Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Contamination and Human Health Risk Assessment of Toxic Trace Elements in Drinking Water of Gilgit-Baltistan, Pakistan

View through CrossRef
This study investigated the contamination level and risk associated with toxic trace elements in springs’ water from Gilgit-Baltistan, Pakistan. Toxic trace elements, including Hg, As, and Zn, were analyzed by metalyzer, HM 2000 serial no. MY-011-006, while elements such as Cr, Al, B, Ni, Cu, Mn, and Fe were analyzed using Metalometer HM 2000 serial no. MM005-007, the United Kingdom. The mean concentrations of TTEs in water samples from Skardu were ordered as, Mn < Cu < Fe < Zn < Al < Cr < As < Ni < Hg, in Gilgit, Mn < Cu < Zn < Ni < B < Cr < Fe < As < Hg, in Ghizer Cu < Mn < Zn < Ni < Cr < Fe < As < Hg, while in Nagar the concentration of TTEs in water samples were ordered as Cu < Mn < Fe < Ni < Al < Cr < Zn < As < Hg. Results obtained from this study showed that the concentrations of As, Hg, Ni, Cr, Al, and Mn in some water samples were higher than the limits recommended by WHO and Pak-NDWQS. However, the chronic daily intake indices (CDIs) and health risk index (HRI) in all samples were found below the US-EPA standards. The correlation analysis revealed a positive association among different elements, which revealed that the sources of TTES in water samples were mainly geological strata and anthropogenic activities.
Title: Contamination and Human Health Risk Assessment of Toxic Trace Elements in Drinking Water of Gilgit-Baltistan, Pakistan
Description:
This study investigated the contamination level and risk associated with toxic trace elements in springs’ water from Gilgit-Baltistan, Pakistan.
Toxic trace elements, including Hg, As, and Zn, were analyzed by metalyzer, HM 2000 serial no.
MY-011-006, while elements such as Cr, Al, B, Ni, Cu, Mn, and Fe were analyzed using Metalometer HM 2000 serial no.
MM005-007, the United Kingdom.
The mean concentrations of TTEs in water samples from Skardu were ordered as, Mn < Cu < Fe < Zn < Al < Cr < As < Ni < Hg, in Gilgit, Mn < Cu < Zn < Ni < B < Cr < Fe < As < Hg, in Ghizer Cu < Mn < Zn < Ni < Cr < Fe < As < Hg, while in Nagar the concentration of TTEs in water samples were ordered as Cu < Mn < Fe < Ni < Al < Cr < Zn < As < Hg.
Results obtained from this study showed that the concentrations of As, Hg, Ni, Cr, Al, and Mn in some water samples were higher than the limits recommended by WHO and Pak-NDWQS.
However, the chronic daily intake indices (CDIs) and health risk index (HRI) in all samples were found below the US-EPA standards.
The correlation analysis revealed a positive association among different elements, which revealed that the sources of TTES in water samples were mainly geological strata and anthropogenic activities.

Related Results

Echinococcus granulosus in Environmental Samples: A Cross-Sectional Molecular Study
Echinococcus granulosus in Environmental Samples: A Cross-Sectional Molecular Study
Abstract Introduction Echinococcosis, caused by tapeworms of the Echinococcus genus, remains a significant zoonotic disease globally. The disease is particularly prevalent in areas...
CLIMATE CHANGE IMPACT ON MOUNTAIN BIODIVERSITY: A SPECIAL REFERENCE TO GILGIT-BALTISTAN OF PAKISTAN
CLIMATE CHANGE IMPACT ON MOUNTAIN BIODIVERSITY: A SPECIAL REFERENCE TO GILGIT-BALTISTAN OF PAKISTAN
Climate Change is not a stationary phenomenon; it moves from time to time, it represents a major threat to mountainous biodiversity and to ecosystem integrity. The present study is...
Climate Change and the Erosion of Traditional Practices: A Case Study of Gilgit-Baltistan
Climate Change and the Erosion of Traditional Practices: A Case Study of Gilgit-Baltistan
This paper examines the local responses towards climate change that impacting the traditional knowledge and practices in Gilgit Baltistan. Gilgit Baltistan is one of the finest tou...
Machine Learning to Access and Ensure Safe Drinking Water Supply: A Systematic Review
Machine Learning to Access and Ensure Safe Drinking Water Supply: A Systematic Review
Drinking water is essential to public health and socioeconomic growth. Therefore, assessing and ensuring drinking water supply is a critical task in modern society. Conventional ap...

Back to Top