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dc.contributor.author
Orcellet, Emiliana Elisabet  
dc.contributor.author
Villanova, Martina  
dc.contributor.author
Noir, Jorge Omar  
dc.contributor.author
Caire, Daiana Marisol  
dc.date.available
2023-06-21T13:22:42Z  
dc.date.issued
2022-08  
dc.identifier.citation
Orcellet, Emiliana Elisabet; Villanova, Martina; Noir, Jorge Omar; Caire, Daiana Marisol; Atmospheric dispersion of hydrogen sulfide using a modified ARPS model: a case study; Sociedade Brasileira de Ecotoxicologia; Ecotoxicology and Environmental Contamination; 17; 1; 8-2022; 93-105  
dc.identifier.issn
2317-9643  
dc.identifier.uri
http://hdl.handle.net/11336/200934  
dc.description.abstract
Exposure to disgusting smells constitutes a type of atmospheric pollution from industrial and human activities. Complaints stemming from various sources of unpleasant odors have become a serious concern in both sparsely and densely populated countries. Hydrogen sulfide is a compound characterized by its disgusting odor. In this work, a new chemical reaction was incorporated to Advanced Regional Prediction System (ARPS) model, to calculate the H2 S air concentrations. A turbulent boundary layer flow is computed using the LES code ARPS 4.5.2. A LES coupled with a Lagrangian stochastic model has been applied to the study of reactive scalar dispersion downwind of a localized source of H2 S. The study case corresponds to the H2 S emission of cellulose mill. Two bad odor event was evaluating in order to compare the result of the model with the measured concentrations. The results of this model application provides good description of the plumes for two event of bad odor records in the zone. The values resulting from the analysis of the air samples are within the concentration range estimated by the model. The model is a valid and useful tool to simulate atmospheric pollution episodes that involve non-conservative pollutants, that is, chemical species that, when in contact with the atmospheric components, react, and giving rise to the formation of secondary compounds. It is possible used the developed modeling system in cases of diagnosis and prognosis of real situations and even emergencies, with an appropriate level of precision for studies of this type.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Sociedade Brasileira de Ecotoxicologia  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ATMOSPHERIC ODOR POLLUTION  
dc.subject
HYDROGEN SULFIDE  
dc.subject
ARPS  
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POLLUTANT DISPERSION  
dc.subject
CHEMICAL REACTION  
dc.subject.classification
Ciencias Medioambientales  
dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Atmospheric dispersion of hydrogen sulfide using a modified ARPS model: a case study  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-06-21T10:49:35Z  
dc.journal.volume
17  
dc.journal.number
1  
dc.journal.pagination
93-105  
dc.journal.pais
Brasil  
dc.description.fil
Fil: Orcellet, Emiliana Elisabet. Universidad Nacional de Entre Rios. Facultad de Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Villanova, Martina. Universidad Nacional de Entre Rios. Facultad de Ciencias de la Salud; Argentina  
dc.description.fil
Fil: Noir, Jorge Omar. Universidad Nacional de Entre Rios. Facultad de Ciencias de la Salud; Argentina  
dc.description.fil
Fil: Caire, Daiana Marisol. Universidad Nacional de Entre Rios. Facultad de Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.journal.title
Ecotoxicology and Environmental Contamination  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://ecotoxbrasil.org.br/upload/eb07df7b924fb679cc8b63fc858d14ad-article%209%20(eec-2022-9).pdf  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.5132/eec.2022.01.09