Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres
Abstract
Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Our uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1302508
- Alternate Identifier(s):
- OSTI ID: 1324521
- Report Number(s):
- LLNL-JRNL-676479
Journal ID: ISSN 1352-2310; S1352231016306136; PII: S1352231016306136
- Grant/Contract Number:
- PLS-14ERD006; AC52-07NA27344
- Resource Type:
- Published Article
- Journal Name:
- Atmospheric Environment (1994)
- Additional Journal Information:
- Journal Name: Atmospheric Environment (1994) Journal Volume: 143 Journal Issue: C; Journal ID: ISSN 1352-2310
- Publisher:
- Elsevier
- Country of Publication:
- United Kingdom
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; meteorological inflow uncertainty; source estimation; Bayesian inversion
Citation Formats
Lucas, Donald D., Gowardhan, Akshay, Cameron-Smith, Philip, and Baskett, Ronald L. Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres. United Kingdom: N. p., 2016.
Web. doi:10.1016/j.atmosenv.2016.08.019.
Lucas, Donald D., Gowardhan, Akshay, Cameron-Smith, Philip, & Baskett, Ronald L. Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres. United Kingdom. https://doi.org/10.1016/j.atmosenv.2016.08.019
Lucas, Donald D., Gowardhan, Akshay, Cameron-Smith, Philip, and Baskett, Ronald L. Sat .
"Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres". United Kingdom. https://doi.org/10.1016/j.atmosenv.2016.08.019.
@article{osti_1302508,
title = {Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres},
author = {Lucas, Donald D. and Gowardhan, Akshay and Cameron-Smith, Philip and Baskett, Ronald L.},
abstractNote = {Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Our uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.},
doi = {10.1016/j.atmosenv.2016.08.019},
journal = {Atmospheric Environment (1994)},
number = C,
volume = 143,
place = {United Kingdom},
year = {Sat Oct 01 00:00:00 EDT 2016},
month = {Sat Oct 01 00:00:00 EDT 2016}
}
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https://doi.org/10.1016/j.atmosenv.2016.08.019
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