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Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software

Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected acros...

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Autores principales: Badeenezhad, Ahmad, Soleimani, Hamed, Shahsavani, Samaneh, Parseh, Iman, Mohammadpour, Amin, Azadbakht, Omid, Javanmardi, Parviz, Faraji, Hossein, Babakrpur Nalosi, Kamal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517167/
https://www.ncbi.nlm.nih.gov/pubmed/37740101
http://dx.doi.org/10.1038/s41598-023-43161-3
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author Badeenezhad, Ahmad
Soleimani, Hamed
Shahsavani, Samaneh
Parseh, Iman
Mohammadpour, Amin
Azadbakht, Omid
Javanmardi, Parviz
Faraji, Hossein
Babakrpur Nalosi, Kamal
author_facet Badeenezhad, Ahmad
Soleimani, Hamed
Shahsavani, Samaneh
Parseh, Iman
Mohammadpour, Amin
Azadbakht, Omid
Javanmardi, Parviz
Faraji, Hossein
Babakrpur Nalosi, Kamal
author_sort Badeenezhad, Ahmad
collection PubMed
description Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected across wet and dry seasons. Water quality was comprehensively assessed using several indices, including the heavy metals evaluation index (HEI), heavy metal pollution index (HPI), contamination degree (CD), and metal index (MI). Carcinogenic and non-carcinogenic risk assessments were conducted using deterministic and probabilistic approaches for exposed populations. In the non-carcinogenic risk assessment, the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) are employed. The precision of risk assessment was bolstered through the utilization of Monte Carlo simulation, executed using the R software platform. Based on the results, in both wet and dry seasons, Zinc (Zn) consistently demonstrates the highest mean concentration, followed by Manganese (Mn) and Chromium (Cr). During the wet and dry seasons, 25% and 40% of the regions exhibited high CD, respectively. According to non-carcinogenic risk assessment, Cr presents the highest CDI and HQ in children and adults, followed by Mn, As and HI values, indicating elevated risk for children. The highest carcinogenic risk was for Cr in adults, while the lowest was for Cd in children. The sensitivity analysis found that heavy metal concentration and ingestion rate significantly impact both carcinogenic and non-carcinogenic risks. These findings provide critical insights for shaping policy and allocating resources towards effectively managing heavy metal contamination in residential drinking water.
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spelling pubmed-105171672023-09-24 Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software Badeenezhad, Ahmad Soleimani, Hamed Shahsavani, Samaneh Parseh, Iman Mohammadpour, Amin Azadbakht, Omid Javanmardi, Parviz Faraji, Hossein Babakrpur Nalosi, Kamal Sci Rep Article Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected across wet and dry seasons. Water quality was comprehensively assessed using several indices, including the heavy metals evaluation index (HEI), heavy metal pollution index (HPI), contamination degree (CD), and metal index (MI). Carcinogenic and non-carcinogenic risk assessments were conducted using deterministic and probabilistic approaches for exposed populations. In the non-carcinogenic risk assessment, the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) are employed. The precision of risk assessment was bolstered through the utilization of Monte Carlo simulation, executed using the R software platform. Based on the results, in both wet and dry seasons, Zinc (Zn) consistently demonstrates the highest mean concentration, followed by Manganese (Mn) and Chromium (Cr). During the wet and dry seasons, 25% and 40% of the regions exhibited high CD, respectively. According to non-carcinogenic risk assessment, Cr presents the highest CDI and HQ in children and adults, followed by Mn, As and HI values, indicating elevated risk for children. The highest carcinogenic risk was for Cr in adults, while the lowest was for Cd in children. The sensitivity analysis found that heavy metal concentration and ingestion rate significantly impact both carcinogenic and non-carcinogenic risks. These findings provide critical insights for shaping policy and allocating resources towards effectively managing heavy metal contamination in residential drinking water. Nature Publishing Group UK 2023-09-22 /pmc/articles/PMC10517167/ /pubmed/37740101 http://dx.doi.org/10.1038/s41598-023-43161-3 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
Badeenezhad, Ahmad
Soleimani, Hamed
Shahsavani, Samaneh
Parseh, Iman
Mohammadpour, Amin
Azadbakht, Omid
Javanmardi, Parviz
Faraji, Hossein
Babakrpur Nalosi, Kamal
Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title_full Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title_fullStr Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title_full_unstemmed Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title_short Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software
title_sort comprehensive health risk analysis of heavy metal pollution using water quality indices and monte carlo simulation in r software
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517167/
https://www.ncbi.nlm.nih.gov/pubmed/37740101
http://dx.doi.org/10.1038/s41598-023-43161-3
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