Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Bayesian estimation of airborne fugitive emissions using a Gaussian plume model
https://orcid.org/0000-0001-7519-4311
Abstract A new method is proposed for estimating the rate of fugitive emissions of particulate matter from multiple time-dependent sources via measurements of deposition and concentration. We cast this source inversion problem within the Bayesian framework, and use a forward model based on a Gaussian plume solution. We present three alternate models for constructing the prior distribution on the emission rates as functions of time. Next, we present an industrial case study in which our framework is applied to estimate the rate of fugitive emissions of lead particulates from a smelter in Trail, British Columbia, Canada. The Bayesian framework not only provides an approximate solution to the inverse problem, but also quantifies the uncertainty in the solution. Using this information we perform an uncertainty propagation study in order to assess the impact of the estimated sources on the area surrounding the industrial site.
Highlights Novel formulation of source inversion as a Bayesian inverse problem. Three different models for modelling of prior knowledge. Industrial case study of fugitive lead emissions in Trail, BC, Canada. Uncertainty propagation study and impact assessment.
Bayesian estimation of airborne fugitive emissions using a Gaussian plume model
https://orcid.org/0000-0001-7519-4311
Abstract A new method is proposed for estimating the rate of fugitive emissions of particulate matter from multiple time-dependent sources via measurements of deposition and concentration. We cast this source inversion problem within the Bayesian framework, and use a forward model based on a Gaussian plume solution. We present three alternate models for constructing the prior distribution on the emission rates as functions of time. Next, we present an industrial case study in which our framework is applied to estimate the rate of fugitive emissions of lead particulates from a smelter in Trail, British Columbia, Canada. The Bayesian framework not only provides an approximate solution to the inverse problem, but also quantifies the uncertainty in the solution. Using this information we perform an uncertainty propagation study in order to assess the impact of the estimated sources on the area surrounding the industrial site.
Highlights Novel formulation of source inversion as a Bayesian inverse problem. Three different models for modelling of prior knowledge. Industrial case study of fugitive lead emissions in Trail, BC, Canada. Uncertainty propagation study and impact assessment.
Bayesian estimation of airborne fugitive emissions using a Gaussian plume model
https://orcid.org/0000-0001-7519-4311
Abstract A new method is proposed for estimating the rate of fugitive emissions of particulate matter from multiple time-dependent sources via measurements of deposition and concentration. We cast this source inversion problem within the Bayesian framework, and use a forward model based on a Gaussian plume solution. We present three alternate models for constructing the prior distribution on the emission rates as functions of time. Next, we present an industrial case study in which our framework is applied to estimate the rate of fugitive emissions of lead particulates from a smelter in Trail, British Columbia, Canada. The Bayesian framework not only provides an approximate solution to the inverse problem, but also quantifies the uncertainty in the solution. Using this information we perform an uncertainty propagation study in order to assess the impact of the estimated sources on the area surrounding the industrial site.
Highlights Novel formulation of source inversion as a Bayesian inverse problem. Three different models for modelling of prior knowledge. Industrial case study of fugitive lead emissions in Trail, BC, Canada. Uncertainty propagation study and impact assessment.
Bayesian estimation of airborne fugitive emissions using a Gaussian plume model
Hosseini, Bamdad (Autor:in) / Stockie, John M. (Autor:in)
Atmospheric Environment ; 141 ; 122-138
17.06.2016
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| Elsevier | 2025
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| British Library Conference Proceedings | 1994
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