Véronique Tatry

Nathalie Bocquet

Tamara Menard

Michel Nomine

Veronique Tatry

Experimental underground facility to evaluate remote sensing instruments

Keywords: optical remote sensing, evaluation, quality assurance, air quality

To carry out metrological tests on the automatic devices used in air quality monitoring networks, INERIS follows a Standard text. In order to apply it, the instruments have been fed with reference mixtures of gases in several reproductible concentrations. Compliance with this requirement is quite easy to obtain, in the case of conventional techniques, but the problems remain with optical remote sensing instruments. The difficulties can be solved by using the Beer-Lambert law indicating that the product of the concentration by the distance is a constant value. To implement this optical law, INERIS uses a system with a two meters glass cell with quartz Windows inserted in the Instrument beam and fed dynamically with known concentrations of reference mixtures of gases. The test-bench facility is set up in a tunnel 90 meters long in INERIS. Tests on SC>2, N02 and Oy were carried out in 1997 on two types ofDOAS Systems set up in parallel: an OPSIS system and an Environment SA SANOA system. The following features were tested: the detection lünit, the linearity and the drift. The tests results on the response of the two types of instruments are in agreement with the results obtained by the ERLAP at the Joint Research Center in Ispra.

l. INTRODUCTION

Since the end of eighties optical remote sensing instruments have been used by French air quality monitoring networks. This type of instrument offers new perspectives to characterise the atmospheric pollution. Indeed, it is possible to measure simultaneously several pollutants like S02, NO, N02, Oa, hydrocarbons, and specific pollutants such äs NH3, naphtalene,... Before putting such an instrument into Operation on a monitoring place, it is necessary to evaluate its capacities and also to detennine its metrological performances.

INERIS has set up an experimental procedure to validate Differential Optical Absorption Spectroscopy (DOAS) devices. The procedure is based on that used for conventional point monitors which is described in the French Standard NF X 20-300. This text drives the evaluations in terms ofthe following metrological features : response time, linearity, limits, drift, influence ofphysical parameters, ofchemical compounds. In order to apply this text, the Instruments have been fed with reference mixtures of gases in several reproducible concentrations. Compliance with this requirement is quite easy to achieve, in the case of conventional techniques (e.g. fluorescence detection in UV, chemiluminescence, photometry) but problems remain with optical remote sensing instruments. Indeed, it is quite impossible to manufacture a measurement cell äs long äs the optical path (greaterthan 100 meters).

But this difficulty can be solved by using the Beer-Lambert law indicating that the product ofthe concentration by the distance is a constant value.

To implement this optical law, INERIS uses a system with short glass cell and quartz Windows inserted in the instrument beam and fed dynamically with known concentrations of reference mixtures of gases, in altemance with zero gas (nitrogen).

International Symposium on Envirosense, Munich, 14-18 juin 1999, b. HfL, i/S. ^ A Standard sequence is defined äs the measurement of the zero gas during a period and • the measurement of the studied gas concentration during a following period ofsame duration.

The figure l shows the Standard sequence. On one hand the duration of the sequence integrales the necessary time of cell sweeping to obtain a stable and repeatable measurement values, and on other hand it permits to collect enough data for further caiculations. This procedure is adopted with slight differences by US EPA, and by VDI/DIN in Germany.

EVALUATION TESTS ON DOAS INSTRUMENTS ON A SHORT PATH IN AN CLIMATIC ENCLOSURE

At the beginning of the nineties two types of DOAS instrument, an OPSIS System and an Environnement SA SANOA system, were tested in a 40 m climatic enclosure on a short optical path (about two meters) and by using a two meters glass calibrating cell. As the SANOA system uses 0; to autolock the spectral band , it was necessary to add a cell containing pure Oi pressure at high pressure to simulate real environmental conditions on the test path (21 % Oz equivalence). Unfortunatly, the diameter ofthis cell was smaller man the diameter ofthe beam and thus only a part of the light emitted by the xenon lamp was taken into account. For the two Instruments it was also necessary to modify the light intensity which was too strong for the distance between the projector and the receiver. For that, the operator had to defocus the light beam, by an action on the projector mirrors.

The features were studied with six pollutant gases: sulfür dioxide (SO^), nitrogen dioxide (NOz), ozone (Oa), formaldehyde (HCHO), benzene (CsF^) and toluene ^Hs).

Tests [START_REF] Poulleau | Evaluation de l'appareil de mesure de polluants atmospheriques OPSIS (S02[END_REF][START_REF] Poulleau | Evaluation de l'appareil de mesure de polluants atmospherigues SANpA CD[END_REF] gave the following results :

" the detection limits were identical or even better man those obtained with conventional point monitors for SOz, NOz and 03; but for organic compounds they were quite similar to the background ambient air concentrations.

' the response coefficient varies from an instrument to the other for the same compounds ; in one case they are under estimated, in the other case they are over estimated.

' the study of the temperature influence only with SOi showed a significant effect for a 20 degrees Variation only for one ofthe instruments

• the study ofchemical interferences carried out by crossed procedure showed significant influence of ozone during the organic compounds -benzene and toluene-measurements

• satisfying results were obtained for linearity, zero drift deviation, signal drift deviation for one concentration value on the scale, and for parasite light influence.

The practice ofthese devices is easy and the soft is user-friendly.

SvicesSe usua^y carried out for measurements on distances äs few hundred meters m open areas. Therefore, INERIS imagined a test-bench set up in a tunnel present on its premises.

TESTS ON DOAS INSTRUMENTS ON A LONG PATH IN A TUNNEL

in order to match more closely the real environmental conditions, in 1997 the test-bench facility has been set up in a tunnel that is 100 meters long and 2.5 meters high m INERIS.

This tunnel presents major advantages such äs :

• although the calibrating cell is still 2 meters long, the distance between the projector and the receiver is closer to reality (approximatively 90 meters)

" it is not influenced by the day-light or the wind

• the gas composition, the temperature (measured by Pt sensors in three points in the tunnel) and the humidity were quite constant during the tests (each test lasted few days)

In 1997, the two types ofbistatic DOAS, an OPSIS 300 System and a SANOA 3C System set up side by side, were tested in parallel and simultaneously in the tunnel.

The followmg pollutants were studied successively : S0" NO. and 03. ITie same test procedure äs the previous A^aZty^fbr each compound was put in the exit of the cells to monitor continuously the gas mixture concTnSn The SO, monitor was a Siemens IR absorption instrument, the NO^ monitor a Cosma chemTScen.^ Instrument and the 0, monitor an Environnement SA UV photometry mstrument. The testbench is schematized on the figure 2.

OPSIS receiver <----dislance betwccn projector and receiver is 91 metcra --> OPSIS projeclor For each gas all the hosepipes were changed.

Besides the zero gas, four concentrations Ci were generated in the cell (from 2 ppm to 30 ppm for SO-i and NOz and from 0.7 ppm to 16 ppm for Oa) and six cycles (zero-Q) per concentration were carried out. For SÖ2 and NOz certified gas cylinders associated with a sonic nozzle diluter were used, and for 03 a generator associated with a massflow System was used.

The following characteristics were tested : the detection limit, the linearity and the drift.

Based on Beer-Lambert law, we formulate the following assumption : the product between the concentration and the optical path length is constant, then it is possible to present the results for an equivalent optical path. We choose an equivalent optical path of300 meters, which is a mean value in real conditions.

Therefore the detection limits for the three gases are :

-between 1.5 and 2 ug/m for SÖ2 -between 2. l and 3.7 ug/m for 03 -and around 4.7 ug/m for N02

The results are acceptable for the drift test (0.04% per day) and for the linearity. (1) the optical path was 178 meters long, the test cell l meter long and placed on the optical path was fed by gas from cylinders for SÖ2 and NO:», and by a generator for 03.

(2) this result is influenced by a discrepancy between the measure and the theory for a concentration value during the linearity test When DOAS instruments are used in fieldworks, it is possible to control their response by using a very small calibration cell (few centimetres). Each instrument is fitted out with a calibration cell integrated on the optical path of the instrument. For the SANOA this cell is placed in the receiver and is 0.034 -meter long, and for the OPSIS the cell is placed in front of the receiver and is about 0.050 meter long (the exact length is indicated on the cell).

To use these cells it is necessary to feed them with very high gas concentrations such äs few hundred ppms. And some recommendations are given by the manufacturer, especially on the level ofthe gas flow and the pressure in the cell for the SANOA System : 0.5 1/mn and 300 ± 50 mbar.

Furthermore, it is recommended to operate preferably in conditions of atmospheric stability, and of constant pollution during this calibration.

A test on the influence ofthe gas flow on the response coefficient was carried out on the two calibration Systems and compared with results obtained on our test-bench fitted with two meters long cell.

The devices were set up on the test-bench in the tunnel, and the test-cells (2 meters long) were put out of the optical path during these tests.

The results are given in the table 2.

Gas flow in 1/mn 0.3 0.5 0.7 0.9 1.3 The flow Variation between 0.3 to 2 1/mn does not influence the response ofthe instrument.

We did not observe a significant difference between the results obtained with the small calibration cell and the test-bench cell ifthe uncertainties from gas generation are taken into account.

On the base of these results, it is possible to accept the procedure proposed by the manufacturers.

  Figure l : Standard sequence representation

3 Figure 2 :

 32 Figure 2 : test-bench for S02 set up in tunnel

  Furthermore our tests results on the response of the two types of instruments are in good agreement with the results obtained by the ERLAP at the Joint Research Center inIspra (1996 and[START_REF] Ottobrini | Evaluating the performance ofthe SANOA/ DOAS system for S02, N02 and 03 measurements[END_REF]. The following table l presents the results ofthis comparison.

			PSIS instrument	SANOA instrument
		INERIS	RLAP( 1 )	INERIS	ERLAPW
	SO?	0.98		1.00	0.97	1.03
	NOz	1.01		0.99	1.04	1.04
						0.96
	0^O O^E	0.98	0.95	1.06

Table l

 l : response coefficients of OPSIS and SANOA DOAS obtained for SO 2, N02 and 03 by INERIS and ERLAP The optical facility developed in INERIS tunnel and validated with different DOAS instrument, is now used systematically to test DOAS Systems before they are installed in a air quality monitoring network.

	It is
	interesting:
	" to have a data bank on metroiogical features on optical remote sensing monitors
	" to test the calibration procedure proposed by the manufacturers
	' and to test these instruments for the measurement ofpollutants such äs hydrocarbons
	In 1998, other tests were carried out on the calibration Systems used for these devices.

Table 2 :

 2 response coefficients of OPSIS and SANOA DQAS obtained for SO 2, and N02 by using the calibration cells fed at different values ofgas flow

		OPSIS Instrument	SANOA instrument
		SO-2	N02	SO'2	N02
		776 ppm (±2%)	718 ppm (£2%)	776ppm (£2%)	718 ppm (£2%)
		l	0.994	0.996	0.996
		0.996	1.002	0.992	0.998
		0.999	1.001	0.991	0.995
		1.002	1.008	0.994	0.994
		1.002	1.006	0.999	0.998
	2	1.003	1.011	/	/
	Response coefficient	0.979	1.031	0.97	1.03
	obtained with the
	test-bench cell

ACKNOWLEDGES

This work was supported by French Ministry of Territorial Planning and Environment under contracts 23/96 and 13/97.


Claude Cwiklinski

A Tewarsonc

AN ANALYSIS OF SOME PRACTICAL METHODS FOR ESTIMATING HEATS OF COMBUSTION IN FIRE SAFETY STUDIES Guv Marlair(+)

The theoretical (net) heat of combustion of materials is a basic information important for fire safety studies. This paper is a review of existing methods ranging from use of tabulated data to calculations relying on more or less sophisticated engineering correlations based on the elemental compositions of materials and in some cases on their chemical structures. The presentation emphasises only those calculation methods that allow user-friendly estimations of the heats of combustion, that is to say when at most a simple datasheet processor is the only tool required. Empirical correlations developed in early times of combustion science by Dulong (France), Boie (Germany) and some others are examined here in the context of fire engineering. More recently proposed predictive methods of heats of combustion in fire or chemical engineering background, taking account of structural effects of the molecules on their heats of combustion are then presented and compared. Finally, consideration of the relevance and accuracy of the listed methods is provided and commented either by comparison of literature and calculated values, either by reference to measured data obtained by use of conventional oxygen bomb calorimetry.

atoms

INTRODUCTION

The theoretical heat of combustion of a given product is the maximum amount of heat that a product liberates in a fire as a result of complete combustion. Depending on the context of use, this parameter is also referred to as the enthalpy of combustion, the calorific or the heating value. In a fire, water as a product is present as a gas, the use of the net heat of combustion (lower heating value with water as gas) is more appropriate than the gross heat of combustion or calorific value (upper of higher heating value, water as liquid). However, the gross calorific value is most often the commonly reported value obtained from measurements in the oxygen bomb calorimeter and in a series of empirical correlations developed from actual measurements databases. In practice, heats of combustion may be reported in various units (kcal/kg, kJ/kg, MJ/kg, kJ/mol,...) and may vary in extreme cases for substances liable to sustain oxidative processes between a few MJ/kg to some 130 MJ/kg (hydrogen). Most net heating values for organics lie within a range of 20 MJ/kg to 45 MJ/kg. The heat of combustion of materials and products in enclosures or storage commodities may easily be related to the fire load of a given premise or its fire load density, which may give a first valuable information in a preliminary risk assessment process. The fire load of an enclosure is generally defined as the total amount of energy that can be liberated by all combustible matter present in the enclosure. The fire load density is the same quantity normalised by the overall floor surface area.

Extensive analysis of fire load densities typical from various premises has been published by Rabash in the Fire Safety Journal 1 (1987).

In France, a value of 2500 kJ/kg is used as a limit value to consider inherent non-combustibility property of building products (Rating 'MO' of building materials [START_REF] Becker | Buildings » chapter 9 in : International Plastics Flammability Handbook, J. Troitzch[END_REF] ). French insurers also base a very rough classification of the fire hazard in terms of critical values of fire load densities [START_REF]Traité pratique de sécurité incendie 1993-1996[END_REF] . 'Low' risk is admitted if the fire load remains below 25 kg /m2 wood equivalent (425 MJ/m2), a value of 50 kg/m2 wood equivalent (850 MJ/m^) is rated as a 'medium' fire risk, and a value of more than 100 kg/m2 wood equivalent (1700 MJ/m^) is rated as 'high' fire risk. Drastic limitation of fire load inherent to structural elements and to furnishing materials in rooms is also a basic safety measure implemented by law enforcement in French high-rise buildings [START_REF]Arrêté du 18 octobre 1977 modifié[END_REF] , whatever occupancy is housed in. In the same way, fire load is also a basic consideration to determine areas of special fire risks in hospitals and other healthcare premises [START_REF] Marlair | Healthcare fire safety in France[END_REF] . Heats of combustion may also in turn be correlated to other safety parameters, for example as suggested by Suzuki 6 to flammability limits. The assessment of fire risk based on heat of combustion, naturally, has limitation. For example, two materials with same heat of combustion can have different heat release rates depending on the total exposed surface area burning, heat of gasification of the materials and flame heat transferred back to the burning materials. Moreover, fire dynamics may lead to significant changes in the course of a single fire process [START_REF] Marlair | A Review of Large-scale fire testing focusing on the fire behaviour of chemicals[END_REF] . Measurement of actual heat release rate using fire calorimetry based on OC or CDG will then provide more detailed information when required to qualify materials fire behaviour 879 .

Despite the limitations, it may be advantageous to use of a number of simple predictions rules for the theoretical heats of combustion. For practical reasons, the evaluation of the heat of combustion cannot systematically rely on conventional means of determination such as actual measurement, reference to tabulated data, or calculation derived from thermochemistry laws. The authors wish to comment on that in a first section. Then, for the benefit of the fire specialists, they present and comment on a selection of other simple predictive methods based on empirical correlations derived from measured data, and making use of information regarding elemental composition of the products.

TABULATED DATA AND SIMPLE CALCULATIONS BY USE OF THE THERMOCHEMISTRY LAWS

Finding the actual heat of combustion of the desired product in a universal table is probably the wish of every fire engineer. Indeed, extensive compilations have been done in the past in the context of combustion, chemical engineering and fire science that give numerous values for a variety of products 3 " 10713 . The accuracy of the data concerning common pure organics are commonly within 2-3% from one table to another, but may easily reach 5 to 10 % with less well defined products, in terms of technical grades, isomers and so on . The user will draw advantage of using a single reference database as far as possible to limit discrepancies. However, further care may sometimes be required, when the selection of heating values for uncommon chemicals or chemicals departing significantly from hydrocarbons by their chemical composition is dealt with. As an illustration of this, tables 1 and 2 have been plotted from previous literature review regarding non hydrocarbon chemicals, sulphur and carbon disulphide, for which printing mistakes is probably a better explanation of the abnormal values observed than incertitudes or heterogeneities on thermodynamic data with respect of the physical state or phase considered for reference. 2

: comparison of existing tabulated values for heat of combustion of carbon disulphide

To check the most proper tabulated values for sulphur and carbon disulphide presented in the above tables, we have performed very well know calculations based on the thermochemistry laws including the Hess law of constant heat summation that relates in an easy way the heat of combustion of a product to the enthalpy change between the reactants and the products of combustion [START_REF] Drysdale | Fire Science and combustion[END_REF] . However this method remains simple only if the enthalpy of formation in standard conditions of temperature and presssure of the product is tabulated in some thermodynamic properties database such as given in Reference 15. Although a large number of organic products are listed in the tables, data for many products of interest such heavy weight molecules as agrochemicals or pharmaceutical drugs are not available.

SIMPLE CORRELATIONS DERIVED FROM FOSSIL FUELS COMBUSTION SCIENCE

The heats of combustion of any organic compound is associated with the bond energies between the atoms forming the chemical structure of the compound, and therefore with the character of the bonds. However, in spite of the absence of fundamental scientific validation, the possibility that the heat of combustion might be calculated for solid fuels (e.g. coals) with fair accuracy from elementary composition alone has led many researchers to establish empirical correlations from their commonly measured characteristics. Those correlations are often expressed in the form of linear combinations of the weight percentages of the atom elements C, H, O, sometimes expanded to S and N. The reason is that major elements in the chemical composition of fossil fuels is actually limited to C, H, O, N, and S in their organic part.

Table 3 shows a selection of such empirical correlations giving the gross heat of combustion AHg ross of the given fuel. The net heat of combustion AH ne t may then easily be derived from the gross heat of combustion by deduction of the latent heat of vaporisation of water, e.g. by use of eq. ( 1) :

AH ne t = AH gwss -21.96 H (MJ/kg) ( 1
)
where H is the mass fraction of hydrogen in the product.

formula name

Dulong As can be seen, most expressions are of the form of eq.2 :

AH = aC + p// + yS -aO + (2)
where C, H, O, N, S are the weight fractions or weight percentages of the corresponding elements in the fuel, and a, p, y, a « calorimetric » coefficients the values of which are dependant on the units of expression of AH.

These correlations are the results of extensive experimental determinations of parallel sets of ultimate analyses of fuels and related measured heats of combustion by means of oxygen bomb calorimetry. Dulong who pioneered the work at the end of XlXth century assumed, as can be seen in the earliest expression of his formula (see eq. 3, with original units) [START_REF] Claudel | Formules, tables et renseignements usuels -Aide-mémoire des ingénieurs, des architectes, partie pratique[END_REF] , that oxygen was associated in the proper ratio with hydrogen as water, the excess hydrogen being available for combustion. The accuracy of the Dulong formula in its expanded form (see table 3) is reported to within 1.5 % of actual values determined by use of a oxygen-bomb calorimeter for coals [START_REF] Selvig | Calorific Value of Coal[END_REF] . All other correlations of table 3 with exception of the Boie formula may indeed be considered as inspired of the Dulong formula, with modified assumptions as regard the way oxygen is associated to the hydrocarbon frame. The extrapolation of such correlations to other types of combustible organic materials is feasible to some extent for more or less simple chemicals, when accuracy requirement is not severe.

Table 4 : gross heats of combustion (values in MJ/ke) as predicted bv first generation of correlations for hydrocarbons and other chemicals departing from fossil fuels

It is worth noticing that the Boie formula is the only one of the series that was introduced to give heats of combustion of other products than coals, whereas the Dulong formula is perhaps the most well known correlation in the field of the combustion science. The formula of Vondracek, of a non linear type, seems also very good in terms of accuracy, as argued by Patary [START_REF] Patary | Calorific Values[END_REF] at the light of table 4.

The initial database on which Boie established his correlation contained 149 solid and liquid products including biomass fuels, coal/coke/char fuels and oil fuels [START_REF] Annamalei | Interactive Processes in Gasification and Combustion -II Isolated Carbon, Coal and Porous Char Particles[END_REF] . Further use of the equation for 300 new solid and liquid fossil fuels led to a maximum error of 3% [START_REF] Ringen | Calculating the heating values from elemental composition of fossil fuels[END_REF] The French professional association Infoplasi13 in the 80's and Marlair [START_REF] Marlair | Smoke from warehouse fires : thermal and chemical aspects[END_REF] in the 90's first investigated capabilities of the Boie and Dulong formulae for fire safety purposes. Brief relevance of those correlations were shown for easy and fast running estimation of heats of combustion of plastics and agrochemicals, respectively. Indeed, table 4 clearly outlines the fairly good predictive capacity of the Dulong (expanded) and Boie formulae, even for products bearing high N or S contents, when those elements are generally only present in minor quantities in coals. However, one may also notice that high concentrations of the quoted hetero-atoms in the sample molecules lead with other listed formulae to some erroneous or aberrant predictions for extreme cases.(products containing unusual high mass fractions of sulphur).

Surprisingly, even for products containing other hetero-atoms than those included in the initial products databases that were used to derive the aforementioned formulae, the predicted values derived from Boie, Dulong or Vondracek are still in reasonable agreement with 'actual' values (e.g. measured or tabulated in literature), with exception of a few cases, as shown hereafter. It must be noticed however that part of the apparent deviation between predicted values and values quoted as reference data may be attributed to the technical grades of pesticides that were used for the measurements of 'actual' heats of combustion by use of an oxygen bomb-calorimeter, whereas predicted values are derived from elemental composition of pure molecules.

Since the beginning of the 50 's, both following ideas have emerged to develop new prediction methods for the heats of combustion, starting once again from the combustion science, to further improve the scope and the accuracy of the correlations presented so far :

-take account of relevant structure effect of the products on their enthalpies of combustion -expand first generation of correlations by use of chemical databases including other hetero-atoms in their elemental composition such as the halogen elements. Examples of R&D works bringing milestones in that way have been reported by Van Krevelen [START_REF] Selvig | Calorific Value of Coal[END_REF] .

MORE RECENT INPUTS FROM FIRE SCIENCE AND CHEMICAL ENGINEERING

In 1986, Carozo suggested a method based on the first order correspondence between the enthalpy of combustion and the total number of carbon, correction factors being introduced for functional groups and chain branching [START_REF] Cardozo | Prediction of the enthalpy of Combustion of Organic Compounds[END_REF] , but the application of his method requires again fastidious calculations. Seaton et al n listed a series of other contributions of the kind not reported here.

More useful looks the correlation developed by FMRC giving the net heat of combustion of chemicals according to their generic group belonging, for reason that it is to our knowledge the only one specially built in the context of fire engineering [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF] . Based on the correlations between the heat of combustion and molecular weight of materials within each generic group, the following equation (eq. 4) has been established :

(mj/M) ( 4
)
where AKj is the net heat of complete combustion (kJ/g), hj is the mass coefficient for the heat of combustion (kJ/g), mx is the molar coefficient for the heat of combustion, a function of the heat of formation of the bonds in the material (kJ/mole) and M is the molecular weight (g/mole).

using the FMRC correlation

In the chemical engineering background, sometimes requiring more accuracy than in other scientific disciplines, the most recent contribution for the development of user-friendly correlations giving net heats of combustion leads to a two step procedure according to equation 5 The expression of the net heat of combustion according to Garvin 29 follows : b J where w / is the weight fraction of element i in the fuel and the coefficients a; are given in table 8, with equivalent a 'i coefficients for the Boie formula are given for comparison. The second term is a correction factor taking account of functional group contributions according to table 8, where bj is the group contribution factor coefficient, nj the number of occurrences of each group and M is the chemical's molecular weight (kg.kgmoH). According to Garvin's method, the first step of the procedure consists in determining the main contributing factor of the enthalpy of combustion of the product (first term of equ.5), the role of which can be directly compared to formulae of the first generation. It may be noticed that the Garvin formula, so limited to the first contribution factor behaves in a similar fashion that the Boie formula and other 'good' formulae of the first generation : these correlations all overpredict slightly the heat of combustion of pure graphitic carbon. Refinements of the data obtained by application of second step of the procedure will probably satisfy all fire scientists (comparisons of predicted values and actual values listed in the original database lead to average absolute error and maximum error to 0.53 and 2.7%, respectively) owing to final limitations of any other more complex calculation procedures requiring more sophisticated tools to take account of detailed energy bonds contributions, as stressed by Seaton et al. As guessed, there is a majority of cases (compounds containing high mass fractions of halogens) where predictions have been improved by comparison of performance achieved by use of the Boie formula. However, the heat of combustion of the organophosphorous compound is as badly predicted by both correlations, as P was not included in the databases used for the regression analysis.

Garvin

Although developed in different contexts, similarities appear clearly in the two methods presented in this section. They are both taking account of structural effects, although the calculation of the massic heat of combustion and the molar heat of combustion (correction factor) are not calculated in the same way. Both may be expected to lead to the better compromise 'accuracy versus simplicity' but do not put an end to any interest of formerly developed methods in the context of fire safety studies.

CONCLUSION

The heat of combustion is often the very first thermal characteristic of materials that the fire safety engineer may wish to estimate. Although this parameter does not reveal how far and how fast this potential energy would be liberated in a fire, this data is often required in practice for various purposes, e.g. : preliminary safety studies based on the analysis of fire load, fire load densities, or more scientific purposes such as the determination of combustion efficiency of chemicals in fire conditions. Gross or net heats of combustion may be derived from conventional experimental measurements, using oxygen bomb calorimetry or by referring to thermochemistry laws, the latter method rapidly meaning fastidious calculations or requiring specialised computational softwares. Hopefully, in a number of cases, one may refer to tabulated values that have been compiled by previous scientists in various backgrounds (combustion science, chemical engineering, fire science). Some scatter may however be expected between values of a single product from one table to another and even -though not frequent-some erroneous values may be faced. More technical limitation regards the lack of quoted values for chemicals having complex structures including several heteroatoms, or for technical grades of products. Alternatively, our review has led to the selection of a number of user-friendly ways to get reasonable up to fairly accurate values of heats of combustion by simple calculations derived from regression analysis of actual measurements data or other very simple assumptions. Those methods are generally applicable provided either elemental composition, or chemical nature is known. Our analysis finally leads to the following statement: -Among very simple correlations of the first generation, developed from end of last century to the 50's, the Boie formula, validated on an extensive number of C-H-O-N-S compounds is probably the more appropriate for a reasonable accuracy in the context of fire engineering, while the Dulong formula (same kind of compounds) remains the best known in the combustion science. The use of Voudracek formulae, although of slightly more complex configuration, is also a good compromise of similar performance ; -Increased relevance or better accuracy may yet be expected, if required, by use and further development of a new generation of correlations, such as the formula reported by Garvin taking account a large number of atoms, including the halogens, and taking account of the structure of chemicals, in terms of correcting factors. Good examples of those have been recently reported by FMRC (1995) or Garvin (1998).

It would be a valuable work to go on collecting measured data on molecules of the fine chemistry to extend predictive capabilities of both last methods presented in this section (for instance data referring to organophosphorous and organometallic compounds). Among the metallic elements, Si would also be worth being taken into consideration due to commercially-important applications of silicones based materials and their related fire problems [START_REF] Buch | Radiative Emission Fraction of Pool Fires Burning Silicone Fluids[END_REF] .

REFERENCE LIST

gross 8 ,

 8 080 C+34,462 (H--) (in kcal I kg) 8 (3)

  (a) unknown author, reported by Patary zl -(b) not relevant

Table 1 : comparison of existing tabulated values for heat of combustion of sulphur

 1

	product : Sulphur (S)	AH (MJ/kg)	ref.	relative scatter (A%)
	tabulated	11.03	after Weiss 14	+ 19.1%
	(polysulfur) tabulated	09.72	(a)	+ 5.0 %
	tabulated	04.64	(b)	-49.9 %
	tabulated	09.27	(c)	+ 0.1%
	tabulated	09.28	(d)	+ 0.1%
	tabulated	09.3	(e)	-15.7
	(Boie formula) predicted	10.46	(see next section)	+ 12.9 %
	calculated (Hess's law)		this work (required
	S as a solid	09.26	datafromlS)	0%
	(a) to (e ) miscellaneous literature references
	product : CS2	AH (MJ/kg)	ref.	relative scatter (A%)
	tabulated	13.52	liSëTWeïss 1 *	-4.3%
	tabulated	06.34	(a)	-55.1 %
	tabulated	13.60	(f>	+0.6 %
	tabulated	13.86	(c)	-1.9%
	(Boie formula) predicted	14.37	(see next section)	+1.7%
	calculated (Hess's law)	14.13	this work (required	0%
			datafroml^)
	(a) (c) (f ) miscellaneous literature references in agreement with 1nomenclature of table 1

Table

Table 3 : examples of early correlations developed to predict heats of combustion

 3 +144.153 H-18.019 0 +9.412 S AH = 33.8 C+ 144.0 H -18.0 O+ 10.46 S AH = 33.9 C + 143.4 H + 22.25 S -30.4 0 AH = 35.160 C + 116.225 H -11.090 O + 6.280 N + 10.465 S AH = 51.87 C+ 162.4 #-17.87 + 10.46(O)* AH = 34.05 C + 143.23 H-15.32 O + 10.46 S AH = 34.03 C + 124.31 H-9.836 O + 6.278 N + 19.09 S AH = (37.29-2.595 C)C+ 113 H-11.3 O+ 10.46 S AH = (32.9+3.7 (1-Q"-^>)C + 89.99 H-9O+ 10.46 S AH = 34.07 C + 144.4 H-12.56 (O +N) AH= 35.58C+113H-11.3 O+10.465 AH = 33.61 C + 141.9 H -14.52 O + 9.417 S (if O 2 < 15%) else Q = 33.61 C + 141.9 H -(15.32 -7.20 0)0 + 9 All S (a) gives the net heating value contrary to the other correlations presented, (b) reported by Patary, author unknown

			expression of AH sross (in MJ/kg)
			(concentrations of designated elements as mass fractions)
	1 'D	AH= 33.8 C+144.2 H-18.03O
	ulong		AH = 33.8 C
	(expanded) '
	Dulong&Petit zl
	D'Huart"
	Boie" 11 """
	Seyler iy
	Strache-Lant zz
	Gumz zz
	Vondracek zl ' zz
	Vondracek 24 (a)
	Mahler zl
	Patary (a) zl
	Mott	&
	Spooner 19 ' 22

Table 4

 4 gives a comparison of predictive values of heats of combustion by use of formerly mentioned equations for a number of simple chemicals.

	formula name	carbon	n-	xylene	acetone	aniline	carbon	sulphur
		graphitic	heptane				disulphide	(solid)
	ref. Q gross value	c 32.80	C 7 H16 48.07	Qf to 42.89	C 3 H 6 O 30.83	QH 7 N 36.44	CS 2 14.13	S 9.26
	Dulong ""z u	33.8	51.6	44.3	31.0	37.1	5.3	-(b)
	Dulong (expanded) ls>	33.8	51.6	44.3	31.0	37.1	13.3	9.4
	Dulong&Petit zl	33.8	51.5	44.3	31.0	37.1	14.1	10.5
	D'Huart zz	33.9	51.5	44.3	27.6	37.1	24.1	22.3
	Boie 1 " -1	35.2	48.2	42.9	30.9	37.0	14.4	10.5
	Seyler"	34.0	51.8	44.5	32	34.6	-9.7	-17.9
	Strache-Lant z	34.1	51.6	44.4	31.8	37.2	14.2	10.5
	Gumz zz	34.0	48.6	42.6	31.4	36.7	21.4	19.1
	Vondracek zl ' zz	34.7	47.65	42.3	30.8	35.9	14.6	10.5
	Mahler zl	34.6	51.8	44.6	32.7	35.4	5.4	-(b)
	Patary (a) zl	35.6	48.0	42.9	30.7	36.1	14.4	10.5
	Mott & Spooner iy ' zz	33.6	51	43.9	31.95	36.8	13.2	9.4

Table 5

 5 focuses on examples of predicted values by the Dulong, Boie and Vondracek formulae for more complex molecules selected among pesticides and polymers, principally.

			ref.
			values	Predicted values of heats of combustion
			(MJ/kg)			(MJ/kg)
			Lit. or	Boie	Dulong	Vondracek
			measure	value	error	(expanded)	24
		chemical formula	AH	AH net	A(%)	AH net	AH ne t
	TDI (e)	C 9 H 6 O 2 N2	23.6 (d)	24.1	+ 2.3	21.9	23.7
	Nylon	(C 6 H U NO) n	30.8 (b)	30.8	0	31.0	30.3
	PVC	(C2H3Cl)n	16.9 (c)	18.1	+ 07.1	18.9	18.3
	chlorobenzene	C6H5C1	26.5 (g)	26.7	+ 0.8	27.1	26.9
	fluorobenzene	C6H5F	30.9 (f)	31.3	1.3	31.8	31.4
	isoproturon	C 12 Hi 8 N 2 O	31.84 (a)	32.8	+ 3.0	33.0	32.1
	atrazine	C 8 Hi 4 ClN 5	22.28 (a)	23.9	+ 07.3	23.1	22.0
	aclonifen (91%)	C12H9CIN2O3	20.45 (a)	18.8	-8.1	19.3	21.0
	phosalone (94%)	C15H15CINO4PS2	20.32 (a)	17.8	-12.4	16.8	18.1
	chlormephos	C5H12CIO2PS2	19.10 (a)	15.2	-20.4	15.1	15.6
	(96%)
	mancozebe (85%)	(C4H 6 N2S 4 Mn)Zno	15.62 (a)	13.9	-11.0	13.1	13.4
		.1
	Rigid	CHi. 2 O 0 .22N0.l)n	25. (c)	27.9	-11.6	27	27.9
	polyurethane (b)	(b)
	Tefzel ETFE (b)	(CHF) n (b)	12.6	16.2	+ 28.5	16.5	16.4
			(b/c)

(a) determined by INERIS (according to AFNOR M0 003), from oxygen bomb calorimetry, corrected for water as gas and for the residue ; (b) from ref. ; (c)determined by FMRC, from oxygen bomb calorimetry, corrected for water as gas and for the residue ; (d) from ref. 11 ; (e) Toluene diisocyanate ; (f) from ref. 12 ; (g) from ref 10 .

Table 5 : typical prediction of net heats of combustion derived from the Puions-, Boie formulae, or by use of the Vondracek formula

 5

-Predictions shown in table 5 present higher relative errors, in most cases than in those of table 4, likely due to the presence of 'new' hetero-atoms like halogens and phosphorus in the sample molecules.

Table 6 : Expression of the mass coefficient hT and the molar coefficient Mt of the predicted net heats of combustion, for various chemical groups, according to FMRC work

 6 The values of hj amd mj for a selection of chemical groups are listed in Table6. The coefficients depend on the generic nature of the material, mj is negative for materials with oxygen, nitrogen, sulphur and halogenated atoms in the chemical structure. For materials gasifying as high molecular weight products, AHj » hj. Calculations based on Eq. 4 have been validated via direct measurements for materials with complex chemical structures. Example of predictive values obtained by the use of this correlation are listed in table 7:

		Lit values predicted values error (%)
	n heptane	44.56
	n-heptene	44.3
	xylene	40.9
	ethanol	26.8
	acetone	28.6
	TDI	23.6
	aclonifen	20.4

Table 7 : example of predicted net heats

 7

	44.6	~0
	44.6	+ 0.7
	39.4	-3.7
	27.7	+ 3.3
	29.7	+ 3.8
	24.0	+ 1.7
	19.7	-3.
	of combustion

Table 8 : a; values for the prediction of the net heat of combustion using the Garvin formula, after!2, (by permission)

 8

	Boie (a)

Table 9

 9 gives the bj coefficients obtained by multiregression analysis that minimises the absolute error from actual values of the products included in the database used by Garvin (458 compounds from Cl to C20, including halogenated products of all types, and satisfying the conditions of a minimum heating value of 5,000 kJ/kg. and of enough hydrogen for the conversion of Cl in HC1, F in HF, and O into water vapour. From errors calculations quoted by the author between predicted and referenced values included in the original database (average absolute error of 1.7 % and maximum error of 16%), first step of Garvin's procedure is expected to provide estimation of the net heat of combustion good enough in most practical cases interesting the fire safety engineer.

	Functional group	bj, (MJ/kgmol)
	C-C double bond	70
	C-C triple bond	190
	Nitrile CN	0
	Carbonyl CO	0
	Acid COOH	-55
	Ester COO	-30
	Amide CON	-85
	Nitro NO2	200
	Alcohol OH	20
	Aminé N	-30
	Aldehyde CHO	60
	Ether 0	50
	Anhydride CO-O-CO	-60
	Benzene Ring	-15
	3-Member Ring (*)	105
	4-Member Ring (*)	90
	5-Member Ring (*)	0
	6-Member Ring (*)	-40
	7-Member Ring (*)	-40
	9-Member Ring (*)	-160
	(*) not to be applied to aromatic compounds or to their aromatic substitution derivatives

Table 9 : Group contribution bj, for eq. 5, (by permission)

 9

Table 10 : predicted values of net heats of combustion for complex molecules according to Garvin-

 10 Calculation of the predicted values of heats of combustion for most products listed in table 5 by use of the Garvin method (first step only) are summarised in table 10.

		(without correction ) error (%)
	TDI	24.9	+5.5
	Nylon	31.3	+1.6
	PVC	17.1	~ 0
	chlorobenzene	26.5	~ 0
	fluorobenzene	31.1	+1.2
	isoproturon	33.4	+5
	atrazine	24.2	+8.5
	aclonifen	21.5	+4.9
	phosalone	19.1	-6.0
	chlormephos	15.0	-20.4
	mancozebe	15.3	-1.9


S Brohez

C Delvosalle

G Marlair

A Tewarson

SOOT GENERATION IN FIRES: AN IMPORTANT PARAMETER FOR ACCURATE CALCULATION OF HEAT RELEASE

Keywords: fire tests, heat release rate, carbon dioxide generation calorimetry, soot generation NOTATION

Oxygen consumption (OC) calorimetry and carbon dioxide generation (CDG) calorimetry are usual methods to determine the heat release rate (HRR) in bench-scale and large-scale fire tests. The paper emphasises on measuring problems associated with fires releasing large amounts of soot. Until now, the soot-related energy transfer was hardly ever taken into consideration in practical applications of HRR calculations. From standard CDG calorimetry, a generalised relationship is introduced in order to take into account the soot generation in the accurate determination of the heat release produced in sooty fires. The analysis of the significance of this correction factor is discussed by theoretical consideration as well as from results of lab-scale experiments recently carried out on chemicals by means of the INERIS fire calorimeter.

E COi

Energy release per unit mole of CO 2 produced for complete combustion (kJ.mole" 1

) E' co

Energy release per unit mole of CO produced for incomplete combustion to CO (kJ.mole" 1 ) E" s Energy release per unit mole of soot produced (assumed to be carbon) for incomplete combustion to soot (kJ.mole" Refers to molar fractions in the analyser prior to the test 0

Refers to incoming air

INTRODUCTION

Heat release rate evaluation is a common practice in any fire risk assessment procedure. Usual methods to measure heat release rate are based on the application of the oxygen consumption (OC) [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF][START_REF] Parker | An Investigation of the Fire Environment in the ASTM E84 Tunnel Test[END_REF][START_REF] Hinkley | Rates of heat Output and Heat Transfer in the Fire Propagation Test[END_REF][START_REF] Huggett | Estimation of the Rate of Heat Release by Means of Oxygen Consumption[END_REF] and carbon dioxide generation (CDG) calorimetry [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF]. The OC calorimetry states that heat of complete combustion per unit mass of oxygen consumed is approximately constant for many carbon and hydrogen containing organic solid, liquid and gaseous compounds [START_REF] Huggett | Estimation of the Rate of Heat Release by Means of Oxygen Consumption[END_REF][START_REF]The Relation of Oxygen to the Heat of Combustion of Organic Compounds[END_REF].

CDG calorimetry similarly states that heat of complete combustion per unit mass of carbon dioxide generated is approximately constant for most organic liquid, gaseous and solid compounds [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF]. The heat of combustion per unit mass of carbon dioxide generated for a large number of gases, liquids and solids is 13.3 kJ/g with a ± 11% variation.

The heat release rates calculated from CDG calorimetry using average values of the heat of combustion per unit mass of carbon dioxide and carbon monoxide generated are only approximate. For accurate heat release rate calculations, actual elemental composition of the material and net heat of complete combustion are required.

In addition, high molecular weight organic compounds or halogen containing chemical substances may release large amounts of soot irrespective of the ventilation conditions. Ventilation controlled fires also provide favourable conditions for increasing yields of soot for various chemical substances. Classical CDG calorimetric relationships have thus been reviewed to derive adequate procedures capable of appraising the effect of soot production on effective heat release calculation. The assessment of the significance of the soot correction factor is examined by use of experimental data at lab-scale.

THEORETICAL BACKGROUND OF MODERN FIRE CALORIMETRY

The OC and CDG calorimetry are extensively used both in bench-scale and large-scale fire tests [START_REF] Janssens | Calorimetry[END_REF][START_REF] Peacock | Analysis of Large-scale Fire Test Data[END_REF][START_REF] Tewarson | Flammability Parameters of Materials: Ignition, Combustion and Fire Propagation[END_REF][START_REF] Marlair | Modélisation Incendie Simulant les Transferts et les Risques A L'environnement[END_REF][START_REF] Marlair | A Review of Large-Scale Fire Testing Focusing on the Fire Behaviour of Chemicals[END_REF][START_REF] Marlair | Experimental Evaluation of the Fire Hazard of Organophosphorous Insecticides by Use of Various Test Methods[END_REF]. Most of these tests are carried out in open or semi-open systems, where a hood is used above the burning item to exhaust all combustion products plus dilution air. In practice, the measurements of the gas flow rate, temperature and effluent composition (molar fractions of oxygen, carbon dioxide and carbon monoxide, essentially) allow easy calculation of the heat release rate of the experimental fire by derivation of mass balances on oxygen and/or carbon.

In the standard CDG calorimetry, the heat release rate is calculated from the measurement of the mass generation rate of CO 2 , corrected for the mass generation rate of CO [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF] : Since the water vapour is removed from the sampling line before the measurement of molar fractions of O 2 , CO 2 and CO, the mass flow rate of CO 2 in the incoming air, m°C O2 , is given by: By substituting equations ( 2), ( 3) and ( 4) into equation ( 1), the equation to calculate the heat release rate by CDG calorimetry becomes

° _™an Y 0 )V A°- ~rr ( 1 ~YH 2 O ) Y co 2 ™°co 2 _m Y o ]Y A°M co 2
q = ^-(1-Y H2O ) (E C02 Y C A O2 + E' CO Yéo)-^-(l-Y^o) E CO2 Yéo 2 (5) M M
Due to the large dilution factor of the combustion gases generally induced by the air entrained into the exhaust hood, it can generally be assumed that M e is nearly equal to M a .

The same technical background hopefully justifies in most practical applications a further simplification in the effective calculation procedure by neglecting the influence of water vapour molar fractions. In many cases the error is negligible. A more detailed evaluation of the water molar fractions influence has been provided recently in another paper [START_REF] Brohez | Accurate Calculations of Heat Release in Fires[END_REF] considering the case of methane which represents a worst case because it is the hydrocarbon with the highest hydrogen to carbon ratio.

The mass flow rate of incoming air may be calculated from the following equation [START_REF] Janssens | Oxygen Consumption Calorimetry[END_REF]:

* (6) l) with, <fi = ^ ±- -i- ( 7
)
The nomenclature is the same as that used by Janssens and Parker [START_REF] Janssens | Oxygen Consumption Calorimetry[END_REF]. The superscript A refers to molar fraction of any species measured in the analyser (which is different from the corresponding molar fraction in the exhaust flow).

INTRODUCING A SOOT GENERATION CORRECTION FACTOR

The chemical nature of the burning material or specific fire conditions (e.g. underventilation) can lead to large productions of soot [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF][START_REF] Hietaniemi | Fires at Chemical Warehouses, A Cone Calorimeter Study on the Burning Characteristics and Fire Effluent Composition of Selected Chemical Compounds[END_REF][START_REF] Anderson | Simulated Fires in Substances of Pesticide Type[END_REF]. This statement has led us to study a modified equation allowing the calculation of heat release based on CDG to take into account the soot production: Chemical analysis shows that (mature) soot particles generated from hydrocarbons burning in diffusion flames contain only a few percents by weight of hydrogen and oxygen [START_REF] Palmer | The formation of carbon from gases[END_REF][START_REF] Gaydon | Solid Carbon in Flames[END_REF]. It can thus be assumed that soot particles are principally made of carbon.

(8) ^ 2
Since condensable species and soot particles are removed from the sampling line before measurement of molar fractions of O 2 , CO 2 and CO, the mass flow rates of carbon dioxide and carbon monoxide in the exhaust duct are given by: It has been shown that light extinction coefficient k is proportional to mass concentration of soot particles [START_REF] Foster | Attenuation of Light by Wood Smoke[END_REF][START_REF] Seader | Correlation of the Smoke Tendency of Materials[END_REF]:

T-= Tr Y c (l-YY d -Y s ) (9) C O 2 K ^^e S ) (10
k = cr s C s ( 12
)
where, C s = Mass concentration of smoke particles (g.m 3 ) cr s -Specific extinction area per unit mass of soot (nf.g' 1 )

The value of the specific extinction area cr s is roughly constant for fuels burning in flaming mode and producing primarily carbon soot [START_REF] Mulholland | The effect of Scale on Smoke Emission[END_REF]. In open systems, since the attenuation of light through smoke is measured in the exhaust duct, the mass flow rate of soot follows as:

m s =C s V e =^- (13)
where V e -Volume flow rate in the exhaust duct at the actual temperature where the photometer is located (irf.s' 1 )

The molar fraction of soot in the exhaust duct can be written as *-**-£• ( 14)

m e M s
Finally, the heat release rate taking account of the soot generation is given by: For a practical application of equation ( 15), the user still requires the values of the calorimetric coefficients E co ,E' CO and E" s . With some exceptions, the value of E C02 is approximately constant [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF]. Tewarson calculated the calorimetric coefficient E COi for a list of about 200 compounds. From these actual values, the average value of the calorimetric coefficient E C02 is 585,2 kJ per mole with an average variation s co of 8,5% 2 .

! Average variation calculated from actual values of Eco2

By application of the Hess law, the calorimetric coefficients E' co and E" s may be calculated from From equations ( 16) and ( 17), it comes out that the calorimetric coefficients E C02 ,E' C0 and E" s have the same average absolute variation of 49,7 kJ/mole. The average relative variations of E' co and E" s may be calculated from:

E'co = E co 2 -AH co = 302,2 -- (16) 2 mole E "s = E C 0 -AH s = 191.7-- (17)
Eco 7 --^-= 16,5 % (18) CO _L ^259% ciQ'l
The average calorimetric coefficients may be useful especially for materials of unknown molecular compositions. Unfortunately, the values of the average relative variations are important. Therefore, if the actual values of the calorimetric coefficients are available for the burning material, these values should be used in the calculations instead of the approximate values.

SIGNIFICANCE OF THE SOOT GENERATION CORRECTION FACTOR ON HRR

The heat release rate may be expressed as function of yields of CO2, CO and soot. In practice, by use of the definition of yield of product i,

j -m. m ( 20
)
and according to equations ( 8) and ( 1), the heat release rate with or without soot correction is given respectively by To assess the significance of the soot correction factor appearing in equation ( 15), the ratio r of the standard heat release rate (equation Ibis) to the corrected heat release rate (equation 8bi S ) was introduced and expressed in terms of measurable parameters according to the following procedure:

A -m / • 'CO2 P 1 /CO PT , fs p n ) /o \ ^corrected ~ m f ( ~ h CO 2 + ~ h CO + TT~ h S ) (Sbis) M CO 22 M co M s 4standard =™f(~ E co + - E' c0 ) • (1 bis ) E co+ " M co
H s tan dard Q corrected Qco r f C °2 1 JCO-, ,, J " M co 2 E co 2 , , ' JCO M C0 2 E'co E 'co E 'co M C o -+ fs E" M t s s ( 21
)
Equation ( 21) may be normalised in the form of

E , Y E 'co co fv frn M co M co r = function (x s = -Jj -,x co = -^2_; -- ^ - ( 22
)
JCO 2 JCO 2 , " E , x t CO , Y £ 5 M co 2 M co M s
Several researchers [START_REF] Tewarson | Generation of Heat and Chemical Compounds in Fires[END_REF][START_REF] Hietaniemi | Fires at Chemical Warehouses, A Cone Calorimeter Study on the Burning Characteristics and Fire Effluent Composition of Selected Chemical Compounds[END_REF][START_REF] Mulholland | Smoke Production and Properties[END_REF][START_REF] Tewarson | Combustion of Halogenated Polymers[END_REF] published experimental results about yields of soot and carbon dioxide. Some of the higher values of xs are listed in table 1. According to the review of their experimental data, the value of 0.4 seems to be a reasonable upper limit of this variable (for common products). To analyse the contribution factor of soot production, the ratio r has been plotted as a function of xs, with two extreme values [START_REF] Janssens | Calorimetry[END_REF] of the parameter XCO (see figure 1). The error by ignoring the soot correction in the heat release rate calculation may be clearly significant if the variable xs takes a large value. As an example, for a 0.3 value of the parameter xs, the heat release rate would be underestimated of about 25 percent if the soot correction is neglected.

Compounds

To provide a further analysis on the influence of soot production on heat release calculation in fires, different chemicals were selected for small-scale experiments, according to their varying sooting tendency. The substances studied in the experiments are isooctane, cyclohexane, benzene, toluene, 1-2-4-trimethylbenzene, chlorobenzene and 1-2-dichlorobenzene. The mass of the substances burned in the experiments ranged from 25 to 70 g.

Apparatus

The experiments were performed in the INERIS bench scale calorimeter (figure 2). As can be seen in figure 2, the INERIS calorimeter is fitted with a gas-tight air dilution system at the level of the collection hood of the fire gases to allow safe use of the apparatus on toxic chemical samples [START_REF] Marlair | On-going Experimental Fire Research and Testing in France Using Tests Rigs Derived from the "Tewarson" Apparatus[END_REF].

In all the experiments, a cylindrical sample holder made of glass with a diameter of 88 mm was used. The infra-red heaters were usually not used in the experiments. However, for chlorobenzene and trimethylbenzene an incident heat flux of 20 kW/m 2 was applied until ignition. For dichlorobenzene, an incident heat flux of 10 kW/m 2 had to be maintained during all test procedure to ensure flaming combustion. For the measurement of total unburned hydrocarbons concentration (THC), a heated line (180°C) was used to draw fumes sample (through heated filter, 180°C) to the analyser (flame ionisation detector). This analyser was calibrated with the studied material by evaporating a substance sample. The mass flow rate of air at the bottom of the quartz tube was fixed at 0.2 nmVmin. For all experiments, this mass flow rate led to well-ventilated fire conditions. The mass flow rate of fumes in the exhaust duct was regulated to a constant value of 80 nmVh.

Results

From the measured data, the yields of carbon dioxide, carbon monoxide and unburned hydrocarbons were calculated. The results (which are averages of three tests for each substance) are given in table 2. Because measurements by direct sampling of soot or use of optical properties were not still implemented, the yield of soot was calculated from the mass balance of carbon: The parameters xs, xco and r were determined 4 from the yields values f t (see table 2). As can be seen in table 2, the soot correction in the heat release rate calculation is negligible for materials such as alkanes. However, this correction may become important for arènes and substituted arènes even in well-ventilated fire conditions. As an example, for chlorobenzene, the heat release rate would be underestimated by about 11% if the soot correction is neglected.

CONCLUSION

Heat release rate in fires is one of the major parameter for fire safety engineering. Standard CDG calorimetry making use of CO 2 and CO measurements has been reviewed.

It has been studied whether sooting tendency of materials might be an important consideration for accurate calculations of heat release rate. A correction accounting for soot production on heat release rate calculation by CDG calorimetry has been proposed. The importance of this correction factor depends on both the chemical nature of the material being burned and the degree of ventilation of the fire.

A calorimetric coefficient E" s corresponding to soot generation has been introduced and calculated. An average value of 191.7 kJ per mole of carbon generated is proposed with an average variation of 25.9 %. Due to the importance of this variation, the actual value of the calorimetric coefficient should be used in the calculations instead of the approximate value.

Similar considerations on soot related energy transfer on OC calorimetry is being studied and will be discussed in a forthcoming publication. ACKNOWLEDGEMENT Part of this work was financially supported by: -La Communauté française de Belgique (Belgium) -Le Ministère de l'Aménagement du Territoire et de l'Environnement (France)

  rate of incoming air (g.s' 1 ) M a = Molar weight of incoming air (29 g.mole' 1 ) Y'ù 20 = Molar fraction of water vapour in the incoming air Y* Oi = Measured 1 molar fraction of carbon dioxide in the incoming air The mass flow rates of CO 2 and CO in the exhaust duct are given respectively by where rh e = Mass flow rate in the exhaust duct (g.s' 1 ) M e -Molar weight of fumes in the exhaust duct (g.mole 1 ) Y H J 0 = Molar fraction of water vapour in the exhaust flow Y co 2 Y co -Measured 1 molar fraction ofCO 2 and CO respectively (during the combustion test)

2 =

 2 Measured molar fraction of oxygen in the incoming air rA Y Q2 = Measured molar fraction of oxygen during the combustion test a = Expansion factor (average value & 1,105)

  nd,n = Molar fractions of condensable species such as H 2 O, acid gases (HO,...) in the exhaust duct Y s = Molar fraction of soot in the exhaust duct The mass flow rate of soot can be measured by direct sampling or calculated from optical smoke measurements. According to Lambert-Beer law, the attenuation of monochromatic light over a given optical path through the smoke generated by the burning fuel can be expressed as intensity of incident light I = intensity of the transmitted light through smoke L = optical path length through smoke (m) k = light extinction coefficient (m 1 )

  Energy release by complete combustion of CO per unit mole of CO consumed (283 kJ. mole') AH S= Energy release by complete combustion of soot (assumed to be C) per unit mole of carbon consumed (393.5 kJ. mote1 )

=

  Yield ofi (mass ofi produced to mass of fuel lost) rhf= Mass loss rate of fuel (g.s 1 )

3 OFIGURE 1 :

 31 FIGURE 1: Influence of soot generation on the HRR calculation by CDG calorimetry

FIGURE 2 :

 2 FIGURE 2: The INERIS bench-scale calorimeter.

  carbon atoms in the test molecule CaHbO c Cla Mfuei = Molecular weight of the burning material (g.mole" )

  Ratio of yield of product i to yield of CO 2 (normalised yield of product i)YjMolar fraction of i AH C0 Energy release per unit mole of CO consumed in the burning of CO (283 kJ.mole" 1 ) AH S Energy release per unit mole of carbon consumed in the burning of carbon (393.5 kJ.mole" 1 )

		1 )
	ft	Yield of i (mass of i produced to mass of fuel lost)
	I o	Intensity of incident light
	/	Intensity of the transmitted light through smoke
	k	Light extinction coefficient (m" 1 )
	L	Optical path length through smoke (m)
	m	Mass flow rate (g.s" 1 )
	M	Molecular weight (g.mor 1 )
	q	Heat Release Rate (kW)
	r	Ratio of HRR without soot correction to the actual HRR.
	V e	Volume flow rate in the exhaust duct (m 3 .s 4 )
	x t
	a	Expansion factor (=1.105)
	s	Average relative variation
	<f>	Oxygen depletion factor (see equation 7)
	0	Equivalence ratio
	Subscripts
	a	Refers to incoming air
	e	Refers to fumes in the exhaust duct
	/	Refers to burning fuel
	1	Refers to compounds
	Superscripts
	A A 0	Refers to molar fractions in the analyser

a s Specific extinction area per unit mass of soot (nr^.g' 1 )

. _ £ 'CO 2 ..

			.0	\ , E QO	.	n q
	-	Mco 7	( iitQQ-j -COt s	M co	CO	\^-)
	where
	q	= Heat release rate (kW)
	E co	= Energy release per unit mole of CO 2 generated for complete combustion to CO 2 (kJ.mole 1 )
	E' co	= Energy release per unit mole of CO generated for incomplete combustion to CO (kJ.mole' 1 )
	M COi = Molecular weight of carbon dioxide (44 g.mole' 1 )
	M co	= Molecular weight of carbon monoxide (28 g.mole' 1 )
	m°C Oi = Mass flow rate of CO 2 in the incoming air (g.s 1 )
	m C02	= Mass flow rate of CO 2 in the exhaust duct (g.s' 1 )
	m co	= Mass flow rate of CO in the exhaust duct (g.s' 1 )

TABLE 1 :

 1 Some of the higher values of ratio of soot to carbon dioxide yields.

	Substance	X S ~ r
		Jco 2
	Benzene	0.08
	Polyvinylchloride ( o> < 0.35) 3	0.37
	Polystyrene (<D= 0.2)	0.07
	Polystyrene ( <D = 2)	0.19
	Polystyrene ( o = 3)	0.32

TABLE 2 :

 2 Yields of combustion products and significance of the proposed soot correction

	Substances	fco 2 (g/g)fco(g'g )	) fco(g'g)	fmcis's)fs(g'g)	fs(g'g)	x co	x s	r(%)
	Isooctane	3.00	0.017	0.0017	0.025	0.006	0.0083	98.9
	Cyclohexane	2.98	0.008	0.0003	0.04	0.003	0.013	98.3
	Benzene	2.51	0.056	0.037	0.18	0.022	0.072	94.0
	Toluene	2.56	0.071	0.057	0.13	0.028	0.051	95.8
	1,2,4 Trimethylbenzene	2.25	0.062	0.055	0.21	0.027	0.093	92.3
	Chlorobenzene	0.97	0.09	0.26	0.165	0.093	0.17	88.8
	1,2 Dichlorobenzene	0.62	0.11	0.35	0.097	0.18	0.15	91.9


Christian Tauziède

Zbigniew Pokryszka

Pierre Schroeter

Mitigation of air leakage through the goaf of retreat coalfaces

In HBL (Lorraine coalfield), large amounts of air are used in order to dilute methane in retreat coalfaces. A parasite flow of air exists in the goaf, leading to the risk of spontaneous combustion of remaining coal as well as to a diminution of firedamp drainage efficiency. The evaluation of various means for reducing this flow has been done through the use of models : a physical model and a numerical model based on a CFD package. The efficiency on air leakage reduction, decrease of methane concentration in the air return or increase of methane concentration of drainage has been quantified for one or more stoppings set up in the abandoned gates or for their backfilling. The influence is small but positive as regards drainage efficiency improvement but almost zero on risk mitigation of spontaneous combustion in the goaf.

Foreword

The Lorraine Coalfield mine coal by longwall in retreat coalfaces. The seams are thick (from 3.5 to 4.5 m) and prone to relatively high firedamp emission (the dissolvable concentration of coal to methane ranges from 4 to 10 m 3 /t, and the spécifie discharge from 20 to 50 m It). Unitary productions are high (from 4,000 to 6,000 t/day), thus, the implementation of large quantities of air is required. The ventilation of these coalfaces is performed according to the traditional retreat coalface scheme, i.e. according to a U: air intake by bottom gate and air return by tail gate. After the face passage, these accompaniment roadways are not upheld. Air flows usually implemented on sites range from 30 to 60 m /s, and allow to sufficiently dilute firedamp in order to observe the statutory limit concentrations in the face air return. To this regard, firedamp drainage is also nearly systematically performed.

Unfortunately, a part of the district air flow is deviated towards the goaf, concurrently to the air circulating in the coalface, as the goaf constitutes a porous and permeable medium. The air leakage rate is defined as the ratio between the air flow going through the goaf and the district total air flow. This ratio changes from one site to the other, mainly according to the type of strata constituting the roof of the mined seam, and to the land's pressure. Indeed, many on-site measurements performed with tracer gas (SF 6 -sulphur hexafluoride) allowed to establish leakage rates ranging from 10 to 30%, and sometimes reaching 35%! A simple calculation allows to acknowledge the importance of the air flow circulating in the goaf: for an air flow of 50 m7s and a leakage rate of 30%, which is quite a common situation, an amount of 15 m /s of air flows through the goaf.

Although this flow contributes to firedamp dilution on the district as a whole, nevertheless, it represents a problem, which can become critical for certain faces, for at least two reasons:

• the first problem comes from the fact that this parasitic flow interferes with the firedamp drainage that is usually directly performed in the panel, at the high point of the face start-up line (drainage chamber method). The parasitic air reduces the methane concentration in this area, sometimes to the extent that any drainage becomes impossible, and can hinder the furtherance of the working; • the second problem, which is maybe the most important, comes from the fact that coal from these coalfield is particularly subject to spontaneous combustion. There is always a more or less large quantity of coal in the goaf, either because it was abandoned to the roof of the mined seam when it is too thick, or because it comes from a close-by satellite coal seam.

Parasitic air flows, whether in the part of the panel which is already exploited, or in an already mined neighbouring or superior panel, can create favourable conditions for coal heating: oxygen inflow and lack of heat discharge. It is difficult to control such a situation and it can lead to an incident, if not a serious accident, linked to firedamp ignition for example.

Model development

As of 1990, Charbonnages de France ordered research from INERIS to study gas circulation in the goaf and to find means to fight the existing hazards, as well as answers to the problems mentioned above. Although still underway, these research projects led to the design and development of flow models. A physical scale model, and a computerised numeric model grounded on the use of a Computational Fluid Dynamics package. Then very concrete results were obtained thanks to the practical use of these models, pertaining to the establishment of optimum firedamp drainage parameters, as well as to the optimisation of nitrogen injection in the goaf to prevent the occurrence of coal spontaneous combustion in such areas [START_REF] Tauziède | Modelling of gas flows in the goaf of retreating faces -25[END_REF][START_REF] Pokryszka | Application of numerical gas flows modelling to optimisation of nitrogen injections in the goaf -27[END_REF].

Results mentioned in the present paper concern the search for ways of reducing global leakage of parasitic air flow through the goaf. However, a brief presentation of the two available models is previously performed.

Firstly, as regards the physical model, it is a 1/70 * scale model, developed jointly with the Institute of Occupational Medicine in Edinburgh (Scotland) [START_REF] Jones | A physical scale model of flows in the waste of a retreat longwall coalface[END_REF]]. The similarity factors were carefully established in order to guarantee that flows are identical to those which exist in a real coalface. To that end, the model was reversed, SF 6 replacing methane. This gas is injected and distributed in a non-uniform way in the model. The distribution of granular materials representing the waste is not uniform either, in order to take into account spatial variations, which exist in reality, because of the non-homogeneous re-compaction of the strata in the goaf.

As regards the numerical model, it was developed based on the PHOENICS "CFD package", to which fluid dynamics equations ruling flows, whether in a free medium or in a porous medium, were integrated [START_REF] Tauziède | Modelling of gas flows in the goaf of retreating faces -25[END_REF]].

Numerous on-site tests and measurements were conducted to qualify and quantify the influential parameters, and to set the two models on different real coalface configurations [Pokryszka 1995].

The results obtained by operating one or the other of the two models on a specific case, come in the form of gas concentration spatial distributions (methane, air, and possibly nitrogen, if this gas is used to make the goaf inert). Therefore, the efficiency of a specific mean as regards the behaviour of these gases can easily be assessed. Models were used to optimise firedamp drainage and to make the injections of nitrogen as efficient as possible to prevent or fight coal combustion [START_REF] Tauziède | Modelling of gas circulations in the goaf of retreat faces[END_REF][START_REF] Pokryszka | Application of numerical gas flows modelling to optimisation of nitrogen injections in the goaf -27[END_REF]],

Modelling of the treatment efficiency of the roadways in terms of reduction of air leakage through the goaf

Results mentioned in the present paper pertain to the comparison of the influence of various treatments envisioned in the face gates. Indeed, these roadways which are abandoned after the face passage are often a privileged vector for a parasitic air flow in the goaf. The idea is to reduce the general air flow circulating in this medium. Therefore, the prime objective of these treatments is to improve drainage efficiency because of a weaker firedamp dilution by the parasitic air. The second objective consists in improving natural goaf inerting, also due to the presence of firedamp at higher concentrations.

Therefore, specific modellings were performed to assess the compared efficiency of:

• stoppings, in one or the other gates, behind the face, or in the two roadways at the same time;

• or backfilling of these galleries.

Modelling on scale model

As regards modellings performed on the scale model, they pertained to two different coalface configurations, with one or several stoppings set up in the tail and/or bottom gates: stoppings located immediately behind the face for bottom gate or tail gate, 3 or 4 approximately regularly distributed stoppings along the bottom gate. The face which was subject to simulations had the following characteristics: Figure 1 shows the results of these models.

Results from physical scale model air flow 31,5 m3/s -air leak rate : -25%

Results from physical scale model air flow 50 m 3 /s -air leak rate : -16%

• CH4 drainâië 7%) ! -CH4 air return (%)! CH4 in drainage (%) (no nitrogen) -D-CH4 in drainage (%) (nitrogen) -•-CH4 in return (%) (no nitrogen) -*• CH4 in return (%) (nitrogen) no
1 slopping 1 stopping 1 stopping 1 stopping 1 stopping 2 stopping at return at intake at intake at intake at return & stoppings (90m) (260m) (0m) 1 at intake at intake (0 & 90m) stoppings at intake stoppings at intake

Figure 1 : Results from physical modelling

These results are expressed in terms of methane concentration in the air return and methane concentration in drainage. Compared to the reference situation on the left-hand side of each graph, the following comments should be highlighted:

• for case No. 1 (31.5 m /s air flow), one can note the effect of a stopping or of two stoppings together. A stopping located on the air intake side is more efficient than a stopping on the air return side. The highest efficiency is obtained with two stoppings along the abandoned air intake roadway; • for case No. 2 (50 m /s air flow), one can note the influence of 3 or 4 stoppings in the abandoned air intake roadway when there is no nitrogen injection (continuous lines) or when there is an injection of nitrogen (dotted lines).

Numerical modelling

With the numerical model, simulations were performed on a face geometry very similar to that of the scale modelling. The case of a stopping at air intake and/or at air return was tested, as well as those corresponding to a full backfilling of the air return and/or intake roadway. The following numeric values were used:

• air leakage rate: 17% or 34%;

• air flow: 36 m /s or 50 m /s; • methane drainage flow: 0 or 0.45 m /s; • nitrogen injection flow: 0.

In figure 2, results are expressed in terms of air leakage rate through the goaf, which allows direct evaluation of the effect of treatment simulated.

The strongest leak rate reduction is observed with the backfilling of one or, even better, the two abandoned roadways. This improvement is mostly significant when the air leak rate is high, as shown on the bottom graph.

Results from numerical model air flow 50 m3/s -air leak rate : -34% Results from numerical model airflow 36 or 50 m3/s -air leak rate : -17% -airflow : 36 m3/s -drainage ; 0,45 m3/s j In the event that firedamp drainage is performed, the reduction in the air leak through the goaf leads to a reduction in methane concentration in the air return (figure 3). In both simulated cases, results are coherent with those obtained from the scale model, i.e.:

• the efficiency of a treatment on an abandoned air intake gate is higher than a treatment on the abandoned return gate; • full backfilling of one or the two roadways is more efficient that simple stoppings.

Results analysis

However, these two series of tests and simulations highlight that the obtained results, i.e. the efficiency of the implemented means, remain rather disappointing. Indeed, in the best simulated case, the relative decrease in methane concentration in the return roadway is only of ca. 8%. This reduction in concentration on the air return, obtained by an improved goaf tightness, constitutes a significant improvement as it allows improving firedamp drainage, even if only slightly. Therefore, expansion foam stoppings are systematically implemented in the abandoned air intake and air return roadways of all faces of Lorraine Coalfield. Sometimes, the full backfilling of the abandoned air intake roadway is performed. Therefore, the prime expected objective of these treatments is partly achieved.

Unfortunately, the second objective of abandoned roadway treatment, i.e. improvement of natural goaf inerting, is not achieved. Indeed, these stoppings or backfillings do not allow significantly to reduce air leakage rate in the goaf, under the studied conditions. In most cases, notably when the leakage rate is very high, the concentration in oxygen remains high enough for coal self-heating. To prevent this, it is often necessary to perform massive and continuous injections of nitrogen in the goaf in critical cases. Very heavy means, such as massive injection of backfilling in the waste would be required to significantly reduce the parasitic air leakage through the goaf. However, the implementation of such solutions raises major technical and economic problems.

Perspectives

In spite of the relatively slight results mentioned above, a positive conclusion to the use of these models can be drawn. The development of these tools was a long and rather tedious task which took place over several years. However, they provide a significant help to analyse the effect of specific means to fight against firedamp or spontaneous combustion. Therefore, they contribute to the improvement of collective safety of the workings. More specifically, the numeric model has a high versatility and can be adapted to all configurations, notably geometric. Thus, it is superior to the physical scale model.

Evidently, these models will still be subject to many developments in the future, as it is already the case today in several coal producing countries.

Credits

We would like to thank Charbonnages de France for financing this research work, as well as our colleagues from HBL, and especially the Centre de Calcul d'Aérage (Ventilation Calculation Centre), for letting us use their data.

  • face length: 240 m; • face progression from its start-up line: 260 m; • air leakage rate: 25% (case No. 1) or 16% (case No. 2); • air flow: 31.5 m /s (case No. 1) or 50 m /s (case No. 2); • methane drainage flow: 0.3 m7s; • nitrogen injection flow : 0 (case No. 1) or 0 or 2,000 m/hr (case No. 2).

Figure 2 :

 2 Figure 2 : Results from numerical modelling

Figure 3 :

 3 Figure 3 : Results from numerical modelling (continuation)


Antoinette Accorsi

Jean-Philippe P Pineau

Alain Prats

A Accorsi'

Health, safety and environment management system : a

Keywords: safety management System, ranking, health, safety, environment

INTRODUCTION

ISO 14 000 series Standards allowed the development of Environmental Management Systems by reference to the model "Plan, Do, Check, Act (PDCA)".

Quality Standards are currently under revision by using the same PDCA scheme.

In Occupational Health and Safety, many reference documents intemal (Du Pont, Shell ...) äs well äs extemal (BSI Standard 8800 and AS/NZS 4804000) are in existence. üntil now, the international standardisation is progressing slowly owing to the fact of various regulatory approaches.

The PDCA scheme in ISO 14001 Standard could be considered äs a starting point for any Health, Safety and Environment Management System (HSEMS).

Elf Atochem, one of the French greatest chemical group, and INERIS, the National Institute for Industrial Environment and Risks, have worked together to devise an operational tool for HSEMS dedicated to small and medium enterprises. The field application was checked in nine facilities.

The goal of INERIS, acting in this case äs a consultant, was to offer a tested methodology for any small and medium enterprises.

In this review paper, we will firstly describe the documents requested for such a task by reference to the various aspects to be dealt with. Then, we will insist on the need of a ranking System allowing the choice of significant health safety and environmental aspects.

At the very end of this document, difficulties to be overcome in such a work will be pointed out.

REFERENCE DOCUMENTS

Occupational Health, Safety and Environment : linked ßelds

The exact fields of Occupational Health, Safety and Environment are not so easy to be defined. However, there is a clear link : on a chemical plant, one accident (e.g. accidental release of toxic fluid) may lead to health problems (e.g. illness), safety troubles (risks of fire) and undemüning of the environment (water pollution). But while fields are linked, limits are none the less easy to draw.

Interconnection between those three aspects are not really so clear. For example, industrial doctors consider Occupational accidents äs Safety issues, whereas people interested in major accidents mitigation believe that "minor" accidents remain in the field of Occupational health and safety (see figure l). Moreover, major accidents may have serious impacts on goods and people, but also on the environment (e.g. the Seveso plant accident, or the Tchemobyl case ; see figure 2). Finally, the field of environment grows larger and larger including health problems, especially public health (see the transgenic food case).

Sequence of documents for a relevant management System

By reference to ISO 14001 Standard and the requirements given in 96/82/CE Directive, a basic general document "The HSE referential" was written. It includes the following and successive Steps :

• policy (objectives)

• plamüng (hazard identification, risk assessment taking account of the existing regulations, in order to define the HSE significative aspects) • control and corrective action (accident investigation ...) • management review. Another general document is the application guide in which developments and explanations are given on each part of the HSE referential.

Specific documents more adapted to a given sector or a given process are then derived.

The first specific one is the operational guide in which detailed information is given on the aspects to be dealt with in the final document : the HSE Management System for the facility, used for the Operation of the plant.

Implementation of the System

The HSE Referential and the application guide were written in a preliminary task by a general group consisting of ELF ATOCHEM and INERIS experts.

Nine plants all over France participated in the test Operation. Seven visits per plant had to take place, made by the INERIS consultants in dose connections with the manager and operators of the facility. Specific tools have not been created for each chapter of the HSE referential. For the Policy for instance, only examples were given. For most chapters, only charts or logigrams were required. But some parts needed a more in-depth study, especially the analysis in which the ranking of HSE aspects is perfönned.

This ranking allows the management system to become relevant. Its goal is to establish a list of significant HSE aspects which will be ameliorated or cured afterwards.

While this approach was validated for chemical plants, between 20 and 300 people in size, it is nevertheless currenüy used in other industries (pharmaceutical laboratory ...).

A RANKING SYSTEM

Ranking the various Occupational, Healtli, Safety and Environment aspects is the only mean to be sure that an exhaustive HSE analysis is carried out and is the basis of the managerial decisions on the aspects considered äs significant.

The significant aspects are those from which the risks are the highest for the Occupational Health, Safety and Environment and the controls are the worst.

The methodology includes five Steps. In a first step, the various parts of the plant are distributed in sectors when it is a very extended firm, or in basic activities in the other cases. Figure 3

Greenhouse effect

In a third step, for each aspect, a ranking between l and 4 is given on the basis of three criteria : occurrence, severity and control.

Figure 5 It should be pointed out that the confonnity to existing regulations is to be taken into account in the ranking ; when the non-conformity exists, the aspect is always considered äs significant.

Finally (fifth step), it is the personal responsibility of the managing staff to define the level at which an aspect is considered äs significant.

When the ranking is obtained, the specific means for the improvement of the Situation are to be established considering the economic aspects, the available technologies and the staff needed.

DIFFICULTIES, LESSONS LEARNT AND RULES FOR THE SUCCESS

Currently, teachings come from the experience within ELF ATOCHEM plants. In existing plans, the Operation of a HSE management System can be more or less difficult depending on previous experience and practice with quality System (ISO 9000 series) or environmental System (ISO 14000 series). Ttüs is related to the fact that written structured documents exist or not.

In this particular case, three levels of documentations were distinguished : general manuals, procedures and operating and instruction ruies. The responsibility of the first two levels may be controlled by the management staff, the third level may be left to the operators.

For the control and corrective action of the System, a difficulty can occur from the lack of experience about the report of non conformities and how to treat them. As an alternative, the Supervisor reports can be used. Investigations of accidents and incidents are also a way forward for non-conformity approach.

The analysis of functions to be carried out and the definition of jobs are important to be discussed with all implied staff.

It is also necessary to use this opportunity of putting into Operation a HSE management System for the definition of the follow-up of regulations and the definition of an auditing on documentation System, Operation and confonnity to the regulations.

Some success factors

At a first step, all staff must be made aware and sensitive to the improvement of the Situation. This is related to the need of a steering committee for all the work to be undertaken and the complete implication of all staff.

In general, a lot of existing written documents can be used äs parts for the implementation of the HSE management System.

The approach of non confonnity is rather difficult and may be based on investigations of accidents and incidents.

In fact, the approach is the one adopted for any industrial plan : a clear policy at the top management level, participation of all staff, objectives definition, check regulary, readjust objectives and means when necessary, make the personnel sensitive at every step.

CONCLUSION

A safety management System tested, checked and validated in a pilot Operation in nine plants can be directiy used by ELF ATOCHEM for all of its other small and medium facilities. The purpose of INERIS was mainly to use it for any small enterprise. For the füture, the referential and the application guide can be used without changes, but the operational tools (operational guide) might be adapted to any specific industrial field.

Such a System implies a ranking of significant health, safety and environment aspects. This ranking considers three aspects : occurrence, severity, control (instruction and equipment). From this ranking, significant aspects may be extracted and become the basis of the definition of means for improving the Situation.

Success in implementation of a HSE management System is related to all staff beconüng sensitive to the positive improvement of the Situation, the introduction of a written culture (general instructions, procedures ...), the need of enough time, the leaming from accidents and incidents and the use of existing means.

Figure 2 .

 2 Figure l. The limit between Occupational Health and Safety

Figure 3 .

 3 Figure 3. Examples of industrial activities In a second step, the HSE impact factors are examined for each activity or sector. Some examples of these factors are given in Figure 4.

Figure 5 .

 5 Figure 5. Notes for the ranking of HSE aspects Multiplication of the three notes to get a global note allows a ranking in the fourth step.It should be pointed out that the confonnity to existing regulations is to be taken into account in the ranking ; when the non-conformity exists, the aspect is always considered äs significant.Finally (fifth step), it is the personal responsibility of the managing staff to define the level at which an aspect is considered äs significant.When the ranking is obtained, the specific means for the improvement of the Situation are to be established considering the economic aspects, the available technologies and the staff needed.

  explains the various notes.

	Occurrence	1. none or annual frequency
		2. monthly frequency
		3. weekly frequency
		4. daily frequency or more
	Severity	1. minor
		2. notable
		3. critical
		4. major
	Control (monitoring)	1. detection possible ; controlled if detected by regularly
		checked instructions or monitoring equipment
		2. detection possible ; controlled if detected by unregularly
		checked instruction or monitoring equipment
		3. detectable ; uncontrolled if detected (unadapted equipment
		and instructions)
		4. undetected

For each activity, one or more impact factors are to be considered in order to define the impact factors and the HSE aspects.

The link between these notions can be explained on the following example.