Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Statistical Analysis of Arsenic Contamination in Drinking Water in a City of Iran and Its Modeling Using Gis Publisher Pubmed



Sadeghi F1 ; Nasseri S1, 2, 3 ; Mosaferi M4 ; Nabizadeh R2, 5 ; Yunesian M2 ; Mesdaghinia A1, 2
Authors

Source: Environmental Monitoring and Assessment Published:2017


Abstract

In this research, probable arsenic contamination in drinking water in the city of Ardabil was studied in 163 samples during four seasons. In each season, sampling was carried out randomly in the study area. Results were analyzed statistically applying SPSS 19 software, and the data was also modeled by Arc GIS 10.1 software. The maximum permissible arsenic concentration in drinking water defined by the World Health Organization and Iranian national standard is 10 μg/L. Statistical analysis showed 75, 88, 47, and 69% of samples in autumn, winter, spring, and summer, respectively, had concentrations higher than the national standard. The mean concentrations of arsenic in autumn, winter, spring, and summer were 19.89, 15.9, 10.87, and 14.6 μg/L, respectively, and the overall average in all samples through the year was 15.32 μg/L. Although GIS outputs indicated that the concentration distribution profiles changed in four consecutive seasons, variance analysis of the results showed that statistically there is no significant difference in arsenic levels in four seasons. © 2017, Springer International Publishing Switzerland.
Experts (# of related papers)
Other Related Docs
10. Human Health Risk Assessment of Trace Elements in Drinking Tap Water in Zahedan City, Iran, Journal of Environmental Health Science and Engineering (2019)
11. Dose-Response Meta-Analysis of Arsenic Exposure in Drinking Water and Intelligence Quotient, Journal of Environmental Health Science and Engineering (2020)
17. Strategies to Reduce the Arsenic Contamination in the Soil-Plant System, Arsenic in Plants: Uptake# Consequences and Remediation Techniques (2022)