Gaiasens Technologies

Description

Gaiasens Technologies, une entreprise innovante issue de l'EPFL, se spécialise dans les solutions de surveillance de l'environnement en temps réel. Leur expertise réside dans la mise en place de stations de mesure autonomes et économes en énergie pour surveiller divers risques environnementaux tels que les avalanches, les glaciers rocheux et la pollution atmosphérique. En combinant les mesures météorologiques et la surveillance visuelle, elles fournissent des indications précieuses pour la gestion de la sécurité dans les environnements extrêmes. Gaiasens excelle également dans la modélisation et la prévision de la qualité de l'air, offrant des solutions pour la prévision régionale et urbaine de la qualité de l'air. Avec une équipe multidisciplinaire d'ingénieurs et de spécialistes, ils développent, déploient et maintiennent des systèmes de mesure de pointe adaptés aux terrains montagneux et difficiles.

Source officielle

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Pollution de l'air

vignette|En 2013, l'Organisation mondiale de la santé a reconnu que la pollution de l'air extérieur est un cancérigène certain. vignette|Les émissions de monoxyde de carbone, de soufre, de suies et de particules liées à la combustion du charbon ont probablement été la première source de pollution majeure de l'air, dès le début de l'ère industrielle. Les transports ferroviaires y contribuaient largement, davantage par la construction des infrastructures (notamment la fabrication des rails) que du fait des émanations des locomotives.

Indice de qualité de l'air

Un indice de la qualité de l'air est une mesure de la qualité de l'air, permettant de synthétiser différentes données sous la forme d'une valeur unique. En 2016, d'après un nouveau modèle de qualité de l'air basé sur des données satellitaires, du transport aérien et plus de d'analyse de l'air au sol (rurales et urbaines), produit par l'Organisation mondiale de la santé (OMS) et l'Université de Bath, 92 % de la population mondiale respire un air trop pollué.

Modélisation de la dispersion atmosphérique

La modélisation de la dispersion atmosphérique est une simulation de la dispersion de panaches de pollution dans un contexte et une temporalité donnée, faite à l'aide d'outils mathématiques et de logiciels informatiques et cartographiques. Les modèles cherchent à prendre en compte les conséquences directes et indirectes, dans l'espace et dans le temps des rejets (accidentels ou non) de substances (gaz, particules, aérosols, radionucléides...) indésirables, dangereuses ou toxiques.

Roadway air dispersion modeling

Roadway air dispersion modeling is the study of air pollutant transport from a roadway or other linear emitter. Computer models are required to conduct this analysis, because of the complex variables involved, including vehicle emissions, vehicle speed, meteorology, and terrain geometry. Line source dispersion has been studied since at least the 1960s, when the regulatory framework in the United States began requiring quantitative analysis of the air pollution consequences of major roadway and airport projects.

Prévision numérique du temps

La prévision numérique du temps (PNT) est une application de la météorologie et de l'informatique. Elle repose sur le choix d'équations mathématiques offrant une proche approximation du comportement de l'atmosphère réelle. Ces équations sont ensuite résolues, à l'aide d'un ordinateur, pour obtenir une simulation accélérée des états futurs de l'atmosphère. Le logiciel mettant en œuvre cette simulation est appelé un modèle de prévision numérique du temps.

Improvement of an urban turbulence parametrization for meteorological operational forecast and air quality modeling

Clive Muller

During the last century, urban pollution has increased with the growth of cities. Urban air quality has become a high priority as it is directly linked to concerns such as human exposure and health. The present work is dedicated to urban air quality modeling with focus on urban meteorology. The main goal is to improve meteorological and air quality simulations in urban areas. Based on measurements and numerical air quality simulations, Chapter 3 describes the meteorological situation and tests an emission inventory for an ozone pollution episode in Mexico City (2 March 1997), in order to determine the principal factors to be accounted in an air quality study. The Mexico City case shows the great influence of meteorological conditions and pollutant emissions on air quality. A thorough understanding of the phenomena governing the meteorological conditions, like small scale convergence, and an accurate emission inventory validated by VOC measurements in the city, are sensitive elements in an air quality study. In Chapter 4, the presence of an Urban Heat Island (UHI) is underlined over the city of Basel (Switzerland) with the BUBBLE measurements. Further on, the ability of aLMo (the operational weather prediction model of MeteoSwiss) to reproduce the effect of a city on the boundary layer atmospheric flow fields is investigated. Results show that aLMo is not able to reproduce the UHI and hence that its surface scheme based on the Monin-Obukhov Similarity Theory (MOST) is not adapted for the urban areas. Therefore, the Buildings Effects Parametrization (BEP) which has been developed by Martilli et al.(2002) especially for urban areas, is implemented in aLMo. Results show that alMo is now able to reproduce the main behavior of the urban boundary layer as the UHI and BEP has hence a real enhancement potential for aLMo. Chapter 5 shows the sensitivity of aLMo with respect to its vertical resolution. In order to limit the sensitivity of aLMo to the grid resolution, BEP is modified. The mesoscale model furnishes the upper boundary conditions for the inner calculation of BEP. That is, BEP recalculates independently the vertical profiles of wind, temperature and energy based on the surface fluxes of momentum, heat and turbulent kinetic energy. The results obtained show a decrease in the sensitivity to the resolution and a better agreement with the measurements. Furthermore, the modified version of BEP gives additional meteorological fields (temperature, wind and TKE) in the urban canopy. The computed temperature in the urban canopy shows a good agreement with measurements in a Basel street canyon. This work shows that it is not necessary to have a high resolution for taking into account modification of the atmospheric flow fields induced by a city.

EPFL2007

Validation and application of an urban turbulence parameterisation scheme for mesoscale atmospheric models

Yves-Alain F. Roulet

Growing population, extensive use (and abuse) of the natural resources, increasing pollutants emissions in the atmosphere: these are a few obstacles (and not the least) one has to face with nowadays to ensure the sustainability of our planet in general, and of the air quality in particular. In the case of air pollution, the processes that govern the transport and the chemical transformation of pollutants are highly complex and non-linear. The use of numerical models for simulating meteorological fields, which in turn will determine the transport of pollutants in the atmosphere, is thus a very appropriate tool to describe and understand the air pollution problematic. This work focuses on the meteorological simulation, using a mesoscale model. The stress is particularly put on the parameterisation of urban induced effects on the meteorological fields above a city. A detailed urban parameterisation scheme has been implemented in a mesoscale model in a previous work. This new scheme takes into account the presence of a city in a more accurate way as the traditional method usually used in mesoscale models. In the first part of this work, the urban module was validated for a one-dimensional off-line simulation within and above a street canyon in the city of Basel/Switzerland. The simulation results were compared with measurements taken within and above the same street canyon during an intensive observation period in the frame of the BUBBLE project (Basel UrBan Boundary Layer Experiment). The comparison with the measurements and with a simulation using the traditional urban parameterisation showed that the detailed urban scheme improved the quality of the simulation of turbulent fluxes and meteorological parameters (wind, temperature) in the urban canopy. Further on, the mesoscale was applied for a three-dimensional simulation over the city of Basel and its surroundings. The results showed that the model is able to reproduce the wind pattern that prevailed during the simulated episode, and that the accuracy of the temperature simulation in the city is improved with the urban module. In the third part of this work, an air quality study was performed over the Mexico City basin. The mesoscale model simulated the meteorological conditions for the chosen episode (1 and 2 March 1997). The results were then passed to TAPOM, a Eulerian photochemical model that calculates the space and time distribution of air pollutants. The simulated concentrations over the basin showed good agreement with the observed values. The validated model could then be used to test some emissions reduction scenarios for Mexico City. The use of the detailed urban parameterisation scheme for meteorological fields and air pollutants concentration simulation improved the quality of the results in almost all the applied situations. Consequently, the full modelling tool presented and validated in this work can be used for air quality modelling studies over cities and their surroundings.

EPFL2004

Vehicle emissions control

Vehicle emissions control is the study of reducing the emissions produced by motor vehicles, especially internal combustion engines. Emissions of many air pollutants have been shown to have variety of negative effects on public health and the natural environment. Emissions that are principal pollutants of concern include: Hydrocarbons (HC) – A class of burned or partially burned fuel, hydrocarbons are toxins. Hydrocarbons are a major contributor to smog, which can be a major problem in urban areas.

Environmental policy

Environmental policy is the commitment of an organization or government to the laws, regulations, and other policy mechanisms concerning environmental issues. These issues generally include air and water pollution, waste management, ecosystem management, maintenance of biodiversity, the management of natural resources, wildlife and endangered species. For example, concerning environmental policy, the implementation of an eco-energy-oriented policy at a global level to address the issues of global warming and climate changes could be addressed.

Science de l'environnement

La science de l'environnement ou science environnementale est une discipline qui intègre les sciences physiques et biologiques telles la physique, la chimie (la biochimie et la chimie de l'environnement), la biologie, l'écologie, la pédologie, la géologie, la géomorphologie, la géographie, la climatologie, l'écologie rétrospective, l'histoire environnementale, etc. afin de mener l'étude de l'environnement.

Applied sciences

The following outline is provided as an overview of and topical guide to applied science: Applied science – the branch of science that applies existing scientific knowledge to develop more practical applications, including inventions and other technological advancements. Science itself is the systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Applied cryptography – applications of cryptography.