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Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India
This case drew national attention in 2018. About 100 people died and more than 300 hospitalized in a span of few years in a village of 1200 people in a tribal stretch in central India. Medical teams visiting the area reported severe renal failure and blamed the local eating and drinking habits as ca...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630383/ https://www.ncbi.nlm.nih.gov/pubmed/37935700 http://dx.doi.org/10.1038/s41598-023-45622-1 |
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author | Herojeet, Rajkumar Dewangan, Rakesh K. Naik, Pradeep K. Verma, Janak R. |
author_facet | Herojeet, Rajkumar Dewangan, Rakesh K. Naik, Pradeep K. Verma, Janak R. |
author_sort | Herojeet, Rajkumar |
collection | PubMed |
description | This case drew national attention in 2018. About 100 people died and more than 300 hospitalized in a span of few years in a village of 1200 people in a tribal stretch in central India. Medical teams visiting the area reported severe renal failure and blamed the local eating and drinking habits as causative factors. This human health assessment based on geochemical investigations finds nitrate (NO(3)(−)) and fluoride (F(−)) pollution as well in village’s groundwater. Both deterministic and probabilistic techniques are employed to decipher the contamination pathways and extent of contamination. Source apportionments of NO(3)(−) and F(−) and their relationship with other ions in groundwater are carried out through chemometric modelling. Latent factors controlling the hydrogeochemistry of groundwater too are explored. While hazard quotients ([Formula: see text] ) of the chemical parameters ([Formula: see text] and [Formula: see text] ) identify ingestion as the prominent pathway, the calculated risk certainty levels (RCL) of the hazard index (HI) values above unity are compared between the deterministic and probabilistic approaches. Deterministic model overestimates the HI values and magnify the contamination problems. Probabilistic model gives realistic results that stand at infants ([Formula: see text] = 34.03%, [Formula: see text] = 24.17%) > children ([Formula: see text] = 23.01%, [Formula: see text] = 10.56%) > teens ([Formula: see text] = 13.17%, [Formula: see text] = 2.00%) > adults ([Formula: see text] = 11.62%, [Formula: see text] = 1.25%). Geochemically, about 90% of the samples are controlled by rock-water interaction with Ca(2+)–Mg(2+)–HCO(3)(−) (~ 56%) as the dominant hydrochemical facies. Chemometric modelling confirms Ca(2+), Mg(2+), HCO(3)(−), F(−), and SO(4)(2−) to originate from geogenic sources, Cl(−) and NO(3)(−) from anthropogenic inputs and Na(+) and K(+) from mixed factors. The area needs treated groundwater for human consumption. |
format | Online Article Text |
id | pubmed-10630383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106303832023-11-07 Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India Herojeet, Rajkumar Dewangan, Rakesh K. Naik, Pradeep K. Verma, Janak R. Sci Rep Article This case drew national attention in 2018. About 100 people died and more than 300 hospitalized in a span of few years in a village of 1200 people in a tribal stretch in central India. Medical teams visiting the area reported severe renal failure and blamed the local eating and drinking habits as causative factors. This human health assessment based on geochemical investigations finds nitrate (NO(3)(−)) and fluoride (F(−)) pollution as well in village’s groundwater. Both deterministic and probabilistic techniques are employed to decipher the contamination pathways and extent of contamination. Source apportionments of NO(3)(−) and F(−) and their relationship with other ions in groundwater are carried out through chemometric modelling. Latent factors controlling the hydrogeochemistry of groundwater too are explored. While hazard quotients ([Formula: see text] ) of the chemical parameters ([Formula: see text] and [Formula: see text] ) identify ingestion as the prominent pathway, the calculated risk certainty levels (RCL) of the hazard index (HI) values above unity are compared between the deterministic and probabilistic approaches. Deterministic model overestimates the HI values and magnify the contamination problems. Probabilistic model gives realistic results that stand at infants ([Formula: see text] = 34.03%, [Formula: see text] = 24.17%) > children ([Formula: see text] = 23.01%, [Formula: see text] = 10.56%) > teens ([Formula: see text] = 13.17%, [Formula: see text] = 2.00%) > adults ([Formula: see text] = 11.62%, [Formula: see text] = 1.25%). Geochemically, about 90% of the samples are controlled by rock-water interaction with Ca(2+)–Mg(2+)–HCO(3)(−) (~ 56%) as the dominant hydrochemical facies. Chemometric modelling confirms Ca(2+), Mg(2+), HCO(3)(−), F(−), and SO(4)(2−) to originate from geogenic sources, Cl(−) and NO(3)(−) from anthropogenic inputs and Na(+) and K(+) from mixed factors. The area needs treated groundwater for human consumption. Nature Publishing Group UK 2023-11-07 /pmc/articles/PMC10630383/ /pubmed/37935700 http://dx.doi.org/10.1038/s41598-023-45622-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Herojeet, Rajkumar Dewangan, Rakesh K. Naik, Pradeep K. Verma, Janak R. Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title | Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title_full | Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title_fullStr | Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title_full_unstemmed | Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title_short | Probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central India |
title_sort | probabilistic modelling is superior to deterministic approaches in the human health risk assessment: an example from a tribal stretch in central india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630383/ https://www.ncbi.nlm.nih.gov/pubmed/37935700 http://dx.doi.org/10.1038/s41598-023-45622-1 |
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