ARIA Technologies


ARIA Technologies

Time filter
Source Type

Anfossi D.,Institute of Atmospheric science and Climate ISAC | Tinarelli G.,ARIANET Srl | Trini Castelli S.,Institute of Atmospheric science and Climate ISAC | Nibart M.,ARIA Technologies | And 2 more authors.
Atmospheric Environment | Year: 2010

A Lagrangian stochastic model (MicroSpray), able to simulate the airborne dispersion in complex terrain and in presence of obstacles, was modified to simulate the dispersion of dense gas clouds. This is accomplished by taking into account the following processes: negative buoyancy, gravity spreading and the particle's reflection at the bottom computational boundary. Elevated and ground level sources, continuous and instantaneous emissions, time varying sources, plumes with initial momentum (horizontal, vertical or oblique in any direction), plumes without initial momentum are considered. MicroSpray is part of the model system MSS, which also includes the diagnostic MicroSwift model for the reconstruction of the 3-D wind field in presence of obstacles and orography. To evaluate the MSS ability to simulate the dispersion of heavy gases, its simulation performances are compared in detail to two field experiments (Thorney Island and Kit Fox) and to a chlorine railway accident (Macdona). Then, a comprehensive analysis considering several experiments of the Modelers Data Archive is presented. The statistical analysis on the overall available data reveals that the performance of the new MicroSpray version for dense gas releases is generally reliable. For instance, the agreement between concentration predictions and observations is within a factor of two in the 72% up to 99% of the occurrences for the case studies considered. The values of other performance measures, such as correlation coefficient, geometric mean bias and geometric variance, mostly set in the ranges indicated as good-model performances in the specialized literature. © 2009 Elsevier Ltd. All rights reserved.

Oldrini O.,MOKILI | Nibart M.,ARIA Technologies | Armand P.,CEA DAM Ile-de-France | Olry C.,ARIA Technologies | And 2 more authors.
Proceedings of the 15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO 2013 | Year: 2013

Parallel SWIFT is used in the AIRCITY project to model the air quality at a few meters resolution over the whole Paris area. Hence, it is crucial to provide the capability to correctly handle the downscaling from meso scale modelling to local scale modelling over build-up areas. Build-up areas have directional specificities due to the orientation of streets, or also the river Seine for the Paris case, that lead to directional bulk effects. To overcome this, we have developed an approach based on directional drag coefficients. Drag coefficients of buildings within their neighbourhood are derived once and for all for a set of wind directions. A methodology has been implemented in Micro-SWIFT to derive this, but data obtained from other CFD models can be used. This static database of drag coefficients is then used to create directional matrices of Cionco type canopy densities, at the wished resolution. The capability to handle and create canopy laws according to the flow direction has been implemented in SWIFT. Results are presented on test cases.

Duchenne C.,CEA DAM Ile-de-France | Armand P.,CEA DAM Ile-de-France | Oldrini O.,MOKILI | Olry C.,ARIA Technologies | Moussafir J.,ARIA Technologies
HARMO 2011 - Proceedings of the 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2011

The development of PMSS, the parallel version of the Micro-SWIFT-SPRAY suite, allows now to process 3D flow calculation, atmospheric dispersion of hazardous species and health impact assessment at the microscale, on extended Urban areas, in a reduced computing time. Test cases on Paris show the feasibility of such calculations and the ability to obtain a very detailed representation of output fields, even far away from the release source. Evaluations of speedup prove that the parallelization of PSWIFT is very efficient both for tile's parallelization and timeframe's parallelization. Performances obtained with PSPRAY are quite good too but, as communications between cores are more important, parallelization may be less efficient for huge numbers of core.

Oldrini O.,MOKILI | Olry C.,ARIA Technologies | Moussafir J.,ARIA Technologies | Armand P.,CEA DAM Ile-de-France | Duchenne C.,CEA DAM Ile-de-France
HARMO 2011 - Proceedings of the 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2011

Micro-SWIFT-SPRAY is a fast transport and dispersion modelling system. It is designed for local scale and takes into account buildings. A parallel version of MSS has been developed by ARIA Technologies, MOKILI and CEA. MSS consists of SWIFT, a mass consistent nested wind field model, and SPRAY, a Lagrangian particle dispersion model. PMSS has been designed to decrease the computational time on very large, high resolution, domains with high number of particles. Parallelization has been successfully implemented both for splitting geographically big memory domains being split, and based on code specific properties to gain speed up. Geographic parallelization is achieved through classical Eulerian tile splitting. Most of the speed up is achieved on SWIFT based on the diagnostic property of the code: different time frames can be computed at the same time without any communication. Geographic parallelization is driven by master core: domain is being divided into sub domains. Specific geographic information, such as topography or roughness, is sent to relevant cores. Building data needed specific attention due to Röckle type algorithm to handle wind initialization. Communication and calculation between cores on adjacent tiles are performed in such way to allow results to be identical to the simulation without geographic parallelization. Transition to parallel SPRAY is handled smoothly: SPRAY uses domain decomposition inherited from SWIFT parallel computation. SPRAY speedup is achieved by particle splitting between cores. SPRAY allows loading in memory sub domains according to source locations at first and then containing active particles. SPRAY has very elaborated load balancing to provide sub domains containing numerous particles with maximum core power and is able to transition particles between sub domains. Quality of results is very good and performances, even with high number of cores, are in line with expectations as shown on several traditional MSS test cases. PMSS is designed to take advantage of computer power on a diversity of architectures, from multi core laptops to very large super computer cluster. Applications of PMSS are ranging from air quality modelling to emergency response purposes.

Cariou S.,Ecole des Mines d'Ales | Fanlo J.-L.,Ecole des Mines d'Ales | Stitou Y.,ISEO | Buty D.,Aria Technologies | And 2 more authors.
Chemical Engineering Transactions | Year: 2016

Odour annoyance represents a very important issue of societal and industrial perspective. It can be due to the intrinsic character of the odour, its frequency and the moment of the perception. Location of industries depends on their odour acceptability in the neighbourhood. As 13 to 20% of the population in European countries would be annoyed by environmental odours, stringent regulations are being enforced for odor monitoring and recently, several works have been carried out to determine suitable and valuable strategies/methods to limit odor annoyance. Industrial and agricultural activities generate atmospheric pollution and olfactive nuisances due to the emission of a complex mixture of volatile compounds. Hydrogen sulphide (H2S) and ammonia (NH3) are clearly identified within composting plants (Cabrol et al, 2012) and due to their high olfactory impact, have to be monitored as mentioned in a report of the French Environmental and Energy Management Agency (ADEME, 2012). ODEMS is a system composed by a network of miniature and autonomous sensors combined with reversed dispersion (Figure 1) and dispersion (Figure 2) modelling systems and enable to provide reliable spatial and temporal information down to the low ppbv level. The miniaturized cost-effective sensors Cairsens are based on amperometric detection and are developed by Cairpol company. Ammonia and hydrogen sulfide sensors have been deployed within a composting plant for determining the odorous sources and evaluating the real impact on the neighbourhood. After a period of data collection, considering weather conditions, this study revealed that this system is also able to predict the impact of a site-specific activity. © 2016, AIDIC Servizi S.r.l.

Zhang Q.,ARIA Technologies | Zhang Q.,French National Center for Scientific Research | Laurent B.,French National Center for Scientific Research | Velay-Lasry F.,ARIA Technologies | And 4 more authors.
Journal of Environmental Sciences | Year: 2012

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly. © 2012 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences.

Guttikunda S.K.,Desert Research Institute | Calori G.,ARIA Technologies
Atmospheric Environment | Year: 2013

In Delhi, between 2008 and 2011, at seven monitoring stations, the daily average of particulates with diameter <2.5 μm (PM2.5) was 123 ± 87 μg m-3 and particulates with diameter <10 μm (PM10) was 208 ± 137 μg m-3. The bulk of the pollution is due to motorization, power generation, and construction activities. In this paper, we present a multi-pollutant emissions inventory for the National Capital Territory of Delhi, covering the main district and its satellite cities - Gurgaon, Noida, Faridabad, and Ghaziabad. For the base year 2010, we estimate emissions (to the nearest 000's) of 63,000 tons of PM2.5, 114,000 tons of PM10, 37,000 tons of sulfur dioxide, 376,000 tons of nitrogen oxides, 1.42 million tons of carbon monoxide, and 261,000 tons of volatile organic compounds. The inventory is further spatially disaggregated into 80 × 80 grids at 0.01° resolution for each of the contributing sectors, which include vehicle exhaust, road dust re-suspension, domestic cooking and heating, power plants, industries (including brick kilns), diesel generator sets and waste burning. The GIS based spatial inventory coupled with temporal resolution of 1 h, was utilized for chemical transport modeling using the ATMoS dispersion model. The modeled annual average PM2.5 concentrations were 122 ± 10 μg m-3 for South Delhi; 90 ± 20 μg m-3 for Gurgaon and Dwarka; 93 ± 26 μg m-3 for North-West Delhi; 93 ± 23 μg m-3 for North-East Delhi; 42 ± 10 μg m-3 for Greater Noida; 77 ± 11 μg m-3 for Faridabad industrial area. The results have been compared to measured ambient PM pollution to validate the emissions inventory. © 2012 Elsevier Ltd.

Lacome J.M.,INERIS | Tognet F.,INERIS | Olry C.,Aria Technologies | Nibart M.,Aria Technologies
Proceedings of the 15th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO 2013 | Year: 2013

A new version of the lagrangian dispersion modelling system Micro-SWIFT-SPRAY (MSS developed by ARIA Technologies and ARIANET) has been developed in order to allow simulation of wet plume, microorganisms, insecticide or pesticide dispersion. For all these applications, it is necessary to take into account both gas and liquid phase evolution including mass and heat transfer. In the particular case of microorganisms distinct behaviors potentially occur when transported by the liquid and/or the gas phase. Following the MSS lagrangian approach, it is easy to define a mass quantity of vapor and a large number of droplets of the same diameter by a virtual particle. Hence a spectrum of different size of droplets can be model using several virtual particles. The development of the new module consists of modelling the physical phenomenon of evaporation and condensation inside a wet plume taking into account temperature and humidity of ambient atmosphere. Microphysics of droplet is solved using the classical laws of evaporation/condensation processes in the surrounding atmosphere. The calculated evaporation rate allows to estimate the diameter evolution and the temperature inside the droplet. The difficulty consists in characterizing the surrounding atmosphere. The interaction between droplets and ambient humidity has been performed on an eulerian frame. Two methods of two way coupling have been tested on academic cases (0D). The proposed paper will present the two approaches and the obtained results.

Rajaona H.,Telecom Lille 1 | Rajaona H.,CEA DAM Ile-de-France | Septier F.,Telecom Lille 1 | Armand P.,CEA DAM Ile-de-France | And 4 more authors.
Atmospheric Environment | Year: 2015

In the eventuality of an accidental or intentional atmospheric release, the reconstruction of the source term using measurements from a set of sensors is an important and challenging inverse problem. A rapid and accurate estimation of the source allows faster and more efficient action for first-response teams, in addition to providing better damage assessment.This paper presents a Bayesian probabilistic approach to estimate the location and the temporal emission profile of a pointwise source. The release rate is evaluated analytically by using a Gaussian assumption on its prior distribution, and is enhanced with a positivity constraint to improve the estimation. The source location is obtained by the means of an advanced iterative Monte-Carlo technique called Adaptive Multiple Importance Sampling (AMIS), which uses a recycling process at each iteration to accelerate its convergence.The proposed methodology is tested using synthetic and real concentration data in the framework of the Fusion Field Trials 2007 (FFT-07) experiment. The quality of the obtained results is comparable to those coming from the Markov Chain Monte Carlo (MCMC) algorithm, a popular Bayesian method used for source estimation. Moreover, the adaptive processing of the AMIS provides a better sampling efficiency by reusing all the generated samples. © 2015 Elsevier Ltd.

Liao G.-L.,Guangxi Meteorological Service Center | Zeng P.,Guangxi Meteorological Service Center | Zhang Q.-J.,ARIA Technologies | Cheng P.,Guangxi Weather Modification Office | Mo Y.-C.,Guangxi Meteorological Service Center
HARMO 2014 - 16th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Proceedings | Year: 2014

Based on the data provided by surface automatic weather stations over Guangxi, Nanning conventional weather station, and the air pollution daily average concentrations in Nanning, a serious air pollution process in Nanning has been analyzed by using Empirical Orthogonal Function (EOF), air trajectory and other analytical methods. The EOF analysis shows that the second mode of the serious air pollution process has obvious diurnal variation. Influenced by local meso-scale and micro-scale circulation systems, pollution is localized which leads to the important air pollution level. © Crown Copyright 2014 Dstl.

Loading ARIA Technologies collaborators
Loading ARIA Technologies collaborators