A probabilistic-deterministic analysis of human health risk related to the exposure to potentially toxic elements in groundwater of Urmia coastal aquifer (NW of Iran) with a special focus on arsenic speciation and temporal variation

• Published in: Stochastic environmental research and risk assessment Vol. 35; no. 7; pp. 1509 - 1528
• Main Authors: Sohrabi, Nassim, Kalantari, Nasrollah, Amiri, Vahab, Saha, Narottam, Berndtsson, Ronny, Bhattacharya, Prosun, Ahmad, Arslan
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2021; Springer Nature B.V
• Subjects: Aluminum; Aquatic Pollution; Aquifers; Arbetsmedicin och miljömedicin; Arsenic; Arsenic speciation; Barium; Cadmium; Carcinogenic health risk; Carcinogens; Chemistry and Earth Sciences; Clay minerals; Coastal aquifers; Coastal waters; Computational Intelligence; Computer Science; Contamination; Controlling mechanism; Copper; Deterministic analysis; Deterministic and probabilistic estimation; Earth and Environmental Science; Earth Sciences; Element concentrations; Environment; Environmental Health and Occupational Health; Exposure; Groundwater; Groundwater contamination; Groundwater pollution; Groundwater resources; Health; Health risk assessment; Health risks; Health Sciences; Hälsovetenskap; Ingestion; Iron; Iron compounds; Lead; Manganese; Math. Appl. in Environmental Science; Medical and Health Sciences; Medicin och hälsovetenskap; Minerals; Monte Carlo methods; Monte Carlo simulation; Multivariant analysis; Multivariate analysis; Multivariate statistics; Nickel; Original Paper; Physics; Potentially toxic elements; Probability Theory and Stochastic Processes; Public health; Public risks; Reductive dissolution; Risk assessment; Risk perception; Selenium; Sensitivity analysis; Significant variables; Speciation; Statistical analysis; Statistical methods; Statistics for Engineering; Temporal variations; Waste Water Technology; Water analysis; Water consumption; Water Management; Water pollution; Water Pollution Control; Water resources; Water sampling; Zinc; Deterministic and probabilistic estimation; Arsenic speciation; Groundwater pollution; Carcinogenic health risk; Monte Carlo simulation
• ISSN: 1436-3240; 1436-3259; 1436-3259
• DOI: 10.1007/s00477-020-01934-6

The human exposure to groundwater contamination with toxic elements is a worldwide concern. In this study, multivariate statistics coupled with probabilistic and deterministic risk estimation approaches were applied to 173 groundwater samples of Urmia aquifer (UA) to evaluate human health risks in relation to the consumption of groundwater contaminated with toxic elements. The concentrations of aluminum (Al), barium (Ba), cadmium (Cd), copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn) were below their corresponding maximum permissible levels as advised by the WHO, USEPA, and Iranian guidelines. However, arsenic (As), lead (Pb), iron (Fe), and selenium (Se) were elevated at some locations. Monte Carlo simulation-based probabilistic risk estimation suggested ingestion as the dominant pathway for water-hosted element exposure. Mean values of hazard index estimated for As exposure from combined ingestion and dermal contact pathways exceeded the safe level of 1.0 for both adults and children, indicated potential non-carcinogenic health risks. The total cancer risk induced by groundwater As exceeded the acceptable limit of 1 × 10 –4 . Sensitivity analysis highlighted exposure duration, element concentration in water, and average time as the most significant variables causing the probable health risks. Speciation modeling using PHREEQC highlighted the occurrence of As(V) and As(III) in groundwater of the UA. Reductive dissolution of Fe(III) (oxyhydr)oxides and clay minerals was identified as the main controlling mechanism of As mobilization. This communication emphasizes the need for appropriate approaches in mitigating toxic element contamination of water resources in coastal parts of the UA to safeguard public health from carcinogenic and non-carcinogenic risks.