APPLICATION OF A LAGRANGIAN RANDOM PARTICLE MODEL TO FORWARD AND INVERSE AIR QUALITY MODELING
Item
Title (Dublin Core)
eng
APPLICATION OF A LAGRANGIAN RANDOM PARTICLE MODEL TO FORWARD AND INVERSE AIR QUALITY MODELING
Description (Dublin Core)
eng
Two methods of using a Lagrangian random particle dispersion model in air quality simulations will be presented. For the purpose of source-oriented modeling, a hybrid Lagrangian dispersion and Eulerian chemistry were coupled to study the effects of ozone in a coastal region. The Lagrangian model was providing transport and dispersion of ozone and ozone precursors, while a chemical module was treating chemical transformations within a Eulerian framework. The Lagrangian particles had chemical dimensions that were updated after each chemical model step. This hybrid model allowed for the treatment of air parcels from numerous sources and reproduced their non-linear chemical evolution.
For the purpose of receptor-oriented modeling, the Lagrangian random particle model was adapted to be run in an inverse mode to determine the most probable sources impacting particular receptors. This inverse modeling improved source location estimates of the backtrajectory analysis and standard receptor models. These two methods indicate that the Lagrangian random particle model can be a useful tool in improving the accuracy of air quality models. Moreover, due to the fact that the Lagrangian framework can be applied to the highest resolutions, these approaches arc appropriate for any complexity of regional, mesoscale, and microscalc domains.
For the purpose of receptor-oriented modeling, the Lagrangian random particle model was adapted to be run in an inverse mode to determine the most probable sources impacting particular receptors. This inverse modeling improved source location estimates of the backtrajectory analysis and standard receptor models. These two methods indicate that the Lagrangian random particle model can be a useful tool in improving the accuracy of air quality models. Moreover, due to the fact that the Lagrangian framework can be applied to the highest resolutions, these approaches arc appropriate for any complexity of regional, mesoscale, and microscalc domains.
Creator (Dublin Core)
Koraćin, Darko
Erez, Weinroth
Koraćin, Julide
Vellore, Ramesh
Lowenthal, Doug
DuBois, David
Chen, Lung-Wen
Gertler, Alan
Publisher (Dublin Core)
Croatian meteorological society
Date (Dublin Core)
2008
Type (Dublin Core)
text
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Format (Dublin Core)
application/pdf
Identifier (Dublin Core)
https://hrcak.srce.hr/64255
eng
https://hrcak.srce.hr/file/96372
Source (Dublin Core)
Hrvatski meteorološki časopis
ISSN 1330-0083 (Print)
ISSN 1849-0700 (Online)
Volume 43
Issue 43/1
Language (Dublin Core)
eng
Rights (Dublin Core)
info:eu-repo/semantics/openAccess
The papers of this Journal are free of charge for personal or educational use, with respect of copyright of authors and publisher.