Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout
A gas well blowout in south central Texas in November 2019 that lasted for 20 days provided a unique opportunity to test the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model’s plume dispersion against hydrocarbon air monitoring data at two nearby state monitoring stations. We...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/13/3/486 |
| _version_ | 1797472823890935808 |
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| author | Gunnar W. Schade Mitchell L. Gregg |
| author_facet | Gunnar W. Schade Mitchell L. Gregg |
| author_sort | Gunnar W. Schade |
| collection | DOAJ |
| description | A gas well blowout in south central Texas in November 2019 that lasted for 20 days provided a unique opportunity to test the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model’s plume dispersion against hydrocarbon air monitoring data at two nearby state monitoring stations. We estimated daily blowout hydrocarbon emission rates from satellite measurement-based results on methane emissions in conjunction with previously reported composition data of the local hydrocarbon resource. Using highly elevated hydrocarbon mixing ratios observed during several days at the two downwind monitoring stations, we calculated excess abundances above expected local background mixing ratios. Subsequent comparisons to HYSPLIT plume dispersion model outputs, generated using High-Resolution Rapid Refresh (HRRR) or North American Mesoscale (NAM) forecast meteorological input data, showed that the model generally reproduces both the timing and magnitude of the plume in various meteorological conditions. Absolute hydrocarbon mixing ratios could typically be reproduced within a factor of two. However, when lower emission rate estimates provided by the company in charge of the well were used, downwind hydrocarbon observations could not be reproduced. Overall, our results suggest that HYSPLIT, in combination with high-resolution meteorological input data, is a useful tool to accurately forecast chemical plume dispersion and potential human exposure in disaster situations. |
| first_indexed | 2024-03-09T20:07:38Z |
| format | Article |
| id | doaj.art-467b46b8217a4dbd93bd14255c81bc5e |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-09T20:07:38Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-467b46b8217a4dbd93bd14255c81bc5e2023-11-24T00:27:41ZengMDPI AGAtmosphere2073-44332022-03-0113348610.3390/atmos13030486Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well BlowoutGunnar W. Schade0Mitchell L. Gregg1Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USADepartment of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USAA gas well blowout in south central Texas in November 2019 that lasted for 20 days provided a unique opportunity to test the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model’s plume dispersion against hydrocarbon air monitoring data at two nearby state monitoring stations. We estimated daily blowout hydrocarbon emission rates from satellite measurement-based results on methane emissions in conjunction with previously reported composition data of the local hydrocarbon resource. Using highly elevated hydrocarbon mixing ratios observed during several days at the two downwind monitoring stations, we calculated excess abundances above expected local background mixing ratios. Subsequent comparisons to HYSPLIT plume dispersion model outputs, generated using High-Resolution Rapid Refresh (HRRR) or North American Mesoscale (NAM) forecast meteorological input data, showed that the model generally reproduces both the timing and magnitude of the plume in various meteorological conditions. Absolute hydrocarbon mixing ratios could typically be reproduced within a factor of two. However, when lower emission rate estimates provided by the company in charge of the well were used, downwind hydrocarbon observations could not be reproduced. Overall, our results suggest that HYSPLIT, in combination with high-resolution meteorological input data, is a useful tool to accurately forecast chemical plume dispersion and potential human exposure in disaster situations.https://www.mdpi.com/2073-4433/13/3/486well blowouthydrocarbonsHYSPLITplume dispersionmodel performance |
| spellingShingle | Gunnar W. Schade Mitchell L. Gregg Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout Atmosphere well blowout hydrocarbons HYSPLIT plume dispersion model performance |
| title | Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout |
| title_full | Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout |
| title_fullStr | Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout |
| title_full_unstemmed | Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout |
| title_short | Testing HYSPLIT Plume Dispersion Model Performance Using Regional Hydrocarbon Monitoring Data during a Gas Well Blowout |
| title_sort | testing hysplit plume dispersion model performance using regional hydrocarbon monitoring data during a gas well blowout |
| topic | well blowout hydrocarbons HYSPLIT plume dispersion model performance |
| url | https://www.mdpi.com/2073-4433/13/3/486 |
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