Southeastern Section - 62nd Annual Meeting (20-21 March 2013)

Paper No. 3
Presentation Time: 8:00 AM-5:30 PM

DETECTION AND ANALYSIS OF GAS AND ASH CLOUDS FROM PACAYA, FUEGO AND SANTIAGUITO VOLCANOES, GUATEMALA, USING SATELLITE IMAGES FROM OMI


MERCADO ROSARIO, Daniel J., University of Puerto Rico, Mayagüez, PO Box 9000, Mayagüez, PR 00681, RODRÍGUEZ, Lizzette A., University of Puerto Rico, Mayagüez, PO Box 9000, Mayaguez, PR 00681, GAETAN, Donna, Leesburg, VA 20175 and CHIGNA, Gustavo, INSIVUMEH, 7a Avenida 14-57 Zona 13, Guatemala City, NA, Guatemala, daniel.mercado1@upr.edu

Monitoring volcanic emissions is crucial to understand volcanic behavior and the different influences these materials exert over the atmosphere, the land and on human health. Studying SO2 emissions through remote sensing techniques with sensors such as the Ozone Monitoring Instrument (OMI) is economically beneficial and work-wise efficient since it can be done for extended periods of time with the analyst in a safe place, away from risk. The SO2 emission trends in this study showed in general that there was an increase in SO2 before eruptions and a decrease later on. The average SO2 fluxes for Pacaya, Fuego, and Santiaguito volcanoes were 750 tonnes per day (t/d), 259 t/d, and 660 t/d, respectively. The highest flux was measured at Pacaya volcano, with 23 kilotons per day emitted on May 29, 2010. Although Pacaya showed the highest flux during the eruptive period, based on the data and comparing with previous fluxes, Fuego is the most consistent SO2 emitter of the Guatemalan volcanoes, since it is constantly degassing detectable fluxes of SO2, which was not observed for either Pacaya or Santiaguito volcanoes. Ash is also a very important volcanic material that needs to be detected due the risk it poses over crops (by damaging them), that could consequently affect livestock, as well as interrupting air traffic. Aerosol Indices (AI) were used to detect ash content in plumes and although some showed moderately good results, in general, most AIs were poor at detecting ash.