S Vardoulakis

N Gonzalez-Flesca

B E A Fisher

K Pericleous

SMALL-SCALE SPATIAL VARIABILITY 0F Am POLLUTION IN A COMPLEX ROADSIDE ENVIRONMENT: REPRESENTATIVENESS 0F MONITORING DATA

Thé strong spatial and temporal variability of air pollution detected at roadside locations in a number of European cities has raised thé question of how représentative thé site and time period of air quality measurements actually can be. To address this question, a long-term sampling campaign was carried out on a major road axis leading to a very busy intersection in central Paris, covering thé surroundings of a permanent air quality monitoring station. Diffùsive BTX samplers as well as a mobile monitoring unit equipped with gas analysers and meteorological instruments were used to reveal thé small-scale pollution gradients and temporal trends near thé permanent monitoring station. Thé diffusive measurements were taken at différent heights aboyé thé ground and distances from thé kerb covering summer and winter periods. Thé analysis of this comprehensive data set may help to assess thé representativeness of air quality monitoring information and generally revise thé existing siting criteria for roadside receptors.

INTRODUCTION

Since thé total number of permanent air quality monitoring stations in a city is limited due to practidal constraints (cost and bulk of equipment, power supply, etc.), alternative measurement techniques are needed in order to assess urban air quality with respect to population exposure and compliance with régulations.

In général, receptors should be located near places of expected pollution hotspots but aiso must be reasonable as related to population exposure over thé averaging times associated with ambient air quality régulations. It has been suggested in thé past that receptors should be placed at thé edge of pavement, at thé corner of two intersecting streets. Although such locations may satisfy thé criterion of maximum ambient concentrations, it can be argued that pedestrians do not usually spend a lot of time at street corners. Spécifie EU guidelines require that sampling points be located between 1.5 and 4 m above thé ground, at least 25 m away from thé edge of any major junctions, and at least 4 m from thé centre of the nearest traffic lane. For CO, thé sampling inlet should be no more than 5 m from thé kerbside and for benzène it should be located near thé building line, but at least 0.5 m away from thé nearest wall (European Commission, 2000).

In order to study thé small-scale spatial and seasonal variability of trafïic-related pollutants in a complex urban site in central Paris, a combination of air quality monitoring techniques was used between June and December 2001. Bofh active and passive means were applied to sample a wide range of trafïic-related pollutants at différent roadside and background locations.

METHODOLOGY

Thé measurements were carried out in thé asymmetric canyon of Avenue Leclerc and thé major intersection of Place Basch. Avenue Leclerc is a busy road axis linking Bd. Périphérique (i.e. me major ring motorway of Paris) in thé south with thé city centre in thé north. Roadside measurements were taken within me straight road segment between Rue Sarrette (south) and PI. Basch (north), and around PI. Basch where four avenues are intersecting. In addition, urban background measurements were carried out in Montsouris Park, at approximately 800 m distance in thé SE of the roadside monitoring site (Fig. 1).

Thé height and shape of the urban canopy surrounding Av. Leclerc is not unifbrm, since there is a mixture of traditional (usually) six-storey buildings, modem tower blocks, and few detached houses. Thé large road segment between Rue Sarrette and Rue Daudet can be considered as an asymmetric street canyon, with thé buildings on thé east side being approximately 12 m taller than those on thé west side. Thé traffic flow in Av. Leclerc is very high (approx. 66,000 veh/day) and quite congested during moming and aftemoon rush hours.

Diffiisive BTX samplers (Perkin Elmer) were exposed to ambient air during 28 consécutive seven day periods between June andDecember 2001 (Vardoulaids, 2002). Thé samplers were placed at 2.6 m height at thé ten roadside locations indicated in Fig. 1, and at one urban background site in Montsouris Park. In addition, diffasive samplers were exposed at différent heights (2 1 "1, 5"' and 10"' floor) near thé walls of thé asymmetric canyon in Av. Leclerc during one week (16-23 July). During thé same week, a mobile monitoring unit was parked on thé east side of thé canyon, inside thé separate parking lane. That allowed to record real time CO, N0, and O a values (24/24 h). Furthermore, active VOC sampling was conducted at thé same location by drawing ambient air during several one hour intervais at a constant flow through Supelco tubes.

Continuons CO and NO x measurements were obtained from a roadside air quality monitoring station (AIRPARIF) permanenuy operating in PI. Basch. Thé exact location of this station is on a narrow traffic island in thé middie of a pedestrian crossing in Av. Leclerc, very near PI. Basch (Fig. 1). Synoptic meteorological data were obtained from thé Montsouris and Orly weather Stations throughout thé campaign. During thé intensive monitoring period (16-23 July), two anemometers and a weather mini-station were located at thé kerb, near thé mobile unit. Traffic volume and average vehicle speed were obtained from permanent automatic counters pperated by thé Local Authority of Paris (Mairie de Paris) within thé selected road segment. Manual vehicle counts were taken during thé campaign and compared for consistency with thé data obtained from thé automatic network. Thé vehicle fleet composition was estimated from on site spot measurements. Finally, a QA/QC programme including sampling duplicates, field and laboratory blanks, and instrument calibration with standard gases was followed.

RESULTS AND DISCUSSION

Thé diffusive sampling measurements revealed that location H (roundabout) was thé most polluted sampling site during thé campaign. This is thé location were thé highest weekiy mean concentrations of benzène were detected for 16 out of 28 weeks of sampling, as well as thé highest benzène value averaged over thé seven months of thé campaign. Locations D, A and F were thé second, third and fourth most polluted sites respectively, according to thé same criteria. It should be noted that thèse three locations are on thé west site of Av. Leclerc, which was more often leeward than thé opposite side of the canyon (Fig. 1). Thé lowest benzène concentrations were observed at locations C and J, on thé mostly windward pavement of thé asymmetric canyon of Av. Leclerc (i.e. east side). Apart from thé prevailing wind direction, thé relative large distance (12 m) of receptors C and J from thé main traffic lanes of Av. Leclerc may explain thèse relatively low concentrations. In thé asymmetric canyon, there was no significant réduction in ambient benzène concentrations along with height above thé ground (16-23 July), probably due to thé présence of big trees, which increased mechanical turbulence and hence vertical mixing within thé street.

There was no marked seasonal variation in thé observed benzène levels in PI. Basch and Av. Leclerc, although in most roadside sampling locations slightiy lower concentrations occurred during thé summer months. At ail locations, thé highest benzène concentrations were observed in thé month of October, due to thé relatively low winds (average wind speed = 2.8 m/s) coming from thé S and SW, thus parallel to Av. Leclerc. Thèse meteorological conditions probably induced wind flow along Av. Leclerc, transporting polluted air masses from Bd. Périphérique and Porte d'Orléans junction towards PI. Basch. Thé lowest benzène concentrations were at most roadside locations observed in August, mainly due to thé reduced traffic density during this month.

During sampling, background benzène concentrations at Montsouris Park were significantly lower than those detected at ail roadside locations. Monthly averages were within thé range of 0.5 -1.0 ppb at thé background (BG), except for thé month of October when thé benzène average value in Montsouris Park was 1.5 ppb. On thé roadside, monthly benzène averages ranged between 1.3 and 4.0 ppb (Fig. 1).

Thé influence of thé synoptic wind direction on pollutant dispersion within thé asymmetric canyon is illustrated on thé pollution rosés plotted for CO and N0, (Fig. 2a). Hourly mean CO and NO x concentrations observed in Av. Leclerc (canyon) and normalised with respect to thé wind speed and traffic volume, were assigned to thé corresponding synoptic wind directions, and then mean concentrations were calculated for each wind direction sector. Both CO and N0, rosés demonstrate a clear dependence of pollution levels on thé synoptic wind direction. They show that, keeping thé other factors constant, winds paralle) or near-parallel to thé street axis (i.e. from S and N directions) favour pollution built-up on thé kerbside, while perpendicular winds (i.e. from W and NW directions) provide better dispersion conditions. Furthermore, it can be observed that normalised CO and NO x concentrations were significantly higher for southerly winds than for winds coming from thé north. This might be explained by thé contribution of Bd. Périphérique and Porte d'Orléans junction, which are both major air pollution sources in thé south of Av. Leclerc.

Following thé same methodology, normalised CO and NO x concentrations fi-om thé AIRPARIF station were used to plot pollution rosés, in order to identify thé influence of wind direction on pollutant dispersion in PI. Basch (Fig. 2b). According to this graph, there is no clear dependence of the observed pollution levels on thé synoptic wind direction, although higher normalised CO and NO x concentrations are more often associated with parallel and near-parallel winds.

Thé AIRPARIF monitoring station in PI. Basch has recorded thé highest CO and NO x concentrations during récent years in thé région of Paris (AIRPARIF, 1999). Thé CO and N0, values recorded by AIRPARIF were much higher than thé values observed within thé asymmetric canyon sector of Av. Leclerc during thé intensive monitoring campaign (16-23 July). That mainly reflected thé influence of the high trafïic density and thé short distance between thé AIRPARIF station and thé car exhausts.

Thé average N0 ; value in thé asymmetric canyon during thé intensive monitoring period (16-23 July) was 24 ppb, thus exceeding thé annual EU objective of 21 ppb. Although thé averaging times were différent, this value indicates that thé air quality objective for NO z might not be met in thé long run. Thé long-term (i.e. seven-month) benzène averages at ail roadside locations were clearly above thé annual EU limit of 1.6 ppb, while thé average value in Montsouris Park was below this threshold during thé same time period.

CONCLUSIONS

Diffusive BTX sampling was proved an efficient technique for revealing thé spatial variability of air pollution in a complex roadside environment. Thé air circulation within Av. Leclerc gave rise to relatively high pollutant concentrations on thé leeward side of the street. Nevertheless, winds parallel or near-parallel to thé street axis induced thé highest roadside concentrations, while perpendicular winds generally reduced pollution levels (especially on thé windward side of thé street). There was no marked seasonal variation in thé observed values. Higher concentrations were mainly associated with relatively low southerly winds, which probably transported polluted air masses from Bd. Périphérique toward PI. Basch. Concem was created over thé observed benzène values, which seemed to exceed thé EU objective at ail roadside locations, although thé urban background average remained below thé same threshold. Given thé pronounced smallscale spatial variability of urban air pollution, thé siting of monitoring equipment becomes crucial.

Thé permanent AIRPARIF monitoring station in PI. Basch does not fùlfil thé siting criteria specified in thé EU directive, since thé sampling inlet is placed in thé middie of a very busy avenue and very close to a major intersection. At this position, thé direct intake of undiluted exhaust gases cannot be excluded. Not surprisingly, thé AIRPARIF station in PI, Basch has recorded thé highest CO and NO x concentrations during récent years in thé région of Paris. Furthermore, thé CO and NO x values recorded in this station were much higher than thé concentrations observed within thé asymmetric canyon segment of Av. Leclerc during an intensive one-week monitoring period. Even though people hâve access to thé narrow traffic island where thé AIRPARIF station is permanently located, they do not stay there for long. Therefore, it can be argued that this is not an appropriate monitoring site for estimating population exposure in Paris, although it may be still usefùl for observing traffic émission trends.

Parking laoe

Six

Fig. 1 :Fig. 2 :

 12 Fig. 1: Average benzène concentrations (ppb) in Av. Leclerc -PI. Basch during seven months (plan view).

ACKNOWLEDGEMENTS

This study was funded by thé French Ministry for thé Environment. Thé authors would like to thank Jean-Claud Pinard for his technical assistance, Armelle Frezier for thé chemical analysis of thé samples and Nathalie François for thé préparation of thé déviées at INERIS. Thé Local Authority of Paris is aiso acknowledged for providing traffic information.


Patrice Mestayer'

Pierre Durand

Patrick Augustin

Jean-Marc Boirnefond

Bruno Bénech

Bernard Campistron

Alexis Coppalle

Hervé Delbarre

Bénédicte Dousset

Philippe Drobinski

Aimé Druilhet

Emeric Fréjafon

Sue Grimmond

Dominique Groleau

Mark Irvine

Claude Kergomard

Saïda Kermadi

Jean-Pierre Lagouarde

Aude Lemonsu

Fabienne Lohou

Nathalie Long'

Valéry Masson

Clotilde Moppert

Joël Noilhan

Brian Ofïerle

Tim Oke'

Grégoire Pigeon

Vincent Puygrenier

Jean-Michel Rosant'

Frédérique Saïd

Jennifer Salmond

Martine Talbaut

James Voogt

UBL/CLU-ESCOMPTE : THE URBAN BOUNDARY LAYER FIELD EXPERIMENT OVER MARSEILLE AND THE DATA BASE

Thé UBL/CLU experiment is a side project of thé régional photochemistry experiment ESCOMPTE over thé Berre-Marseille area. ït took advantage of thé large expérimental set-up, with chemistry and dynamics, ground-based and airbome instrumentations, including a large array of vertical and 3D sounders. With additional spécifie instrumentation in thé lower urban atmosphère, thé UBL/CLU project aimed at documenting thé dynamics and thermodynamics of the urban boundary layer (UBL) of the Marseille area during sunny periods. To date thé initial data analyses include (a) thé quality control inter-comparison of energy flux instrumentations, (b) thé quality évaluation of thé measurements at thé urban stations, (c) thé comparison of thé Town Energy Balance model with thé data obtained over thé city center, (d) thé évaluation of heat flux measurements with thé scintillometers, (e) thé température and moisture variability at thé canopy level, (f) thé 3D structure of the UBL during sea breeze épisodes, (g) thé visible and thermal infrared signatures of the urban canopy, (h) thé numerical urban data base and satellite data analysis to generate high resolution land use and aerodynamic roughness maps.

INTRODUCTION

Thé ESCOMPTE field campaign took place over an area of 120 km x 120 km, from June 4 to July 16, 2001. Thé set-up involved 20 stations, equipped for gas (ozone, nitrogen oxides, VOCs, ...) and/or particle measurements, among which two on ships, and two in trucks. Thé surface energy budget was measured at 9 sites. Thé meteorological basic parameters were aiso measured at 5 complementary sites. Wind profile was continuousiy measured at 12 sites by 7 sodars, 4 UHF and 4 VHP radars. Three Lidars were aiso operated, as well as 4 radiosonde Systems, and 7 aircrafts. Finally 33 constant-volume balloons were launched and tracked during thé Intense Observing Periods (lOPs). Thé UBL/CLU experiment aimed at documenting thé four-dimensional structure of thé urban boundary layer in connection with thé urban canopy energy exchanges with thé atmosphère during a summer period of low wind and breeze conditions. Thé objectives were (1) to compare urban and rural atmospheric boundary layers (ABL), explore thé influence of sea breeze on thé UBL, and document thé UBL turbulent fieids, and (2) to construct a data base allowing to test urban energy exchange schemes, surface température remote sensing from satellites, and high resolution meteorological and chemistry-transport models. During thé campaign, two types of intensive observation periods were more densely documented : -thé 5 ESCOMPTE lOPs (called 1, 2a, 2b, 3 and 4, for a total of 15 days) during situations of land-sea breeze and high insulation, mixed with a light Mistral during thé lOPs 2a and 4. During thèse periods one airplane flew over Marseille to document thé urban boundary layer, measuring thé atmospheric composition and thé wind and turbulence within or at thé top of the boundary layer.

-thé 4 Infrared lOPs when a light airplane equipped with a thermal infrared mapping caméra scanned thé urban canopy at différent times in thé day. Thé influence of spatial resolution and sensor orientation on thé surface température measurements were documented by flying successively in 8 différent directions with respect to thé sun over thé same sites : 3 typical city quarters including thé city center around thé CAA site monitored by thé array of IR radio-thermometers. Radio-sondes were launched from thé Observatoire site during thèse lOPs, and air température was aiso monitored at thé 2 m level with a car driven under thé flight paths. After data qualification/validation, most of thé data hâve been delivered to thé ESCOMPTE structured data base (http://medias.obs-mip.fr/escompte) which will be freely accessible after April 2003 for model validation.

THE EXPERIMENTAL SET-UP AND THE FIRST RESULTS

Some spécifie features of Marseille must be noted (Figure 1). It is located within an arena of hills, 400-650 m high, separated by small valleys converging towards thé city center ancient harbor (Vieux Port) and thé Prado beach, which are themselves separated by two steep hills about 250 m high. Thé city faces thé sea on thé west, in thé southem part of a large bay, while at a scale of ~100km thé coast is facing thé Mediterranean Sea to thé SSW. This combination of orientations requires spécial attention during thé breeze épisodes as welî as when thé weather is dominated by a low Mistral, thé northem wind exiting from thé Rhône valley. Thé population of thé urban area is slightiy less than one million inhabitants. Except in thé city cenler, thé harbor area and thé outskirts, thé urban fabric is most often composed of an irregular admixture of small individual or collective houses and small ensembles of 4-10 levels collective dwellings.

In thé city center, roughiy a circle 2 km in radius around thé Vieux Port, thé streets are relatively regular and thé constructions form a dense canopy averaging 15 m in height, with sparse, higher, isolated buildings. Thé harbor area is a strip of low storage constructions and surfaces, about hait a kilometer wide, ail along thé Northem coast. Thé outskirts are mainly composed of individual houses with gardens, rarely over very large surfaces without any collective building ; they spread over thé hill slopes. Thé city contains quite few high rise towers, aiways isolated, In thé urban area, thé permanent instrumentation was mainly deployed at five sites along thé' North-South axis of the city, roughiy parallel to thé shoreline (Figure 1). Three urban/suburban stations (GLM, CAA, STJ) were equipped with micro-meteorological masts where thé turbulent and radiation fluxes necessary to monitor thé canopy surface energy budget were continuousiy measured : thé masts raised some 12 to 20 m above thé urban canopy level and thé turbulent fluxes were measured at 2 levels. Thé other two sites (OBS, VAL) aiso included turbulence instrumentation on 12 and 10 m masts, respectively, as a ground référence of vertical profilers (see below).

Thé central site (CAA) was located in thé rather uniform, 18-19th Century, dense part of the city center. Surface energy balance fluxes were measured using eddy covariance instruments and radiometers, mounted on a pneumatic tower on thé roof of thé Cour d'Appel Administrative, 20.7 m above roof level. Two scintillometers were aiso deployed to evaluate thé integrated heat flux over thé city center, with 2 km optical paths oriented N-S and E-W respectively. In addition thé site was aiso equipped with an array of up to 19 IR radio-thermometers, either fixed to monitor thé surface température of selected elementary surfaces, or hand-held to evaluate surface température distributions during periods of intense observation (two IR radio-thermometers were aiso operated at thé suburban site STJ to monitor thé composite surface températures of the ensembles immediately North and South of the site). In this urban fragment thermometers aiso monitored thé heat exchanges between building inside and outside during some periods.

Figure 2 shows examples of diumal cycles of the energy balance components over thé IOP 2, used to test thé urban energy schemes LUMPS and TEB. Thé TEB model was evaluated using air-température from within urban canyons, surface températures for roads, roofs and walls, and flux measurements from thé tower and scintillometers. AU thé energy fluxes were simulated well and thé model succeeded in producing a positive sensible heat flux at night, and thé correct daily cycle of heat storage. An array of 20 T-RH sensors with continuons recorders, at a 6 m height above thé ground allowed to monitor thé dependency of thé urban heat island on thé meteorological conditions. In addition some transect T-RH measurements were occasionally obtained with a car equipped with T-RH ventilated sensors at z = 2 m. Thé set-up included an array of four vertical sounders : two Sodars at thé sub-urban sites GLM and STJ, sounding thé atmospheric surface layer, a wind profiler UHF Radar and a tethered balloon occasionally measuring thermodynamic and ozone profiles from 20 to 300 m, at thé OBS site, close to thé city center, and a RASS-sodar température and wind vertical sounder at thé VAL site. At this site, located at thé border of thé city and overlooking most of thé urban area two Lidars were scanning thé atmosphère horizontally and vertically up to a distance of about 10km : a UV Lidar measuring thé 03 concentration, and a 10 (im Doppler Lidar (called TWL, transportable wind Lidar) measuring thé radial wind ; both instruments were operated in parallel to générale tomographic observations of thé aérosol content and thé UBL structure in thé scanned volume (Figure 4) . Thèse sounders were aiso part of a larger array of vertical sounders within thé ESCOMPTE expérimental set-up allowing to monitor thé 3-D structure of the ABL over thé régional demain. Thé data from thé sounders are composed with those obtained during thé airplane flights over Marseille (Figure 3) to provide complète understanding of the UBL/ABL structure. Satellite images were collected during thé experiment, from a variety of sensors and platforms. About 150 useable images from thé Advanced Very High Resolution Radiometer (AVHRR) on board satellites NOAA-12, NOAA-14 and NOAA-16, collected at thé University of Modena by F. Parmigiani, were contributed to thé project, an average of 4 images/day for thé period 4 June to 13 July 2001. Sixty-six images from MODIS on board thé TERRA satellite were aiso obtained from thé NASA/EOSDIS data center. Finally, a single high resolution ASTER image was obtained from NASA/JPL and NASDA on 27 May 2001; this was complemented by an additional image on 2 August 2002. Thé thermal data set aiso includes airbome measurements using a PRT5 Bames radiometer (8-14 uni spectral band) aboard thé Merlin IV aircraft providing nadir surface température, and a thermal infrared (TIR) caméra (INFRAMETRICS model 760, 7.5-13 um spectral window) equipped with 80° wide-angle lenses and placed aboard a PA28 aircraft, inclined about 20° backward. Flying several axis crossing above thé city allowed to obtain TIR measurements in a -60° to +60° range of zénith view angles and in ail azimuth directions, and to characterize TIR directional effects as thé différence between oblique and nadir measurements of radiative surface température. As an example. Figure 5 shows thé AVHRR (channel 4 not corrected for atmosphère), Inframetrics caméra, and SC500 FUR scanner thermal infrared images of July 10 2001 at 13:18 UTC. Différences in brightness température of up to 5 and 8 C are observed between rural areas, and thé urban-industrial areas of Marseille. In thé city, surface températures (LST) reach 31 °C in thé densely built areas, with small parks generating cool islands of 1.5 to 3.5 °C. LST are somewhat lower in residential areas (29 °C), probably due to larger proportions of végétation.

Multi-spectral and panchromatic SPOT images were aiso analyzed to obtain with a very high resolution thé types of surface coverages. Spécifie statistical analysis of the 3-D data base BDTopo of IGN (thé French national géographie institute), describing such urban objects as buildings, constructions, végétation, etc., hâve been combined with satellite data to générale high resolution maps of the surface energy model input parameters such as urban land uses, roughness length, albedo, etc.

Figure

  Figure 1. Map of thé Marseille area. Thé shaded rectangle shows thé area covered by thé IGN data base BDTopo. Thé grey levels indicate thé terrain altitude. Thé poly-lines are thé building contours. From North to South thé hill lines are called l'Etoile, Garlaban St Cyr, Carpiagne, Les Calanques, Marseilleveyre

Figure 2 .

 2 Figure 2. Surface energy balance fluxes at thé central station CAA for six days during IOP 2

Figure 3 .

 3 Figure 3. Dissipation rate of turbulent kinetic energy (mY 3 ) measured with thé Merlin IV (MeteoFrance) along thé south-north legs at levels 1050, 750 and 500 m. Thé overflown relief is aiso represented with thé sea on thé left (south). Thé duration of the flight over thé town, between thé Calanques ridge to thé south and thé Etoile massif to thé north, is 3 minutes. Thé energy spectrum high frequency tail is a relevant indicator of turbulence intensity in such inhomogeneous conditions.

Figure 4 :

 4 Figure 4 : Vertical cross section of radial velocities with TWL pointing eastward towards land ( azimuth 110°). Thé arrows indicate thé flow circulation in thé section.

Figure 5 .

 5 Figure 5. Example of multi-scale approach of the TIR over Marseille city with NOAA-AVHRR channel 4 (a), airbome Inframetrics 760. caméra (b), SC500 FLIR scanner from roof level (c) (brightness températures wilhout atmospheric correction, scales of 17.5-32.5, 29.0-43.0 and 20.0-50.0 °C respectively) _i.*r-.~7«-*«-

ACKNOWLEDGEMENTS

Through thé coopérative projects CLU and TUE, thé UBL/CLLJ-Escompte experiment was funded by thé CNRS programs for atmospheric dynamics (PATOM) and remote sensing from space (PNTS). As an ESCOMPTE associated project it aiso benefited from thé ESCOMPTE funding. Thé BDTopo urban data base was provided by thé Institut Géographique National (IGN).


H Y Wang

P Joulain

A Carrau

Risk assessment of a fire involving Combustible Materials in a Warehouse

Keywords: warehouse fire, combustible materials, flame spread, thermal impact, toxic effects

This paper shows how a quantitative risk analysis method may be used to evaluate the risk to which the environment of a warehouse may be subjected if a fire breaks out. The purpose of this paper is to present the results the numerical simulations performed with the code FDS [1] in a large volume representative of a warehouse. Evolution of the thermodynamic system is governed by the equations of conservation (mass, energy and chemical species) and by the ideal gas law equation. The results and findings have implications for the modeling of flame spread in warehouse, and for the identification and the assessment of the risks associated with the product storage. Both quantity and type of combustible materials, once ignited, play a major role on the flame height (thermal impact) and on the emission of toxic chemical species, such as carbon monoxide (CO) and soot (C). The present work has been undertaken to study the aspect of gas temperature, velocity, chemical species and radiative intensity during combustion in the case of warehouse fire.

Introduction

Warehouse fires are particularly serious. Warehouse fires are usually much more highly localized but behave as intense emitters of heat, smoke and other combustion products. In the warehousing field, fire safety is fundamental for the protection of human beings and the environment. In this paper, a methodology for simulating the near field hazard associated with the flame height and toxic chemical species as a function of the combustible materials is presented. The spread fire along the solid surface has always been occupied a large proportion of the research effort in fire science. The model described here is a numerical implementation of a thermal and fluid-dynamic theory to predict the rate of flame spread. Assessing the hazard of combustible materials requires an understanding of the effect of such geometries on flame height. However, task of obtaining the experimental data or analytical solution for a large warehouse fire is not possible to describe the flame-surface heat flux which is responsible for the fire to spread. It is now relatively expensive to perform a CFD calculation in the design phase for safety consideration of a warehouse. Therefore, engineering methods have become important with the development of tools to assist in the design procedure. However, in the case of warehouses, fire safety engineering techniques are less developed, there is no method available which will reveals whether this calculation is sufficiently safe and economic.

A collaborative projet between LCD and INERIS was set up that aims at evaluating and improving fire modeling methods and engineering tools for use in warehouse fire safety. The first task of the collaborative projet is to evaluate the current capability of fire models to analyse the warehouse hazard. INERIS is specificaly covering safety issues of industrial premises and related to the environment. This carries out studies for fire safety purposes in France and intervenes as a technical support to the authorities for the evaluation of fire safety of the industry.

CFD theoretical analysis

The gas phase model consistes of the conservation equations for total mass, momentum (full Navier-Stockes), energy, and species mass fractions (fuel and oxygen), formulated as,

^ ^ (1)
(2)

dt d Xi uiuj) dp dt ô X j dxi LL Ôh dph | g(puih) Dp = Ô dt d Xj Dt di Pn dx-K
Here, u is the velocity, p the perturbation pressure from ambient, p density, gi the acceleration of gravity, q c the rate of heat release per unit volume due to combustion, q r the radiant energy flux, and Pr t (=0.5) the turbulent Prandtl number. The Large-Eddy-Simulation method is used in which the large-scale eddies that govern the mixing of the gases are directly simulated. The sub-grid scale motion is calculated by use of the Smagorinsky model [START_REF] Kb. Mcgrattan | Fire Dynamics Simulator[END_REF] which relates the unknown subgrid scale (SGS) Reynolds stresses, T^SGS? to me local large scale rate of strain.

TjisGs -Tisses 5ii = 2 [i t Sa with Sij = ---+ -- (4) ~* ^ y ^ Aj w AI J
The eddy viscosity is given as, u t = Cs P A 2 |Sij| with Cs « 0.21 (5) where the length scale, A, is tied to the grid used in the calculations, and the time scale is determined by the local resolvable dissipation. The perfect gas law is used to describe the equation of state, Here, 9? is the universal gas constant, T the temperature, w s the molecular weight of species i, and Yi mass fraction of species i.

The following global one-step irreversible chemical reaction for complete combustion of a hydrocarbon fuel is assumed,

C x H y O z + v 02 (O 2 + 3.75 N 2 )-> vco CO + VcO2 C O 2 + v H2 o H 2 O + v s C + 3.75v O2 N 2
Combustion process is assumed to be controlled by diffusion, permitting a mixture-fractionbased modeling approach,

dpf | a(Pttjf) = ô U t of) dt 8 Xj d Xj (sctd Xj J
where Sc t (=0.5) denotes the turbulent Schmidt number.

The heat release rate is directly proportional to the rate of consumption of oxygen, q c = -Hocb o (9) which is calculated from the local mixture fraction and a state relation [START_REF] Kb. Mcgrattan | Fire Dynamics Simulator[END_REF]. Here, H o is the heat release rate per unit mass of oxygen consumed.

Radiation model

The radiant flux vector in the energy equation ( 3) is calculated by integrating the radiation intensity over all directions. The radiation intensity is found by solving the following Radiative Transfer Equation (RTE) without scattering, VÎ)I + KI = K-(10) n The absorption coefficient, K , is a function of the mixture fraction.

Pyrolysis model

It is assumed that the solid material is thermally thick, homogeneous and its thermal properties are independent of temperature. A one-dimensional heat conduction for the condensed phase temperature, T(n,t), is applied in the direction n, rs ' ôt "' on 2 where p s , c s and k s are the density, specific heat and conductivity of the material. The mass loss rate, rh s • > of volatiles from the surface is assumed to obey the simple Arrhenius equation, m,. = A e " E/RT (12)

Method of resolution

The boundary condition at the solid surface (n=0) is ^ c (13) on where q" c , q" r are the convective and radiative heat fluxes, and A H v is the heat of vaporization (1.6lxl0 3 kJ/kg for PMMA). The mixture fraction at the burning surface is adjusted as follows, (l-f,)m,=-^-A, Us %« (14) Set dz dz Here, At is the time step, and u s the fuel injection velocity (m/s). Zero gradient conditions are used at the free boundary and the inert solid surface. The finite-difference technique is used to discretize the partial differential equations and the associated boundary conditions (13-14). All the spatial derivatives are approximated by a second-order central differences scheme and the flow variables are updated in time using an explicit second-order Runge-Kutta scheme. The pressure is found by applying the divergence condition to the momentum [START_REF] Kb. Mcgrattan | Fire Dynamics Simulator[END_REF].

CFD results and discussion

At first, the work was focused on using the FDS code to model the flame spread rates primarily controlled by radiation from the turbulent flame to the unburnt fuel surface. As an exemple, let us consider a rack fire of PMMA, as shown in Figure 1, with the fuel sizes of 1.0 m in the x and y directions, and with the total stack height.of 5.2 m. Figure 1 shows the inherently time dependent fire situation at four consecutive infinitesimal time steps from t=30 (ignition), 60, 90 to 150 s. The phenomenological analysis of flame spread between adjacent stacks is made to gain insight into the mechanisms governing the fire growth. The ignition delay time is about 30 s for a level of irradiance of 50 kW/m 2 , and can be reduced at higher heat flux. The result is a fully coupled solution to both the fluid dynamics and radiative transport equations. During a fire, convective and mainly radiative heat transfers from the flame towards the solid or liquid fuel lead to the vaporization of the fuel. In case of fire, the pyrolysis fuel and the oxygen are initially separated. Combustion takes place in the zone of mixture of fuel gases and oxidant in proportions close to the stoichiometry. The structure of a turbulent diffusion flame is composed of two areas: 1) a reaction area (flame zone) of higher temperature where the temperature is higher than 500 °C; the velocity of the fire-induced flow can increases up to 15 m/s; 2) an inert area, the thermal plume located above the flame zone composed of a hot mixture of air and combustion products. Once ignited, the flame height, Hf, is proportional to the rate of the heat release. As shown in Figure 2, a linear time-dependent of the fire growth rate is observed before t=120 s, which corresponds to 3200 kW. From the time t>120 s, the flames start to accelerate upward from the ignition source, the fire growth rate increases with an exponential function, Q oc e at , up to 20 MW. The total heat release rate generated (Q) is convected (Q c ) upwards by the fire plume and radiated (Q r ) away from the combustion region with a radiative fraction lower than 0.3. The surface temperatures of solid combustible (PMMA) in the fire growth period are presented in Figure 3. PMMA is assumed to ignite and burn at a given temperature of 653 K. The upward time-dependent velocity of the flame front is written as, Vf(t)=dz/dt (m/s). The estimates of upward flame spread velocity from Figure 3 for a rack height of 5.2 m is found to increase from 0.01 m/s for t<135 s to 0.2 m/s as t>140 s. From the above description of the fire growth in storage arrays, it can be seen that the vertical channels between adjacent stacks offer an ideal pathway for fire growth. In rack storage fire, the flame reachs rapidly the ceiling as the fire growth rate becomes extremely important. The plume fills the overall warehouse in less 10 minutes. As the time elapses, collapse of the roof (usually steel) occurs due to the material heating by heat feed back from the fire. Two warehouse configurations, differing each other by the ratio between length and width, LAV, are considered. The length (L) and width (W) of the warehouse are 150 m and 75 m for L/W=2, and 250 m and 30 m for LAV=8 with a warehouse height (H) of 13 m. The scenario chosen here is as follows: 1) a fire is generalized over a whole warehouse with a surface of 7500 m 2 ; 2) a large number of racks (49 in this study) with a width of 2 m in the x direction, a length of the warehouse width, W, in the y direction, and a height of 10 m is considered; 3) the whole surfaces of the solid or liquid materials stocked in each rack are in combustion with a mean surface burning rate of 7 g/m 2 s. The value of surface burning rate is provided by FDS [START_REF] Kb. Mcgrattan | Fire Dynamics Simulator[END_REF] Database file for a large rack fire of plastic products in warehouse. This scenario is chosen both for its intrinsic importance and because it illustrates the data needed to generate a relatively realistic simulation of such an event. Figure 4 shows a schematic representation of a warehouse open fire from a computation of the reacting fluid dynamics with about 600000 grid cells. Volatiles originating at the combustible materials due to heat feed back from the fire, mix with the surrounding air to form a diffusion flame. The simulated instantaneous visible flame shape corresponding to a gas temperature of about 500 °C for L/W=8 on the median plane perpendicular to racks is presented in Figure 5. The mean temperature contours in the cross-section parallel to racks is shown in Figure 6. Two distinct regimes are observed leading to a persistent flame zone (T>500 °C) established aibove the solid fuel (PMMA) and a buoyancy plume zone. The criterion of 500 °C is used for determining the predicted mean flame height. The numerical results show that flame height, Hf, in rack storage is a parameter depending on both the stored materials (heptane, PMMA, wood and sugar) and the warehouse length/width ratio, LAV. For the same material (for exemple, heptane), the flame height, Hf, increases from about 30 m for LAV=8 up to 75 m for LAV=2. In general, heptane and PMMA are with a high energy density, giving a flame height more important as compared to the other type of materials, such as wood and sugar. We wish to validate the computations results by comparing with the correlations. Among relations for the flame height which have been proposed, the MacCaffrey correlation [START_REF] Mac | Purely buoyant diffusion flames: some experimental results[END_REF] derived for the particular purpose of fire applications appears most suitable. A comparison between the predictions and analytical correlation for the flame height as a function of the heat release is presented in Figure 7 that shows a relatively good agreement. Moreover, it should be noted that near the fire, over a distance comparable to the flame height, the radiant energy flux can be sufficiently high to threaten both the structual integrity of neighboring buildings, and the physical safety of firefighters and personnel. The predicted soot and CO concentrations contours on the median plane for PMMA are presented in Figures 8 et 9. Variation of CO' and soot concentrations with height for four different materials, such as heptane, PMMA, wood and sugar is presented in Figures 10 and11. In general, for hydrocarbons fuels, a large fraction of the fuel mass is converted to soot, and the soot introduced is allowed to absorb radiant energy. Thus, the soot generation rate is assumed to be 10% of the consumption rate for heptane, 2%for PMMA, and 1% for wood and sugar, hi a warehouse, fuel-rich conditions for liquid hydrocarbons fuels (heptane) result in large concentrations of CO (1000 ppm) and soot (0.04 ppm) due to a significant decrease of combustion efficiency (about 0.3). It should be noted that inhalation of carbon monoxide is the main cause of fire fatalities, and air pollution. The mass flow rate in the plume at a particular elevation consists almost entirely of air entrained at lower elevations, resulting in an increase of the vertical velocity up to 30 m/s for L/W=8 and 50 m/s for L/W=2. CO and soot formed during combustion can be transported up to a height of 30-50 m by the buoyant plume through the vertical convection process. Such fires interact strongly with the vertical distribution of wind and temperature in the atmosphere. Moreover, the ambient wind and temperature fields must play a significant role as they do in the downwind smoke dispersion. Typically, much longer length scales than plume height intervene for consideration of fire plume dispersion problems. Depending on various parameters, remaining concentrations of fire gases and soot may be a source of concern at ground levels for environmental reasons.

Analytical approach

Despite this knowledge however, the complexity of the problem is such that a general CFD solution encompassing realistic, arbitrary conditions remained intractable. Fire safety design has been highly reliant on prescriptive rules in warehouse codes which specify the maximum allowed distance to a fire exposed personnel. The relevant fire safety design values shall be chosen so as to cover the credible worst-case scenario. INERIS has developped an analytical software, FNAP [START_REF] Ineris | Feux de Nappe[END_REF] based on the flame solid concept which permits to investigate easily a large number of events. This code specifies only some parameters, such as radiation intensity (<)) 0 ) from flame, transmission in air (x) and adds the relevant view factors (F) to obtain the local heat flux, <| > = <|> 0 Fc (kW/m 2 ) (15)

As shown in Figure 4, the warehouse fire is rather similar to a cone with a rectangular warehouse base. For the perpendicular sides to racks, the flame shape can be considered as a fire wall with a surface of L O b x L m 2 where L o b is the oblique side of the cone, given as :

(m) (16) For the parallel sides to racks, the flame shape can be considered as a triangular fire wall with a surface of 0.5*Hf*W m 2 . The volume of the cone with a rectangular base can be obtained as : Voone = 0.5Wx Hf xL (m 3 ) (17) The warehouse walls can be accounted for by blocking portions of the radiation through the reduction in the cone volume. The radiation intensity from flame is obtained by, ^XrXeQc (kW/m 2 ) (18)

Sf

According to FDS simulation, the maximum effective heat release generated by a warehouse fire with a surface of 7500 m 2 can reach to 3000 MW for a solid material (PMMA), and 5000 MW for an hydrocarbon fuel (heptane), which account for about 30 percent of the theoretical total heat release (that is, % c = 0.3 ). hi FDS code, the radiative fraction, % r , is assumed to be 0.35 for the large-scale fire. For L/W=2, the warehouse fire can be simulated by a cylindrical pool-like fire with an equivalent diameter obtained from,

The equivalent flame surface is calculated by,

q q Hf (m 2 ) (20) However, for L/W=8, the cone with a rectangular warehouse base, as shown in Figure 4, shall be considered for the view factors (F). The flame surface corresponding to the cone est, S f = 2LobL + LW + W Hf (m 2 ) (21) It is important to understand how much radiant energy is emitted by flame. The radiation intensity calculated from Eq. ( 18) is plotted in Table I for different products. Once the parameters, such as the flame height, Hf, from the MacCaffrey correlation, the radiation intensity, (j) 0 , from Table I, and the view factors, F, from a cone configuration, are specified, the risk analysis software, FNAP [START_REF] Ineris | Feux de Nappe[END_REF] can be used for determining the location for the physical safety of the humans where the heat flux from flame should be lower than 3 kW/m 2 for personnel and 5 kW/m 2 for firefighters.

Conclusion

According to this study, the flame spread velocity is found very fast along the rack, and increases with the rack height. The calculated mean flame height is about 3 times the pyrolysis (rack) height for L/W=8, and however, 7 times the rack height for L/W=2. For the rack fire, contribution of radiation is higher than 90%. As compared to the numerical results, the mean flame height is correctly determined by Mac Caffrey correlation.

However, there is still a lack in understanding in full details about how a rack fire is evolved spatially and temporally in a confined fire configuration. The results as presented here cannot yet be regarded as complete. It can therefore be stated, that despite the relatively simple analytical solution to achieve a fire safety design, they are inflexible and may lead to unnecessarilly expensive warehouses. It would be highly desirable to relate the burning rate to the total heat flux from the flame to the fuel surface. Also, future development should relate the soot generation rate to the local oxygen and temperature fields for determining the real radiative fraction.

Figure 1 .

 1 Figure 1. Fire growth in storage arrays between adjacent stacks

Figure 2 .

 2 Figure 2. Fire growth rate and radiation loss Figure 3. Fuel surface temperature with height

Figure 4 .

 4 Figure 4. Schematic representation of a warehouse open fire

Figure 5 .Figure 6 .Figure 10 .

 5610 Figure 5. Temperature contours on the median plane perpendicular to racks

Table I .

 I Radiation intensity for four diffrent products

		Hydrocarbon	Plastic products	Cellulosic	feeding products
	(kW/m 2 )	products		products
	L/W=2	68	41	36	23
	L/W=8	45	26	22	15


C Hulot

B Hazebrouck
email: benoit.hazebrouck@ineris.fr

G Gay

L Malherbe
email: laure.malherbe@ineris.fr

Z Pokryszka
email: zbigniew.pokryszka@ineris.fr

VAPOR EMISSIONS FROM CONTAMINATED SOILS INTO BUILDINGS: COIV1PAR1SON BETWEEN PREDICTIONS FROM TRANSPORT MODELS AND FIELD MEASUREMENTS Updated Version 14 mai 2003

Keywords: contaminated soil, soil-vapor émissions into buildings, field measurements, models prédictions 1

Soil vapor migration into house, with subséquent inhalation, is often thé main exposure pathway to humans at sites contaminated with Volatile Organic Compounds (VOCs). In thé case of VOCs contamination, quantification of indoor gas concentrations is therefore essential while assessing risks for human health. Two approaches are commonly used for quantification of indoor concentrations: indoor gas measurement or transfer modelization from thé source (soil, soil vapor phase, groundwater). Model development is relatively well advanced but measurements for model calibration and "validation" hardiy exist in thé literature. Furthermore, prédictions of indoor gas concentrations from différent models may vary by several orders of magnitude, depending on thé application. Therefore, thé validity of thé risk calculation obtained through models, and hence ofthe site management, remains highiy uncertain. Thé research project presented hère aims at providing such "validation" data. Long-term goals of thé research are improvement of modelization and aiso development of tools for site-related model-selection. Thé program consisted in comparing modelization and expérimental measurements on a test site. Thé site was a former factory with a concrète slab, contaminated with chlorinated solvents (trichloroethene and perchloroethylene) in unsaturated soils. Measurements concerned contaminant concentrations and fluxes in différent média and at différent transfer stages, but aiso key mode! parameters. Thé équations of Johnson & Ettinger and VOLASOIL models were used. Air concentrations measured at various times show significant variations, and aiso differ from model prédiction by one or two orders of magnitude. Despite thorough parameter measurements, uncertainty on input values, related to site heterogeneity, induced high uncertainty in thé modelization. Thé preliminary results presented hère show intrinsic limitation of some measurements and hence of model validation, but aiso thé need for data on more sites, including very important site instrumentation which would allow to document thé impact of site-heterogeneity.

Introduction

Soil vapor migration into house, with subséquent inhalation, is often thé main exposure pathway to humans at sites contaminated with Volatile Organic Compounds (VOCs). In thé case of VOCs contamination, quantification of indoor air concentrations is therefore essential while assessing risks for human health. Two approaches are commonly used to produce indoor air concentrations: • repeated indoor air measurement; • transfer modelization from thé source (soil, soil vapor phase, groundwater), from concentrations measured in soil, in groundwater or in soil gas.

1/9

Soil-vapor modeling is often required to predict thé risk on such sites: modelization can limit thé uncertainty in measurements due to thé high time-variability of thé soi! gas to indoor air transfer, and aiso allows prédictions for future situations. Several soi! vapor intrusion models hâve been developed to predict indoor air concentrations. Thé most frequently used in France, Europe and probably in thé worid, are:

• thé VOLASOIL model from thé Dutch RIVM [START_REF] Waitz | Thé VOLASOIL risk assessment model based on CSOIL for soils contaminated with volatile compounds[END_REF], which is included in thé Dutch computer model RISC-HUMAN; • thé model developed by [START_REF] Johnson | Heuristic Model for Predicting thé Intrusion Rate of Contaminant Vapors into Buildings[END_REF], proposed in Johnson & Ettinger computer model from thé US EPA (1997), which is included in many American or British commercial computer models, such as RBCA, RISC BP,...; • empirical "ruies of thumb" on dilution factors between soil air and atmospheric air [START_REF] Rippen | [END_REF]. Thé "ruies of thumb" model is hardiy adaptable for a précise site management, and of limited accuracy considering thé main factors which may impact on thé transfer. Thé physical models VOLASOIL and Johnson & Ettinger are generally used as "black boxes", thé sitesuitability and validity of which remains unknown. Actually, conceptual validation of thé équations can be found, either directiy in thé officiai model présentation for VOLASOIL [START_REF] Waitz | Thé VOLASOIL risk assessment model based on CSOIL for soils contaminated with volatile compounds[END_REF], or in thé background literature for Johnson & Ettinger and some steps of VOLASOIL. On thé contrary, one common criticism of several models is thé lack of expérimental validation. Few or no studies for certain models, or oniy for some compounds (pesticides, benzène) were carried out in order to evaluate thé operational use for each model, and compare models prédictions with field or laboratory data [START_REF] Evans | Vapour transfer of soil contaminants. Contaminated soil[END_REF][START_REF] Oison | Characterizing exposure to chemicals from soil vapor intrusion using a twocompartment model[END_REF]. Thé Johnson & Ettinger parameters were calibrated with actual empirical results from radon [START_REF] Nazaroff | Predicting thé rate of ^Rn entry from soil into thé basement of a dwelling due to pressure-driven airflow[END_REF], whereas thé calibration ofthe VOLASOIL model is not documented in [START_REF] Waitz | Thé VOLASOIL risk assessment model based on CSOIL for soils contaminated with volatile compounds[END_REF]. So far as we know, validation through further comparison between models prédictions and field measurements is not reported for neither VOLASOIL [START_REF] Lijzen | Transcription Answers to questions Session 6. Design and Exposure multi-media models. Conditions of application to soil pollutants[END_REF] nor Johnson & Ettinger. Furthermore, prédictions of indoor air concentrations from différent models may vary by several orders of magnitude, depending on thé application. Therefore, thé validity of thé risk calculation obtained through those models, and hence ofthe site management, remains highiy uncertain. That is why INERIS launched a long term research project, co-funded by thé MEDD (Ministère de l'Ecologie et du Développement Durable) and ADEME (Agence de l'Environnement et de la Maîtrise de l'Energie), which aims to document thé empirical validity of those models in différent relevant situations. Long-term goals of thé research are improvement of modelization and aiso development of tools for siterelated model-selection. Thé following procédure was used to conduct thé comparison-study between transport models prédictions and field measurements: • review of literature and analysis of transport models in terms of their modeling conditions, parameters sensitivity..., and ofcase studies; • field studies on contaminated sites; • comparison of calculated indoor air concentrations with field measurements using différent models and site input parameters; • évaluation and interprétation based on models concepts and input parameters. This paper reports thé first field study realized and its preliminary results, and draws some conséquence for thé whole program.

Expérimental methods

EXPERIMENTAL SITE

Thé study reported hère was set up in a part of a former factory located in urban zone. Former investigations had shown a main pollution by chlorinated solvents (trichloroethylene -TCE, tetrachloroethylene -PCE) in soil and soil air (2-8 m deep), and in groundwater (about 25 m). Thé study area corresponds to a building with a concrète slab, surrounded by old buildings, asphalt or concrète roads and bare ground.

2/9

Thé investigation realized for thé study aimed at measuring: • thé contaminant transfers between média (soil, soil air, flux at he surface, indoor air); • thé model key parameters: source depth, soil and concrète characteristics, ventilation and other characteristics ofthe building.

MEASUREMENTS

Flux measurements at thé soil surface Two measurement materials developed by INERIS were chosen to estimate flow rates of chlorinated solvents.

Thé "accumulation chamber":

This system [START_REF] Pokryszka | Method of measuring surface émissions of méthane[END_REF]) is based upon a principle of accumulation chamber connected with an analyzer, in this case a FID (Figure 1). Gases emitted from thé site within an elementary surface (50 cm x 50 cm) are pumped, sent to thé analyzer and reinjected into thé chamber, creating a recirculating flow. In that way thé atmosphère enclosed in thé chamber is enriched with contaminant compounds. Thé local flow can be easily deduced from thé measurement of thé atmosphère enrichment as a function of time. Thé flow of contaminant gas is expressed in relative total flow, in this case, PCE équivalent.

Pump This measurement system is easy to operate. One measurement can be performed every 5 to 10 minutes (therefore 30 to 60 measurements per day), which ensures a rather dense sampling grid in thé study area. Due to thé low précision of thé FID, for low measured concentrations (as in thé case of thé site), this tool provides oniy indicative and relative results.

Thé "dynamic scanning chamber": Thé "dynamic scanning-chamber" [START_REF] Pokryszka | Développement and validation of a method for measuring biogas émissions using a dynamic chamber. 5[END_REF] displayed in Figure 2 is a chamber connected to an inert gas supply system and an exit with measurement points. Thé system gathers contaminant gas emitted from soil within thé inert gas flow. Thé mixed gas sampled on charcoal are analyzed. Therefore thé measured parameters (concentrations and outgoing air-flows) allow to quantify thé flow of emitted vapors outgoing from thé chamber, and thus to deduce thé flow released through thé concrète slab.

Because of thé size of thé chamber (250 cm x 100 cm x 15 cm) and its time of operating System, and aiso those ofgas pumping required for thé analysis ofthis case, thé portability is not real. Oniy between 1 and 3 points per day may be measured.

3/9

"tracei" gas i-y-,------1

Contaminant gas

Figure 2: "Dynamic scanning chamber" diagram Ventilation rate measu rement A tracer-gas, in this case SF6, was injectée! into thé indoor air. Air samples were collected at two heights (1 m and 4 m) at différent times and analyzed by chromatography. Thé air exchange rate is then calculated using thé following formula:

Ln(C/CO) = -x (t-tO),
where C is thé tracer-gas concentration at time t, CO is thé tracer gas concentration at time tO, x is thé air exchange rate in thé buildings. Thé results of thé field survey of November 2002 are given in Figure 3. ----^-------------------------------------------- -----------------------------^^-g • 1 m height 0 2m height ---linear régression (2 m height) "' i liiinai legieif&iun (1 in lieîylil) |

£ -5 o• -1 1 -2 • Time (min) ^i -->à> ^------ ^t ----------1 *^.------------ ->s. ---------------
Figure 3: Air exchange rate Sampling, soil gas wells, concentrations measurements Soil was sampled at différent depths using techniques which limit vapor loss: quick sampling from an hollow shape boring into brown-glass, gas-proofglasses,... Soil gas weils were built in thé bore-holes: they consist of:

• a 1 1/4 " fulI-HDPE tube surrounded by clay at no-sampling depths;

• a 1 1/4 " filter-HDPE tube surrounded by gravel at sampling depth;

• a HDPE gas-proof sealing with sampling valve. Indoor air or soil air concentrations were pumped through charcoal at a rate (< 1 I/ min) and with a volume in thé recommended constructor range. Thé charcoal was then analyzed.

4/9

Atmospheric / soil pressure différence Thé atmospheric / soil pressure différence was measured using a differential pressure measuring device, with a détection limit and a précision of 1 Pa.

Other measurements Other measurements (soil and concrète water-permeability, grain size distribution,...) were performed according to relevant standards.

FIELD INVESTIGATIONS

Investigations performed:

In March 2001, nine soil gas wells hâve been installed at various depths in thé unsaturated zone in a selected area in and outside ofthe building. According to existing data on lithology and contamination, soil air samples were collected at various depths between 0,4-1,3 m and 6,8-8 m.

In order to consider thé potential seasonal variations of thé vapor émissions, field investigations were performed atdifferentseasons (April, July, September, November). Samples were collected to analyze thé following parameters :

• organic compounds in thé soil : benzène, toluène, ethylbenzene, xylenes (BTEX) and volatile halogenated organic compounds (VHOC) such as trichloroethylene, tetrachloroethylene, cis and trans dichloroethylene, vinylchloride; • physico-chemical parameters of thé soils : organic carbon fraction, water permeability, grain size distribution...; • physical parameters of thé concrète slab; • organic compounds in thé soil air, indoor and outdoor air (aiso with thé "dynamic scanning chamber"), with sampling on charcoal. About sixty measurements of soii-to-air fluxes with thé "accumulation chamber" were carried out at two field investigations (April and July). Firstly according to a regular grid, and secondiy following thé results, at points where thé highest fluxes had been recorded. Thé "dynamic scanning chamber" points were located on thé points of highest fluxes as measured by thé "accumulation chamber" (4 points). Thé pressure différence between soil air and indoor air was measured twice (July, September), and thé air exchange rate of thé building once (November). Thé summary of thé contaminant measures for trichloroethylene (TCE) and tetrachloroethylene (PCE) ' Other components proved not to be relevant, due to very low concentrations. Results for non-contaminant parameters are presented below with thé parametrisation ofthe modelization. 2 Due to sampling or analyse: results are below détection limit (<0,04 ug/m 3 TCE and <0,08 ug/m 3 PCE on ail points) are discarded because they do not appear compatible with usual background concentrations (>0,1 ug/m 3 ).

5/9

Those investigation results show significant time-variations in soil air and indoor air concentrations and in fluxes. No cohérence between those time-variations could be observed considering:

• soil gas concentrations, fluxes, and indoor air concentrations: thé highest concentrations in indoor air (July) were neither linked to highest soil air concentrations, nor to thé highest fluxes with thé "dynamic scanning chamber"; • spatial repartition for Surface flux, "accumulation chamber"; • soil gas spatial repartition in one campaign compared to thé two others.

Possible causes for those time-variations and uncertainty sources include: • meteorological conditions;

• major excavation works 50 m from thé building; • analytical results? But measures on soil gas samples which were repeated within a day showed less than 30% variation. On thé contrary, a relatively good spatial cohérence was observed between soil concentrations, soil gas concentrations (in two campaigns oui of three), Surface flux obtained with thé "dynamic chamber" (one campaign with enough points), and indoor air concentrations (one campaign with enough points)3 .

Modelization

Simulations hâve been conducted with thé équations of Thé [START_REF] Johnson | Heuristic Model for Predicting thé Intrusion Rate of Contaminant Vapors into Buildings[END_REF] ; with infinité source équations) and VOLASOIL [START_REF] Waitz | Thé VOLASOIL risk assessment model based on CSOIL for soils contaminated with volatile compounds[END_REF] Thé VOLASOIL model was designed and explained for thé case of a crawl space and a one-layer soil over thé contamination source which is not relevant to thé situation of thé expérimental site. Therefore, starting from thé basic diffusion and convection équations, we developed thé VOLASOIL équations for a multi-layer soil, which allowed us to apply it for a concrète layer over a soil layer.

Main parameters used in modeling and input values are presented in Table 3 Based on site observations, thé soil layer above thé source was considered homogeneous. Actually, thé site observations did not prove précise enough for thé needed characterization of thé diffusion and convection parameters. For ail parameters, thé overall cohérence of obtained values was checked. That led to thé revision of ail parameter values for thé upper soil layer: before revision for example, thé input values would hâve induced a négative air-filled porosity. Thé soil / building pressure différence was so low (< 1 Pa) that it could not be measured. This can be due to thé lack of heating of thé building (unused) and to thé général soil coverage with concrète or asphalt slab and with buildings, which both are in contradiction with thé assumptions for typical pressure différences (4 Pa). Therefore, thé uncertainty of thé integrated diffusion (effective diffusivity) and convection parameter (soil gas permeability, pressure différence) appears very high (x or/ 20 or more), with a corresponding impact on model prédictions. More precisely, intermediate results from thé modelization show that in this case, thé VOCs transport mecanism is: • mainly diffusion with VOLASOIL (60-80%), limited by air-filled porosity; • mainly convection with Johnson and Ettinger (99%), limited by soil gas permeability.

Further simulations with 0,1 Pa, not reported hère, show a réduction ofthe building air concentration (factor between 1,6 to 5, depending ofthe models) with thé permeability reported hère. 5 A further simulation with 1 m, not reported hère, shows an increasing of thé building air concentration (factor between 1 to 2, depending ofthe models).

7/9

In Modelization with VOLASOIL équations appears more conservative than with J&E équations in this case. Possible reasons could include uncertainty on concentrations (soils, soil-gas,...), and on soil and slab parameters:

• with VOLASOIL, an air-filled porosity of 0,21 instead of 0,06 leads to fluxes and indoor concentrations 15 times higher; • with Johnson and Ettinger, an air permeability of 5E-15 m 2 instead of E-12 m 2 leads to fluxes and indoor concentrations 75 times lower. Possible reasons could aiso include validity problems in thé models, but possibilities for accurate interprétation in that direction are strictiy limited due to thé high possible impact of other uncertainties.

Conclusions

In this experiment, important différence between predicted and measured values were observed. But possibilities for accurate interprétation in term of model validity are strictiy limited due to thé high possible impact of other uncertainties which still remain in spite of intensive site-instrumentation. Thé time variability of field results and thé impacts of remaining uncertainties on some input parameters on model results demonstrate thé importance of précise measurements and quantification of thé main site parameters. Précision on some input parameters (diffusion parameters, soil gas permeability) can be improved by more measures, but may still be intrinsically limited in regard to thé needs of thé modelization (depending of thé site characteristics). Documenting thé empirical validity of models is aiways a difficult and time-consuming work. This is especially true for soil-atmosphere vapor transfer models, where an accurate quantification of ail thé main site parameters is hardiy reachable, due to soil heterogeneity and limits of thé measurement methods. Important instrumentation, several field measurements on each site and on différent sites, are required.

8/9

More field data are needed, in particular différent building designs, constructed materials, soils.... Sites both adéquate for characterization ("simple", homogeneous soil instead of filling) and représentative of typical model conditions (heating ofthe building,...) should be looked for, which may prove difficult: used (heated) buildings on sites contaminated with VOCs are quite seldom. That is why gathering ail works on thé subject would be necessary with thé collaboration of ail concerned private and public entities.

Figure 1 :

 1 Figure 1 : Flux chamber diagramFigure 1: "Accumulation chamber" diagram

  -.-..., . ...... , ... , 9 *,<»..<!• ; »,..», a.,

  rt^,------| 10 20 30 40 50 60 70 SOS^Q. 100 110 120 .3 i..................,....-...-....-,.....,..^^^^-

  /kg TCE, 5,2 pg/kg PCE Average March 6,1 ring/m" TCE, 43 ring/m" PCE Average July Measured From standard values of similar soils, with filling of grave! gaps by sand and cohérence with measured water content ~ water permeability of 8E-6 m/s: from measured water permeability (4E-8 m/s) and standard values for similar soils (5E-5 m/s) Minimal depth of maximal concentrations in soil gas or in soil Measured Average measured Measured (July, September): < 1 Pa Measured (December)

  : below quantification limit; nd : not detected Tableau 4: Modelization results Thé results show important différences between predicted and observed values in this case: Soil / soil-gas repartition: Measured values are equal to 1 to 150 times thé predicted values. Possible reasons could include uncertainty on soil concentrations or source depth. Indoor air and surface flux: Measured values are equal to: • ^10 to 10.000 times thé predicted values starting from soil concentrations; • ^50 to 1.000 times thé predicted values starting from soil-gas concentrations.

Table 1 :

 1 1 , taking account March to September data, are presented in Table 1: Summary ofthe contaminant measures for TCE and PCE

	Média	nit		TCE			PCE
	Soil	ug/kg		1 -8			<1°-15
	Surface flux,	ug/m^/s			< 0,35-1
	"accumulation chamber"	eq.PCE			(FID, ppm levels)
	Surface flux,	ug/m"7s	< E-4 -0,006		0,4 E-4 -0,025
	"dynamic scanning chamber"
	Soil-gas	mg/mM		0,15-38		0,73-1900
			April	July	Sept	April	July	ept
	Indoor air	g/mû	<1°-1	<1"-15	nd	0,4-2	2-40	nd
	Background air	g/m'	<1"	1	nd	0,3 -0,7	<0,3°S nd
	(*): below quantification limit;	nd : not détectéeÛ

Table 2 :

 2 models. Thé main characteristics of those two models are summarized in table 2. Main model characteristics

	Référence	Model type	Source pollution	Vapor transport	Building foundation
	Johnson & Ettinger	Steady-state	Finite or infinité	Diffusion and	Basement or constructed
	(Johnson & Ettinger, 1991)	Semi-analytical		convection	slab-on-grade
	VOLASOIL (Waitz et al,	Steady-state	Infinité	Diffusion and	Crawl space
	1996)	Semi-analytical		convection

  . Site spécifie values were used when available.

	SOIL
	Organic carbon fraction
	Dry bulk density
	Total porosity
	Water content
	Water-filled porosity
	Air-filled porosity
	Gas permeability
	BUILDING
	Slab characteristics regarding
	diffusion
	Slab characteristics regarding
	convection
	Length, width, height
	Floor thickness
	Soil-building pressure
	différence
	Air exchange rate
	SOURCE
	Depth
	Soi) concentrations
	Soil gas concentrations

Table 3 :

 3 Main modeling parameters

  Table 4, thé main modelization results, starting from soi! or soil gas concentrations, are summarized and compared to measurement results.

					TCE				PCE
				Measured	Calculated with		Measured	Calculated with
			(average, <5m)	VOLASOIL	J&E	(average, <5m)	VOLASOIL
				Modelization starting from soil concentrations
	Soil	d-ig/kg)		4,8					5,2
			April	July	Sept			April	July	Sept
	Soil-gas	(mg/m')	2,1	6,1	14	3,3		24	43	421
	Surface flux (ug/m^s)	<E-4	~E-3	6E-3	9,2 E-5	9,1 E-6	~E-4	6E-3	2E-2
	(Dynamic chamber) Building air (ug/nT 3 )	n=3 <1"	n=2 5,6	n=1 nd	0,014	0,001	n=3 1	n=2 17	n=1 nd
		Modelization starting from soil-gas concentrations (one synchronized campaign : July)
	Soil-gas	(mg/m )		6,1					43
	Surface	flux (ug/m^/s)		~E-3 n=2	1.7E-4	1,8 E-5	6E-3 n=2
	Building	air (iJg/nT')		5,6		0,03	0,003		17

No spatial cohérence was observed on fluxes between thé two chamber tools, but this can not be commented, considering thé solely indicative rôle ofthe accumulation chamber in thé case ofthe low FID values measured.6/9

Acknowledgements

This work is part of a research-project financially supported by thé MEDD and ADEME. We are gratefui to thé site owners for thé their collaboration. Thé opinions expressed in this paper are those of thé authors and do not necessary represent those of thé funding organizations.


C Rollin

H Baroudi
email: hafid.baroudi@ineris.fr

M Garcia

MODELING 0F PAH TRANSPORT IN SOILS AND GROUNDWATER 0. BOLII-(-I)

Introduction

Risk assessment for groundwater resources requires most of thé time thé use of numerical models. Thèse models are used to describe thé migration and thé transport of pollutants and to predict thé contaminant évolution. Thé models and their parameters sélection dépend on thé extension and thé quality of thé diagnosis data. Thé modeller has to know thé limits of application of thé modelling approach to improve thé quality of thé assessment. Thé research program TRANSPOL was undertaken in order to bring a better and a common practice of thé use of transport models for varions groups of pollutants with similar behaviour (PAH, metals, chlorine solvents . PAHs hâve a spécifie behaviour due to their strong affinity for thé organic matter, their low solubility, and their density. Thèse compounds are often associated with other contaminants and they are thé major pollutants of disused coke plants, wood preservative treatment plants and ancient gas production plants. PAHs can aiso be found in thé environment after major incidents or spills (fuels may indeed contain significant PAHs concentration). Thé particular behaviour of those compounds and their présent and past uses justify to study thé transport of thé soluble and non-soluble phases. Naphthalene was especially studied with two complementary approaches. Naphthalene is used commonly as a tracer of pollution for thé PAHs contamination due to its high solubility and its low capacity of adsorption, which increase its mobility. Two cases hâve been studied. Thé first case (case n 1) is a real case of PAH contamination observed 40 years after thé dismantling of a coke plant. Contamination is found in thé soil and both in superficial and chalk aquifer. Five teams hâve studied thé behaviour of naphthalene dissolved phase with thé same input data. Thèse teams used 5 différent models to predict thé naphthalene concentration in thé chalk aquifer at différent specified observation points. A real case of massive crude oil spill following thé rupture of a pipeline has been modified (case n 2). Three teams hâve studied this case (cf. Table 1 Thé superficial aquifer créâtes a dispersion and advection of thé contaminant that reaches thé deeper chalk aquifer. As 2 aquifers are présent, modellers used multilayered models. Each team had to make assumptions and to sélect thé proper parameters for thé models. That first work was rather difficult but it corresponds to thé first phase of thé work of a modeling project. Due to thé relatively complex geology, which was observed, thé range of parameters' values, which was used, is large. Thé range of variation of thé permeability values and partition coefficient exceeds one order of magnitude. Thé range of variation is lower for thé surface of thé source of naphthalene (cf. Table 2).

PA

wherea is thé bulk soil density, K c i thé partition coefficient and thé total porosity of the soil.

Thé gréât différences between parameters' values are thé main factor explaining thé range of thé results obtained by thé teams [START_REF] Rollin | Groundwater risk assessment for a polycyclic Aromatic Hydrocarbons (PAH) contaminated site ; benchmarking and validation of numerical transport models[END_REF]. This range reaches more than two orders of magnitude oencerning thé prédiction of thé naphthalene concentration in well PZ10, 200 years after thé dismantling of thé coke plant.

Courbes de restitution du naphtal ne pour le pi om tre PZ10 Thé teams hâve considered a source of naphthalene with a concentration equal to thé solubility. Thé différences of thé source volume is oniy linked to thé choice of its surface. Thé variation of thé extension of thé source is lower than one order of magnitude but thé locations are aiso différent and may influence thé range of variation of naphthalene concentration at a particular observation point. Thé flow through thé clay formation is ontrolle by thé permeability and thé dispersivity of thé clay. Thé diagnosis data allows to choose différent couples of permeability and recharge which lead to thé same fit with thé measured water table level. A more accurate value for thé permeability of thé clay is needed to reduce thé range of thé permeability values used in thé model. Thé retardation coefficient has aiso a strong effect on thé calculated concentration of naphthalene. Ail thé teams hâve considered a constant source of naphthalene and no biodégradation phenomena. Thé effect of thé retardation coefficient is especially observed in thé first two hundred years, before each curve reaches thé maximal concentration.

Modeling thé behaviour of naphthalene in thé NAPL phase

In this case (case n 2), thé modified data cornes from an accidentai spill of crude oil (cf. Figure 3). Ail thé parameters which describe thé flow and transport model were provided to thé 3 teams [START_REF] Panday | A composite numerical model for assessing subsurface transport for oily wastes and chemical constituents[END_REF][START_REF] Lebon | TRANSPOL -Intercomparaison des m thodes et des mod les de migration de polluants dans les sols et les eaux. Proposition de cas-type 1 (version 1.1 )[END_REF]. Thé modified data set concems thé infiltration of a volume of 105 m 3 of naphthalene during 6.9 days and thé redistribution of thé pollutant. Each team had to predict thé concentration and thé saturation of naphthalene at 4 observation points which are located at a distance of 50 m, 100 m, 150 et 200 m far downward from thé source. In order to simplify thé comparison of thé results and due to thé complexity of thé multiphase approach, each team used approximately thé same grid for thé numerical simulations. Thé description of the main features of the three codes used in thé simulation are displayed in table 3 Table 3 Thé average hydraulic gradient of thé water table is 0.026. As thé problem is symmetric, oniy naïf of thé field has been modeHed. Thé three simulators can model thé multiphase flow and allow thé use of van Genuchten relations [START_REF] Van Genuchten | A closed-form equation for predicting thé hydraulic conductivity of unsaturated soils[END_REF] and Parker relations [START_REF] Parker | A parametric model for constitutive properties goveming multiphase flow in porous média[END_REF]. Because of the limitations of the UTCHEM interface with GMS oniy a diphasic problem with injection of naphthalene in thé saturated zone was considered (cf. figure 4). Due to thé sinking behaviour of naphthalene and to thé rather weak oil residual saturation used (0.05), thé différence between thé volume of thé injection used by thé other teams is small enough (minus 15% relative error) to make thèse simplifications.

Thé évolution of thé profile of saturation given by thé three teams is similar. Naphthalene migrâtes quickly per descendum and builds a lens of pure NAPL phase on thé wall of thé aquifer. Thé volume of this lens decreases slowly and continuousiy with thé dissolution of naphthalene. Thé évolution of thé concentration in thé aquifer is controlled by thé hydraulic gradient and thé distribution of thé saturation of naphthalene (cf Figure 5). Thé contaminant plume increases preferentially at he bottom of thé aquifer where naphthalene tends to accumulate in pure NAPL phase.

Conclusion

For case n 1 (real PAHs contamination) thé simulation of thé PAHs behaviour in thé dissolved phase is strongly influenced by thé choice of key parameters like thé partition coefficient and thé permeability of thé clay. Thèse parameters control thé flow through thé clay and thé retardation coefficient used in thé simulation of thé transport of naphthalene. Other parameters could hâve a significant influence on thé calculated value of thé naphthalene concentration. Thé biodégradation phenomenon has not been taken into account in this case due to thé anaerobic conditions of thé chalk aquifer. In this case, a more accurate diagnosis is needed in order to reduce thé uncertainty of thé risk assessment. A sensibility study would aiso hâve highiighted thèses parameters but it would not hâve provided thé same gréât range of results. Thé uncertainty concerning thé prédiction of thé naphthalene concentration reaches 2 orders of magnitude with a rather complète data set. This data set concerns thé analysis of 40 sample soils and more than two campaigns of analyses of 18 wells and piezometers. In this case, more measures of thé clay permeability and of thé partition coefficient, made afterwards, (instead of thé use of thé data available in thé literature) hâve reduced thé uncertainty. For case n 2 (multiphase transport simulations), each team hâve reproduced thé behaviour of a heavy mixture of PAHs such as créosote, which sinks to thé wall of thé aquifer. Due to thé lack of real data for thé comparison with thé simulated concentrations, thé first intercomparison of thé results hâve shown thé importance to reproduce thé ground water velocity fields. Thé model used for thé relative permeability is thé same for thé three simulators and reduces thé uncertainty between thé results of thé teams. Thé behaviour of thé pure DNAPL phase contrasts with thé dissolved phase. In case of a massive pollution, a secondary source of pollution, more intense and durable is build during thé first stage of thé pollution transport. This pool of naphthalene is then available for further redistribution, mainly by spreading to form thin lenses and by dissolution.

Table 2 :

 2 Range of parameter used by thé 5

Figure 2 :

 2 Figure 2 : Results of calculated concentration in thé chalk aquifer (PZ10)

Figure 3 :

 3 Figure 3 : Modeling domain

Figure 4 :Figure 5 :

 45 Figure 4: Grid used (measures in foot) with UTCHEM and GMS 3.1 for thé modeling of a confined aquiferThé three oedes are able to reproduce thé particular type of DNAPL plume but thé time of arrivai and thé concentration at thé observation points may vary more or less according to thé use and thé différent features of thé numerical codes. Due to thé choice of thé model of an unconfined aquifer, which strictiy respects thé domain of modeling, two teams had to check thé influence of thé superposition of thé régional gradient and thé recharge by thé rains. Thé coupling of thé fixed upstream and downstream conditions of potential with thé recharge produces a hydraulic gradient with a continuous variation which hâve to fit thé data.I

Table 1 :

 1 ). Thé différent teams and codes used in thé intercomparison process Modeling thé behaviour of naphthalene in thé dissolved phase Thé coke plant was built on heterogeneous filling materials. Under thèse superficial layers, a superficial aquifer is présent. Thé chalk aquifer is separated from thé superficial one by a layer of clay. A geological cross section of thé site is shown in Figure1.

	Case studied	Teams and model
		1NERIS, MODFLOW + MT3D [1,2,3]
	Case 1 : modeling of thé dissolved	BRGM, MISP [4,5]
	phase with a real data set coming	FSS, Visual MODFLOW + MT3D [6]
	from diagnosis	ANTEA, MARTHE V5.4 [7]
		CNRSSP, FEFLOW 4.7
	Case 2 : modeling thé flow of naphthalene as a NAPL	INERIS, UTCHEM [8] LAEGO/IFP, SIMUSCOPP FSS, TOUGH2/T2VOC [9]

re 1 eolo al ross se t on o thé s te

Acknowledgments

We thank thé participants of thé TRANSPOL program for their contributions to thé research program as well as thé French Ministry of thé Environment and of thé Sustainable Development for thé financial support.

Références