A fluctuating plume dispersion model for the prediction of odour-impact frequencies from continuous stationary sources

Mussio, Peter.; Gnyp, A. W.; Henshaw, Paul

doi:10.1016/s1352-2310(00)00419-2

Cited by 36 publications

(21 citation statements)

References 9 publications

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“…Smith (1995) used a Gaussian model for estimating odor emissions from area sources. A fluctuating plume dispersion model (Mussino et al, 2001) was used for the prediction of odor-impact frequencies from continuous stationary sources. Sarkar et al (2003) investigated odor emission of solid waste landfill site in north London using COMPLEX-1 software developed by the US-EPA.…”

Section: Introductionmentioning

confidence: 99%

CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

Jeong¹

2011

Asian J. Atmos. Environ

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This study assesses the dispersion and emission rates of odor form industrial area source. CALPUFF and AERMOD Gaussian models were used for predicting downwind odor concentration and calculating odor emission rates. The studied region was Seobu industrial complex in Korea. Odor samples were collected five days over a year period in 2006. In-site meteorological data (wind direction and wind speed) were used to predict concentration. The BOOT statistical examination software was used to analyze the data. Comparison between the predicted and field sampled downwind concentration using BOOT analysis indicates that the CALPUFF model prediction is a little better than AERMOD prediction for average downwind odor concentrations. Predicted concentrations of AERMOD model have a little larger scatter than that of CALPUFF model. The results also show odor emission rates of Seobu industrial complex area were an order of 10 smaller than that of beef cattle feed lots.

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Section: Introductionmentioning

confidence: 99%

CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

Jeong¹

2011

Asian J. Atmos. Environ

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“…Using these time integration periods, short-time concentration fluctuations are usually ignored by dispersion models. However, short-time fluctuations may influence considerably the nuisance potential (Nicell, 2009) and therefore should be considered when predicting the odour plume (Sykes & Gabruk, 1997;Mussio et al, 2001).…”

Section: Odour Dispersion Modellingmentioning

confidence: 99%

Strategies to control odours in livestock facilities: a critical review

Ubeda

Jiménez

Nicolas

et al. 2013

Span. j. agric. res.

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Odours generated in livestock buildings constitute one of the most relevant air quality issues of intensive livestock production. Reducing nuisance episodes related to odour exposure is therefore essential for a sustainable livestock production. In this study, the state-of-the-art on odour mitigation techniques in livestock housing is critically reviewed. Scientific advances in the last decade are revised and research needs are also identified. The complex nature of livestock odours is firstly reviewed and examined. Then, the most relevant odour control strategies are analyzed in terms of present knowledge and future needs. The strategies considered are: nutritional strategies, manure additives, building design, air filtration, manure covers, manure treatment systems and windbreaks. Finally, future research needs and priorities when establishing mitigation techniques are identified. Despite important recent advances, there are still some challenges for scientists, producers and regulators, particularly related to field evaluation of odours. Therefore, to control livestock odours effectively, using standardized f ield assessment techniques will be required. Also, investigating measurement and model errors may be useful to better understand the limitations of the current methods, as well as to identify research priorities.

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“…4 However, a short averaging time plume has the appearance of a fluctuating plume in which the plume meanders in the lateral and vertical directions because of the spatial…”

Section: Model Theorymentioning

confidence: 99%

“…Then the frequency of a certain odor level during a 1-hr period can be derived from the calculated subhour concentrations. In the fluctuating plume model developed by Mussio et al, 4 200 random values were generated during a 1-hr period to calculate the frequency. Results showed that this method was effective at estimating the odor frequency.…”

Section: Instantaneous Odor Concentrationsmentioning

confidence: 99%

“…They concluded that the modified model was superior to Gaussian models for estimating odor exposures based on hourly averages. Mussio et al 4 developed a fluctuating plume dispersion model to predict the odor-impact frequencies in the communities surrounding elevated point sources. Their model provided good simulation of total frequencies of occurrence when the odor occurrence was frequent.…”

Section: Introductionmentioning

confidence: 99%

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Development of a Livestock Odor Dispersion Model: Part I. Model Theory and Development

Guo

Laguë

2011

Journal of the Air & Waste Management Association

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A livestock odor dispersion model (LODM) was developed to predict mean odor concentration, odor frequency, instantaneous odor concentration, and peak odor concentration from livestock operations. This model is based on the Gaussian fluctuating plume model and has the ability to consider the instantaneous concentration fluctuations and the differences between odor and traditional air pollutants. It can predict odor frequency from the routine hourly meteorological data input and deal with different types of sources and multiple sources. Also, the relationship between odor intensity and odor concentration was incorporated into the model. INTRODUCTIONResearchers have used industrial air dispersion models to predict livestock odors downwind of livestock operations since the 1980s. The main drawback of these industrial air dispersion models is that most of them can only calculate long time average concentration. However, a series of short exposures to detectable odors can cause nuisances and generate community complaints although the hourly averaged concentrations remain at very low or undetectable levels (Ͻ1 odor unit [OU]/m

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A fluctuating plume dispersion model for the prediction of odour-impact frequencies from continuous stationary sources

Cited by 36 publications

References 9 publications

CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

Strategies to control odours in livestock facilities: a critical review

Development of a Livestock Odor Dispersion Model: Part I. Model Theory and Development

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