2 Fig. 2. Box-plots of the recoveries obtained with the PIE factorial design (t-3 static extraction cydes of 5-15min at 80-140"C) forlight PAHs (ACE-+ PYR) and heavy PAHs (B(a)A-+ B(ghi)P). The box boundaries indicate the 25th and 75th percentiles. The horizontal !ines and plus signs ( +) within the boxes represent the median and mean values respectively.

( 1 -"

 1 4), the colour of the extracts was Jess intense than at 140°C[START_REF] Nauss | Diesel Exhaust: A Critical Analysis of Emissions, Exposure and Health Effects, Health Effects lnstitute (HEl) Special Report, Health Effects lnstitute[END_REF][START_REF] Dejean | [END_REF](7)[START_REF] Carree | Biosurveillance végétale de la qualité de l'air -Concepts, méthodes et applications (Air Quality Biomonitoring with Plants -Concepts, Methods and Applications)[END_REF], as Iow temperatures induced Jess co-extraction of matrix compounds, as shown previously by jânskâ et al.[39]. Moreover, with 80 oc static extraction temperatures, extracts were darker when the PLE was operated with 1 cycle (experiments 1 and 4) than with 3 cycles (experiments 2 and 3). Canying out severa! cycles ensures better in-cell cleanup by FlorisiJIZ, as Jess extract passes through the sorbent during each flush. As low interference is necessary during HPLC-FID analysis, extractions should therefore be performed at 80 oc with at !east two static cycles. To develop the shortest analytical procedure possible, and since total extraction time bad barely any influence on PAH recoveries, the optimal extraction appeared to be with 2 cycles of 5 min.After studying the quantitative and qualitative aspects of the PLE method, the optimal parameters chosen were:-Extraction temperature: 80 oc. -Static extraction time: 5 min. -Number of cycles: 2. These conditions were similar to those found in the literature concerning the optimization of PAH extraction by PLE in 72% 70% Total extraction time (min) ftg.1 Response surface of the factorial design representing recoveries of the heavy PAH fraction (B(a)A-+ B(ghi)P), obtained by plotting extraction temperature against total extraction time.

  Table4 Mean PAH concentrations (ngg-1 dry weight) and corresponding standard deviations (SD) measured in Isothedum myorusoides Brid by HPI.C-FID after extraction with the optimal PI.E conditions (n = 6) and comparison with the levels measured after Soxtec extraction (n=3

  l'tg. S. Light and heavy PAH recoveries obtained un der the optimal PLE conditions as a function of the SPE sorbents used for post -extraction deanup. The error bars represent the standard deviation obtained by repeating the extraction(deanup(analysis procedure flve times with each type of cartridge.

  Time (min) l'tg. 6. HPLC chromatograms obtained by ftuorescence detection (emission) after il\iection of: (a) a standard solution ofPAHs at 10 ng L _, in HPLC-grade acetorutrile (prepared with Mix 16 HAP, LGC Standards, France). (b) An extract of Hypnum cupressiforme moss sampled in 2010 in the Bertiz Nature Reserve, obtained with the optimal PI.E method followed by deanup using Florisile SPE cartridges. See text andTable 2 for chromatographie experimental conditions.

  PAH val ues gi ven by the IAEA (ng g •' DW) fi&. 7. Concentrations of9 target PAHs measured in the reference materialiAEA-140/0C Fucus (35g} {ANAIAB, France} as a function of the recommended values {ngg-1 , based on dry weight DW}. The analytical procedure was performed on 3 replicates of reference material. The experimental levels are represented by the mean concentration, and the error bars correspond to the concentration range measured (minimum and maximum). The recommended values are represented by the mean value given by the IAEA, and the error bars correspond to the 95% confidence intervals (based on 8-28 results depending on compound}. The dotted line (y =x} represents the case where the experimental value is equal to the recommended value.

  splendens and H. cupressiforme masses sam pied over the past years in rural areas of European countries [ 4,2 7 ,32]. A previous study carried out in 2008 Mean and median individual and total concentrations (ngg-1 dry weight} and corresponding standard deviations {SD} of 13 PAHs in two species of moss (Hylocomium splendens {Hedw.} Schimp. and Hypnum cupressi.forme Hedw.} sampled at a remote site in the .Aralar Range {Navarra, Spain}. The results were obtained by applying the optimal extraction/deanupjanalysis procedure to 9 sam pies of ffy/ocomium sp/endens and 3 sam pies of Hypnum cupressi{onne. PAHs Acenaphthene {ACE) Fluorene (FIR) Phenanthrene {PHE) Anthracene (AN'Ij Fluoranthene (FTN) Pyrene {PYR} Benz(a)anthracene (B(a}A} Chrysene {CHR) Benzo{b)fluoranthene (B(b)F) Benzo{k}fluoranthene {B{k}F} Benzo{a)pyrene {B(a}P) Dibenz{a,h}anthracene {D{ah)A} Benzo(g.h.i)perylene {B{ghi)P) Total Concentrations (ngg-1 DW} Hylocmnium splendens {Hedw.} Schimp.

Table ]

 ] Multilinear regression coefficients of the first order models of light and heavy PAH recoveries associated with the p-values obtained by Student's t test and their degree of "statisticalsignificanoe•.

	Parameter	Variable	Ught PAH recoveries
			Coefficient	p value
			0.6525	<0.0001
		T	-0.0022	0.8900
		t,	-0.0041	0.7990
		N	-0.0194	0.2540
		T.t,	-0.0074	0.6480
		T.N	0.0014	0.9310
		t,.N	-0.0286	0.1030
	• p<O.OS.
	•• p<0.01.
	-• p<0.001.
	80 oc, average recoveries varied insignificantlywith total extraction
	ti me.

  ) . Concentrated extracts obtained from experiments 1-8 of the factorial design. See Table1for details.

	3
	PAHs	OptimaiPLE(n-6)	Soxtec (n-3)
		Mean	SD	Mean	SD
	ACE	2.0	0.1	2.6	0.2
	FLR	35.6	3.3	14.0	2.2
	PHE	29.4	3.1	29.6	3.7
	ANT	1.8	0.4	1.7	0.2
	FfN	43.4	1.8	42.0	6.8
	PYR	96.7	1.3	100.5	18.1
	B(a)A	3.4	0.6	4.2	0.4
	CHR	9.5	1.1	11 .0	1.3
	B(b)F	2.3	0.2	2.4	0.1
	B(k)F	2.2	0.4	2.1	0.1
	B(a)P	4.1	0.5	4.1	0.2
	D(ah)A	0.7	0.1	0.9	0.1
	B(ghi)P	5.4	0.5	5.3	0.3
	Total	233.5	5.5	2203	31.1

l'tg. 4.

Acknowledgments

This work was supported by the Communauté de Travail des PyrénéesfCommunidad de Trabajo de los Pirineos (CTP). We wish to thankAlicia Ederra from the Departamento de Biologia Vegetal of the University ofNavarra (Pamplona, Spain) for helping us with her botanical knowledge during the moss species identification phase, and Nerea Aragonés, Raul Bermejo, Laura Gonzâlez, josé Miguel Otano and jesus Miguel Santamaria of the Laboratorio Integrado de Calidad Ambiental (LICA) of the University of Navarra (Pamplona, Spain) for supplying us with moss samples. We also wish to thank Laure Candy and Christine Raynaud from the Laboratoire de Chimie Agro-Industrielle (LCA) for their advice on experimental designs.