Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration

Abstract Mt. Baekdu’s eruption precursors are continuously observed and have become a global social issue. Volcanic activities in neighboring Japan are also active. There are no direct risks of proximity-related disasters in South Korea from the volcanic eruptions at Japan or Mt. Baekdu; however, se...

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Autores principales:	Jooyong Lee, Sungsu Lee, HyunA Son, Waon-ho Yi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1a9c80e9e4194a3da9abde5bbea07020
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spelling	oai:doaj.org-article:1a9c80e9e4194a3da9abde5bbea070202021-12-02T13:18:01ZDevelopment of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration10.1038/s41598-021-86039-y2045-2322https://doaj.org/article/1a9c80e9e4194a3da9abde5bbea070202021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86039-yhttps://doaj.org/toc/2045-2322Abstract Mt. Baekdu’s eruption precursors are continuously observed and have become a global social issue. Volcanic activities in neighboring Japan are also active. There are no direct risks of proximity-related disasters in South Korea from the volcanic eruptions at Japan or Mt. Baekdu; however, severe impacts are expected from the spread of volcanic ash. Numerical analysis models are generally used to predict and analyze the diffusion of volcanic ash, and each numerical analysis model has its own limitations caused by the computational algorithm it employs. In this study, we analyzed the PUFF–UAF model, an ash dispersion model based on the Lagrangian approach, and observed that the number of particles used in tracking substantially affected the results. Even with the presence of millions of particles, the concentration of ash predicted by the PUFF–UAF model does not accurately represent the dispersion. To overcome this deficit and utilize the computational efficiency of the Lagrangian model, we developed a PUFF–Gaussian model to consider the dispersive nature of ash by applying the Gaussian dispersion theory to the results of the PUFF–UAF model. The results of the proposed method were compared with the field measurements from actual volcanic eruptions, and the comparison showed that the proposed method can produce reasonably accurate predictions for ash dispersion.Jooyong LeeSungsu LeeHyunA SonWaon-ho YiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jooyong Lee Sungsu Lee HyunA Son Waon-ho Yi Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
description	Abstract Mt. Baekdu’s eruption precursors are continuously observed and have become a global social issue. Volcanic activities in neighboring Japan are also active. There are no direct risks of proximity-related disasters in South Korea from the volcanic eruptions at Japan or Mt. Baekdu; however, severe impacts are expected from the spread of volcanic ash. Numerical analysis models are generally used to predict and analyze the diffusion of volcanic ash, and each numerical analysis model has its own limitations caused by the computational algorithm it employs. In this study, we analyzed the PUFF–UAF model, an ash dispersion model based on the Lagrangian approach, and observed that the number of particles used in tracking substantially affected the results. Even with the presence of millions of particles, the concentration of ash predicted by the PUFF–UAF model does not accurately represent the dispersion. To overcome this deficit and utilize the computational efficiency of the Lagrangian model, we developed a PUFF–Gaussian model to consider the dispersive nature of ash by applying the Gaussian dispersion theory to the results of the PUFF–UAF model. The results of the proposed method were compared with the field measurements from actual volcanic eruptions, and the comparison showed that the proposed method can produce reasonably accurate predictions for ash dispersion.
format	article
author	Jooyong Lee Sungsu Lee HyunA Son Waon-ho Yi
author_facet	Jooyong Lee Sungsu Lee HyunA Son Waon-ho Yi
author_sort	Jooyong Lee
title	Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
title_short	Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
title_full	Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
title_fullStr	Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
title_full_unstemmed	Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
title_sort	development of puff–gaussian dispersion model for the prediction of atmospheric distribution of particle concentration
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1a9c80e9e4194a3da9abde5bbea07020
work_keys_str_mv	AT jooyonglee developmentofpuffgaussiandispersionmodelforthepredictionofatmosphericdistributionofparticleconcentration AT sungsulee developmentofpuffgaussiandispersionmodelforthepredictionofatmosphericdistributionofparticleconcentration AT hyunason developmentofpuffgaussiandispersionmodelforthepredictionofatmosphericdistributionofparticleconcentration AT waonhoyi developmentofpuffgaussiandispersionmodelforthepredictionofatmosphericdistributionofparticleconcentration
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Development of PUFF–Gaussian dispersion model for the prediction of atmospheric distribution of particle concentration

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