Chemical reactions at street scale using a Lagrangian particle dispersion model

Kaplan, H.; Olry, Christophe; Moussafir, Jacques; Oldrini, Olivier; Mahe, Frédéric; Albergel, Armand

doi:10.1504/ijep.2014.065920

Cited by 4 publications

(2 citation statements)

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“…The VPA model has been successfully evaluated against wind tunnel experimental data of dispersion in a neutral boundary layer [59,60], canopy turbulence [59] and decaying grid turbulence [60]. It has also been used for environmental analysis involving reacting pollutants [61].…”

Section: Volumetric Particle Approachmentioning

confidence: 99%

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

et al. 2019

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In this paper, a review of the Lagrangian stochastic models developed in the last decades for the simulation of the concentration–fluctuation dispersion is presented. The main approaches available in the literature are described and their ability in reproducing the higher order moments of the probability density function is discussed. Then, the Lagrangian approaches for evaluating of the odor annoyance are presented. It is worth to notice that, while Lagrangian stochastic models for mean concentrations are well-known and their ability in correctly reproducing the observation is well assessed, concerning concentration fluctuations the approaches are often new and unknown for most of the scientific community.

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Section: Volumetric Particle Approachmentioning

confidence: 99%

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

et al. 2019

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“…To consider the transformation between NO and NO 2 , a simple chemical scheme has been added in PSPRAY [24].…”

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confidence: 99%

Optimization of HPC Use for 3D High Resolution Urban Air Quality Assessment and Downstream Services

et al. 2021

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The number of cities, or parts of cities, where air quality has been computed using the PMSS 3D model now appears to be sufficient to allow assessment and understanding of performance. Two fields of application explain the growing number of sites: the first is the long-term air quality assessment required in urban areas for any building or road project. The geometric complexity found in such areas can justify the use of a 3D approach, as opposed to Gaussian ones. However, these studies have constraining rules that can make the modelling challenging: several scenarios are needed (current, future with project, future without project), the long-term impact implies a long physical time period to be computed, and the spatial extension of the domain can be large in order to cover the traffic impact zone of the project. The second type of application is dedicated to services and, essentially, to forecasting. As for impact assessments, the modelling can be challenging here because of the extension of the domain if the target area is a whole city. Forecast also adds the constraint of time, as results are requested early, and the constraint of robustness. The CPU amount needed to meet all these requirements is important. It is therefore crucial to optimize all possible parts of the modelling chain in order to limit cost and delay. The sites presented in the article have been modelled with PMSS for long periods. This allows feedback to be provided on different topics: (a) daily forecasts offer an opportunity to increase the robustness of the modelling chain; (b) quantitative validation at air quality measurement stations; (c) comparison of annual impact based on a whole year, and based on a sampling list of dates selected thanks to a classification process; (d) large calculation domains with widespread pollutant emissions offer a great opportunity to qualitatively check and improve model results on numerous geometrical configurations; (e) CPU time variations between different sites provide valuable information to select the best parametrizations, to predict the cost of the services, and to design the needed hardware for a new site.

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