FLUIDYN-PANAIR is a self-contained fully 3-D Computational Fluid Dynamics (CFD) software package designed to simulate atmospheric pollutant dispersion over complex topography of industrial and urban areas. It is a dedicated module of the software family Fluidyn-PANACHE and simulates general air quality in various weather conditions, especially for low wind velocities and by including vertical air flow due to natural convection in the urban canopy. Beyond prediction of high pollution exceedency periods, this software helps in finding optimal responses to them. Thus users can micromanage topography & traffic or industrial parameters to mitigate the effect on air quality. Non-homogenous meteorology over a complex terrain is as easily managed as over a flat terrain. FLUIDYN–PANAIR has been validated in European & East American regions and is used often for the simulation of the air quality when other general purpose CFD software besides of course Gaussian and integral models fail because of terrain complexity or source variability. It can evaluate simultaneous contribution of multiple kinds of sources to the air pollution, including the vehicles, the heat emissions from industries and urban areas. The ozone formation and its regional transport is simulated by chemical reaction mechanisms. FLUIDYN–PANAIR was developed in collaboration with ADEME (French Ministry and Environmental Agency). It was later officially recognised by the US EPA (US Environmental Protection Agency, ref. Federal Register 8-12-96, Vol. 61 N° 156, Pages 41884-41885) and in the book “How to Obtain Air Quality Permits’ of Roger Greenway, published in accordance with US EPA Regulations, Chapter 8: US EPA Recommended Models, Page 108. A number of comparisons and publications have further strengthened the validity and relevance of Fluidyn PANACHE simulations. FLUIDYN has further participated in numerous Conferences and Workshops to validate and improve the performances of FLUIDYN-PANACHE. Compared to Gaussian and Integral models, for similar input data quality, FLUIDYN-PANACHE family gives highly precise simulation results in similar computer time. This is possible today as computational power of PC’s, even laptops, has gone up sharply. Fluidyn-PANAIR simulation accounts for effects of all topographical features: complex urban buildings layout, forests, water bodies, industrial heat sources, etc. In order to model atmospheric air flow, FLUIDYN-PANAIR uses a deterministic 3D resolution of the fluid dynamics Euler equations. In this regard, all the phenomena and parameters that could influence the transport / diffusion of pollutants in the air are taken into account:

• 3D complex topography with land cover (urban areas, forests, fields, water bodies).

• Meteorological conditions (fixed or variable) and Atmospheric turbulence. • Pollutant specific characteristics and properties

It has the following integrated modules (autonomous software): • FLUIDYN-PANROAD: Road-traffic impact on air quality • FLUIDYN-PANEIA: Industrial sources impact on air quality. They are based on the wind & pollutants emissions calculated by: • FLUIDYN–PANWIND: Air flow over a complex topography • FLUIDYN–PANTRAFFIC: Traffic emissions factors evaluation Supplementary modules: • FLUIDYN-PANREG: Regional air quality • FLUIDYN-PANAIRPORT: Air quality near airports.

Internal Ventilation and Air Quality software: • FLUIDYN–VENTCLIM: Ventilation of industrial premises, offices, houses • FLUIDYN–VENTUNNEL: Air quality in underground rail, road and river tunnels • FLUIDYN–VENTMINE: Air flow in Underground mine network of shafts/galleries

GENERAL DESCRIPTION

FLUIDYN-PANROAD: ROAD TRAFFIC IMPACT ON AIR QUALITY

FLUIDYN-PANROAD is part of FLUIDYN-PANAIR, designed to simulate the dispersion of pollutants emission by vehicles on roads and highways. Designed for highway planners and environmental engineers, FLUIDYN-PANROAD assesses the impact of modifications in existing infrastructures and the effects of pollution for upcoming projects. FLUIDYN-PANROAD models:

• Impact of any changes in the infrastructure layout (number of lanes, traffic lights, etc); modifications in the existing roads (detours, construction of crossroads, additional roads, speed limitation…);

• Pollution impact due to noise mitigation barriers; • Pollution dispersion from and around tunnels portals.

INTEGRATED FEATURES

Easy User interface for design/ environmental engineers for simulating dispersion of pollutants from vehicles on highways and secondary roads.

Models combined effect of complex topography: obstacles e.g. noise barriers, buildings, vegetation, water bodies, and complex terrain (tunnels, bridges, road trenches)

Calculates by specialized modules turbulent wind field in 3D as well as traffic emissions

Calculates the Pollution index for general population and effect on sensitive population as hospitals, schools etc.

Rapid and advanced numerical techniques to simulate dispersion with 3 CFD, or complete wind-rose. Accurate calculation of percentiles and exceedencies.

The results of the calculations are displayed on a background map in the form of colour concentration contours, concentration profiles on traffic routes, wind fields etc.… The concentration data in air and in the deposits provide the quantification elements of health effects due to inhalation or ingestion. In addition, it can be coupled with FLUIDYN-VENTUNNEL to study the pollutant dispersion inside tunnels by taking into account specific phenomena (fires, ventilation with jet fans, air and smoke extraction, traffic piston…).

MAIN INTEGRATED MODULES

FLUIDYN-PANEIA: INDUSTRIAL IMPACT ON AIR QUALITY

FLUIDYN-PANEIA models the atmospheric dispersion of industrial emissions in the air, released from point or continuous sources. FLUIDYN-PANEIA is designed for environmental engineers & decision makers to confirm or ensure that industrial sites comply with national air quality regulations. APPLICATIONS • Flow and turbulence around buildings • Effects caused by changes in industrial sites layout • 3D Dispersion by Gaussian, Lagrangian and Euler methods • Wind rose calculations from hourly data • Droplets and particles transportation • Odours: dispersion • Efficiency & proper sitting of wind & pollution

monitors • Visibility of plume • Quantification elements for health studies The Gaussian model ISCST (industrial source complex short term) developed by the US EPA (US Environmental Protection Agency) solving probabilistic equations is available in FLUIDYN -PANEIA. Like all other Gaussian models, this ISCST model is relevant only for simple sites.

In-depth comparisons of techniques provided by other non-CFD based codes with advantages and drawbacks are provided in the section Comparison of Techniques.

FLUIDYN-PANWIND: WIND FIELD CALCULATIONS

The FLUIDYN–PANWIND model is the meteorological pre-processor which calculates the wind field on an flat or undulating terrain in urban and peri- urban zone by taking into account the influence of height. The effect of atmospheric turbulence is one of the elements aiding the software to provide good results. All ground occupation parameters influence the wind fields in particular close to the ground : the local roughness parameter calculated for urban zones or quarters, industrial areas, fields and forests as well as water bodies influence the wind profile. FLUIDYN–PANWIND can take into account, depending on their availability, the stack emissions from neighbouring industries, the emissions due to urban heating or from any other significant heat or momentum source for predicting air quality. After having interpolated the wind field from the weather station data, the wind field is refined by the introduction of atmospheric turbulence effects. By using the similarity theory of Monin-Obukhov, the atmospheric stability can be estimated from a heat exchange chart between ground & the atmosphere. This theory eventually serves to mitigate the partial loss of vertical weather data (mast or balloon soundings). The final step modifies the flow field in the domain of calculation, solving for CFD, Navier-Stokes (momentum, mass, enthalpie or energy equations) for steady or transient situations.

FLUIDYN- PANTRAFFIC: TRAFFIC EMISSION EVALUATION

FLUIDYN – PANTRAFFIC evaluates the emissions of gaseous pollutants (NOx, CO, HC, etc.) or particulate matter (PM10, Pb, etc.) emitted by vehicles starting from the available traffic data on different highways and roads, for a standard fleet of vehicles. FLUIDYN – PANTRAFFIC conforms to the directives laid down by the COPERT III European program. The emissions from road traffic are taken into account by FLUIDYN – PANTRAFFIC but other data obtained from any external source (other traffic emission codes, measurements..) for each road segment can also be exploited for the dispersion calculation. type of roads and traffic: urban, rural, highways, yearly, hourly average or peak hour topography and ambient conditions: steep slopes, temperatures percentage of heavy vehicles average velocity of the traffic accounting for crossroads, signals, traffic jams, stop signs

Location and numerical terrain (GIS import)

Embedded and unstructured mesh for accurate modelling

Wind Speed and Turbulence

Concentration contours of Urban scale simulations

PANAIR SIMULATIONS- ILLUSTRATIONS

VALIDATION CASES COMPLETED BY FLUIDYN The validation cases were done on the following chemical species: sulphur hexafluoride (SF6), liquefied natural gas (LNG), Ammonia (NH3), nitrogen dioxide (NO2), carbon monoxide (CO), hydrofluoric acid (HF). The validation of FLUIDYN Panache has been done on light gases as well as on heavy (or cryogenic) gases

Table: FLUIDYN Panache Validation Case (industrial releases)

Experimental Studies Pollutants MOL Workshop : Lillestrom Sulphur Hexafluoride (SF6)

MOL Workshop : Kincaid Sulphur Hexafluoride (SF6) MOL Workshop : Copenhagen Sulphur Hexafluoride (SF6)

BURRO Series Liquefied Natural Gas Desert Tortoise Series Ammonia (NH3)

Eagle Series Nitrogen Dioxide (NO2) Goldfish Series Hydrofluoric Acid (HF)

The first series of Lillestrom experimental data (measurements done to validate the Gaussian models and as a result are closer to the optimal conditions of Gaussian models) is given here. This is a SF6 dispersion. The comparison with the experimental results is given below.

SF6 concentration (µg/m3) Monitor Distance (km) Experimental Panache

Error

M1 0.16 7.6 7.41 2.5% M2 0.49 4.8 5.54 15.4% M3 0.81 3.7 3.61 2.69%

The validation tests show that the results obtained with FLUIDYN-PANACHE are quite satisfactory when compared to the experimental results. The results are better than those given by the Gaussian software even under conditions advantageous to Gaussian simulations. Contrary to Gaussian simulations, with varying degrees of performance, the precision of 3D software is always the same irrespective of the emission configuration.

Table: FLUIDYN Panache Validation Case (Road or Urban air quality cases)

Experimental Studies

Pollutants

HIGHWAY A1 (local scale)

Carbon Monoxide (CO)

Lyon City and suburbs (urban/meso-scale range)

Nox, SO2, C6H6,Pm…

The validation manual is available on request. Examples are given below for the Road and Urban air quality cases.

VALIDATION for PANACHE FAMILY CODES

LYON City Transient (36h pollution episode with in situ data 12/12/98 case)

NOX emissions due to traffic pollution at two monitor points

Highway A1: (local scale dispersion)

Highway model and winds (1h) and Comparisons with in situ monitor for CO (hourly basis)

Numerical model for large scale simulation (road network, urban areas)

In situ measurement emission patterns at 12 and

18 h

Wind field and Nox concentration at ground

level

M2 - GARIBALDI: NOx

0

20

40

60

80

100

120

140

0 5 10 15 20 25 30

Time in Hrs.

Con

c. in

mic

ro g

m/c

umMonitoredPredictedM4 - BERTHELOT: NOx

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25 30

Time in Hrs.

Con

c. in

mic

ro g

m/c

um

MonitoredPredicted

The software FLUIDYN-PANACHE has been certified by the USEPA (Environmental Protection Agency, equivalent to the Environment Ministry) in 1996. To certify PANACHE, EPA have tested and validated the software on a test bench and in comparison with its own software ISCST3. Goldwire, H.C. Jr, T.G. McRae, G.W. Johnson, D.L. Hipple, R.P. Koopman, J.W. McClure, L.K. Morris and R.T. Cederhall, 1985. Desert Tortoise Series Data Report: 1983 Pressurized Ammonia Spills. UCID 20562, Lawrence Livermore National Laboratory; Livermore, California. Gryning, S.E. and E. Lyck, 1984. Atmospheric Dispersion from Elevated Sources in an Urban Area: Comparison Between Tracer Experiments and Model Calculations. J. of Climate and Appl. Meteor., 23: 651-660. McQuaid, J. (ed), 1985. Heavy Gas Dispersion Trials at Thorney Island. Proc. of a Symposium held at the University of Sheffield, Great Britain Green, S.R., 1992. Modeling Turbulent Air Flow in a Stand of Widely Spaced Trees, The PHOENICS Journal of Computational Fluid Dynamics and Its Applications, 5: 294-312. Pavitskiy, N.Y., A.A. Yakuskin and S.V. Zhubrin, 1993. Vehicular Exhaust Dispersion Around Group of Buildings. The PHOENICS Journal of Computational Fluid Dynamics and Its Applications, 6: 270-285. Tripathi, S., 1994. Evaluation of FLUIDYN-PANACHE on Heavy Gas Dispersion Test Case. Seminar on Evaluation of Models of Heavy Gas Dispersion, Organized by European Commission; Mol, Belgium. Havens, J., T. Spicer, H. Walker and T. Williams, 1995. Validation of Mathematical Models Using Wind-Tunnel Data Sets for Dense Gas Dispersion in the Presence of Obstacles. University of Arkansas, 8th International Symposium-Loss Prevention and Safety Promotion in the Process Industries; Antwerp, Belgium. Rashmi S.Patil IIT Mumbai & S.Gupta, India Performance Evaluation of CFD Model PANAIR for Air Pollution Dispersion of Industrial Stack Emissions, EPA Golden Jubilee Symposium on Air Quality Modelling and its Applications, Durham, NC , 2005 Richard Hill, Alistair Arnott, Westlakes Scientific Consultancy Ltd., Tim Parker, British Nuclear Group, Paul Hayden, Tom Lawton and Alan Robins, Environmental Flow Research Centre, University of Surrey: Field and Wind Tunnel Evaluation of CFD Model PANACHE: Predictions of local dispersion from an area source on a complex industrial site, 11th International Conference on Harmonisation within Atmospheric Dispersion Modelling, 2007 Alberto Mazzoldi, Tim Hill, Jeremy Colls, School of Bio-sciences, University of Nottingham, Leakages from carbon dioxide transportation and storage facilities: a comparison of CFD (FLUIDYN PANACHE) and Gaussian atmospheric dispersion modelling, Atmospheric Environment Journal, 2008

VALIDATION CASES BY INDEPENDENT ORGANISATIONS

The process of pollutant dispersion modelling should involve simultaneously the solution of winds, temperature and turbulence responsible for the transport and the turbulent diffusion and the dispersion process itself. There are several levels of approximation embedded in non-CFD models such as Gaussian (2D) and integral models even in second and third generation tools. These are illustrated below and compared to full CFD modelling technique. Wind fields: Atmospheric flows show a variety of scales from regional to meso-scale and down to small scale turbulence. For large scale descriptions, a possible technique relies on optimal interpolation of external data (as provided by weather services) and application of simple conservation laws (mass and/or vorticity, conservation). It produces diagnostic horizontal fields coherent with topography at large scale. However, such dynamical fields are missing most of the flow features related to land cover/friction effects and to obstacles, wakes, hill recirculation and stagnation patterns. Similarly only mean values of turbulent diffusion related to average friction and global stability are embedded in such dynamical fields. The locally induced turbulent fields (shear, mechanically forced in buildings wakes) are not included. Only full CFD simulations can produce both large scale flow fields and local disturbances related to either hills/mountains or buildings or urban (street scale) flow and turbulence patterns. Dispersion tools: Apart from the reduced quality of the flow description, non-CFD techniques usually relies on empirical, analytical or approximated formulas for the description of the dispersion itself. The techniques can be split in Gaussian (2D) formulations for the long range neutral gas dispersion and integral formulation at very close range. The transition between the two models, are based on gas concentration or residual momentum in the plume. It is not related to the true flow pictures.

Gaussian models are based on very specific field experiments (flat terrain controlled meteorology, elevated sources), Some modification on rectilinear Gaussian plume formulas may be provided for building effects. This can be seen as patches modifying the plume shape in the wake with parameters such as building shape, wind direction, source/building lag…etc. However, these patches are applied to single building influence with no mutual/combined effect. Explicit recirculation patterns and complex trajectories are not calculated (as far as wind fields and turbulence are not simulated). Integral models exploit semi-empirical and simplified balance (momentum/inertia/buoyancy) in either heavy gas (creeping flows) or jet-like behaviour. Again such close range models neglect the effects of obstacles, walls, buildings, ground vicinity in the formulations. A last specific empirical technique is usually employed for road emission/dispersion pattern in street canyon dilution factors in such particular situation are applied based on lanes width, trench height and aspects ratios. Again such formulas are extrapolated from wind tunnel experiments and simplified geometry cases scarcely encountered in real urban configurations.

Only full CFD simulations on locally calculated 3D flow and turbulence fields can produce the proper dispersion patterns both and continuously at close and long range.

ADVANTAGES of 3D CFD MODEL COMPARISON WITH OTHER TECHNIQUES

For non-CFD based techniques, the quality of the results, also depend on the empirical formulae used and the way topography features are treated. It usually takes an expert user to use it carefully. It is not enough to have the accreditation of the agencies like US EPA or UK’s DOE. There are many case examples where the two most commonly used software (for industrial or urban air quality) ADMS and AERMOD either give results several hundred percent away from the monitored values but also give conflicting results for the same problem. An example is on right graphs. Above figure compares the predictions from ADMS 3.1 and AERMOD PRIME with the wind tunnel measurements of Harvey and Obasaju (1999), varying the wind direction with respect to the industrial. It can be seen that ADMS 3.1 significantly over predicts the maximum ground level concentrations while AERMOD PRIME predictions are within a factor of 2 of the wind tunnel measurements. Hence the assessment of air quality impacts of emissions from Rugby Cement was based on AERMOD PRIME predictions. One should also note that such conclusion should be even worst for cases where the emission is located at ground level rather than at elevated stacks. User may also assume that by using a regulatory software, he is exempt from justifying his results. This is certainly not the case as given in the following case comparison done by Dept of Environment Agency UK (full report attached on demand).

9th Int. Conf. on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes - 156 - 1.32 MODEL INTERCOMPARISON BETWEEN ADMS 3.1, AERMOD ANDAERMOD PRIME Christopher Sidle*, Bethan Tuckett-Jones, Betty Ng and Ji Ping Shi, Air Quality Modelling and Assessment Unit (AQMAU), Environment Agency, 29 Newport Road, Cardiff CF24 0TP UK. CONCLUSIONS Whilst significant differences exist between the model predictions, the study found that few generic conclusions could be reached regarding the implications for the use of the models. AERMOD Prime and ADMS 3.1 show significantly different dependence of building downwash effects on wind directions. There is no simple relationship between the predictions with building effects of AERMOD Prime and ADMS 3.1 over a range of building geometry. With terrain, AERMOD and AERMOD Prime give similar predictions. However, these results are very different from those of ADMS 3.1 in both spatial distribution and magnitude. In unstable conditions, AERMOD Prime predicts lower concentrations than either AERMOD or ADMS 3.1. For regulatory purposes it is therefore useful to make use of two models to gain or lose confidence in the modelled predictions. However model comparison alone cannot determine, for any specific case study, which model is performing better. Hence the value of performing comparisons against measurements or wind tunnel data where feasible and appropriate. Therefore we would encourage further measurement campaigns or validation experiments to be performed to try to address the issues raised by model comparison studies.

The below table shows that the 3D models have a more extended application domain than the 2D models, while giving more realistic results for dispersion phenomena.

Model Integral (2D), Gaussian 3D

Phenomena method

Probabilistic analogy with random walk in uniform steady flow: mathematical and statistical model correlation based

on experimental results

Deterministic: physical description of phenomena, fluid mechanics

Approximation Inherent to the probabilistic method and related to flat terrain without obstacles

No approximations

Application domains

Limited to cases where the model is approximated, extrapolation is difficult

outside validation stage (experiments in flat terrain without obstacles, free

horizontal or vertical jets at very close range).

Extended

Atmosphere 1D (vertical) pressure, temperature,

wind velocity and diffusion profiles, all fields horizontally uniform and steady

3D (vertical / horizontal) pressure, temperature, wind velocity profiles

Takes into account the terrain relief

No Yes

Land cover modeled

One unique type of ground occupation parameter over whole terrain

(roughness height)

Many types of ground occupation parameters for each and several

surface cover in the domain– Accounts simultaneously for

individual buildings

Source Point sources at constant rate or

sources in successive bursts. Point, surface, volume, constant or

variable rate Computational Performance

required

small to moderate depending on grid output for analytical formulations

Moderate to High, depending on domain size and mesh finesse

Calculation time required

small to moderate depending on grid output for analytical formulations

Moderate to High, depending on domain size and mesh finesse

Generally CFD models require significant calculation time. However, the PANACHE solver couples the airflow and pollution impact equations to solve all wind-fields for various meteorological conditions without user intervention even if the calculation lasts for hours. (archiving and switching to next meteorological condition, automatically after convergence)

FLUIDYN-PANACHE also differs from standard general purposes CFD software as it is customized for atmospheric flows. Though the physics solved is not approximated (full fluid mechanics), the simulation model is straight forward with dedicated interface for common objects (buildings, fields, forests, water bodies, elevation curves, automatic reading of GIS files/layout, road network files...) Mesh is generated automatically to fit the sources, the land cover patterns and the obstacles. Similarly the initial and boundary conditions relative to atmospheric boundary layers and meteorological conditions are directly implemented without any user coding or complex procedure. The connection with meteorology is provided either via key-in data (wind direction, speed, temperature, stability class…) or via automatic reading of external in situ measurements (masts, weather stations..) or alternatively via external forcing with gridded meso-scale or regional scale data from numerical weather services (e.g. for large to regional scale simulations).

Comparison between 2D and 3D Models

A brief list of references: Consultancies And Users

Industries: BP, TOTAL, SHELL, EXXON, CEA, AIR LIQUIDE, 3M, AJINOMOTO, AREVA, SOLVAY, AVENTIS, ROCKWOOD, BARC, SUMITOMO, MITSUBISHI, TNO, AKER KVAERNER, RELIANCE INDUSTRIES

Third Party Expertise: ISMA, SECHAUD, NEXTER, TNO Consultancy Firms: BUREAU VERITAS, SOFREGAZ, INGEROP, SOFRESID

NORISKO, SERTIUS, ABSE, WESTLAKES More than 40 consultancies companies in France, Belgium, UK, Italy Several City councils and local authorities in UK. (Brent, Greenwich, Stoke-

on-Trent, Leeds, Highways Agency, Heathrow) RESEARCH LABORATORIES AND UNIVERSITIES

French Universities: University of Versailles, University of Mulhouse, University of Reims, University of Pardubice

European Universities: University of Liege, University of Nottingham, University of Northumbria, University of Pardubice

ACKNOWLEDGEMENTS AND AWARDS

Third party expertise by TNO in December 2006 Presentation before workgroup (INERIS, French environment and sustainable

development ministry, MEDD) 2004 Presentation of third party expertise workgroup for 3D toxic dispersion in

December 2005 to MEDD, Solvay Group and DRIRE Presentation before the Belgian (Flemish department) Environment Ministry

in June 2006: Inspectors, consultancy firms industries Co-presidency of Air quality workgroup in Environment Ministry (ADEME) Selected and awarded for Innovation trophies of Solvay in 2006

REFERENCES

FLUIDYN was created in 2001 with the aim to provide high-quality numerical engineering solutions to complex multi-physics applications to European industries, academic institutions and consultancy groups. FLUIDYN is the exclusive agent of the TRANSOFT International group which has developed, since 1987,a large family of software dedicated to environment,

risk, fluid dynamics, fluid-structure interaction phenomena under the trademark fluidyn. The FLUIDYN software are based on state-of-the art computational technologies and physical models thanks to close collaboration with renowned universities and research institutes. A range of software has been developed in the fields of Environment and Risk analysis. The software include 3D fluid dynamics modeling as well as empirical and analytical formulations from industrial know-how. This approach gives extremely reliable result allowing a clear improvement on performances of environmental engineering. The applications cover the topics of toxic and flammable gas dispersion, fires, explosion, indoor and outdoor air quality, water quality and noise. Some of this software specifically developed for environment and risk applications are now world leaders in the international market in their particular sectors. In order to provide a fast and quality support, FLUIDYN has a network of sister companies worldwide. A team of more than 70 engineers and scientists are distributed in agencies in France, UK, Germany, USA, India, Korea and Japan and provide the guarantee of an easy access to a highly qualified engineer ready to tackle complex problems.

OTHER FLUIDYN SOFTWARE: ENVIRONMENT & RISK

FLUIDYN PANACHE has the following modules for specific applications:

• FLUIDYN-PANEPR: 3D CFD, risk analysis studies (accidental, transient and real time dispersion).

• FLUIDYN-PANWAVE: 3D CFD,

wave effect of containment loss on retention walls of petroleum depots.

• FLUIDYN-PANFIRE: 3D CFD,

thermal fluxes due to solid and liquid fires

• FLUIDYN-VENTEX: 3D CFD,

explosion simulation indoor/outdoor thermal fluxes due to solid and liquid fires

• FLUIDYN-ASSESS-RISK: Risk

analysis of petrochemical sites

• FLUIDYN-PANEOLE: 3CFD, Wind turbine from energy potential.

FLUIDYN / TRANSOFT

Habip M., Tripathi A., Identification of an odour source from various probable sources in an industrial wastewater treatment plant. Environmental Odour Management, Allemagne, 2004 Ait-Hamou L., Tripathi A., Souprayen C., Fluid mechanics modelling of odor dispersion 12th Conference and Congress Eurodeur-Airodeur, Paris, France, 2004. Derkx F., Tripathi A., Prediction of urban pollution impact. Clean Air Conference - London, Royaume-Uni, 2004 Ait-Hamou L., Tripathi A., Ghesquier C. Real time dispersion modelling of odours in urban areas ECRIN Workshop of Air quality and Odour dispersion, 2004 Souprayen C., Fluid mechanics modelling of odour dispersion, 11th Conference and Congress Eurodeur-Airodeur, Evreux, France, 2003. Tripathi A., Environmental Impact Simulation of a Domestic Waste Incinerator, 2nd Regional Conference on Energy Technology towards a clean Environment, Phuket, Thaïland, 2003 Tripathi A., Gils M., Venkatram A., Comparison and Performance Evaluation of CFD based Numerical Model and Gaussian-based models for urban air quality predictions. 96th Air and Waste Management Conference, San Diego, USA, 2003 Lise J., Carrie L., Validation of the FLUIDYN-PANROAD model, using a measurement data set made on a motorway. 4th International Scientific Symposium Transport and Air Pollution in Avignon, France, 1997. Lise J., Monote G., Tripathi S., Complex terrain CFD modelling with FLUIDYN-PANACHE. Urban Air Quality – Monitoring and Modelling, University of Hartfordshire, UK, 1996. Lise J., Monote G., Murthy A., Photochemical dispersion of Nox in Urban Areas, .Pollution & Environment Technology in Indonesia, 1996. Lise J., Monote G., Murthy A, FLUIDYN-PANCHEM, a model for photochemistry and urban air quality. Air Pollution IV, Monitoring, Simulation and Control, in Toulouse, France, 1996. Lise J., Stassinopoulos A., Tripathi S., Dispersion and photochemical reactions of Nox in urban areas. Computing in Environmental Resource Management, EPA, 1996. Tripathi S., Near-field dispersion of pollutants on a complex urban terrain of heavy gases by FLUIDYN-PANACHE. 4th Workshop on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes in Oostende, Belgium, 1996. Lise J., Identification d’une source d’odeur par modélisation. Eurodeur 1995 Panday P., Lise J., Photochemical dispersion of NOx in urban areas. Air Pollution, 1995. Panday P., Lise J., A hydro-meteorological model for the calculation of sulphur di-oxyde washdown from a steady chimney plume. Eurasian Conference, 1995 Evaluation of FLUIDYN-PANACHE on heavy-gas dispersion test case, Seminar on evaluation of models of heavy gas dispersion organised by the European Commission, Belgium. Aniruddha P., Charan K., Tripathi S. A second-order scheme for transient atmospheric dispersion study. Sendai, Japan, 1994.

PUBLICATIONS WITH FLUIDYN-PANACHE for AIR QUALITY AND ATMOSPHERIC DISPERSION