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Comparing large-eddy simulation and Gaussian plume model to sensor measurements of an urban smoke plume

Comparing large-eddy simulation and Gaussian plume model to sensor measurements of an urban smoke plume
Comparing large-eddy simulation and Gaussian plume model to sensor measurements of an urban smoke plume
The fast prediction of the extent and impact of accidental air pollution releases is important
to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low cost sensors, a fire broke out from an outbuilding containing roughly 3,000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modelling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles
of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 minutes at an emission rate 50 g/s of PM2.5. The emission was significantly greater than a ‘normal’ house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast response numerical models at various compromised levels of accuracy, efficiency and cost.
2073-4433
Clements, Dominic
12777501-a093-4b05-a613-2aedfa36512d
Coburn, Matthew
0ee79550-a5f4-470c-a8eb-5354ee9369c8
Cox, Simon
0e62aaed-24ad-4a74-b996-f606e40e5c55
Bulot, Florentin M.J.
064f02d6-98cc-4a1f-9eb4-ff05c45b2af0
Xie, Zheng-Tong
98ced75d-5617-4c2d-b20f-7038c54f4ff0
Vanderwel, Christina
fbc030f0-1822-4c3f-8e90-87f3cd8372bb
Clements, Dominic
12777501-a093-4b05-a613-2aedfa36512d
Coburn, Matthew
0ee79550-a5f4-470c-a8eb-5354ee9369c8
Cox, Simon
0e62aaed-24ad-4a74-b996-f606e40e5c55
Bulot, Florentin M.J.
064f02d6-98cc-4a1f-9eb4-ff05c45b2af0
Xie, Zheng-Tong
98ced75d-5617-4c2d-b20f-7038c54f4ff0
Vanderwel, Christina
fbc030f0-1822-4c3f-8e90-87f3cd8372bb

Clements, Dominic, Coburn, Matthew, Cox, Simon, Bulot, Florentin M.J., Xie, Zheng-Tong and Vanderwel, Christina (2024) Comparing large-eddy simulation and Gaussian plume model to sensor measurements of an urban smoke plume. Atmosphere, 15 (9). (doi:10.3390/atmos15091089).

Record type: Article

Abstract

The fast prediction of the extent and impact of accidental air pollution releases is important
to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low cost sensors, a fire broke out from an outbuilding containing roughly 3,000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modelling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles
of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 minutes at an emission rate 50 g/s of PM2.5. The emission was significantly greater than a ‘normal’ house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast response numerical models at various compromised levels of accuracy, efficiency and cost.

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Accepted/In Press date: 3 September 2024
Published date: 7 September 2024

Identifiers

Local EPrints ID: 494128
URI: http://eprints.soton.ac.uk/id/eprint/494128
ISSN: 2073-4433
PURE UUID: 070ca7f2-b430-432d-acc9-ea47912739d6
ORCID for Zheng-Tong Xie: ORCID iD orcid.org/0000-0002-8119-7532
ORCID for Christina Vanderwel: ORCID iD orcid.org/0000-0002-5114-8377

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Date deposited: 24 Sep 2024 16:46
Last modified: 25 Sep 2024 01:46

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Contributors

Author: Dominic Clements
Author: Matthew Coburn
Author: Simon Cox
Author: Florentin M.J. Bulot
Author: Zheng-Tong Xie ORCID iD

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