LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Numerical Simulations of Volcanic Ash Plume Dispersal for Sakura-Jima Using Real-Time Emission Rate Estimation

Photo from wikipedia

In this study, a real-time volcanic ash dispersion model called PUFF is applied to the Sakura-jima volcano erupted on 16 June 2018 to assess the performance of the new system… Click to show full abstract

In this study, a real-time volcanic ash dispersion model called PUFF is applied to the Sakura-jima volcano erupted on 16 June 2018 to assess the performance of the new system connected with a real-time emission rate estimation. The emission rate of the ash mass from the vent is estimated based on an empirical formula developed for the Sakura-jima volcano using seismic monitoring and ground deformation data. According to the time series of the estimated emission rate, a major eruption occurred at 7:20 JST indicating an emission rate of 1000 t/min and continued for 15 min showing a plume height of 4500 m. It is observed that we need to introduce an adjusting constant to fit the model prediction of the ash fallout with the ground observation. Once the particle mass is calibrated, the distributions of ash fallout are compared with other eruption events to confirm the model performance. According to the PUFF model simulations, an airborne ash concentration of 100 mg/m3extends to a wide area around the volcano within one hour after the eruption. The simulation result quantitatively indicates the location of the danger zone for commercial airliners. The PUFF model system combined with the real-time emission rate estimation is useful for aviation safety purposes as well as for ground transportation and human health around active volcanoes.

Keywords: emission rate; real time; emission; sakura jima

Journal Title: Journal of Disaster Research
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.