An ontology-based study on water quality: probabilistic risk assessment of exposure to fluoride and nitrate in Shiraz drinking water, Iran using fuzzy multi-criteria group decision-making models

Shahsavani, Samaneh; Mohammadpour, Amin; Shooshtarian, Mohammad Reza; Soleimani, Hamed; Ghalhari, Mohammad Rezvani; Badeenezhad, Ahmad; Baboli, Zeynab; Morovati, Roya; Javanmardi, Parviz

doi:10.1007/s10661-022-10664-x

Cited by 24 publications

(5 citation statements)

References 38 publications

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“…2 , the trend of Cd concentration was changed from the southern area in the dry season to the south and southwestern regions of the study area in the wet season (max = 8.86 µg/l in the wet season and 8.17 µg/l in the dry season), with a broader range of the study area experiencing water quality deterioration over time. The high levels in central, southern, and southwestern areas may be due to oxidation and acidification through groundwater pumping, excessive nitrate entry through agricultural fertilizers, and even industrial zones west of the study area 40 .…”

Section: Resultsmentioning

confidence: 99%

“…Table 1 gives the input parameters in the CDI formula, and Eq. ( 1 ) provided below are employed to calculate the CDI values 25 : where CDI chronic daily intake (mg/kg/day), Ci the individual metal concentrations (μg/l), IR the ingestion rate (l/day), EF exposure frequency (days/year), ED The exposure duration (year), BW the average body weight (kg/person), AT the average time (in days).…”

Section: Methodsmentioning

confidence: 99%

“…To determine the geographic coordinates of the sampling locations, a portable GPS device (Model No. GARMIN MONTANA 650, USA) was utilized, providing latitude, longitude, and Universal Transverse Mercator (UTM) coordinates 40 .…”

Section: Methodsmentioning

confidence: 99%

“…Table 1 gives the input parameters in the CDI formula, and Eq. ( 1) provided below are employed to calculate the CDI values 25 :…”

Section: Non-carcinogenic Risk Assessmentmentioning

confidence: 99%

“…The high levels in central, southern, and southwestern areas may be due to oxidation and acidification through groundwater pumping, excessive nitrate entry through agricultural fertilizers, and even industrial zones west of the study area 40 .…”

Section: Groundwater Contamination and The Distribution Of Heavy Meta...mentioning

confidence: 99%

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Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software

Badeenezhad,

Soleimani,

Shahsavani

et al. 2023

Sci Rep

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Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected across wet and dry seasons. Water quality was comprehensively assessed using several indices, including the heavy metals evaluation index (HEI), heavy metal pollution index (HPI), contamination degree (CD), and metal index (MI). Carcinogenic and non-carcinogenic risk assessments were conducted using deterministic and probabilistic approaches for exposed populations. In the non-carcinogenic risk assessment, the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) are employed. The precision of risk assessment was bolstered through the utilization of Monte Carlo simulation, executed using the R software platform. Based on the results, in both wet and dry seasons, Zinc (Zn) consistently demonstrates the highest mean concentration, followed by Manganese (Mn) and Chromium (Cr). During the wet and dry seasons, 25% and 40% of the regions exhibited high CD, respectively. According to non-carcinogenic risk assessment, Cr presents the highest CDI and HQ in children and adults, followed by Mn, As and HI values, indicating elevated risk for children. The highest carcinogenic risk was for Cr in adults, while the lowest was for Cd in children. The sensitivity analysis found that heavy metal concentration and ingestion rate significantly impact both carcinogenic and non-carcinogenic risks. These findings provide critical insights for shaping policy and allocating resources towards effectively managing heavy metal contamination in residential drinking water.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Table 1 gives the input parameters in the CDI formula, and Eq. ( 1) provided below are employed to calculate the CDI values 25 :…”

Section: Non-carcinogenic Risk Assessmentmentioning

confidence: 99%

Section: Groundwater Contamination and The Distribution Of Heavy Meta...mentioning

confidence: 99%