Cargando…

An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings

The USA Environmental Protection Agency’s (EPA) Industrial Source Complex Short Term 3 (ISCST3) dispersion modelling code was used to evaluate radon transport and the effects of local variations around tailings dam using a Gaussian plume model. The tailings dam was modelled as point, flat ground and...

Descripción completa

Detalles Bibliográficos
Autores principales: Komati, Frank, Ntwaeaborwa, Martin, Strydom, Rian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266810/
https://www.ncbi.nlm.nih.gov/pubmed/35805860
http://dx.doi.org/10.3390/ijerph19138201
_version_ 1784743560560508928
author Komati, Frank
Ntwaeaborwa, Martin
Strydom, Rian
author_facet Komati, Frank
Ntwaeaborwa, Martin
Strydom, Rian
author_sort Komati, Frank
collection PubMed
description The USA Environmental Protection Agency’s (EPA) Industrial Source Complex Short Term 3 (ISCST3) dispersion modelling code was used to evaluate radon transport and the effects of local variations around tailings dam using a Gaussian plume model. The tailings dam was modelled as point, flat ground and top level, total emitting surface area (true geometry) and volume source geometries. The true area geometry was considered as the baseline source geometry. To improve the accuracy of the model predictions as compared to traditional approaches, the true geometry area source term was corrected to account for cracks and fissures on the tailings and the geometry of tailings dam was modelled by considering all emitting surfaces as sources. Compared to the baseline, the model overpredicted the flat ground area source by up to 274% and underpredicted the top-level area source by up to 50%. The volume emission source was overpredicted by up to 300% in 60% of the modelling runs and underpredicted by 55% in 40% of the volume model runs. While the top-level area source term produced lower concentrations at near-field ground-level receptors, accounting for the wakes effect increased the radon concentrations from the top-level area source of the tailings dam by up to 239%. From the modelling results, the highest concentration predicted by the model from the true geometry source was found to be 0.843 Bq m(−3), which corresponds to the dose of 0.012 mSv/y to the public due to radon from the tailings. This value is less than the 1 mSv/y dose constraint stipulated by the National Nuclear Regulator.
format Online
Article
Text
id pubmed-9266810
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-92668102022-07-09 An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings Komati, Frank Ntwaeaborwa, Martin Strydom, Rian Int J Environ Res Public Health Article The USA Environmental Protection Agency’s (EPA) Industrial Source Complex Short Term 3 (ISCST3) dispersion modelling code was used to evaluate radon transport and the effects of local variations around tailings dam using a Gaussian plume model. The tailings dam was modelled as point, flat ground and top level, total emitting surface area (true geometry) and volume source geometries. The true area geometry was considered as the baseline source geometry. To improve the accuracy of the model predictions as compared to traditional approaches, the true geometry area source term was corrected to account for cracks and fissures on the tailings and the geometry of tailings dam was modelled by considering all emitting surfaces as sources. Compared to the baseline, the model overpredicted the flat ground area source by up to 274% and underpredicted the top-level area source by up to 50%. The volume emission source was overpredicted by up to 300% in 60% of the modelling runs and underpredicted by 55% in 40% of the volume model runs. While the top-level area source term produced lower concentrations at near-field ground-level receptors, accounting for the wakes effect increased the radon concentrations from the top-level area source of the tailings dam by up to 239%. From the modelling results, the highest concentration predicted by the model from the true geometry source was found to be 0.843 Bq m(−3), which corresponds to the dose of 0.012 mSv/y to the public due to radon from the tailings. This value is less than the 1 mSv/y dose constraint stipulated by the National Nuclear Regulator. MDPI 2022-07-05 /pmc/articles/PMC9266810/ /pubmed/35805860 http://dx.doi.org/10.3390/ijerph19138201 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Komati, Frank
Ntwaeaborwa, Martin
Strydom, Rian
An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title_full An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title_fullStr An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title_full_unstemmed An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title_short An In Toto Approach to Radon Dispersion Modelling from a South African Gold Mine Tailings
title_sort in toto approach to radon dispersion modelling from a south african gold mine tailings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266810/
https://www.ncbi.nlm.nih.gov/pubmed/35805860
http://dx.doi.org/10.3390/ijerph19138201
work_keys_str_mv AT komatifrank anintotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings
AT ntwaeaborwamartin anintotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings
AT strydomrian anintotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings
AT komatifrank intotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings
AT ntwaeaborwamartin intotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings
AT strydomrian intotoapproachtoradondispersionmodellingfromasouthafricangoldminetailings