Health risk assessment of heavy metals and predication of water quality indices with using Arc-GIS software: a case study of South Kerman Province-Reference-Cited by-同舟云学术

Health risk assessment of heavy metals and predication of water quality indices with using Arc-GIS software: a case study of South Kerman Province

Published:2023-11-24 Issue: Volume: Page:1-24
ISSN:0306-7319
Container-title:International Journal of Environmental Analytical Chemistry
language:en
Short-container-title:International Journal of Environmental Analytical Chemistry

Author:

Toolabi Ali¹^ORCID,Tahergorabi Mahsa²³,Movahed Ehsan⁴,Moghbely Damaneh Sajad⁵,Moghbely Damaneh Fatemeh⁶,Fanaei Farzad⁷

Affiliation:

1. Environmental Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran

2. Environmental Health Engineering, Jiroft University of Medical Sciences, Jiroft, Iran

3. Department of Environmental Health Engineering, Sirjan School of Medical Sciences, Sirjan, Iran

4. Department of Public Health, Jiroft University of Medical Sciences, Jiroft, Iran

5. Student Research Committee, School of Health, Jiroft University of Medical Sciences, Jiroft, Iran

6. Occupational Health, School of Public Health, Kerman University of Medical Science, Kerman, Iran

7. Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

Publisher

Informa UK Limited

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health,Pollution,Soil Science,Waste Management and Disposal,Water Science and Technology,Environmental Chemistry,Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/03067319.2023.2282053

Reference60 articles.

1. Health risk assessment of heavy metals and their source apportionment in drinking water of Kohistan region, northern Pakistan

2. Metals risk assessment for children's health in water and particulate matter in a southeastern Brazilian city

3. Applications of various data-driven models for the prediction of groundwater quality index in the Akot basin, Maharashtra, India

4. Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models