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Title: Modeling atmospheric deposition using a stochastic transport model

Abstract

An advanced stochastic transport model has been modified to include the removal mechanisms of dry and wet deposition. Time-dependent wind and turbulence fields are generated with a prognostic mesoscale numerical model and are used to advect and disperse individually released particles that are each assigned a mass. These particles are subjected to mass reduction in two ways depending on their physical location. Particles near the surface experience a decrease in mass using the concept of a dry deposition velocity, while the mass of particles located within areas of precipitation are depleted using a scavenging coefficient. Two levels of complexity are incorporated into the particle model. The simple case assumes constant values of dry deposition velocity and scavenging coefficient, while the more complex case varies the values according to meteorology, surface conditions, release material, and precipitation intensity. Instantaneous and cumulative dry and wet deposition are determined from the mass loss due to these physical mechanisms. A useful means of validating the model results is with data available from a recent accidental release of Cesium-137 from a steel-processing furnace in Algeciras, Spain in May, 1998. This paper describes the deposition modeling technique, as well as a comparison of simulated concentration and depositionmore » with measurements taken for the Algeciras release.« less

Authors:
Publication Date:
Research Org.:
Savannah River Site (US)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
750120
Report Number(s):
WSRC-TR-99-00409
TRN: US0001351
DOE Contract Number:  
AC09-96SR18500
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 17 Dec 1999
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; WASHOUT; DEPOSITION; MATHEMATICAL MODELS; CESIUM 137; RADIONUCLIDE MIGRATION; SPAIN; RADIATION ACCIDENTS; METAL INDUSTRY

Citation Formats

Buckley, R.L. Modeling atmospheric deposition using a stochastic transport model. United States: N. p., 1999. Web. doi:10.2172/750120.
Buckley, R.L. Modeling atmospheric deposition using a stochastic transport model. United States. doi:10.2172/750120.
Buckley, R.L. Fri . "Modeling atmospheric deposition using a stochastic transport model". United States. doi:10.2172/750120. https://www.osti.gov/servlets/purl/750120.
@article{osti_750120,
title = {Modeling atmospheric deposition using a stochastic transport model},
author = {Buckley, R.L.},
abstractNote = {An advanced stochastic transport model has been modified to include the removal mechanisms of dry and wet deposition. Time-dependent wind and turbulence fields are generated with a prognostic mesoscale numerical model and are used to advect and disperse individually released particles that are each assigned a mass. These particles are subjected to mass reduction in two ways depending on their physical location. Particles near the surface experience a decrease in mass using the concept of a dry deposition velocity, while the mass of particles located within areas of precipitation are depleted using a scavenging coefficient. Two levels of complexity are incorporated into the particle model. The simple case assumes constant values of dry deposition velocity and scavenging coefficient, while the more complex case varies the values according to meteorology, surface conditions, release material, and precipitation intensity. Instantaneous and cumulative dry and wet deposition are determined from the mass loss due to these physical mechanisms. A useful means of validating the model results is with data available from a recent accidental release of Cesium-137 from a steel-processing furnace in Algeciras, Spain in May, 1998. This paper describes the deposition modeling technique, as well as a comparison of simulated concentration and deposition with measurements taken for the Algeciras release.},
doi = {10.2172/750120},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Dec 17 00:00:00 EST 1999},
month = {Fri Dec 17 00:00:00 EST 1999}
}

Technical Report:

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