Dispersion of odorous gases in the atmosphere — Part I: Modeling approaches to the phenomenon

Lisboa, Henrique de Melo; Guillot, Jean-Michel; Fanlo, Jean‐Louis; Cloirec, Pierre Le

doi:10.1016/j.scitotenv.2005.05.010

Cited by 22 publications

(8 citation statements)

References 9 publications

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“…Modeling the odor dispersion from a source needs the characteristics of the emissions but also the meteorological conditions, typically wind speed and direction and atmospheric stability (De Melo Lisboa et al 2006). Atmospheric conditions play an important role in odor dispersion as shown (Maïzi et al 2010) with the high influence of the wind speed in the odor released from WWTP.…”

Section: Atmospheric and Dispersion Modelsmentioning

confidence: 99%

Modeling the Odor Generation in WWTP: An Integrated Approach Review

Carrera-Chapela

Donoso‐Bravo

Souto

et al. 2014

Water Air Soil Pollut

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Nuisance odors generation from waste and wastewater treatment plants are a cause of public discomfort and complaints. This situation impairs the air quality and represents a growing social and public health problem, especially in developing countries. Several modeling approaches have been developed and successfully implemented in the frame of a wastewater treatment plant for both the biological treatment and physicochemical processes. The mathematical modeling of the odor generation process is still considered a quite complex issue, mainly due to the fact that olfactory nuisance can be caused by many different chemical compounds and the perception of odors is influenced by subjective thresholds. Moreover, the impact of odor sources on air quality is highly conditioned by complex atmospheric dispersion processes. This review presents a critical state-of-art and

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Section: Atmospheric and Dispersion Modelsmentioning

confidence: 99%

Modeling the Odor Generation in WWTP: An Integrated Approach Review

Carrera-Chapela

Donoso‐Bravo

Souto

et al. 2014

Water Air Soil Pollut

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“…The comparison between field data and theoretical results was imprecise, probably both for the complexity of the field experiment and the strong assumptions of the fluctuating model, for which Gaussian one-point one-time PDF and spatial distribution for the mean concentration were assumed. Yet, based on this notable attempt, similar models have been developed more recently (de Melo Lisboa et al 2006;Dourado et al 2014).…”

Section: Time-series Modelsmentioning

confidence: 99%

“…Yet, based on this notable attempt, similar models have been developed more recently (de Melo Lisboa et al. 2006 ; Dourado et al. 2014 ).…”

Section: Phenomenologically-based Approachesmentioning

confidence: 99%

Concentration Fluctuations from Localized Atmospheric Releases

Cassiani

Bertagni

Marro

et al. 2020

Boundary-Layer Meteorol

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We review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models.

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“…It is usually assumed that odours dilute and gradually diffuse away from the odorant source. However, the consideration of a decreasing gradient does not take into account that the odour dispersal process is rather chaotic, in most cases making it also very difficult to develop mathematical models to calculate the dispersion of odours (18,19) . It seems that at the distance of Particularly during the far-field condition, we observed a high interindividual variance in localization accuracy.…”

Section: Study Limitationsmentioning

confidence: 99%