Spatial Analysis and Soft Computational Modeling for Hazard Assessment of Potential Toxic Elements in Potable Groundwater

Overview

Journal Sci Rep

Specialty Science

Date 2024 Oct 27

PMID 39461981

Authors

R S Aswal

Mukesh Prasad

Jaswinder Singh

Hakam Singh

Utpal Shrivastava

Manoj Wadhwa

Om Prakash Pandey

Johnbosco C Egbueri

Affiliations

Soon will be listed here.

Abstract

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

References

Ghaffari H, Kamari Z, Ranaei V, Pilevar Z, Akbari M, Moridi M . The concentration of potentially hazardous elements (PHEs) in drinking water and non-carcinogenic risk assessment: A case study in Bandar Abbas, Iran. Environ Res. 2021; 201:111567. DOI: 10.1016/j.envres.2021.111567. View

Zhen J, Wang Z, Ni B, Ismail S, El-Baz A, Cui Z . Synergistic Integration of Anammox and Endogenous Denitrification Processes for the Simultaneous Carbon, Nitrogen, and Phosphorus Removal. Environ Sci Technol. 2024; 58(24):10632-10643. DOI: 10.1021/acs.est.4c00558. View

Antoniadis V, Shaheen S, Boersch J, Frohne T, Du Laing G, Rinklebe J . Bioavailability and risk assessment of potentially toxic elements in garden edible vegetables and soils around a highly contaminated former mining area in Germany. J Environ Manage. 2016; 186(Pt 2):192-200. DOI: 10.1016/j.jenvman.2016.04.036. View

Hassen I, Hamzaoui-Azaza F, Bouhlila R . Application of multivariate statistical analysis and hydrochemical and isotopic investigations for evaluation of groundwater quality and its suitability for drinking and agriculture purposes: case of Oum Ali-Thelepte aquifer, central Tunisia. Environ Monit Assess. 2016; 188(3):135. DOI: 10.1007/s10661-016-5124-7. View

Prasad M, Aswal R, Joshi A, Kumar G, Ramola R . A systematic study on occurrence, risk estimation and health implications of heavy metals in potable water from different sources of Garhwal Himalaya, India. Sci Rep. 2022; 12(1):20419. PMC: 9705413. DOI: 10.1038/s41598-022-24925-9. View

Bangotra P, Jakhu R, Prasad M, Aswal R, Ashish A, Mushtaq Z . Investigation of heavy metal contamination and associated health risks in groundwater sources of southwestern Punjab, India. Environ Monit Assess. 2023; 195(3):367. DOI: 10.1007/s10661-023-10959-7. View

Giri S, Singh A . Human health risk assessment via drinking water pathway due to metal contamination in the groundwater of Subarnarekha River Basin, India. Environ Monit Assess. 2015; 187(3):63. DOI: 10.1007/s10661-015-4265-4. View

Dudeja D, Bartarya S, Biyani A . Hydrochemical and water quality assessment of groundwater in Doon Valley of Outer Himalaya, Uttarakhand, India. Environ Monit Assess. 2011; 181(1-4):183-204. DOI: 10.1007/s10661-010-1823-7. View

Nayak A, Matta G, Uniyal D . Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas. Environ Dev Sustain. 2022; :1-32. PMC: 9468253. DOI: 10.1007/s10668-022-02661-4. View

10.

Aswal R, Prasad M, Patel N, Srivastav A, Egbueri J, Kumar G . Occurrences, sources and health hazard estimation of potentially toxic elements in the groundwater of Garhwal Himalaya, India. Sci Rep. 2023; 13(1):13069. PMC: 10421880. DOI: 10.1038/s41598-023-40266-7. View

11.

Sharma T, Litoria P, Bajwa B, Kaur I . Appraisal of groundwater quality and associated risks in Mansa district (Punjab, India). Environ Monit Assess. 2021; 193(4):159. DOI: 10.1007/s10661-021-08892-8. View

12.

Egbueri J, Enyigwe M, Ayejoto D . Modeling the impact of potentially harmful elements on the groundwater quality of a mining area (Nigeria) by integrating NSFWQI, HERisk code, and HCs. Environ Monit Assess. 2022; 194(3):150. DOI: 10.1007/s10661-022-09789-w. View

13.

Mukherjee A, Agrawal S, Agrawal M . Responses of tropical tree species to urban air pollutants: ROS/RNS formation and scavenging. Sci Total Environ. 2020; 710:136363. DOI: 10.1016/j.scitotenv.2019.136363. View

14.

Zhitkovich A . Chromium in drinking water: sources, metabolism, and cancer risks. Chem Res Toxicol. 2011; 24(10):1617-29. PMC: 3196244. DOI: 10.1021/tx200251t. View

15.

Beaumont J, Sedman R, Reynolds S, Sherman C, Li L, Howd R . Cancer mortality in a Chinese population exposed to hexavalent chromium in drinking water. Epidemiology. 2007; 19(1):12-23. DOI: 10.1097/EDE.0b013e31815cea4c. View

16.

Wu B, Zhao D, Jia H, Zhang Y, Zhang X, Cheng S . Preliminary risk assessment of trace metal pollution in surface water from Yangtze River in Nanjing Section, China. Bull Environ Contam Toxicol. 2009; 82(4):405-9. DOI: 10.1007/s00128-008-9497-3. View