Source Detection of SO2 Emissions with Unknown Origins Using UV Remote Sensing and Numerical Modeling
| dc.contributor.advisor | Cervone, Guido | |
| dc.contributor.author | Mandable, Lori | |
| dc.creator | Mandable, Lori | |
| dc.date | 2013-05-01 | |
| dc.date.accessioned | 2013-09-12T16:27:36Z | |
| dc.date.available | 2013-09-12T16:27:36Z | |
| dc.date.issued | 2013-09-12 | |
| dc.description.abstract | Trace gases such as sulfur dioxide (SO2) are capable of causing deleterious effects such as radiation damage, climate change, respiratory issues in animals and development of corrosive acid rain. Detection of such trace gases is typically conducted via ground and satellite remote sensing instrument measurements, and when used in tandem with an atmospheric Transport & Dispersion (T&D) model such as the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) system, the results can be used to solve trace gas source detection problems. This proposal discusses a methodology that combines HYSPLIT backward and forward modeling simulations to identify the characteristics of an unknown source of trace gas emissions. Specifically, this methodology will be used in the case of back tracing a passive SO2 release to determine the volcanic source. The AURA/OMI satellite can measure atmospheric trace gases, such as SO2, at a spectral resolution of 0.5nm from UV/VIS wavelengths of 270-500nm covering Earth daily (Levelt et al., 2006, Draxler & Rolph, 2003). HYSPLIT is a T&D modeling system that can compute concentrations and trajectories associated with atmospheric emissions. It is flexible in its ability to run normal, matrix and ensemble trajectory models at multiple tropospheric heights and incorporate meteorological data from North American or global sources (R. Draxler, Stunder, Rolph, Stein, & Taylor, 2009). The goal of this research is to identify the important characteristics of an unknown source, such as location, start time, duration of release and the altitude of the top of the release using numerical modeling in tandem with ground/satellite observations. For problems like passive volcanic release where the source is unknown, identifying the location is the primary source term to be estimated. For other problems in which the source location is known, source terms such as duration of the release and the altitude of the top of the release can be determined. By combining the forward and backward modes, the complete potential of the models is fully harnessed. This system combines the high accuracy associated with forward simulations, assuming known source characteristics, with the flexibility of work with unknown sources associated with backward simulations. Ultimately, this will be a useful tool in back tracing any type of spectrally identified emissions to their source, which could include power and chemical plants, smelting operations, and volcanoes for improved SO2 emission monitoring and emergency preparedness. | |
| dc.identifier.uri | https://hdl.handle.net/1920/8475 | |
| dc.language.iso | en | |
| dc.subject | Sulfur dioxide | |
| dc.subject | Ultraviolet remote sensing | |
| dc.subject | OMI | |
| dc.subject | HYSPLIT | |
| dc.subject | Mt. Etna | |
| dc.subject | Nerado del Huila | |
| dc.title | Source Detection of SO2 Emissions with Unknown Origins Using UV Remote Sensing and Numerical Modeling | |
| dc.type | Thesis | |
| thesis.degree.discipline | Earth Systems Science | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Master's | |
| thesis.degree.name | Master of Science in Earth Systems Science |