Karine Leger

Sef Van Den Elshout

Anthony Ung

Laure Malherbe

Frédérik Meleux

Charlotte Songeur

Cécile Honore

Delphine Pernot

a common website and air quality indices to compare cities across europe

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

still join the website. Différent sections of the website provide a platform to compare différent data (year average, daily, hourly). Participation is therefore not limited to those with their own automatic monitoring network. Other cities are invited to join and upload their data as well. Www.airqualitynow.eu does not aim to replace more targeted existing local information. This would be an unrealistic ambition as in many cities the public has got used to the local, tailor-made index. The proposed common indices are, by the nature of the fact that they are common to a wide area, a non-specific compromise. CITEAIR envisages that there is room for two sources of air quality information on the internet: a local website, in the national language with a dedicated présentation (often using a well established and known local index); and a common website aimed at comparing -in near real time -the air quality in your own city to the air quality in other European cities. Moreover, to facilitate an international use, www.airqualitynow.eu is now available in four European languages: English, French, Dutch and Spanish, while other European translations are under préparation.

Compare the outrent air quality in différent European cities

Figure 1 : Home page of the CITEAIR common web site www.airqualitynow.eu presenting the comparison of air quality in European cities through common indices (background situation for the 26/03/10 at 11:30 pm).

INTERNATIONAL COMPARISON OF CITIES THANKS TO COMMON AIR QUALITY INDICES

A common daily and hourly index (CAQI)

As already explained, comparing air quality in différent cities is a tricky issue. Is the air quality being determined in the same way (this mainly applies to particulate matter) and at comparable locations? This is not an issue that the CITEAIR project and its indices can solve. Its common website will take for granted whatever a city supplies as input data. As a first step to improve comparability, the indices will be reported both for roadside and city background locations. This is considered an important improvement over city averages: some monitoring networks are designed to monitor or spot areas of poor air quality (with possibly a high number of roadside stations) whereas others are aimed at providing an average city picture. The Common Air Quality Index (CAQI) consists of both a daily and an hourly index. In the website the daily index is shown for the past day (D-1). For the current day, the hourly index is available, and is updated every hour. A daily index for today needs forecasting or 'nowcasting', a facility that is not available in each city with a monitoring network, hence the option of an hourly index will be available soon (see section 3). The hourly index is also a reasonably dynamic parameter, enticing repeated visits to a website. The CAQI is calculated according to the grid in figure 2, by linear interpolation between the class borders. between the participating cities. The dividing line between médium and high is often linked mainly to the values mentioned in the directives: alert thresholds (SO2, NO2, O3) or air quality objectives when available on a daily basis (CO and PM10). Class borders were regularly spaced for the main components. PM10 is an exception. To avoid that the CAQI is completely dominated by PM10 the value of 50 |lg/m 3 as a daily average was positioned as the bordering line between low and médium. For the setting of the CO and SO2 borders additional inspiration was sought from Cairncross and John and the DAPPS index [2004] which aims to define the component sub-indices based on the relative risks attributed to each component. The CAQI resembles the French ATMO index and it differs substantially from for example the UK and US-EPA indices. It therefore shares the drawbacks of the ATMO: no clear link with health effects, fairly arbitrarily qualitative interprétation of hourly values. But it also shares its advantage: frequently changing index values that capture the hour-by-hour changes and make a website dynamic. The latter was of overriding importance as raising awareness is a key objective of the common website. De Leeuw and Mol [2005] compared the CAQI to a number of other indices. Whereas the calculation grid for hourly and daily values is the same for most components, PM10 poses a particular problem. Consistency had to be found between the hourly and the daily index scales. Many networks only report 24-hour (moving) average data. This différent averaging time implies that their concentration readings are always lower than those for the networks reporting true hourly values. In order to solve this problem, a sélection of 52 urban and suburban monitoring stations from Airbase for the period 2001-2004 has been used to calculate the ratio between daily maximum hourly concentration and daily average concentration. This average ratio appears to be 0.55. Based on a wide sélection of stations, it is used to link the hourly and daily index scales Figure 3 présents how the CAQI is displayed on www.airqualitynow.eu for the almost 70 current participating cities and the possible comparisons for a particular day and hour enabled by the index for two time scales and two types of exposure. As an example, the détails of the CAQI calculation for Paris through its sub-indices are also provided.

Current situation

A common year average index (YACAQI)

Year average indices are not very common in air quality reporting but they are nevertheless a useful indicator for nonexperts, facilitating the comparison of cities at a glance. Comparing cities by their individual pollutant levels is difficult as one city might be better on one pollutant and worse on the other. In addition, some cities might monitor différent pollutants than others. Even comparing progress in a single city from one year to the other is difficult as progress might be made for one pollutant whereas in another field things might hâve deteriorated. A year average index is a huge simplification but it does provide an easy way to make some kind of relative assessment on the position of one city to the other or for one city from year to year.

In CITEAIR the way of making such a médium term index is the "distance to target" principle. One advantage of the distance to target principle is that each parameter considered contributes to the index (unlike the principle where the worst parameter détermines the index). A distance to target indicator calculâtes, for each pollutant, a ratio of how far the actual measurement is away from the target value, for example a limit value. The overall index/indicator is the average of the sub-indices. A distance to target index is based on policy targets or limit values. The limit and target values hâve important implications both for environmental policy makers and for the public. Besides, they do hâve a link to health risks: in Europe they are most of the time related to the recommendations of the World Health Organisation [2005]. The distance to target way of making an index is the year average index presented in this paper and used on www.airqualitynow.eu. The calculation of the sub-indices is detailed in table 1. Sub-indices are calculated for each pollutant by dividing the actual year average by the EU limit or target value. The overall city index is the average of the sub-indices for NO 2 , PMio (both year average and daily averages) and ozone for the city background index. For the traffic year average index the averages of the sub-indices for NO 2 and PMio (both year average and daily averages) are being used. The other pollutants, if data are available, are used in the présentation of the YACAQI but do not enter the calculation of the city average index. They are treated as additional pollutants like in the hourly and daily indices. The main reason is that not every city is monitoring the full range of pollutants. Furthermore for SO2 we expect that the situation in différent kinds of cities is very far apart, being no problem in most cities and a concern in others. Figure 4 présents how the YACAQI is displayed on www.airqualitynow.eu for a sélection of cities, for two types of exposure, over a number of years, and the détails for Paris. This type of présentation provides valuable additional information when comparing two cities or the same city over two years. At a glance it becomes évident what the main problems are and where progress for the situation is satisfactory.

DEVELOPMENT OF A FORECAST FOR THE COMMON AIR QUALITY INDEX

CITEAIR II is developing and implementing a forecast for the CITEAIR II air quality daily index with three levels of complexity to meet the needs and requirements of European cities:

-Level 1: "Easy approach": the objective is to individually forecast air quality for each mandatory pollutant at the monitoring stations in order to dérive a forecast air quality index at the city scale. The methodology is based on local statistical adaptation of PREV'AIR large (European) scale forecasts. It consists in writing concentrations at each monitoring station as a multi-linear function of PREV'AIR large scale outputs, past measurements and other relevant quantitative or qualitative predictors -Level 2: "Mid-level approach": the objective is to produce a forecast index map over the city. Locally forecast concentrations resulting from level 1 are spatialised by geostatistical kriging methods. Auxiliary variables known over the whole area (e.g. émission inventories, population, land cover, meteorological fields) and correlated to concentrations are introduced in the estimation to enhance the map précision. This approach requires a rather homogeneous distribution and a sufficiently large number (at least >15) of monitoring points over the city and its surroundings.

-Level 3: "Sophisticated approach": the objective is to forecast air quality over the whole city at fine-scale resolution. This approach is based on high resolution chemistry transport models implemented with proper émission patterns and relevant chemical schemes. European chemistry transport model outputs are used as boundary conditions for the model area.

Which level a city applies dépends on the local conditions and resources. Nevertheless, the level 1 was designed to be available to forecast the CITEAIR air quality indices for every city in www.airqualitynow.eu. The forecasted indices will be displayed on the common website for D+0 and D+1.

As an example, Figure 5 From this figure, one can see that level 1 approach substantially improves the CAQI forecast. The underlying statistical model is based in this spécifie case on a very limited set of prédictive variables: measurements of the day before and European model outputs. Other models -based on a larger set of prédictive variables such as meteorological parametershâve also been built, and in most cases, they give satisfactory results in term of forecast comparison to observations.

CONCLUSION

Full détails on the élaboration of CAQI and YACAQI, as well as sample application, are available on www.airqualitynow.eu. Maps of forecasted concentrations of the pollutants of main concern derived from PREV'AIR hâve already been added and will be soon complemented by forecasted air quality indices during the life time of CITEAIR IL Further developments of thèse common tools will concern: participation of new cities and new média partnerships to display the indices, intégration of PM 2 .5 in the indices according to the CAFE directive, as well as translations in several EU languages. Cities are engaged in communication with the public, not only because of légal obligations but also to raise awareness. This implies that air quality issues hâve to be presented in an attractive and educational way. The possibility to compare your own local air quality to a number of other European cities is an asset in this respect. The purpose of common indices and website is not to replace more detailed local information nor to check EU régulation compliance but to complément it. The added value is to provide, for the first time, a European and comparable picture of the air quality in near real-time, forecasted and understandable by anybody. In addition, the provision of separate indices for two types of environmental conditions and three time scales is a methodological innovation. It could also be an alternative to raise public awareness for cities which do not already operate a website.

Figure 2 :

 2 Figure 2: Pollutants and calculation grid for the CAQI

Figure 3 :

 3 Figure 3: CAQI results for the cities part of CITE AIR and détails of the CAQI results for the agglomération of Paris on www.airqualitynow.eu.

Figure 4 :

 4 Figure 4: YACAQI results for cities part of the CITEAIR project and détails for the agglomération of Paris on www.airqualitvnow.eu.

Figure 5 :

 5 Figure 5: Comparison over year 2009 for the city of Rotterdam of the daily CAQI forecast for D+0 between: the European, low resolution PREV'AIR system output (in green); level 1 forecast (in red) derived within the CITEAIR II framework; the index computed based on observations (in black).

Common air quality index calculation grid g ROADSIDE INDEX Mandatory pollutant

									,a BACKGROUND INDEX
	The final index is the highest value of the sub-indices for each component. As can be seen there are two CAQI-s: one for traffic monitoring	Index Class	Grid	HO2	i hour	PM10 24 hours	Auxiliary pollutant CO	HO2	Mandatory pollutant PM10 1 hour 24 hours	03	Auxiliary pollutant CO SD2
	sites and one for city background sites.		>100	>400	>100	>100	•20 000	•4(0	>100	•100	>240	•20 000	•500
	The traffic index comprises NO2 and PM10, with CO as an auxiliary component. The background	hïBh	100 76	400 201	100 91	100 51	20 000 10 001	400 201	180 91	100 51	240 101	20 000 10 001	500 301
	index obligatory comprises NO2, PM10 and O3, with CO and SO 2 as auxiliary components. In most cities the auxiliary components will rarely détermine the index (that is why they are auxiliary) but in a city with industrial pollution or a seaport, SO 2 might	Médium Low VeryLow	75 51 50 26 25 0	200 101 100 51 50 0	90 51 50 26 25 0	50 26 25 13 12 0	10 000 7 501 7 500 5 001 5 000 0	200 ioi 100 51 50 0	90 51 50 26 25 0	50 26 25 13 12 0	180 121 120 61 60 0	10 000 7 501 7 500 5 001 5 000 0	300 101 100 51 50 0
	occasionally play a rôle. Benzène is considered a
	long-term exposure issue. The number of cities
	with online monitoring of benzène is limited and it
	is therefore not included in the short-term indices.
	The choice of the classes in the CAQI is inspired by
	the EU législation and based on a compromise

NO2, 03, SO2: hourly value/ maximum hourly value in ug'm3 • PM10: hourly value/ maximum hourly value oradjusted daily average in ua'm3 • CO: 8 hours moving average / maximum 8 hours moving average in ug/m3

Table 1

 1 and city background sites. It is up to each city what they want to contribute (monitored or modeled data). In most cases, the cities choose to provide data from one or more monitoring sites. When a city provides data from several sites, each index is based on the average of the data from the number of sites.

	:
	Calculation for the year average basis index. Like the hourly and daily index, the Year Average Common Air Quality Index (YACAQI) is calculated for traffic Pollutant NO 2 PM 10 Ozone SO 2 Benzène CO	Target value / limit value Year average is 40 (ig/m Year average is 40 (ig/m 3 Max. number of daily averages above 50 (ig/m 3 35 days with ~ year average of 31 (ig/m 3 25 days with an 8-hour average value >= 120 (ig/m 3 Year average is 20 (ig/m 3 Year average is 5 (ig/m 3	Calculation Year average / 40 Year average / 40 Year average / 31 # days with 8-hour average >=120 / 25 Year average / 20 Year average / 5 Not calculated
			Paris Yearly Air Quality Index

  European), low resolution (50*50km 2 ) PREV'AIR system; the level 1 forecast derived within the CITEAIR II framework; the index computed based on observations; the observations are relative to year 2009, whereas the statistical model is built on 2008. The comparison is performed hère for the city of Rotterdam.

	Rotterdam
	jany.

displays a comparison of the daily CAQI forecast for D+0 between: the large scale (

ACKNOWLEDGEMENTS

CITEAIR II consists of 11 partners (14 partners for the previous project) from 8 European countries. This work is the result of contributions from all of them and supports from INTERREG (IIIc and IVc), the users community as well as the EEA.


Matthias Beekmann

Laura Chiappini

Olivier Favez

Gilles Aymoz

Bertrand Bessagnet

Laurence Rouil

Stéphanie

U Baltensperget

A Borbon

J Sciare

V Gros

A Baklanov

M Lawrence

S Pandis

V Kostenidou

M Psichoudaki

L Gomes

P Tulet

A Wiedensohler

A Held

L Poulain

Kkamilli

W Birmli

A Schwarzenboeck

K Sellegri

A Colomb

J M Pichon

E Ferna

J L Jaffrezo

P La

C Afif

V Ait-Helal

B Aumont

S Chevallier

P Chelin

I Coll

J F Doussin

R Durand-Jolibois

H Macleod

V Michoud

K Miet

N Grand

S Perrier

H Petetin

T Raventos

C Schmechtig

G Siour

C Viatte

Q Zhang

P Chazette

M Bressi

M Lopez

P Royer

R Sarda-Esteve

F Drewnick

J Schneider

M Brands

S Bormann

K Dzepina

F Freutel

S Gallavardin

T Klimach

T Marbach

R Shaiganfar

S L Von Der Weiden

T Wagner

S Zorn

P De Carlo

A Prevot

M Crippa

C Mohr

Marie Laborde

M Gysef

Roberto Chirico

Maarten Heringa

A Buter

A Bourdon

E Mathieu

SAFIRE T Perrin

J Wenger

R Healy

I O Connor

E Me Gillicuddy

P Alto

J Pjalkanen

M Kulmala

P Lameloise

V Ghersi

O Sanchez

A Kauffman

H Marfaing

C Honoré

F Melleux

S Rossignol

M Haeffelin

C Pietras

J C Dupont

S Kukui

E Dieudonné

F Ravetta

J Craut

G Ancellet

F Goutail

J L Besombes

N Marchand

Y Lemoullec

J Cuesta

Y Te

' N Laccoge

S Lollp

L Sauvage

S Loannec

D Ptak

A Schmidt

S Conif

The megapoli paris campaign for urban aerosol characterisation -a comprehensive data set for air quality model evaluation

Keywords: organic aérosol, particulate matter, primary and secondary sources, benchmark for model évaluation

INTRODUCTION

Very dense pollutant émissions over megacities are strongly affecting air quality on an urban scale and chemical composition on a régional and even global scale. This ultimately affects both public health and régional to global climate. In order to assess the overall effects of megacity émissions, ail links between émissions, transport, chemical transformation and déposition processes should be well understood, which is currently not yet achieved. In particular, despite its adverse effects on health and their potential effects on régional and global, primary and secondary sources of particulate matter in the urban atmosphère are not well qualified and quantified.

The FP7 and national French MEGAPOLI project aims at gaining an increasing compréhension of major processes affecting the abundance of particulate matter in a polluted atmosphère, in particular:

To reach thèse objectives, an expérimental campaign in the Paris agglomération, a major anthropogenic émission source surrounded by rural areas, has been conducted. A particular focus has been put on organic carbon, for which not only secondary formation, but also primary émissions are still not well quantified, despite the major contribution of organic carbon to urban and régional scale fine particulate matter levels. Greater Paris has been chosen for a large expérimental air pollution campaign because it is a major and dense pollution source (more than 10 million inhabitants), surrounded by rural areas and relatively flat terrain.

Detailed aérosol measurements and gaseous precursor measurements hâve been conducted at an urban and two sub-urban sites, from five mobile platforms and from the French ATR-42 and Piper-Aztec research aircraft. State of the art instrumentation has allowed détermination of aérosol chemical composition, either with very high frequency (several minutes to half an hour), or with large chemical détail (several dozens of organic compounds from filter samples). In addition, the size distribution, optical, hygroscopic and mixing properties hâve been determined in order to relate the aérosol chemical composition to its potential radiative and climate impact in the urban région and its plume. Gas phase measurements hâve focussed especially on detailed VOC measurements in order to relate SOA build-up to gaseous precursor species abundance. A network of backscatter lidars including urban, sub-urban and rural sites, in addition to mobile platforms gives access to the aérosol vertical distribution in the région and to variations of the boundary layer height at the urban / rural interface.

The results of this measurement campaign will constitute a comprehensive data set of aérosol composition and properties, for gaseous aérosol precursor species, for pollution tracers and for dynamical parameters. This data set will constitute an important benchmark for air quality model évaluation. In this paper, the campaign objectives will be presented, the expérimental set-up will be described, first results will be presented and benchmarks for model évaluation will be identified

OBJECTIVES OFTHE CAMPAIGN

The first major objective of the campaign deals with closing identified knowledge gaps and to provide expérimental data for model improvement and évaluation. This concerns in particular formation processes of primary and secondary aérosol at régional scale, with a spécifie focus on organic matter. A number of spécifie objectives are pursued: • to document the aérosol composition and properties, and gaseous precursor concentrations, within a large agglomération and in its plume, with a focus on the chemical speciation of organic carbon; • to provide source apportionment of elemental and organic carbon PM, in order to improve régional scale émission inventories, • to document pathways of secondary organic aérosol build-up from gaseous precursors within the agglomération and in its plume, • finally, to use expérimental data obtained through the project and already existing data bases in order to evaluate and to improve process (0D) and air quality (3D) models for a large range of conditions (effective émission strength, meteorological variables).

EXPERIMENTAL SET-UP

The intensive campaigns were active in both a summer and a winter period, from July 1 to 31, 2009, and January 15 to February 15, 2010. At the three primary sites, a very complète set-up of instruments was deployed (Figure 1) allowing for a detailed characterisation of aérosol properties, including their size distribution, volatility, hygroscopicity, optical properties, of aérosol chemical composition (from fast measurements with a time resolution of several minutes, by Aérosol Mass Spectrometry (AMS), including also single particle measurements) and chromatographic measurements (PILS)). This ensemble of instruments gives the mass concentration of inorganic ions, of primary and secondary organic carbon, respectively for PM1 and PM2.5 aérosol. Black carbon measurements were also performed with various methods. In addition, filter measurements were taken to allow for individual analysis of up to 100 individual organic compounds, which are tracers for spécifie émission sources and secondary formation mechanisms. Detailed gas phase measurements were performed, especially of VOC's as precursors of organic aérosol, including also secondary compounds, but also for compounds important for photoxydant pollution and the atmospheric oxidising capacity (ozone, nitrogen species, odd hydrogen radicals). Airborne and mobile measurements allowed in particular to assess the chemical évolution of the pollution plume, up to 200 km from the source région. Mobile platforms were deployed on the basis of chemical forecast provided by INERIS via the PREVAIR system. At one primary site (SIRTA), extensive dynamical measurements were performed, including especially wind profiles, and backscatter lidar measurements. At this site, and during the winter campaign, the cloud (fog) phase was also sampled. At two urban secondary sites (Jussieu in the center and Créteil in the south-east of the agglomération), the spectroscopic column measurements and backscatter lidar measurements were carried out. During the winter campaign, an additional lidar network was set-up at an urban and at four suburban sites (red stars in Figure 1), using a homogeneous set of aérosol backscatter lidars produced by LEOSPHERE.

FIRST RESULTS

One of the interesting results from airborne primary pollutant measurements during the summer and winter campaigns was that the pollution plume was still well defined at more than 100 kilomètres downwind from the agglomération. This implies that a "safe" framework will be obtained for later studying secondary organic aérosol build-up in the plume from Paris agglomération émissions. It also implies that one should be able to dérive spatially average pollutant émission from tracer measurements (for example black carbon measurements shown in Figure 2) in the plume, provided that model transport is correct. Figure 2 also shows black carbon simulations with the CHIMERE model set-up (set-up for the MEGAPOLI campaign with a multiple nesting option over the Paris area (horizontal resolution 50/9/3 km). It appears that the plume position and extension are in gênerai well simulated, with some déviations for particular days.

mm

Figure 1: The campaign design included 3 primary (in black) and 3 secondary (in blue) fixed ground measurement sites, an aircraft and 5 mobile platforms. Primary sites are devoted to aérosols and gas phase chemistry, secondary sites to active and passive remote sensing. A spécifie lidar network was set-up at a central Paris site and at 4 cardinal points during the winter campaign (red stars). For the June 10, the direction of the plume is well simulated, while for June 16, a différence of about 45° is observed. Thèse aircraft data are thus an important constraint for the simulated meteorology. Significant new particle formation events were observed in the Paris area during the whole summer month of the campaign. Thèse events were favoured by the relatively low particulate matter concentration levels and resulting low surface area during most of July 2009.

During both the summer and winter campaign, very preliminary attribution of organic aérosol (OA) from AMS mass spectrometer urban and peri-urban measurements , and also from ground-based mobile measurements in the plume show a large fraction of oxidised organic aérosol (OOA), comprising both chemically processed (oxidized) primary organic aérosol and classical secondary organic aérosol (from aromatic and biogenic VÛC precursors), and a smaller fraction of un-oxidised organic aérosol (HUA) of primary origin. Another aspect is water solubility of ÛA available from PILS-TÛC measurements: At the urban LHVP site, about half of ÛA is water soluble (during the summer campaign), corresponding probably to classical secondary organic aérosol, another half is water insoluble, corresponding probably to primary and chemically processed primary ÛA. Ûbviously, thèse data will be valuable for constraining SOA formation in air quality models; models using SUA formation schemes built on results from older chamber measurements in gênerai underpredict SUA formation from anthropogenic sources (e.g. [START_REF] Volkamer | Secondary organic aérosol formation from anthropogenic air pollution: Rapid and higher than expected[END_REF]. This data set also will allow to test new schemes, like the Volatility Basis Set (see for example Robinson et al. 2007) taking into account in a parameterised form a) the volatility of primary organic aérosol émissions and b) a decrease with time in volatility of semivolatile VÛC species due to ongoing oxidation (see Zhang étal, this issue, for using such a scheme within the CHIMERE model).

During the winter campaign, particulate matter levels were much larger than during summer, reaching more than 100 ug/m 3 PM2.5 at several occasions. Both local sources with a major ÛC fraction, and continental sources with a large nitrate fraction, contributed to thèse levels. A surprise was the major contribution of domestic wood burning to local OC. For this latter source, émission inventories are very uncertain, because émission factors strongly vary with the fire type. Thus campaign results will be very helpful to better constrain émission inventories. Aérosol chemistry Secondary and inorganic aérosol formation Spécifie volatility and oxidative properties of (secondary) OA, constraint on SOA schemes in models Bulk évaluation of biogenic vs. anthropogenic SOA sources Secondary aérosol build-up normalized by émission tracer and by integrated photochemical activity (time integrated OH); this is a very processes oriented benchmark

Notes

(1) The conceptual idea is that for urban background sites, dispersion (vertical turbulence, horizontal advection) is more uncertain than émissions at least for NOx. For airborne maeasurements errors in the model transport can be partly corrected (e.g. boundary layer height) or normalised out (e.g. plume direction), allowing to dérive spatially integrated émission estimâtes from plume measurements.

(2) Using statistical source apportionnement methods

CONCLUSION AND PERSPECTIVES

As a conclusion, the MEGAPOLI campaign allowed to gather a large data set of aérosol, gaseous species and dynamic measurements. First conclusions about the oxidised character of organic aérosol and about the importance of spécifie sources (wood burning in winter) hâve been drawn. As a concluding perspective, we show hère a table, how différent measurements will be used for model évaluation. It appears that différent (combinations of) during the MEGAPOLI campaign will allow to evaluate spécifie modules (gas phase and aérosol chemistry, etc. ) and input data (émissions, ...) within air quality models This data set will be first available for the MEGAPOLI consortium and later for the scientific community.

Figure 2 :

 2 Figure2: On the left, absorption coefficient, measured by a PSAP instrument from LaMP on the ATR-42. This instrument measures an absorption coefficient which can be related to black carbon content (courtesy, Alphons Schwarzenboeck, LaMP). On the right, CHIMERE simulations of black carbon (courtesy Q. Zhang) during the flight hours and at flight altitude (500 m). Top: flight on 10/7/2009, bottom flight on 16/09/2009. For the June 10, the direction of the plume is well simulated, while for June 16, a différence of about 45° is observed. Thèse aircraft data are thus an important constraint for the simulated meteorology. Significant new particle formation events were observed in the Paris area during the whole summer month of the campaign. Thèse events were favoured by the relatively low particulate matter concentration levels and resulting low surface area during most of July 2009.

Table 1 :

 1 Expérimental measurements performed during the MEGAPOLI campaign and constraint on model input data or processes

	Measurement type performed	Model parameter or process to be evaluated
			Meteorology and transport
	Lidar and sodar wind profiles	Synoptic wind speed
	Radiosounding wind and T profiles	Synoptic wind speed and boundary layer height
	Surface meteo network (température)	Urban heat island effect
	Lidar derived boundary layer height	Urban heat island effect on BL height
	Passive émission tracers (NÛx at urban scale from AirParif	Urban scale dispersion	(cumulated with uncertainty on
	network, urban + plume BC and NÛy, including airborne)	émissions), régional scale advection
			Emissions
	Airborne plume measurements of émission tracers (NÛy,	NÛx, VOC, BC émissions (spatially integrated over Paris
	VÛC, BC)	agglomération) '
	Urban scale VOC ratios	VOC émission ratios , source distribution
	PM chemical composition	PM and organic aérosol émission source distributionB
	Airborne measurements of biogenic VÛC and oxidation	iogenic VOC émissions over forested areas surrounding
	products	Paris agglomération
			Gas phase chemistry (non exhaustive)
	Oxidant (sum Û3+NO2) content	Ozone formation efficiency
	VÛC ratios of différent reactivity	Spatially averaged radical (OH) concentration
	Odd hydrogen radical and source/ sink measurements	Odd hydrogen (OH, HO 2 , RO 2 ) radical budget
			Aérosol properties
	Aérosol size distribution, hygroscopicity	Correct	représentation	of	nucleation,	coagulation,
		hygroscopic growth in models
	Hygroscopicity and single particle measurements	Représentation of mixing state
	Chemical PM1, PM2.5 mass closure (AMS, PILS, ...)
	Volatility, thermodenuder + AMS, Û/C ratio
	C14 analysis (modem vs. old carbon)
	OU A/ CO ratio versus -log(NOx/NOy)

ACKNOWLEDGEMENTS

The MEGAPOLI campaign has been supported by the FP7 MEGAPOLI project, by French ANR and LEFE/CHAT programs, and by the Ile de France SEPPE program. The MEGAPOLI project is very warmly thankful and acknowledges the


A Vallée

B Affeltranger
email: bastien.affeltranger@ineris.fr

Ch Duval

Flooding of industrial facilities -Vulnerability réduction in practice

Worldwide exposure of industrial plants to flooding

International databases such as OFDA and CRED show that floods accounted for more than half of disasters registered for the 1990-2001 period Worldwide. With conséquences of climate change largely unpredictable at local level, future statistics are not likely to show any improvement. As human activities historically developed in river areas and floodplains, industrial facilities are structurally exposed to flooding.

ARIA is a database maintained by BARPI, a service of the French Ministry of Ecology, reporting most of major industrial accidents occurring in the country -as well as a sélection of accidents occurring abroad. In January 2008, the French Institute for Industrial Environment and Risks (INERIS) performed an analysis of ARIA data. Results show that less than 3 % of accidents (133 events out of 5050) were caused by one or more natural hazards (e.g. flooding, storm, earthquake...). At first glance the susceptibility of countries to expérience natural-technological hazards (NaTech) appears, in average, rather low.

The figure below indicates the catégories of failures, incidents or accidents triggered by natural hazards, and as reported in the ARIA database: Even if the accidents caused by flooding form a statistically marginal group in terms of events, and when compared to other more fréquent major accidents (technical problems, human errors...), it is clear that human, material and environmental conséquences of NaTech events can be significant and should not be neglected.

• Océanie • Asie • Afrique IAmériquedu Sud • Amériquedu Nord • Europe{hors France) i !••••• II. Cl C2 C3 C4 C5 C6
When flooded, industrial facilities présent the following two types of conséquences:

• Direct conséquences: damage to buildings, tanks, pipes, storage of raw materials and finished products, pumps, electrical, thermal and mechanical equipments... As shown by the analysis of past accidents, such direct damage may cause major accidents within industrial plants. Thèse include release of hazardous material, soil or water pollutions by hazardous substances for the environment, fires, explosions, dispersion of toxic clouds...

• Indirect conséquences: business interruption, temporary unemployment, rising of insurance premium in some countries...

Examples of industrial flooding are many. For instance, heavy rains feeding the El Maleh Oued (river) triggered the flooding of a refinery in Mohammedia (Morocco) on 25 th November 2002. Many damages were reported. In particular, the roof of a tank was broken, while another cracked. Released oil products would then mix with the floodwaters. Oils, floating on the surface of the water, came into contact with hot parts of the units, causing a significant fire and a séries of tanks, electrical equipments and pipes explosions. Human conséquences of this accident counted two dead and four injuries. After the flood, the refinery was closed and its activities were suspended for several months for repair and cleaning. Another example is the flooding (caused by the Aisne river, France) of a building where pesticides and fertilizers were stored (Acy-Romance, 22 nd December 1993). The water washed away containers and dissolved chemicals. As an emergency response measure, the door of the flooded building was sealed in order to contain the hazardous substances. The water within the plant was analyzed and eliminated by spreading of absorbent products.

It is therefore necessary that industrial plants managers improve their understanding of potential impact of flooding on their facility, and analyse major accidents or release of hazardous materials that may cause by such flooding. This holds true for governments as well, as the existence of an appropriate regulatory framework can be a strong impetus for reducing industrial vulnerability to flooding. Such framework should include prévention and protection features, as well as intervention measures against NaTech events.

This communication first présents how accident risk analysis helps in a) identifying floodprone equipments or processes in facilities and b) devising appropriate safety barriers or measures. Second, good practices for vulnerability réduction, as applied by flood-prone industry, are presented and discussed. Third a list of generic safety barriers against flood is proposed.

INERIS methodology integrating flood hazard in industrial safety assessment

The methodology for the intégration of flood hazard in risk-reduction process for new or existing industrial facilities, proposed by INERIS, follows a séquence in 5 steps, as detailed below:

Stepj

Characterization of flood hazard

Step 2

Identification of flood-prone areas within the industrial plant

Step 3

Identification of y facilities and equipment affected by flooding, which may be sources of major accidents

Step 4

Detailed risk analysis performed on facilities and equipment selected at Step 3

Step 5

Risk réduction -Démonstration of risk control The objective of this step is, in the areas which may be flooded, to identify facilities and equipments potential sources of major technological accidents. Selecting items vulnérable to flooding is based on:

• an analysis of hazardous properties of substances and préparations contained in the facilities and équipements (Material Safety Data Sheets), with attention given to the incompatibility of thèse products with water, • a flotation study for the tanks, • an analysis of lessons learned from floods that hâve already occurred on the studied plant or on similar industrial facilities.

2.4

Step 4: Detailed risk analysis on facilities and equipments affected by flooding, which can be sources of major accidents

For each facility and equipment identified in Step 3, the flood hazard should be considered as an external aggression and/or as a hindrance to the functioning of safety barriers.

A systematic risk analysis (Preliminary Risk Assessment -PRA, HAZOP, "bow-tie approach"...) is conducted. The accidentai séquences leading to dangerous phenomena (fire, explosion, toxic cloud dispersion, BLEVE, pollution...) are elicited, while existing safety barriers are highlighted. See table below for an example of the type of accident séquence derived from the risk analysis process. French régulation makes it compulsory to conduct this above analysis as part of safety reports that are mandatory for any high-risk industrial facility.

It should be noted that the management of NaTech accident is not limited at reducing the accident risk at source, but others tools such as river basin management, land-use planning and emergency plans, prepared by authorities, may also limit the number of people exposed in the surroundings.

Good practice for the mitigation of flood impacts on industrial facilities

As an agency placed under supervision of the French Ministry of Ecology, INERIS plays a lead rôle in advising compétent authorities on matters pertaining to industrial safety. In particular, INERIS collects good practices -in France and aboard -for mitigation accident risks triggered by natural hazards. The présent section provides an overview of thèse lessons learned.

Présentation of two case studies in France

a) A SEVESO-classified type of industry, specialised in manufacturing of aeronautic and aerospace equipment and riparian to the Seine River, has established a flood emergency plan.

Three types of flooding hâve been found to potentially impact the plant : overflow of the Seine river, water table rising (alluvial aquifer) and flooding by public sewerage. The référence event chosen for designing the emergency plan was a water level higher than the maximum ever recorded historically (1910 catastrophic flood). Several intermediate levels were defined for progressive warning purposes. Derived actions include:

• monitoring the flooding with graduated scale and piezometers,

• setting up a crisis team,

• building walls to isolate some critical major equipments (protection of the production tools, ensure safety) like gas valve, télécommunications equipments, archives room... • emptying acids tanks located underground, • entering in connection with electricity and natural gas networks operators,

• managing the return to normal situation when the water level begins to décline, including cleaning and pumping opérations, restart of facilities... b) Ruptures of dikes along the Rhône river could cause flooding of a warehouse storing agrochemicals. An emergency plan has been prepared for this storage. But the risk réduction was also made through permanent préventive measures such as:

• modification of storage management in order to store at a higher altitude the products most sensitive to moisture, • installation of electrical equipment above the highest water level already observed in the past,

• increasing of the impermeability of ground and walls by applying resins.

List of possible measures to reduce vulnerability to flooding

An indicative list of possible measures to reduce the vulnerability of industrial facilities to flooding is proposed (may vary depending on the configuration of the plant):

• Build dikes and levées for protection around the plant,

• Build walls around the critical equipments, those which are the most important for opération and safety / Close certain openings,

• Contrai, and if necessary strengthen tanks attachment,

• Move storage to areas that are not likely to be flooded,

• Move equipment, sensors, networks (electricity, gas, water, télécommunications, computer System...) above the highest past flooding water height,

• Install Systems to eut automatically power and gas supplies,

• Provide pathways which cannot be flooded to make intervention easier, and refuge area outside water for staff An emergency plan must detailed driving to follow in case of possible flooding and précautions to be taken depending on the nature of concemed products and processes. Generic features of such plan include:

• Définition of the emergency plan implementation threshold,

• Présentation of means to be informed of the water rising : maps / newsletters written by the agencies responsible of climate / flooding forecasting and monitoring, graduated scales located in the plant or in a nearby point, piezometers to measure the groundwater level, regular monitoring and surveys conducted by employées...,

• Description of the organization during the flood (members of the crisis team, opérations manager...),

• Mapping of areas in the plant that could be flooded,

• List of critical units and equipments,

• List of temporary actions to be undertaken and the people involved to make them (priority, séquence, décision tools...) o Build provisional containments, walls... o Close doors and Windows with blocking devices (mobile panels...) o Move vehicles and non-essential objects out of the plant o Attach objects that may move in order to avoid collision and break of pipe or tank o Empty tanks (raw materials, manufactured products, solid and liquid waste...) o Fill the tanks (over and underground) that may float, provided that the stored products are compatible with water o Put facilities in a safe position (isolate tanks, stop product transfers, stop production...)

• Inventory of equipment (pumps, generators, lifeboat, workers protection...) to use • List of contacts (agencies responsible of climate / flooding forecasting and monitoring, local and national authorities, rescue services, subcontractors...) During the establishment of this emergency plan, it is important not to forget to include the management of the post-flooding period and the return to normal operating. Two important points must be seriously considered for assessing available human and material resources:

• Some employées might not be available to make the planned actions (their own houses could be affected by flooding, dead or injured persons in their families, access to the plant impossible...),

• The external rescue services may not help necessarily the crisis team, because they will provide assistance to the population in priority. Finally exercises must be performed periodically to ensure the effectiveness of this emergency plan.

Flooding vulnerability réduction: difficulties and challenges

The réduction of the vulnerability to flooding of industrial facilities, as explained in paragraphs 2 and 3, may still face some difficulties in its implementation. Although there exist régulations, rules and/or guidelines for natural disasters on one hand and technological major accidents on the other hand, too few similar documents exist for NaTech accidents management. The need to hâve guidelines is real for ail stakeholders; industrials, authorities responsible of the control, rescue services, insurers... would ail be interested.

Authorities and emergency services are not most of the time equipped and prepared to manage multi-hazards disaster such as a major technological accident due to a natural hazard event. Multi-hazards approaches for land-use planning and management of emergencies should eventually be developed.

When a plant is flooded, hazardous substances and préparations may be driven by water and deposited on the soil after the natural phenomenon. It seems that assessment of the short time and long time impacts of this pollution to human health and environment should be further investigated. Experts hâve to progress in this field.

Post-accidental investigations are essential to improve NaTech related knowledge, extend the list of good practice measures in prévention, protection and intervention, and contribute to improve NaTech risk management.

Working groups with représentatives of governments and NaTech experts hâve been created by the European Commission (Joint Reseach Center -Ispra, Italy) and by the Organisation for Economie Co-operation and Development (OECD) to provide answers to thèse still outstanding questions.

Références

• "Guide pour la prise en compte du risque inondation" "Guide for the intégration of flood hazard on industrial facilities" A.

Figure 1 :

 1 Figure 1: Distribution of the 133 NaTech incidents and accidents reported Worldwide

Figure 2 :

 2 Figure 2: Mohammedia refinery fire (Morocco -25 th November 2002)

Figure 3 :

 3 Figure 3 : Intégration of flood hazard on industrial facilities -INERIS approach

Figure 4 :Figure 5 :

 45 Figure 4: Example of flood hazard maps (Somme river -France)

  Most countries hâve initiated policies to reduce impact of natural disasters, and hâve produced flooding maps. This work taking a long time, ail data on floods are not yet available in ail areas potentially affected in the world. Without information on this natural hazard, owners of industrial facilities can not know if their plants are concernée! and if measures are necessary. It should be noted that the Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks requires Member States to identify (end of 2011) and map river basin districts and coastal areas at risk (end of 2013), and develop management plans (end of 2015).

Table 1 :

 1 Extract of Preliminary Risk Assessment -Storage tank containing flammable hquid Initiating events

		Critical event	Dangerous phenomena	Safety barriers
	Ripple effect (for torrential floods) Collisions with floating objects	Significant breach in the tank	-Soil and water pollution -If ignition, fire and explosion	-Attach the bottom of the tank -Drain the tank in case of flood warning

2.5

Step 5: Risk réduction -Démonstration of risk control An analysis of the safety barriers performance is achieved. The aim is to minimize accident risk at the plant level, making existing technical and human safety barriers more robust and / or by installing additional barriers. While doing so, stability of (acceptable) risk level must be demonstrated by the operator (by testing robustness of safety chains, by improving staff training...).

  Vallée, Report INERIS DRA-2004-Ava-P46054, November 2004 • "Learning lessons from NaTech incidents : methodological challenges" B. Affeltranger, L. Steinberg, Abstract book of the 16 th SRA Europe annual meeting, The Hague, Netherlands, 17-19 June 2007, p. 39 • "Prévention des risques d'accident naturel-technologique (NaTech) -Etat des lieux" "Prévention of NaTech accident risk -State of the art and current situation" B. Affeltranger, Ch. Duval, Report INERIS DRA-09-103475-04267B, June 2009


S Descourrière
email: sandrine.descourriere@ineris.fr

S Chaumette

Land Use Planning around hazardous onshore pipelines: implementation of the French new principles

Keywords:

Introduction

Onshore transmission pipelines are one of the common ways, in Europe as in other parts of the world, to transport large amounts of hazardous goods through great distances. They are also the safest way, according to statistics (cf table 1). Table 1: Accident rate in hazardous goods transportation (France, 1998(France, -2003) ) Transportation Despite of this low failure rate, thèse pipelines may generate major accidents, as shown by the following pictures.

Jet fire on a gas pipeline Leak on a crude oil pipeline (Ghislenghien, Belgium, 2004) (Saint-Martin- de-Crau, France, 2009) Thèse examples emphasize the 'major-accident hazard' potential of onshore pipelines. In most of developed countries, their opération is for that matter under safety régulation and submitted to external inspection. But thèse régulation and inspections are not harmonized. As an example, in European Community, onshore pipelines are excluded from the scope of both the Seveso II Directive and the Pressure Equipment Directive, although mostof them carry flammable ortoxic substances at high pressure (from 10 to 80 bars). In this context, the French national authority in charge of onshore pipelines risks-control deeply modified régulations in August 2006, for both existing and new pipelines. In particular it was decided to deal with existing pipelines in urban or suburban areas, through new risk assessment method and land use planning principles. This paper aims at presenting and exemplifying this new framework.

The French pipelines network

In France, the characteristics of transmission networks are

• natural pas : 36 500 km long, 30 years old (average),

• crude oil and oil products : 9 900 km long, 44 years old (average),

• other chemical substances : 3 800 km long, 29 years old (average), miscellaneous substances (ethylene, oxygen, nitrogen, hydrogen ...)•

A new risk assessment and management method

Every existing pipeline in France shall be subject to a safety study, to be completed before the 15 th of September, 2009. This study has to comply with the 2006 régulation principles: a guidance document has been developed for that purpose by the French Oil and Chemical Companies Group for Safety Studies (GESIP). The method (typical semi-quantitative risk analysis) is divided into several steps, as described in Figure 1. Steps 1 to 4 lead to risk assessment: they are detailed in the next chapter, while risk control process is explained in chapter 5.

Risk assessment: a semi-quantitative analysis with harmonized criteria

Steps 1 to 3: Qualitative Analysis

Step 1 : Description Pipeline route and its environment are described in order to collect useful éléments for further analysis, such as external hazards, human and natural targets in case of an accident.

Step 2: Hazard identification Hazard identification is mainly based on past accident analyses:

• Company internai database (if expérience is significant),

• National or international databases, such as -The European Gas pipeline Incident data Group (EGIG), -the oil companies' association for environment, health and safety in refining and distribution (CONCAWE). Some severe accidents are reminded in table 2.

Conséquences

Bridle leaks

Flange leaks

Bridle leaks

Leaks

Détection measures

Instrumentation alarm

Instrumentation alarm

Instrumentation alarm

Periodic surveillance

Risk-reducing measures

Drying / Hygrométrie controls during maintenance activities

Filtration / Spécification check

Pump automatic shutdown

Valve emergency shutdown

Step 3: Critical events

Hazard identification (step 2) leads to the définition of critical events. Main critical events for current route are losses of containment (or leaks). GESIP guidance document defines three breach sizes:

• small (up to 12 mm diameter), mainly caused by construction or material defect, corrosion, érosion, lightning boit...,

• médium (up to 70 mm diameter), mainly caused by third party excavation works,

• rupture (line section), mainly caused by ground movements and third party excavation works (only for gaseous substances under pressure).

Thèse leaks can be followed by several dangerous phenomena, to be detailed in the safety study. The main phenomena are:

• pollution (for polluting liquids such as oil),

• cloud explosion, jet fire or pool fire in case of ignition (for flammable substances),

• toxic cloud (for toxic substances).

4.2

Step 4: Quantitative Analysis (risk level) Qualitative analysis results are used to define the dangerous phenomena. Quantitative analysis leads to characterize each dangerous phenomenon (from each leak), on each point of pipeline route, according to three quantitative criteria: intensity, probability and gravity. In this paragraph ail non-referenced data corne from GESIP guidance document.

Intensity

Intensity is defined by three distances (in meters). Each distance is the nearest distance from the pipeline where référence effects can be observed on population, in case of fire, explosion or toxic release (cf figure 2).

Nota: Référence effects thresholds on human beings are defined by régulation:

• SLE (Significantly Lethal Effects or 5% lethality) -distance D3 ;

• FLE (First Lethal Effects or 1 % lethality)distance D2 ;

• IRE (Irréversible Effects) -distance D1.

People can be supposed to escape, after a reaction time of3 seconds, at the average speed of2.5 meters per second, if operator can prove lack ofphysical obstacle.

Figure 2: Effect distances for one phenomenon (iejet fire after a small leak) Thèse distances are most often calculated by using numerical simulation models of hazardous phenomena. GESIP guidance document contains a table where generic distances for vertical jet fires from gas pipelines are given. If a leak can cause différent phenomena (fire, toxic cloud, overpressure), the worst (with the biggest effect distances) is chosen for the following analysis.

Gravity

For one leak (i.e. médium leak), gravity is defined in each point of the pipeline as the number of people exposed to leak effects. Population has to be counted in effect circles

• centered in this point (assumed to be the release point),

• with a radius equal to distances D3 (Significantly Lethal Effects or SLE), respectively D2 (First Lethal Effects or FLE). Irréversible effects (IRE) are not used hère. Some rules are given for this opération, as for examples consider an average of 2,5 person in houses, the maximal capacity in public buildings, 0,4 person per km of road and for 100 vehicles per day, 10 persons per 10* m 2 for open fields ...

Probability

In this context probability is defined as the probability (per year) that a point M in the vicinity of the pipeline can be exposed to an intensity above a given effect level. Probability is calculated for each référence effect level (respectively SLE and FLE) and for each type of leak which can happen on any point of the pipeline, as follows:

P(M) = F, eak X Pignition X L X Ii(E C Mi X P RFi ) X C X P pres (1 )
where (2) The length L is maximal (L max = 2D) when M is on the pipeline. Figure 3: Calculation of effect length L. Some parameters in équation (1) are deducted from databases analyses:

P(M) = Probability (point M) Fieak = Generic
• F/eafr is observed between 1970 to 1990. It is estimated between 0.1 and 8 (1O 4 .km.year)" 1 for natural gas and oil pipelines,

• Pignition (if applicable) is estimated between 0,02 and 0,30 (dépendant on substance and breach size), • P RFi : for instance 80% of natural gas pipeline ruptures are caused by third party excavation works, and 20% by ground movements.

ECMI is the risk réduction factor induced by the risk-reducing measure, i.e. its PFD (Probability of Failure on Demand). C characterises the environment: as an example, suburban areas (where urbanization is growing) will more likely be submitted to excavation works than open country. E CMi and C are given in GESIP guidance document (cf tables 4 and 5). P pres is equal to 1 in first approximation, but can also be detailed (day or night, empty orfull stadium ...)•

Possible simplification of step 4

In order to simplify risk assessment:

• The pipeline can be divided in homogeneous segments, where intensity and probability are assumed to be uniform. • Probability inside an effect circle can be assumed to be equal to the maximal one, i.e.

if point M is on the pipeline and L = 2D. Nevertheless gravity must be calculated or estimated in each point.

Risk control (step 5): better protecting exposed population and limit its growth

Step 5 must be conducted ail along the pipeline route.

Cumulated probability

Results of previous step can be summarized as follows (cf table 6):

G3 r

In table 6, probability to reach a point is distributed between the three breach sizes. Risk control process is based on "cumulated probability" CP, which is calculated by taking into account ail leaks. Indeed, if d is the distance between pipeline and human targets:

• If d < D2 S : people can be simultaneously impacted by ail the leaks, so CP2 S = P2 S + P2 m + P2 r (3) • If d < D2 m : people can be simultaneously impacted by médium leak and rupture, so CP2 m = P2 m + P2 r (4) • If d < D2 r : people can be impacted only by rupture, so CP2 r = P2 r (5) The same calculation is done for Significantly Lethal Effects (by replacing 2 with 3 in équations (3) (4) and (5).

Risk matrices

Several couples [Probability , Gravity] are then positioned in two risk matrices (cf table 7):

• [ CP2 S , G2 S ], [ CP2 m , G2 m ] and [ CP2 r , G2 r ] are placed according to the first column gravity classes (FLE), • [ CP3 S , G3 S ], [ CP3 m , G3 m ] and [ CP3 r , G3 r ] are placed according to the second column gravity classes (SLE).

Risk control process for existing exposed population

Use of risk matrices requires estimation of pipeline safety factor and location category:

• Safety factor is the ratio between internai stress due to Maximum Allowable Operating Pressure (MAOP) and elastic limit of wall material. Risk is maximal when this factor is equal to 1. The lower MAOP is, the lower this factor is and pipeline opération is safer ; Once existing exposed population had been protected as shown on figure 4, operator has to follow its évolution ail along the pipeline route. For that purpose a Géographie Information System is required for long pipelines, and every five years the safety study is revised.

If exposed population decreases, nothing is required.

If it increases until location category is modified, operator has to refer to the process on figure 4 and take appropriate measures if necessary, Construction or extension of new spécifie buildings (public and very high buildings, nuclear facilities) is not allowed in effect distances (SLE or FLE) of the small leak in ail cases, and in effect distances of other leaks if their probability exceeds 10" 6 per year.

Conclusion

Since 2006 ail existing hazardous onshore pipelines in France hâve been subjected to a complète safety analysis, according to harmonized criteria. Use of risk matrices leads to an homogeneous level of risk exposure ail along the pipeline route. If population increases in the vicinity of the pipeline, operator has to take risk-reducing measures until acceptable risk level is reached. Construction or extension of spécifie buildings (public buildings, very high buildings and nuclear facilities) is not allowed in effect distances of the small leak in ail cases, and in effect distances of other leaks if their probability exceeds 10" 6 per year. New pipelines (i.e. commissioned after the 15 th of September, 2006) are also subjected to the same safety analysis, with some spécifie requirements:

• Safety factor has to comply with location catégories,

• AH accidents must be positioned in white zones of risk matrices,

• Pipeline route must avoid existing spécifie buildings (no such buildings in effect distances of référence leak). The method gives a harmonized framework for risk management around hazardous pipelines in France. However it does not solve ail safety issues about pipelines, in particular ageing of existing networks. Taylor & Francis Group, London, 2006, pp.1973-1981. ISBN 0-415-41620-5

Références

Figure 1 :

 1 Figure 1: Framework of pipeline safety study (source: GESIP guidance document)Steps 1 to 4 lead to risk assessment: they are detailed in the next chapter, while risk control process is explained in chapter 5.

  frequency of the given leak Ignition probability (only for flammable substances) Effect length Each risk factor leading to the given leak Efficacy of each risk-reducing measure against the i risk factor Part of the i risk factor in the given leak Corrective factor dépendant on pipeline environment Ppres = Présence rate ofpeople in the vicinity L is the resuit of géométrie calculation (cf figure 3). leak and effect) d: distance between point M and pipeline L: effect length ie length of the section from where the given phenomenon can reach M with an effect à E L = 2x(D 2 -d 2 ) 1/2

Figure 4 :

 4 Figure 4: Risk control process for existing exposed population

Table 4 :

 4 Examples of recommended values forE CM i

Risk factor: third party excavation works Risk-reducing Measure

			Risk factor: corrosion
		EcMi	Risk-reducing Measure	EcMi
	Concrète sleeves + warning tape	0,01	Cathodic protection	0,01
	Reinforced marking of pipeline	0,3	Internai inspection (robot)	0,01
	Route surveillance (n times per month)	1/n	Scraper	0,3
	Periodic information of land owners	0,3 to 0,8	/	/
	Thèse values can be used if measures comply with GESIP r
	Table 5: Recommended values for C (risk factor is third part_
	Pipeline environment
	Open country
	Car park
	No ground movements

Table 6 :

 6 Results ofstep 4

	Leak	Small
	Effect distances
	(IRE / FLE / SLE)
	Probability
	Gravity

Table 7 :

 7 Risk matrices (source: GESIP guidance document)

	Gravity ( FLE	persons) SLE	5.10'	10*		Probability (year 1 ) 5.10* 10 D	10^	10 J
	>3000	>300	*	*
	1000< <3000	100< <300	*	*	*
	300< <1000	30< <100	*	*	*	*
	100< <300	10< <30
	10< <100	1< <10
	<10	<1
	* Spécifie building (public buildings, very high buildings and nuclear facilities)

•

  Location catégories are defined by 2006 régulation, it dépends on several criteria, such as substance hazards or population density in D3 r effect circle. For each location category a maximal value of the safety factor is given.Once safety factor and location category are defined, matrices are used to assess risk acceptabilité, as shown on figure 4.

	tion ca			Nota: If a spécifie
	Safety factor £			building is placed in a zone with * in
	YES	NO		matrices, at least
				one risk-reducing
	AH accidents in white or grey	Ail accidents in white zones	measure is
	zones of risk matrices ?		of risk matrices?	required.
	Probability réduction (factor E CMj ) cN O No more risk-reducing measures required required More risk-reducing measures	YES NO	Public buildings are considered as far as their capacity is -more than 100 persons for SLE, -more than 300 persons for FLE.

  Arrêté du 04 août 2006 portant règlement de la sécurité des canalisations de transport de gaz combustibles, d'hydrocarbures liquides ou liquéfiés et de produits chimiques Circulaire n°DARQSI/BSEI-06-254 du 04 août 2006 relative au porter à connaissance à fournir dans le cadre de l'établissement des documents d'urbanisme en matière de canalisations de transport de matières dangereuses (gaz combustibles, hydrocarbures liquides ou liquéfiés, produits chimiques) GESIP, Rapport n°2008/01, Guide Méthodologique pour la réalisation d'une étude de sécurité concernant une canalisation de transport (hydrocarbures liquides ou liquéfiés, gaz combustibles et produits chimiques), décembre 2008, reconnu par la décision n°DGPR/BSEI-09-001 du 05 janvier 2009 GESIP, Rapport n°2008/02, Canalisations de transport : dispositions compensatoires, décembre 2008, reconnu par la décision n°DGPR/BSEI-09-105 du 02 juillet 2009 EGIG, 7 th EGIG-report 1970-2007, report n°08.TV-B.0502, December2008 CONCAWE, Western European cross-countries oil pipelines 30-years performance statistics, report n° 1/02, February2002 BOUISSOU C, DESCOURRIERE S., DECHY N. Control of major-accident hazards involving land transmission pipelines. Loss Prévention Symposium, June 2004, Praha. DEBRAY B., RODRIGUES N., SALVI O. Evolution of the risk assessment and land use planning rules around industrial SEVESO II sites in France: A parallel with the ARAMIS methodology. In: Safety and Reliability for Managing Risk. Ed. Guedes Soares & Zio,


Canne Rivière

Guy Marlair

Alexis Vignes

Learning of the rootfactors of incidents potentially impacting the biofuel supply chains from some 100 significant cases 13 th International Symposium on Loss Prévention

A biofuel is most often defined as a liquid or gaseous fuel used for transport purposes that can be produced from biomass substrates or bioresources. There are numerous potential supply chains for the production of biofuels, depending on feedstock, conventional or advanced processes, and final end use. AH stakeholders involved in the promotion of more sustainable biofuels highly welcomed the area of industrialization of so called 2 nd génération type of biofuels. However existing facilities producing 1 st génération biofuels, i.e. bioethanol from sugar based or cereal plants and biodiesel from vegetable oils and fats, hâve sharply increased in number in récent years, allowing for a reasonable survey of safety issues from incidents.

, more globally devoted to the analysis of safety-related issues with the main goal of appraising degree of risk contrai. Further survey of industrial and sanitary risks pertaining to biofuels are currently performed through contributions to two collaborative research initiatives. First, one is BIOMAP (Environmental and socio-technicoeconomic analysis and risks assessments of bioenergy pathways: Practical applications to several case studies) coordinated by IFP. The second, named ALFABIRD (Alternative Fuels and Biofuels for Aircraft Development) is piloted by the European Virtual Institute for Integrated Risk management. They are respectively funded by the French National Research Agency and the European Commission. A common tool for the performance of our contribution in those R&D projects is an incidents database, containing about 100 incident records which is the resource of this présentation.

In this paper, we propose to présent the methodology employed to build this database and its contribution for the research programs aforementioned. The implementation of this incident database allows deriving appropriate information on safety issues pertaining to biofuel supply chains. In order to identify the root factors of incidents potentially impacting the biofuel supply chains, a statistical analysis (univariate and multivariate analysis) was applied on the database. This analysis is illustrated with several actual cases of accidents.

Introduction

Promoting the use of biofuels or liquid fuels produced from biomass is often considered as a key strategy to tackie climate change by decreasing greenhouse gas émissions in the sector of transport. The use of 'sustainable' biofuels also responds to other issues such as increasing energy security of supply, facing progressive raréfaction of petrol and relating increasing fossil fuel priées or contributing to new rural economy. Literature accounts numbers of papers concerning évaluation of environmental [START_REF] Bôrjesson | Goocf or bad bioethanol from a greenhouse gas perspective -What détermines this?[END_REF], energetic political, and économie impacts [Hill et al., 2006] of biofuels. By contrast, very limited scientific studies hâve so far addressed safety aspects of biofuel pathways (apart from material compatibility issues at end use stage) [START_REF] Marlair | Booming industry of biofuels for transport: is Tire safety of concern ?[END_REF]. Existing facilities producing first génération biofuels hâve sharply increased in number in récent years, reaching several hundred at least, and allowing for a reasonable survey of safety issues from incidents. INERIS (Institut National de l'Environnement Industriel et des Risques, France) initiated in 2006 a research work devoted to the overall analysis of safety-related issues of biofuels, including examination of past accidents. Learning on accidents required the preliminary implementation of an incidents database. The scope of this database was to collect ail sorts of incidents (explosions, fires, spills, derailments, road accidents ...) which occurred somewhere in the life cycle of biofuel production. This incidents database serves the goals of several research programs in which INERIS is involved. Thèse programs are presented in section 2. Section 3 présents the incidents database and the methodology used to set it up. Section 4 of this contribution provides a statistical analysis of the root factors of incidents potentially impacting the biofuel supply chains, based on the use of the R software. Conclusions and perspectives of thèse works are given in section 5.

Research programs driving the examination of safety issues and relating contributions by INERIS

The implementation, updating and uses of a Biofuel incidents database are work packages serving 3 collaborative research programs in which INERIS is involved: BIOSAFUEL®, BIOMAP and ALFA-BIRD. The first one, BIOSAFUEL® [START_REF] Marlair | Automotive biofuels: the INERIS project "BIOSAFUEL[END_REF], initiated by INERIS in 2006 with funds coming from the Ministry of Ecology, is more globally devoted to the analysis of safety-related issues that may impact sustainability of the biofuel industry.

The main goal was the identification of hazards and the appraisal of the degree of risk contrai of existing and shortly coming biofuels, from a life cycle perspective. The most outstanding deliverable of this project is a tool, named BIOSAFUEL®, allowing semi-quantitative évaluation and ranking of risks pertaining to 1 st génération biofuel supply chains [START_REF] Rivière | BIOSAFUEL®, a pre-diagnosis tool of risks pertaining to biofuels chains[END_REF]. The incidents database can be used to validate products hazards, identify typical accident scénario and rank risk significance. The second project, BIOMAP (Environmental and socio-technico-economic analysis and risks assessments of bioenergy pathways: Practical applications to several case studies) coordinated by IFP (Institut Français du Pétrole) and funded by the French National Research Agency, aims to further test and consolidate a multicriteria methodology implemented in the framework of a previous project ANABIO [START_REF] Prieur | Environmental & socio-technico-economic ANAlysis of BlOenergy pathways -Guidelines for bioenergy évaluation[END_REF], allowing for studying and comparing energy chains ex biomass, in terms of sustainability criteria. Indeed, the objective of the ANABIO project was to define a multi-criteria methodology to assess the various energy production chains from biomass, taking into account environmental, économie, societal, technological and safety criteria. The contribution of INERIS incidents database to BIOMAP deals more especially with the improvement of the methodology in terms of defining appropriate risk criteria and relating évaluation tools and in terms of ranking safety criteria.

The third project, ALFABIRD (Alternative Fuels and Biofuels for Aircraft Development) [START_REF] Marlair | Un nouveau challenge : offrir une alternative au kérosène[END_REF]] is more prospective. Piloted by the European Virtual Institute for Integrated Risk management (Eu-Vri) and Airbus, it is an EU funded Research project addressing future needs to think about potential alternatives to kérosène, like XtL. The purpose of ALFABIRD is to study and compare a sélection of alternative fuels (promoting among others biobased compounds) that could be used in blending with kérosène for aviation application (drop-in solutions). The implementation of the incidents database allows deriving appropriate information on safety issues pertaining to bio-based fuels supply chains.

Incidents database : procédure of implementation and lay-out

Incidents records considered for input in INERIS incidents database are those which unambiguously relate to the biofuel supply chains wherever they hâve occurred within the biofuel life cycle, from crop production to end-use. Thus, this database includes fire and explosion scénarios in stationary facilities, equipment failures (associated or not with missile effects), accidentai steam release from ducts or containers, leakage in terrestrial transport (road and rail) associated or not with fires and explosions, following derailment, tank truck turnovers or crashes, and ail sorts of environment contamination scénarios... Information about incidents entered in the database were collected from regular survey of specialised literature, extracted from large accident database such as the BARPI one (Bureau d'Analyse des Risques et Pollutions Industrielles) in France. They were also identified from various web sites. Sometimes data were obtained from networking activities with colleagues working in agro-industries. Updating from regular survey of mentioned sources of information was an inhérent part of the process of accident data collection.

The overall procédure of data collection thus encompasses: a) Identification of new occurrences, b) Hard-copy and electronic archiving of relating information (papers, videos, pictures if available, press releases, early reporting...), c) Basic first order analysis of the incident record in order to identify supposed causes and séquences of events leading to the scénario. Conceptualisation of the database, by describing each incident according to a list of predefined variables for the purpose of statistical analysis:

-date and localisation of incident -plant data: name of plant, production capacity of plant, raw materials employed, particular condition of plant at moment of incident (maintenance, works...), year of plant opening -assumed causes of incident: products involved, material or equipment implied, initiator event, localisation of incident -known conséquences of incident: number of fatalities of injured persons, of material damage, environmental damage, intervention features (évacuation of neighbours or not), etc. Currently, the database lists 112 incidents that occurred between 2000 and July 2009. Year 2008 alone, 31 accidents were recorded.

As the database was supplied with information from websites and literature, it is likely that information about some incidents was not spread due to the modesty of conséquences in some cases or due to potential barriers of political, linguistic or technical nature. It could lead to some bias in the data analysis but it should be reminded that thèse data essentially do not aim at making an exhaustive inventory of the accidents and essentially serves the objective of appropriately describing the main typologies of incidents.

Statistical analysis of database

In order to analysis the incidents database and identify the main typologies of incidents pertaining to biofuel pathways, we performed a Multiple Correspondence Analysis (MCA) followed by an ascendant hierarchical classification (AHC). AH relating statistical analysis procédures were carried out making using the R software1 .

Methodology

Multiple Correspondence Analysis (MCA)

Our incident database includes categorical variables. MCA is a factor analysis method particularly suitable for the analysis of such variables. This method transfers a set of categorical variables into a small number of orthogonal variables called principal components, which optimally reflect primary data for statistical analysis purposes. MCA acts hère as a useful technique for multidimensional analysis of categorical data. Moreover, MCA is a pre-processing step for classification purposes. Indeed, hierarchical classification requires quantitative values, and MCA provides quantitative values (coordinate values of incidents in the System of axes defined by the principal components) derived from categorical values of database.

Ascendant Hierarchical Classification (AHC)

Ascendant Hierarchical Classification is an itérative process which principle lies as follows: the algorithm starts with as many clusters as recorded data and progressively sort the data by building up a tree from successive merges of the two nearest clusters. The AHC procédure is often represented by a two dimensional diagram known as a dendrogram which illustrâtes the classification obtained at each successive stage of the analysis. The dendrogram is then eut off -at hand of the user-at a chosen level of clustering to obtain the final classification retained as more appropriate. In our study, the AHC process was performed by use of the AGNES (Agglomerative Nesting) [Kaufman et al. 1990] method.

Results

To implement the MCA followed by the AHC, 8 variables, called "active variables", describing incidents hâve been carefully chosen. Thèse variables deal in our study with gênerai information about each incident, supposed causes and circumstances of the event and conséquences in terms of human, material and environmental losses. The results of the HAC are displayed as a graphical représentation or dendrogram. (see figure 1): Cutting this tree at various levels sorts the relating data in various partitions. The lower this dendrogram is eut, the more signifieant is the number of clusters and the less numerous are incidents in each cluster. Inversely, the higherthis dendrogram is eut, the less signifieant is the number of clusters and the more numerous are incidents in each cluster. The more reasonable clustering in terms of overall significance, according to our expertise, was achieved when the AHC ended up with 5 clusters (eut off line is the red line shown on Figure 1). Figure 2 is a global représentation of thèse clusters in the factor map:

ci

CM E Q -3 -1 Dim1 (3.126%)
F/gure 2: Bio fuel incidents clustering in factorial map Table 2 gives a technical description of each cluster (typology, number of incidents, composition) and a practical example of incident record représentative of the cluster: 2005, West Burlington, lowa (USA): A grain dryer was the initial location of a fire in an ethanol plant. Roads around the plant were closed for about an hour. One plant worker and two firefighters were treated for minor injuries.

April 2008, Calgary, Canada: an explosion occurred and killed a man working at a newly built biodiesel plant. The worker was welding on top of a 30-foot biodiesel tank when the tank exploded. The fire continued to burn in the tank for several hours afterthe explosion. Evacuation of the workers was processed. -88% of incidents occurred during transport of materials, -The product of concern is ethanol in 92% of this cluster's incidents, -The main event is a spill of products followed or not with explosion and/or fire (86% of the cluster), -incidents resuit from train derailment (40% of cases), or tank truck turn over or crash (32% of cases) or take place on maritime/fluvial routes (12% of cases), -32% of incidents of this cluster involved environmental risk and relating 80% of database's incidents involving environmental risk are in this cluster, -84% of this cluster's incidents did not injure anybody. -No identified product implied (100 %), -Not an explosion, nor a fire or a spill event (100%).

-100% of incidents of this cluster occurred due to artisanal biofuel manufacturing at home (or in a garage), -100% of incidents involved biodiesel.

July 2008, Minnesota, USA: derailment of multiple carnages of a train carrying ethanol. The derailment caused an ethanol spill. The incident could be related to the failure of a wooden railroad bridge. No one was wounded and no évacuation was required dutring the emergency crisis management.

February, 2008, Austin, Minnesota ( USA): a man died while working at an ethanol plant under construction.

According to authorities, the man was pinned between a man-lift and a beam in the facilities. May 2008, New York, USA: a garage explosion and resulting fire were the major conséquences of a homemade biodiesel opération. The fire destroyed the garage, greatly damaged a house and another garage. Investigators found a large quantity of vegetable oil and 55-gallon drums of biofuels at the scène.

From the description of thèse 5 clusters, the following main typologies of incidents recorded in INERIS database may be developed in terms of scénarios as follows:

-Scénario séries 1. The scénario initiâtes by an explosion or/and fire in a grain dryer (overheating of equipment, self-heating of grains). This scénario mostly relates to bioethanol production supply chains.

-Scénario séries 2: The scénario essentially consists in an explosion or/and a fire starting in a tank storing a flammable product. This scénario occurs more frequently when the facilities are in maintenance phase or closed. Significant material damages follow up as a common conséquence is such a case.

-Scénario séries 3: This scénario starts with a spill of ethanol during terrestrial transport (road, rail, less often from a boat) and may be followed by an explosion or a fire event. This scénario may correlatively lead to environmental contamination. This type of incidents generally involves limited casualties. Domino effects may also arise (as fire spread to other equipment of vehicles...) -Scénario séries 4: In this séries, the scénario cornes from atypical incidents in which neither explosion / fire nor spill of hazardous product is involved.

-Scénario séries 5: This séries of incidents deals with non professional (home-made) manufacturing of biodiesel. The lack of explosion-proof equipment or other safety devices is generally the root cause in this case. Thèse incident typologies, only based on the analysis of real accidentai cases, highlight some safety issues as prominent, such as transport risk, storage risk or equipment risk. However, some cautions are needed for assessing the related risks in a more global way or for a given plant, according to local parameters. Additionally, as stated previously, some bias linked to data collection mode and performance may arise in the analysis. A better cover of incidents that may hâve occurred in South East Asia (bioethanol from a variety of crops and biodiesel ex Jatropha or ex palm oil) or in South America (sugar cane bioethanol, biodiesel ex soja...) is expected in the future.

Conclusions and perspectives

An analysis of more than 100 incidents that occurred after 2000 during biofuel production life cycle has been proposed. In orderto highlight appropriate information and to learn lessons of this database, a multiple correspondence analysis followed by a hierarchical classification of data hâve been performed. This multivariate statistical treatment enabled to identify 5 main séries of incidents typologies. Thèse typologies outline some safety issues such as: -the significance of the risk during drying of grains (scénario 1).

-the récurrent risk during storage of hazardous materials (scénario 2), such as ethanol, biodiesel or methanol, particularly during works in the facilities.

-the risk during batch transport of hazardous materials such as ethanol (scénario 3).

-the risk of artisanal biodiesel production (scénario 5). Produce biodiesel himself at home is increasingly popular, due to apparent ease of processing. However, consumers are rarely aware of hazards bound to this opération in an environment that is generally not appropriate, as recently recalled in a safety warning addressed on its web site by Health and Safety Executive in the UK [START_REF] Hse | Domestic production of biodiesel -Health and safety warning[END_REF]. This contribution concems first-generation biofuel pathways, the only operational routes of production of biofuels today. However, many facilities are in project to produce so called 2 nd génération biofuels (e.g. cellulosic bioethanol ex lignocellulosic biomass streams) and some démonstration units are already operating. Pressures and températures levels typically pertaining to some processes employed for production of 2G biofuel, such as liquéfaction or Fischer-Tropsch synthesis, are significantly higher than with 1G products, that lead to spécifie safety issues. Other features of such facilities will require due attention in terms of safety. Given the globalization of the biofuel booming industry, it would be highly désirable to implement a common incident data reporting System. This could eventually facilitate and optimize the type of analysis performed in this study, by rendering it more widely applicable and less subject to potential bias. Safety issues could then be treated more consistently, thus bringing a valuable milestone to more sustainable biofuel production world-wide.

Figure

  Figure 1: Dendrogram

Table 2 :

 2 Description of clusters and related typical examples of incidents

		Number of	Composition of cluster	"Real case" examples
		incidents
	Cluster 1	29	-57% of incidents of this cluster occurred in	September,
			a drying System and 100% of database's
			incidents occurring in a dryer are in this
			cluster,
			-89 % of incidents occurred in plants
			under normal opération conditions
			-The main event is an explosion and/or
			fire (100% of recorded incidents in this
			cluster),
			-34% of incidents of this cluster involved
			pulvérulent	product and 59% of
			database's incidents involving pulvérulent
			are in this cluster,
			-86% of incidents of this cluster occurred
			during bioethanol production life cycle.
	Cluster 2	36	-61% of incidents of this cluster started in a
			tank and 100% of database's incidents
			starting in a tank are in this cluster,
			-33% of incidents of this cluster occurred
			during	maintenance	works	and
			accordingly, 80% of database's incidents
			occurring during maintenance are in this
			cluster,
			-14% of incidents of this cluster occurred
			during closing of the plant (grouping ail
			of database's incidents occurring during
			closing of the plant),
			-The main event is an explosion and/or
			fire for 89% of incidents,
			-17% of incidents of this cluster involved
			significant material damages and 86%
			of	database's	incidents	involving
			significant material damages are in this

http://www.r-project.org/


S Bouchet

S Kasprzycki

N Lépine

J-C Morin

Evaluation of Fixed Point H 2 S Gas Detectors Intended for Use in Industrial Safety Applications

Introduction and purpose of the évaluation

H 2 S gas detectors are used by a wide variety of industrial companies for safety reasons, e.g: Oil&Gas, Chemistry, Water Treatment. The detectors are usually installée! where H 2 S can be found in ambient air in order to prevent toxic risk. The tests, requested by the French Ministry for Environment, were conducted by INERIS in partnership with Exera (an association of companies and organizations which invest in instruments, measurement, control and automation Systems). This évaluation was carried out to investigate if H 2 S gas detectors can operate efficiently under différent operating conditions on industrial sites (température, humidity, pressure, interfering species, etc.). The measurement range of the detectors that were evaluated is 0-20 ppm. The two Systems on the market -an electro-chemical System and a semi-conductor Systemwere tested. Out of fourteen apparatus, three had a semi-conductor cell and eleven had an electro-chemical cell. This paper présents the results of the évaluation that was carried out from October 2007 to April 2008 on 14 apparatus from 8 différent manufacturers according to a test protocol that was specifically defined with the partners and involved over 15 tests. AH the tests were conducted in the "detector and safety equipment" laboratory in INERIS' accidentai risks department.

Detector and safety equipment laboratory

Test protocol

The test gas was hydrogen sulphide (H 2 S) at a concentration of 12 ppm The following tests were conducted to evaluate the performance of the H 2 S gas detectors that were tested:

• Response time and alarm trigger duration (set at 5 and 10 ppm)

• Affect of calibration rate

Results

The following table provides a summary of the results. Recovery time up to 36 times higher between two apparatus.

No sensitivity drift as a resuit of this test 3.1 Unknowns during opération and during tests One apparatus was supplied broken and after-sales technicians had to visit several times to fix it. Its installation lasted a total of one month. 4 other detectors were defective during the test period, and the installation durations for some of them took up to two months.

Main lessons

The study of one of the most important parameters for a toxic gas detector, which is response time, showed a différence by a factor of 10 between the slowest machine and the quickest machine. With a test gas at 12 ppm, the response time (t 90 ) varied from 8 to 82 seconds. Another important parameter: "standby". This is an increasingly critical phenomenon. When detectors are not regularly subjected to a gas, then they go into standby mode (this can occur with detectors for ail types of toxic gas). So, for H 2 S, some detectors that had not been subjected to a gas for a month no longer responded at ail. Some, who had not been subjected to a single cloud of H 2 S for 6 months were unchanged. The study of the affect of external parameters such as température or hygrometry also showed large différences between detectors. Out of the température tests conducted between -10 and 50°C, some were affected by température, and others were not affected at ail. For example, one detector lost 50% of its response between 5 and 20°C. For humidity, the detectors were ail more or less affected by an even slight variation in relative humidity (RH) (between 0 and 50% at 20°C). And it was even worse in more severe conditions. Therefore, at 83% RH and at 35°C, the response of several detectors was divided by 5. Low hygrometry tests, quite common particularly in winter in heated premises, were also conducted. In an atmosphère with 10% RH and at 20°C for 15 days, 1 detector out of 14 lost ail its sensitivity, 1 other lost 50% and 3 others between 15 and 20%.

Statistics relating to data provided by manufacturers

Thèse statistics are only valid in the context of this évaluation, but do however highlight a gênerai tendency in the area of gas détection. The data provided by manufacturers were compared to the results of tests conducted in this évaluation. It is appropriate to mention that ail the results are significant when selecting a detector suited to its use. The statistics are provided in the table below.

56%

Data not consistent with the results

44%

Overall, only a third of the results of the tests conducted are shown in the manufacturer leaflets, and one of thèse data out of two is consistent with the results of this évaluation. Some detectors had restrictive and non-compliant spécifications, but were however effective for safety.

Conclusion

The study conducted on the hydrogen sulphide detectors provided the following main conclusions:

• Différent reactions for each detector in terms of response times, long-term stability and "stanby", response to other gases, température, etc. • AH detectors were affected by humidity and dépression.

•

Leaflets provided by manufacturers were incomplète and sometimes optimistic. Overall, out of the panel of detectors tested, the electro-chemical detectors seemed to be more effective than the semi-conductor detectors.

  (25 ppm), NO (25 ppm), nitrogen oxide (25 ppm), C 2 H 3 SH (1 ppm), CH 2 SH 3 semi-conductor detectors (A, B, C) 11 electro-chemical cells (D to N) , E:16s, F: 31 s, G: 35 s, H: 13 s, I: 8 s, J: 18 s, K: 49 s, L:19s, M: 76 s, N:58s K: unaccuraten and not linear AH others: accurate and linear D, G, H, J, N: no loss of sensitivity E, F, I, K, L M: more or less complète loss of sensitivity D: breakdown, E: affected at low température, K, M: affected AH were more or less affected by a relative humidity variation A2 and NO M: CH 2 OH, SO 2 , CO, NO F, H, J, K, N: no response (1ppm) and CS 2

  Apart from the drift test which was conducted on 1 additional apparatus, ail the other tests were conducted on the same apparatus.

	• Response curve for hydrogen sulphide
	• Long-term drift
	• Affect of température / humidity / pressure
	• Response and long-term exposure to other gases (H 2 , CO, CH 2 OH, SO 2 , NO 2 , NO)
	• Response to sulphur compounds (C 2 H 3 SH, CH 2 SH, CS 2 )
	• Low hygrometry
	• Prolonged use with test gas
	• High level of hydrogen sulphide

Table 1 :

 1 Summary of resultsParameters evaluated

	Power Off storage
	Response time
	(t 90 , Response time)
	Response curve
	Test gas: 2, 8,12 and 18
	ppm
	Long-term drift and
	"standby"
	Continuous opération for 6
	months in ambient air,
	followed by exposure to test
	gas
	Température
	(from-10to50°C)
	Humidity
	0 and 50% RH at 20°C
	83% RH at 35°C
	Low hygrometry
	(10%RH-20°Cfor15
	days)
	Pressure
	Tests conducted at 80 and
	100 kPa in air and the test
	gas
	Other gas response
	H 2 (50 ppm), CO (50 ppm),
	CH 2 OH (200 ppm), NO 2

Table 2 :

 2 Statistics for manufacturer data / test data

	Data provided by the	Data consistent with the
	manufacturer compared with	results
	the tests conducted
	34%