Sensitivity analysis of dispersion modeling of volcanic ash from Eyjafjallajökull in May 2010

2012 ◽  
Vol 117 (D20) ◽  
Author(s):  
B. J. Devenish ◽  
P. N. Francis ◽  
B. T. Johnson ◽  
R. S. J. Sparks ◽  
D. J. Thomson
Keyword(s):  
Sensitivity Analysis ◽  
Volcanic Ash ◽  
Dispersion Modeling ◽  
Analysis Of Dispersion

scholarly journals Determination of time- and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Eyjafjallajökull eruption

2011 ◽  
Vol 11 (9) ◽  
pp. 4333-4351 ◽  
Author(s):  
A. Stohl ◽  
A. J. Prata ◽  
S. Eckhardt ◽  
L. Clarisse ◽  
A. Durant ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
General Nature ◽  
Aviation Industry ◽  
Dispersion Modeling ◽  
Source Information ◽  
European Area ◽  
Ash Dispersion

Abstract. The April–May, 2010 volcanic eruptions of Eyjafjallajökull, Iceland caused significant economic and social disruption in Europe whilst state of the art measurements and ash dispersion forecasts were heavily criticized by the aviation industry. Here we demonstrate for the first time that large improvements can be made in quantitative predictions of the fate of volcanic ash emissions, by using an inversion scheme that couples a priori source information and the output of a Lagrangian dispersion model with satellite data to estimate the volcanic ash source strength as a function of altitude and time. From the inversion, we obtain a total fine ash emission of the eruption of 8.3 ± 4.2 Tg for particles in the size range of 2.8–28 μm diameter. We evaluate the results of our model results with a posteriori ash emissions using independent ground-based, airborne and space-borne measurements both in case studies and statistically. Subsequently, we estimate the area over Europe affected by volcanic ash above certain concentration thresholds relevant for the aviation industry. We find that during three episodes in April and May, volcanic ash concentrations at some altitude in the atmosphere exceeded the limits for the "Normal" flying zone in up to 14 % (6–16 %), 2 % (1–3 %) and 7 % (4–11 %), respectively, of the European area. For a limit of 2 mg m−3 only two episodes with fractions of 1.5 % (0.2–2.8 %) and 0.9 % (0.1–1.6 %) occurred, while the current "No-Fly" zone criterion of 4 mg m−3 was rarely exceeded. Our results have important ramifications for determining air space closures and for real-time quantitative estimations of ash concentrations. Furthermore, the general nature of our method yields better constraints on the distribution and fate of volcanic ash in the Earth system.

Volcanic-ash dispersion modeling of the 2006 eruption of Augustine Volcano using the Puff model: Chapter 21 in The 2006 eruption of Augustine Volcano, Alaska

2010 ◽  
pp. 507-526 ◽  
Author(s):  
Peter W. Webley ◽  
Kenneson G. Dean ◽  
Jonathan Dehn ◽  
John E. Bailey ◽  
Rorik Peterson
Keyword(s):  
Volcanic Ash ◽  
Dispersion Modeling ◽  
Ash Dispersion ◽  
2006 Eruption

Dispersion modeling of volcanic ash clouds: North Pacific eruptions, the past 40 years: 1970–2010

2011 ◽  
Vol 61 (2) ◽  
pp. 661-671 ◽  
Author(s):  
P. W. Webley ◽  
K. Dean ◽  
R. Peterson ◽  
A. Steffke ◽  
M. Harrild ◽  
...  
Keyword(s):  
North Pacific ◽  
Volcanic Ash ◽  
Dispersion Modeling ◽  
The Past

scholarly journals NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System

2015 ◽  
Vol 96 (12) ◽  
pp. 2059-2077 ◽  
Author(s):  
A. F. Stein ◽  
R. R. Draxler ◽  
G. D. Rolph ◽  
B. J. B. Stunder ◽  
M. D. Cohen ◽  
...  
Keyword(s):  
Single Particle ◽  
Volcanic Ash ◽  
Atmospheric Transport ◽  
Hazardous Materials ◽  
Dispersion Modeling ◽  
Historical Evolution ◽  
Back Trajectories ◽  
Deposition Of Pollutants ◽  
Wild Fires ◽  
Atmospheric Tracer

Abstract The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), developed by NOAA’s Air Resources Laboratory, is one of the most widely used models for atmospheric trajectory and dispersion calculations. We present the model’s historical evolution over the last 30 years from simple hand-drawn back trajectories to very sophisticated computations of transport, mixing, chemical transformation, and deposition of pollutants and hazardous materials. We highlight recent applications of the HYSPLIT modeling system, including the simulation of atmospheric tracer release experiments, radionuclides, smoke originated from wild fires, volcanic ash, mercury, and wind-blown dust.

Sensitivity Analysis of Dispersion Models for Point and Area Sources

1982 ◽  
Vol 32 (10) ◽  
pp. 1024-1028 ◽  
Author(s):  
Gerhard Gschwandtner ◽  
Kevin Eldridge ◽  
Robert Zerbonia
Keyword(s):  
Sensitivity Analysis ◽  
Dispersion Models ◽  
Analysis Of Dispersion

Global and local sensitivity analysis of the Emission Dispersion Model input parameters

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samia Chettouh
Keyword(s):  
Sensitivity Analysis ◽  
Wind Speed ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Dispersion Modeling ◽  
Content Type ◽  
Initial Concentration ◽  
Model Input ◽  
Input Parameters ◽  
Industrial Fire

PurposeThe objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO2 generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO2) emitted by an industrial fire in a plant located in an industrial region site in Algeria.Design/methodology/approachThe SA was defined for the following input parameters: wind speed, NO2 emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient.FindingsThe study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO2 initial concentration has the most influence on the predicted NO2 levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO2 concentration estimation.Originality/valueThe study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.

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