Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo.

Groundwater is one of the most important sources of drinking and irrigation water in arid and semi-arid areas. This study aimed to investigate the chemical quality of groundwater for drinking and irrigation, assess the non-carcinogenic risk factors resulting from the concentration of fluoride and nitrate ions, and analyze the sensitivity among children, teenagers, and adults using Monte Carlo method. A total of 171 samples were obtained from confined groundwater in Arsanjan. Among other hydrological parameters of water, EC had the highest average (1135.97). TDS ranged from 67.90 to 1878.30 mg/L, with the lowest and highest total hardness values being 2.90 and 680.8, respectively. The water quality index (WQI) results indicated that 33% of the samples were at the poor water level and the irrigation (IWQI) was less than 25 in 96.36% of the samples, which were categorized as excellent. Thus, the majority of the samples were suitable for irrigation purposes. Additionally, the oral and dermal health risks of fluoride and nitrate were less than 1 in all age groups. Concentration factor was the main indicator in the assessment of the non-carcinogenic risk factors of nitrate and fluoride. The results of sensitivity analysis revealed a reverse relationship with body weight. Further, the results of principal component analysis (PCA) showed a negative relationship between fluoride concentration and pH. Hierarchical cluster analysis also showed that the study variables belonged to three main clusters. Some elements in C1 were also found in the first factor in PCA. The elements in C2 were among the dominant compounds of the groundwater resources of the study area, which may be caused by earth cations or human activities. C3 variables may also be one of the consequences of fertilizer use in areas around groundwater sources.

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.

Efficiency of Ag3PO4/TiO2 as a heterogeneous catalyst under solar and visible light for humic acid removal from aqueous solution.

Nowadays, the presence of humic acid (HA) in water sources is highly regarded due to the production of extremely harmful byproducts such as trihalomethanes. In this study, the effectiveness of an Ag3PO4/TiO2 catalyst produced by in situ precipitation as a heterogeneous catalyst for the degradation of humic acid in the existence of visible and solar light was evaluated. The Ag3PO4/TiO2 catalyst's structure was characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS), after which the catalyst dosage, HA concentration, and pH parameters were adjusted. After a 20-min reaction, the highest HA degradation of 88.2% and 85.9% in presence of solar light and visible light were attained at the ideal operating conditions of 0.2 g/L catalyst, 5 mg/L HA, and pH 3, respectively. It was discovered that, based on kinetic models, the degradation of HA matched both Langmuir-Hinshelwood and pseudo-first-order kinetics at concentrations of 5 to 30 mg/L (R2 > 0.8). The Langmuir-Hinshelwood model had surface reaction rate constants (Kc) of 0.729 mg/L.min and adsorption equilibrium constants (KL-H) of 0.036 L/mg. Eventually, a real-water investigation into the process' effectiveness revealed that, under ideal circumstances, the catalyst had a reasonable HA removal efficiency of 56%.

Modelling of n-Hexadecane bioremediation from soil by slurry bioreactors using artificial neural network method.

Diesel oil is known to be one of the major petroleum products that can pollute water and soil. Soil pollution caused by petroleum hydrocarbons has substantially impacted the environment, especially in the Middle East. In this study, modeling and optimization of hexadecane removal from soil was performed using two pure cultures of Acinetobacter and Acromobacter and consortium culture of both bacterial species using artificial neural network (ANN) method. Then the best ANN structure was proposed based on mean square error (MSE) as well as correlation coefficient (R) for pure cultures of Acinetobacter and Acromobacter as well as their consortium. The results showed that the correlations between the actual data and the data predicted by ANN (R2) in Acromobacter, Acinetobacter and consortium of both cultures were 0.50, 0.47 and 0.63, respectively. Despite the low correlation between the experimental data and the data predicted by the ANN, the correlation coefficient and the precision of ANN for the consortium was higher. As a result, ANN had desirable precision to predict hexadecan removal by the cobsertium culture of Ochromobater and Acintobacter.

Investigation of fungal contamination in indoor air and on surfaces of traditional public baths in a historical city.

It has been proven that exposure to bioaerosols is associated with several health effects, such as pulmonary diseases and allergies. The present cross-sectional study was aimed to investigate fungal contamination in indoor air and on the surfaces of four traditional baths in Shiraz, Iran, one of the most historical cities in the world. Samples were taken from indoor air, using a microbial air sampler, as well as the surfaces of the shower, hallway, and dressing rooms of studied baths for 3 months. Totally 180 samples, including 45 air and 135 surfaces samples, were collected from studied baths. The concentrations of fungi collected from the air of studied baths were ranged from 22.6 to 34.6 CFU/m3. Besides, the levels of fungi collected from the surface samples of studied baths were ranged from 21.2 to 60 CFU/m2. The highest and lowest fungi species detected both in air and surfaces samples of the studied baths were Penicillium spp. and Mucor spp. respectively. Although the levels of fungi in the studied baths were lower than the levels recommended by the World Health Organization, some environmental health measures such as washing and disinfecting surfaces and tools after each working shift and periodic inspections are recommended ensuring the safety of costumers who are visiting such places.

Protocol for the estimation of drinking water quality index (DWQI) in water resources: Artificial neural network (ANFIS) and Arc-Gis.

Drinking water sources may be polluted by various pollutants depending on geological conditions and agricultural, industrial, and other human activities. Ensuring the safety of drinking water is, therefore, of a great importance. The purpose of this study was to assess the quality of drinking groundwater in Bardaskan villages and to determine the water quality index. Water samples were taken from 30 villages and eighteen parameters including calcium hardness (CaH), total hardness (TH), turbidity, pH, temperature, total dissolved solids (TDS), electrical conductivity (EC), alkalinity (ALK), magnesium (Mg2+), calcium (Ca2+), potassium (K+), sodium (Na+), sulphate (SO4 2-), bicarbonate (HCO3 -), fluoride (F-), nitrate (NO3 -), nitrite (NO2 -) and chloride (Cl-) were analyzed for the purpose for this study. The water quality index of groundwater has been estimated by using the ANFIS. The spatial locations are shown using GPS. The results of this study showed that water hardness, electrical conductivity, sodium and sulfate in 66, 13, 45 and 12.5% of the studied villages were higher than the Iranian drinking water standards, respectively. Based on the Drinking Water Quality Index (DWQI), water quality in 3.3, 60, 23.3 and 13.3% of villages was excellent, good, poor and very poor, respectively. •Groundwater is one of the sources of drinking water in arid and semi-arid regions such as Bardaskan villages, which monitor the quality of these resources in planning for improving the quality of water resources.•The DWQI can clearly provide information associated with the status of water quality resources in Bardaskan villages.•The results of this study clearly indicated that with appropriate selection of input variables, ANFIS as a soft computing approach can estimate water quality indices properly and reliably.•Some parameters were in the undesirable level is some villages. Therefore, the government should try to improve the chemical and physical quality of drinking water in these areas with the necessary strategies.