Bottled water safety evaluation: A comprehensive health risk assessment of oral exposure to heavy metals through deterministic and probabilistic approaches by Monte Carlo simulation.

The consumption of bottled water has witnessed substantial global expansion in recent times. This study aimed to quantitatively evaluate the concentrations of eight heavy metals (As, Ba, Cd, Cr, Mn, Mo, Ni, and Zn) in 71 high-consumption bottled water brands in Iran. Non-carcinogenic and carcinogenic risk assessments were conducted using both deterministic and probabilistic approaches. Point estimation utilizing the Hazard Quotient (HQ) formula and sensitivity analysis employing the Monte Carlo Simulation (MCS) method through 10,000 repetitions in Oracle Crystal Ball® was used to ascertain the health risks associated with heavy metal exposure. Heavy metal concentrations were quantified through Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). HQ point estimation results indicated that Cr exhibited the highest mean HQ value, whereas Cd demonstrated the lowest. In the probabilistic approach, the highest 95 percentile values were observed for Cr and Mo at 3.9E-01, while the lowest values were recorded for Cr and Mn at 1.10E-02. Heavy metal concentrations emerged as critical factors influencing non-carcinogenic and carcinogenic risks across all groups in the sensitivity analysis. The findings highlight the need for ongoing monitoring, research, and targeted regulations to address health risks from heavy metal exposure in bottled water and ensure public well-being.

Prediction of human health risk and disability-adjusted life years induced by heavy metals exposure through drinking water in Fars Province, Iran.

Exposure to heavy metals in contaminated drinking water is strongly correlated with various cancers, highlighting the burden of disease. This study aimed to assess the non-carcinogenic and carcinogenic risks associated with exposure to heavy metals (As, Pb, Cd, and Cr) in drinking water of Fars province and evaluate the attributed burden of disease. Non-carcinogenic risk assessment was performed using the hazard quotient (HQ) method, while the carcinogenic risk assessment utilized the excess lifetime cancer risk approach. The burden of disease was evaluated in terms of years of life lost, years lived with disability, and disability-adjusted life years (DALY) for three specific cancers: skin, lung, and kidney cancer. The average drinking water concentrations of arsenic (As), cadmium (Cd), chromium (Cr) and lead (Pb) were determined to be 0.72, 0.4, 1.10 and 0.72 µg/L, respectively. The total average HQ of heavy metals in drinking water in the study area were 0.127, 0.0047, 0.0009 and 0.0069, respectively. The average ILCRs of heavy metal in the entire country were in the following order: 1.15 × 10-5 for As, 2.22 × 10-7 for Cd and 3.41 × 10-7 for Cr. The results also indicated that among the various counties analyzed, Fasa experiences the greatest burden of disease in terms of DALYs, with a value of 87.56, specifically attributed to cancers caused by exposure to arsenic. Generally, it can be said that the burden of disease is a critical aspect of public health that requires comprehensive understanding and effective intervention.

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

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.

4-Chlorophenol adsorption from water solutions by activated carbon functionalized with amine groups: response surface method and artificial neural networks.

4-Chlorophenol pollution is a significant environmental concern. In this study, powdered activated carbon modified with amine groups is synthesized and investigated its efficiency in removing 4-chlorophenols from aqueous environments. Response surface methodology (RSM) and central composite design (CCD) were used to investigate the effect of different parameters, including pH, contact time, adsorbent dosage, and initial 4-chlorophenol concentration, on 4-chlorophenol removal efficiency. The RSM-CCD approach was implemented in R software to design and analyze the experiments. The statistical analysis of variance (ANOVA) was used to describe the roles of effecting parameters on response. Isotherm and kinetic studies were done with three Langmuir, Freundlich, and Temkin isotherm models and four pseudo-first-order, pseudo-second-order, Elovich, and intraparticle kinetic models in both linear and non-linear forms. The synthesized adsorbent was characterized using X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) analyses. The results showed that the synthesized modified activated carbon had a maximum adsorption capacity of 316.1 mg/g and exhibited high efficiency in removing 4-chlorophenols. The optimal conditions for the highest removal efficiency were an adsorbent dosage of 0.55 g/L, contact time of 35 min, initial concentration of 4-chlorophenol of 110 mg/L, and pH of 3. The thermodynamic study indicated that the adsorption process was exothermic and spontaneous. The synthesized adsorbent also showed excellent reusability even after five successive cycles. These findings demonstrate the potential of modified activated carbon as an effective method for removing 4-chlorophenols from aqueous environments and contributing to developing sustainable and efficient water treatment technologies.

Acidic modification of natural stone for Remazol Black B dye adsorption from aqueous solution- central composite design (CCD) and response surface methodology (RSM).

This study investigated the adsorption capacity of Remazol Black B (RBB) from aqueous solutions using a pumice stone as a cheap, high-frequent, and available adsorbent. The raw pumice was modified using five acids: Acetic, Sulfuric, Phosphoric, Nitric, and Hydrochloric acid. Fourier transform infrared spectrograph (FTIR), x-ray fluorescence (XRF), and scanning electron microscopy (SEM) were used to analyze the morphological and chemical properties of raw and modified adsorbents. The adsorption capacity equilibrium was investigated using the Langmuir, Freundlich, Temkin, and Dubinin - Radushkevich isotherms. The results indicated that the data are well-fitted with Langmuir isotherm. The maximum adsorption capacity was observed when pumice modified with H2SO4 (qm = 10.00 mg/g) was used, and the RBB removal efficiency was higher than that for raw pumice (qm = 5.26 mg/g). Also, the results were best fitted with pseudo-second-order kinetic. The experiments indicated that increasing the RBB concentration reduces the efficiency of adsorbents while increasing the contact time and adsorbent doses improved the RBB removal efficiency. Accordingly, it can be concluded that pumice stone modified with various acids can be considered a cheap adsorbent with high efficiency in removing RBB from industry effluent.

Ecological risk assessment and heavy metals accumulation in agriculture soils irrigated with treated wastewater effluent, river water, and well water combined with chemical fertilizers.

Contaminated irrigation water can increase trace heavy metals concentration in agricultural soil. The present research aimed to investigate the effect of three types of irrigation water sources, including treated wastewater effluent, Gharasoo river water, and well water with chemical fertilizer, on the accumulation and ecological risk of heavy metals in agricultural soils. Soil samples were collected before and after crop irrigation to evaluate heavy metal concentrations. The samples were analyzed to determine the presence of arsenic, nickel, cadmium, iron, chromium, zinc, lead, copper, and manganese. Based on the results, the concentration of essential metals in the soil before the irrigation process was more than toxic metals. The different irrigation sources increased the concentration of all heavy metals in the soil, and the accumulation of Cr, Ni, and Cd significantly elevated more than others. Irrigation resources' effectiveness in transferring heavy metals to the soil was obtained as treated wastewater effluent < well water with fertilizer < river water. Furthermore, the potential ecological risk index (RI) for irrigated soil was in a high-risk category. Therefore, it is recommended that the river water should not be used to irrigate vegetables to the utmost possible. Finally, the low heavy metals concentration and the presence of nutrients in treated wastewater effluent make this source the most suited source of irrigation because it eliminates the need for chemical fertilizers by farmers and transfers fewer heavy metals to the soil.

Investigation of health risk assessment and the effect of various irrigation water on the accumulation of toxic metals in the most widely consumed vegetables in Iran.

The quality of irrigation water sources can significantly affect the concentrations of heavy metals (HMs) in cultivated vegetables. This study aimed to investigate the effect of various water resources, including treated wastewater effluent (TWE), river water (RW), and well water with chemical fertilizer (WW+F), on the accumulation of heavy metals (HMs) in the three most widely consumed edible vegetables (Coriander, Radish, and Basil) in Iran. A total of 90 samples of edible vegetables, 13 samples of irrigation water, and 10 soil samples were collected to determine HMs concentrations. Iron (Fe), Zinc (Zn), Copper (Cu), Manganese (Mn), Lead (Pb), Cadmium (Cd), Chromium (Cr), Nickel (Ni,) and Arsenic (As) were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES). Eventually, the Total Target Hazard Quotient (TTHQ) for the toxic metals of As, Pb, and Cd was determined. The results revealed that the TTHQ of toxic metals in vegetables was less than the allowable limits (TTHQ = 1). Also, TWE was the best irrigation water type since the HMs content of vegetables was low. By comparing the results with national and international standards, it can be concluded that the Gharasou RW for irrigation of edible vegetables was inappropriate.

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.

World Health Organization reports that 2.2 million people die yearly from insufficient sanitary drinking water. This ontology-based study focused on investigating the chemical quality of drinking water through a new water quality index designed by fuzzy multi-criteria group decision-making methods, merged with GIS, and, secondly, surveying non-carcinogenic risk assessment of fluoride and nitrate using Monte Carlo simulation and sensitivity analysis in Shiraz's water sources. F-, NO3-, NO2-, EC, TDS, alkalinity, TH, SO42-, Cl-, and Na were applied in the WQI. The NO3- mean concentrations were 23.15 and 27.66 mg/L in the cold and warm seasons, while the mean concentrations of fluoride were 0.50 and 0.46 mg/L during the cold and warm period. The 95th centiles of fluoride's HQs among infants, children, teenagers, and adults were 0.56, 0.7, 0.49, and 0.4, respectively, in the cold season, which was 0.65 and 0.81, respectively, 0.57 and 0.46 for mentioned groups in the warm season. In comparison, the 95th centiles of nitrate's HQs among infants, children, teenagers, and adults were 1.27, 1.59, 1.13, and 0.9, respectively. The HQs were more than 1 for infants, children, and teenagers, so nitrate can have various adverse effects, whereas fluoride does not adversely affect all aging groups in both seasons. Also, nitrate concentration can increase the non-carcinogenic risk, which the IR and ED lead to the HQ increasing. In contrast, BW has a negative effect on risk increasing. Overall, source management of these parameters can significantly reduce the concentration of nitrate and their adverse human health effect.

Corrigendum to data on nitrate-nitrite pollution in the groundwater resources a Sonqor plain in Iran [Data in Brief Volume 20 (2018) Pages 394-401].

[This corrects the article DOI: 10.1016/j.dib.2018.08.023.].

Accumulation and human health risk assessment of nitrate in vegetables irrigated with different irrigation water sources- transfer evaluation of nitrate from soil to vegetables.

The present study aimed to investigate the rate of accumulation, human health risk assessment, and nitrate-related transfer factor in vegetables irrigated with different sources, including treated wastewater effluent (TWE) of Kermanshah wastewater treatment plant, Gharasoo river water (RW) of Kermanshah, and well water with chemical fertilizer (WWF). For this purpose, three different types of vegetables, including basil, coriander, and radish, was cultivated, and each of them was irrigated by the three irrigation sources mentioned above. Finally, the amount of nitrate in different sources of irrigation, soil (before growing vegetables and after harvesting vegetables), and the mentioned vegetables was measured. Based on the study results, it can be concluded that the water of the Gharasoo River (RW), compared to the other two irrigation sources, causes more nitrate accumulation in the soil and vegetables grown in it. The highest transmission factor was related to basil vegetables irrigated with WWF. The results showed that the average daily intake of nitrate through the consumption of vegetables grown in Kermanshah with any irrigation water is less than the allowable amount, so the consumption of such vegetables is not dangerous to consumers' health. Therefore, it is suggested that the best irrigation source for vegetable cultivation in Kermanshah is TWE, provided that all of its physical, chemical and microbial parameters meet the standards for reuse in agriculture irrigation. Thus, the use of treated wastewater reduces the need for farmers to use chemical and organic fertilizers and cost-effectiveness, high frequency, and high availability.

Carbon-efficient closed-loop supply chain network: an integrated modeling approach under uncertainty.

Inspired by a circular economy paradigm, an evolving momentum of policies and legislations aims to close the loop of product lifecycles through improved level of recycling, remanufacturing, and reuse, with the objective of adding value to the economy while not endangering the environment. However, the trade-off between the environmental and economic sustainability of designing business processes is inevitable. To address this trade-off in the supply chain context, competing objectives regarding both cost minimization and reduction in carbon emission should be simultaneously considered and integrated into a comprehensive model. This complexity is however elevated when uncertainty of demand is taken into consideration. In this study, the design of a closed-loop supply chain is investigated where competing objectives of cost and sustainability of supply chain operations are evaluated under demand uncertainty. Augmented Weighted Tchebycheff (AWT) and ε-constraint methods are employed to address the multi-objectivity of the problem while a robust optimization approach is applied to deal with the demand uncertainty. The results confirm that the proposed approach provides efficient solutions for designing a green closed-loop supply chain network.

Water quality evaluation and non-cariogenic risk assessment of exposure to nitrate in groundwater resources of Kamyaran, Iran: spatial distribution, Monte-Carlo simulation, and sensitivity analysis.

Water is exceptionally vital for all living beings and socio-economic development. This study aimed to investigate the groundwater suitability for drinking in rural areas of Kamyaran city, Kurdistan province, Iran, by using the water quality index (WQI) and evaluating the non-carcinogenic health risk caused by nitrate from the drinking route. Forty-five groundwater samples were collected (2019) from operated dug-wells, and twelve parameters (TDS, pH, TH, EC, HCO3 -, K+, Na+, Mg2+, Ca2+, Cl-, SO4 2-, and NO3 -) were measured to the calculation of WQI. Hazard Quotient (HQ) and sensitivity analysis (SA) using the Monte-Carlo Simulation technique with 10,000 iterations were employed to determine the non-carcinogenic effects of Nitrate in different exposed groups (Infant, children, teenagers, and adults). The results of WQI showed that 74% of groundwater samples fall within the excellent water quality class, and 26% of rural areas fall in the category of good water type. The nitrate concentration in drinking water ranged from 22.42 ± 11.44 mg/L. The HQ mean for infants, children, teenagers, and adults were 0.5606, 0.7288, 0.5606, and 0.438, respectively. Probability estimation showed the HQ values for the 5th, and 95th percentile in infants, children, teenagers, and adult groups were (0.25-1.81), (0.13-1.08), (0.13-0.97), and (0.07-0.51), respectively. The SA showed that the most significant parameter of non-carcinogenic risk in all exposed populations was nitrate concentration. Generally, nitrate concentration in the study area was relatively high, and remarkably in agriculture and fertilizer management required more attention.

Effect of land use changes on non-carcinogenic health risks due to nitrate exposure to drinking groundwater.

This study aimed to determine the effect of land-use changes on the non-carcinogenic health risk of nitrate ion exposure of underground drinking water resources in Shiraz (Iran). To this end, 175 chemical samples for the nitrate analysis were regularly taken from 35 drinking water wells of Shiraz from 2013 to 2017, and their results were zoned using GIS. Hazard quotient (HQ) induced by nitrate ion exposure was determined in four age groups: infants, children, adolescents, and adults. Area changes of four types of land-use, including residential, agricultural and green space, industrial, and bare land within a radius of 400 m of drinking water wells, were determined using the GIS and Google Earth software. Then, all data was imported to Matlab 2018 for statistical analysis. The results showed that mean nitrate concentration increased by 2.5 mg L-1 from 2013 to 2017. According to the zoning map, 5 and 11.4% of the area in 2013 and 2017, respectively, exceeded the drinking water standard set by nitrate (i.e., 50 mg/L). Air temperature and precipitation variations also influenced nitrate concentrations and HQ changes (Rtemperature = 0.67). Children's age group was the most vulnerable, and during the study period, this vulnerability was an increasing trend, so that the HQ from 0.93 in 2013 to 0.97 in 2017 has increased. The rate of land-use changes in agricultural, industrial, bare, and urban was -1.8%, 1.3%, -4.6%, and 2.1%, respectively, and the highest correlation was observed between HQ and Diff.l residential land use (Rinfant = 0.55). According to the results, the most influential factor in HQ was air temperature (R = 0.66), and urban land-use change (R > 0.44). To sum up, this study's results showed that land-use changes, especially urban and residential development, significantly affect groundwater nitrate concentration and its degree of HQ. Moreover, increasing temperature and decreasing annual precipitation can also increase the severity of this risk.

Magnetic carnosine-based metal-organic framework nanoparticles: fabrication, characterization and application as arsenic adsorbent.

This study centers on the controllable synthesis, characterization, and application of a novel magnetic bio-metal-organic framework (Bio-MOF) for the adsorption and subsequent removal of arsenic from aqueous solutions. Zinc ions and carnosine (Car) were exploited to construct the Car-based MOF on the surface of magnetite (Fe3O4 NPs). The Magnetite precoating with Car led to an increase in the yield and the uniform formation of the magnetic MOF. The prepared magnetic Bio-MOF nanoparticles (Fe3O4-Car-MOF NPs) had semi-spherical shape with the size in the range of 35-77 nm, and the crystalline pattern of both magnetite and Car-based MOF. The NPs were employed as an adsorbent for arsenic (As) removal. The adsorption analyses revealed that all studied independent variables including pH, adsorbent dose, and initial arsenic concentration had a significant effect on the arsenic adsorption, and the adsorption data were well matched to the quadratic model. The predicted adsorption values were close to the experimental values confirming the validity of the suggested model. Furthermore, adsorbent dose and pH had a positive effect on arsenic removal, whereas arsenic concentration had a negative effect. The adsorption isotherm and kinetic studies both revealed that As adsorption fitted best to the Freundlich isotherm model. The maximum monolayer adsorption capacity (94.33 mg/g) was achieved at room temperature, pH of 8.5 and adsorbent dose of 0.4 g/L. Finally, the results demonstrated that the adsorbent could be efficiently applied for arsenic removal from aqueous environment.

Impacts of drought phenomenon on the chemical quality of groundwater resources in the central part of Iran-application of GIS technique.

In the recent decades, global warming has caused water shortages all over the world. This study aimed to investigate the impacts of drought caused by climate change on the chemical quality of groundwater in Saveh County, Markazi province, Iran. The physicochemical parameters of 29 wells were analyzed by the Standardized Precipitation Index (SPI) during the drought period 2004-2015. Wilcox and Schoeller diagrams were applied to evaluate the water quality of wells for irrigation and drinking purposes, respectively. Schoeller diagram was consulted to show the relative concentrations of anions and cations typically expressed in milliequivalents per liter. Also, the Wilcox diagram was consulted to determine the suitability of water for agriculture purposes. Finally, the geographic information system was applied to the zoning of the groundwater quality parameters. According to the results, almost 90% of wells were in the category of "very salty and harmful for agriculture uses" in the last year of the study period (2015). The Schoeller diagram suggests that the water quality of 72.5, 10.4, 65.5, 100, 44.9, and 69% of wells were inappropriate and exceeded the Iranian National Standard level, in terms of TDS, TH, Na+، Mg2+, Cl-, and SO42- in 2015, respectively. A decrease in yearly average precipitation during the studied period has not only caused overuse of groundwater as the primary water resources but also led to a significant decline in its chemical quality.

The investigation of type and concentration of bio-aerosols in the air of surgical rooms: A case study in Shariati hospital, Karaj.

The presence of bio-aerosols is one of the main causes of hospital infections that can be dangerous especially for immunocompromised patients. This research aimed to determine the relationship between hospital infections and surgical incision size in addition to determining the concentration and bacterial and fungal bioaerosols found in the operating rooms. This cross-sectional descriptive-analytic study was carried out in the operating rooms of Shariati Hospital in Karaj, Iran during the years 2016 and 2017. A total of 198 bacterial samples and 198 fungal samples were collected and analyzed using a passive sampling standard method (1/1/1) for 180 days. Tryptic Soy Agar (TSA) and Sabouraud Dextrose Agar (SDA) medium were used for bacterial and fungal samples, respectively. Relevant differential tests were used to determine the genus and species of bacteria and fungi such as DNase test, Bile-esculin, motility test urease test. In general, this work presents: •The present evaluated the relationship between bioaerosols concentration and surgical incision size.•The intraoperative concentration of bacterial and fungal bioaerosols in indoor air of the orthopedic, internal and cesarean operating rooms was significantly higher than their preoperative concentration (p-value<0.05).•Also, there was not significant difference between the bacterial and fungal concentrations in various operating rooms) p-value<0.05).

Estimation of methane gas by LandGEM model from Yasuj municipal solid waste landfill, Iran.

CH4 has a high potential for energy production and by utilizing the proper technology, large amounts of energy can be extracted from it. This study aimed to estimate the amounts of methane emissions from the municipal solid waste landfill in Yasuj city using LandGEM software. The LandGEM model which is used for this aim is based on input data of open landfill year, land closure year, methane production rate, potential methane production capacity, and waste acceptance rate. According to the results, methane gas production during the years 2009, 2010, 2011 and 2012 was obtained to be 250, 275, 303, and 330 m3/h respectively. The results also showed that maximum methane production rate occurred during the years 2010-2012 and then reduced with a soft slope from 2012. The method and results of this research can be used for design and execute of methane gas collection systems and also, control of greenhouse gases emission for the landfills.

Dataset on assessment of physical and chemical quality of groundwater in rural drinking water, west Azerbaijan Province in Iran.

Analyzing the quality of drinking water and comparing it with standards, provides useful information regarding in the state of water supply and health protection to consumers. In the current research, the quality of drinking water in the cities of West Azerbaijan province has been investigated. In the current study, the results of drinking water analysis in 17 counties of West Azerbaijan province (except Urmia city), including 355 analyzes were conducted in 2016. The results were analyzed by SPSS software and compared with the national standard. Based on the analysis, the hardness of drinking water in the West Azerbaijan province ranged from 22 to 912 mg/L as calcium carbonate, and the average of the experiment was measured to be 136 ±â€¯327 mg/L as calcium carbonate. The TDS values in this study were 39-1710 mg/L, and on average 397.7 ±â€¯265.8 mg/L. Also, based on the analyzes performed in this study, the Fluoride concentration was from 0 to 3.45 mg/L, and on average 323.376 ±â€¯0.05 mg/L and the Nitrate concentration was 0-218 mg/L and on average 3.58 ±â€¯1.1 mg/L.

Data on aluminum concentration in drinking water distribution network of rural water supply in Sistan and Baluchistan province, Iran.

The aim of this study is to determine the Aluminum concentration in groundwater resources of Sistan and Baluchestan province, Iran. See the data in this article. For the purpose of this study, a total of 871 water samples were collected and values of quality parameters including pH, turbidity, total dissolved solids (TDS) and Aluminum concentration were measured (with two-time repetitions) according to Standard Methods for the Examination of Water and Wastewater, during the year 2016. The mean, maximum, minimum of Aluminum concentrations in all groundwater resources of Sistan and Baluchistan province, were: 0.015, 0.059, 0.0004 mg/l, respectively and also, the standard deviation was 0.012. Moreover, employing GIS software, the geo-statistical distribution of Aluminum concentration in groundwater aquifer in Sistan and Baluchestan was mapped.

Data on estimation for sodium absorption ratio: Using artificial neural network and multiple linear regressions.

In this article the data of the groundwater quality of Aras catchment area were investigated for estimating the sodium absorption ratio (SAR) in the years 2010-2014. The artificial neural network (ANN) is defined as a system of processor elements, called neurons, which create a network by a set of weights. In the present data article, a 3-layer MLP neural network including a hidden layer, an input layer and an output layer had been designed. The number of neurons in the input and output layers of network was considered to be 4 and 1, respectively, due to having four input variables (including: pH, sulfate, chloride and electrical conductivity (EC)) and only one output variable (sodium absorption ratio). The impact of pH, sulfate, chloride and EC were estimated to be 11.34%, 72.22%, 94% and 91%, respectively. ANN and multiple linear regression methods were used to estimate the rate of sodium absorption ratio of groundwater resources of the Aras catchment area. The data of both methods were compared with the model׳s performance evaluation criteria, namely root mean square error (RMSE), mean absolute error (%) and correlation coefficient. The data showed that ANN is a helpful and exact tool for predicting the amount SAR in groundwater resources of Aras catchment area and these results are not comparable with the results of multiple linear regressions.