Identification and Prioritization of Health Indexes in Nomadic Tribespeople by Fuzzy Delphi Method: An Ecological Study.

The migratory lifestyle of nomadic communities, combined with the lack of a suitable health-related organizational structure, has made it difficult to provide health care services that can improve their health status. To achieve the concept of justice in health and sustainable development, it is imperative to improve the health status of all citizens in Iran, which consists of the nomadic communities, and urban and rural populations. In this ecological study national health indexes in nomadic tribespeople was Identified and prioritized by expert panel and fuzzy Delphi method. In the first step, the national health indexes were extracted from the literature, and then indexes that can be measured, evaluated and representative of the nomadic communities were extracted and prioritized by using fuzzy Delphi and TOPSIS methods, Questionnaire options were analyzed according to 3 criteria of economic efficiency, measurability, and simplicity in the form of 13 components and their indicators. The analysis of the results of the fuzzy Delphi method shows that the mental health component has the lowest real score in the criteria of measurability, simplicity and economic efficiency. The child care component has the highest real score in terms of economic efficiency and the vaccination component has the highest real score based on the criteria of measurability and simplicity in nomadic communities. The results of the TOPSIS method show that the components of vaccination, maternal care and child care have the highest priority for attention and investigation of their indicators in this segment of the population. In general, by designing and implementing systems to record the information of priority indexes extracted from the present study, it is possible for responsible organizations to make effective decisions and plans for the improvement of the health status of nomadic communities.

Bioengineered FeZn/GA@Cu nanocomposite utilizing spent coffee ground extract and gum arabic: Enhanced nitrate removal via (RSM) and machine learning optimization.

This research focused on synthesizing an eco-friendly FeZn/GA@Cu nanocomposite using spent coffee grounds and Gum Arabic (GA). The study aimed to investigate its effectiveness as both a photocatalyst and an adsorbent, specifically for removing nitrates from aqueous solutions. The prepared nanocomposite was characterized using various analytical techniques, including XRD, TGA, FESEM with EDS, TEM, BET, FTIR, zeta potential, UV-DRS, and VSM. The RSM method, an impressive removal efficiency of 95.28 % for nitrate was projected under the specific conditions of an optimal dose of 1.82 g/L, an initial concentration of 60.00 mg/L, a pH level of 5.85, and a reaction duration of 48.90 min. It was ascertained that the peak efficiency of 98.25 % could be achieved with a carefully calibrated dose of 1.94 g/L, an initial concentration of 62.69 mg/L, a pH of 5.16, and a reaction time contained within 45.75 min. The synthesized nanocomposites have shown potential antibacterial activity against gram+ve (Staphylococcus aureus) and gram-ve (Escherichia coli) pathogens. This study suggests that the FeZn/GA@Cu nanocomposite synthesized using spent coffee grounds has potential as a photocatalyst for removing nitrate from aqueous solutions.

Photocatalytic degradation of Acid Red 18 by synthesized AgCoFe2O4@Ch/AC: Recyclable, environmentally friendly, chemically stable, and cost-effective magnetic nano hybrid catalyst.

Chitosan (Ch) is a linear biodegradable natural carbohydrate polymer and the most appealing biopolymer, such as low-cost biodegradability, biocompatibility, hydrophilicity, and non-toxicity. In this case, Ch was utilized to synthesize AgCoFe2O4@Ch/Activated Carbon (AC) by the modified microwave-assisted co-precipitation method. The physical and chemical structure of magnetic nanocomposites was analyzed and characterized by Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), X-ray diffraction (XRD), Energy Dispersive Spectroscopy (EDS), Diffuse Reflection Spectroscopy (DRS), Value stream mapping (VSM), Fourier transform spectroscopy (FTIR) and BET. The effects of various parameters on the removal of dye (Acid Red18), including catalyst dose, dye concentration, pH, and time were studied. Results showed that the highest removal efficiencies were 96.68 % and 84 % for the synthetic sample and actual wastewater, respectively, in optimal conditions (pH: 3, the initial dye concentration: 10 mgL-1, the catalyst dose: 0.14 gL-1, time: 50 min). Mineralization, according to the COD analysis, was 89.56 %. Photocatalytic degradation kinetics of Acid Red 18 followed pseudo-first order and Langmuir-Hinshelwood with constants of kc = 0.12 mg L-1 min-1 and KL-H = 0.115 Lmg-1. Synthesized photocatalytic AgCoFe2O4@Ch/AC showed high stability and after five recycling cycles was able to remove the pollutant with an efficiency of 85.6 %. So, the synthesized heterogenous magnetic nanocatalyst AgCoFe2O4@Ch/AC was easily recycled from aqueous solutions and it can be used in the removal of dyes from industries with high efficiency.

Application of montmorillonite/octadecylamine nanoparticles in the removal of textile dye from aqueous solutions: Modeling, kinetic, and equilibrium studies.

In the study, the proliferation of industries has been associated with an increase in the production of industrial wastewater and subsequent environmental pollution, wherein dyes emerge as prominent pollutants. The characteristics of nanoclay modified with octadecylamine, were elucidated throughvarious techniques, including Field Emission Scanning Electron Microscopy/Energy Dispersive Spectroscopy (FE-SEM/EDS), Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric Analysis (TGA), X-ray Diffraction (XRD), and Brunauer-Emmett-Teller Surface Area Analysis (BET). The research delved into the impact of variables such as pH, initial dye concentration, adsorbent dose, temperature, and ultrasonication time on the removal of Acid Black 1 (AB1) through an ultrasonic process, employing a central composite design (CCD). Optimal conditions for the adsorption process were determined: pH at 5.46, adsorbent mass at 4 mg/30 mL, initial dye concentration at 20 mg/L, ultrasound time at 20 min, and temperature at 50 °C, resulting in a remarkable 96.49% adsorption efficiency. The fitting of experimental equilibrium data to different isotherm models, including Langmuir, Freundlich, and Temkin, indicated thatthe Freundlich model was the most suitable. Analysis of the adsorption data with various kinetic models such as pseudo-first and second-order models, and intraparticle diffusion models, revealed the applicability of the second-order equation model. A thermodynamic study unveiled that the adsorption process was spontaneous and endothermic. In conclusion, the study highlights the significant capability ofmontmorillonite nanoclay modified with octadecylamine in removing AB1 dye, rendering it a viable option for wastewater treatment.

Assessing water quality index and health risk using deterministic and probabilistic approaches in Darab County, Iran; A machine learning for fluoride prediction.

The present study employed deterministic and probabilistic approaches to determine the Water Quality Index (WQI) and assess health risks associated with water consumption in Darab County, Iran. Additionally, pollution levels were predicted using a machine-learning algorithm. The study's findings indicate that certain physicochemical parameters of water in some locations exceeded permissible limits (WHO or EPA), with 79.00 % of total hardness (TH) and 21.74 % of Total dissolved solids (TDS) levels exceeding standard values. The WQI for drinking water was determined to be 94.56 % using the deterministic approach, and 98.4 % of samples included the excellent and good categories according to the WQI classification system using the probabilistic approach. Fluoride (F) exhibited the most substantial impact on WQI values. The Artificial Neural Network (ANN) analysis findings suggest that the pH, nitrate (NO3), and TDS are the most significant factors affecting the prediction of F concentration in water. Multivariate analysis demonstrated that anthropogenic, especially agriculture and geogenic factors, contributed to the water quality in this area. The health risk assessment (HRA) using deterministic methods revealed that water consumption posed a relatively high risk in certain areas. However, Monte Carlo simulation demonstrated that the 5th and 95th percentiles of Hazard Index (HI) for children, teenagers, and adults were within limits of (0.14-2.38), (0.09-1.29), and (0.10-1.00) respectively, with a certainty level of 70 %, 91 %, and 95 %. Interactive indices revealed that the intake of IR and NO3-IR in children, BW and F-BW in teenagers, and NO3 and NO3-IR in adults significantly impacted health risks. Based on these findings, augmenting water treatment processes, regulating fluoride concentrations, and advocating for sustainable agricultural practices complemented by continuous monitoring is imperative.

Green synthesis of sustainable magnetic nanoparticles Fe3O4 and Fe3O4-chitosan derived from Prosopis farcta biomass extract and their performance in the sorption of lead(II).

The sustainable processes are now in tremendous demand for nanomaterial synthesis as a result of their unique properties and characteristics. The magnetic nanoparticles comprised of Fe3O4 and its conjugate with abundant and renewable biopolymer, chitosan, were synthesized using Prosopis farcta biomass extract, and the resulting materials were used to adsorb Pb (II) from aqueous solution. Thermodynamic parameters revealed that the sorption of lead (II) on Fe3O4 as well as Fe3O4-Chitosan (Fe3O4-CS) has been an endothermic and self-regulating procedure wherein the sorption kinetics was defined by a pseudo-second-order pattern and the sorption isotherms corresponded to the Freundlich pattern. A multivariable quadratic technique for adsorption process optimization was implemented to optimize the lead (II) adsorption on Fe3O4 and Fe3O4-chitosan nanoparticles, the optimal conditions being pH 7.9, contact time of 31.2 min, initial lead concentration of 39.2 mg/L, adsorbent amount of 444.3 mg, at a 49.7 °C temperature. The maximum adsorption efficiencies under optimal conditions were found to be 69.02 and 89.54 % for Fe3O4 and Fe3O4-CS adsorbents, respectively. Notably, Fe3O4 and Fe3O4-CS can be easily recovered using an external magnet, indicating that they are a viable and cost-effective lead removal option.

Nitrate concentrations and health risks in cow milk from Iran: Insights from deterministic, probabilistic, and AI modeling.

Excessive nitrate consumption has been linked to potential health risks in humans. Thus, understanding nitrate levels in staple foods such as cow milk can provide insights into their health implications. This study meticulously examined nitrate concentrations in 70 cow milk samples from traditional and industrialized cattle farming systems in Fars province, Iran. A combination of deterministic modeling, a probabilistic approach, and six artificial intelligence algorithms was employed to determine health risk assessments. The data disclosed average nitrate concentrations of 32.63 mg/L in traditional farming and 34.95 mg/L in industrialized systems, presenting no statistically significant difference (p > 0.05). The Hazard Quotient (HQ) was deployed to gauge potential health threats, underscoring heightened vulnerability in children, who exhibited HQ values ranging from 0.05 to 0.58 (mean = 0.19) in contrast to adults, whose values spanned 0.01 to 0.16 (mean = 0.05). Monte Carlo simulations enriched the risk assessment, demarcating the 5th and 95th percentile nitrate concentrations for children at 0.07 and 0.39, respectively. In children, pivotal interactions that influenced HQ encompassed those between nitrate concentration and consumption rate, as well as nitrate concentration and body weight. The interplay between nitrate concentration and consumption rate was most consequential for the adult cohort. Among the algorithms assessed for HQ prediction, Gaussian Naive Bayes (GNB) was optimal for children and eXtreme Gradient Boosting (XGB) for adults, with nitrate concentration being a key determinant. The results underscore the imperative for rigorous oversight of milk nitrate concentrations, highlighting the enhanced susceptibility of children and emphasizing the need for preventive strategies and enlightened consumption.

Dispersion of SO2 emissions in a gas refinery by AERMOD modeling and human health risk: a case study in the Middle East.

This study aimed to model the dispersion of emitted SO2 from stacks and flares in one of the largest Gas Refinery Companies in the Middle East . Pollutant emission coefficients and air pollution's various sources contributions were determined based on the collected data after measuring SO2 concentrations in a fixed monitoring station (stack) and across different distances from it for a year. The SO2 release pattern was simulated, and annual pollutant concentrations in average periods of 1-hr and 24-hr were predicted using AERMOD 8.9.0. The maximum simulated ambient SO2 were 27,447 and 4592 µg/m3 in average sampling times of 1-hr and 24-hr, respectively. The hazard quotient of 95% percentile for children, teenagers, and adults due to inhalation of SO2 was more than one.The maximum concentration of SO2 in the 1-hour and 24-hour period in the study area was higher than the amount introduced by Iran's clean air standard and the WHO standard.

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.

Assessment of air quality using AERMOD modeling: a case study in the Middle East.

Emissions of greenhouse gases from industrial facilities, such as refineries, are one of the most significant environmental problems in many countries. This study aimed to assess the present status of emission sources near a gas refinery region, and the contribution of sources to air pollution was estimated by monitoring CO for a year at a fixed station. This descriptive-analytical study was conducted between January and December 2020. A simulation of CO gas distribution and pollutant concentration prediction was carried out. The results show that the maximum concentration of CO in the 1-h period was 2260 µg/m3, which corresponds to the peak concentration in spring, and in the 8-h period, it was 573 µg/m3, which corresponds to the peak concentration in winter. The studied area's maximum pollutant concentration was also compared to national and international standards for clean air. In all four seasons, the maximum simulated CO concentrations were lower than the Iranian and EPA standards for clean air. Maximum concentrations have occurred in the southern slopes of the study area's heights, and, due to the appropriate wind speed, maximum concentrations in the northeastern mountain peaks occurred at a more considerable distance due to the high altitude of the mountains and the lack of suitable conditions for pollutant escape. Furthermore, because of the height of smokestacks and flares from the ground and the effect of wind on the release height, the concentration of pollutants at the foot of the stacks is low and decreases gradually over a certain distance. Finally, the distribution and deposition of pollutants in the pathway of the smoke were influenced by the type of topography.

Modeling, quality assessment, and Sobol sensitivity of water resources and distribution system in Shiraz: A probabilistic human health risk assessment.

Given water's vital role in supporting life and ecosystems, global climate change and human activities have significantly diminished its availability and quality. This study explores the health risks of drinking water consumption in the shiraz county water resources and distribution system. The result showed that the water was slightly alkaline. However, the average pH values during the study were within the permissible range. The area's abundance of total hardness and calcium was due to the high concentration of minerals in rocks and soils. The nitrate and fluoride concentrations in drinking groundwater varied from 0.02 to 116.70 mg/L and 0.10-1.85 mg/L, respectively. Although the water quality index indicated that 52.63, 45.03, and 20.3 percent of samples were of excellent, good, and poor quality in 2020, those percentages obtained 46.05, 52.09, and 14.0 percent in 2021. The regression values of training, testing, validation, and the proposed artificial neural network model were 0.93, 0.92, 0.85, and 0.92. The maximum levels of hazard quotient of nitrate and fluoride (except for adults) were higher than 1 in all age groups, indicating a high non-carcinogenic risk by exposure to nitrate. Furthermore, according to the Monte Carlo simulation, the 95th percentile hazard index in all groups was more than 1. Children and infants were more inclined towards risk than teens and adults based on the intake of nitrate and fluoride from drinking water. The Sobol sensitivity reflected that the nitrate concentration and ingestion rate are vital parameters that influence the outcome of the oral exposure model for all age groups. The interaction of ingestion rate with a concentration of nitrate and fluoride is an important parameter affecting the health risk assessment. In conclusion, these findings suggest that precise measures can reduce health risks and guarantee safe drinking water for residents of Shiraz County.

Maternal exposure to benzophenone derivatives and their impacts on offspring's birth outcomes in a Middle Eastern population.

Widespread use of benzophenones (BPs), a group of environmental phenolic compounds, is suspected of interfering with human health. The association of prenatal exposure to benzophenone derivatives with birth outcomes including birth weight and length, head, arm and thoracic circumference, abnormalities, corpulence index and anterior fontanelle diameter (AFD) was investigated. Mother-infant pairs of 166 within PERSIAN cohort population in Isfahan, Iran, in the 1st and 3rd trimesters of pregnancy were assessed. Four common benzophenone metabolites including 2,4-dihydroxy benzophenone (BP-1), 2-hydroxy-4-methoxy benzophenone (BP-3), 4-hydroxy benzophenone (4-OH-BP) and 2,2'-dihydroxy-4-methoxy benzophenone (BP-8) were measured in maternal urine samples. The median concentration of 4-OH-BP, BP-3, BP-1 and BP-8 were 3.15, 16.98, 9.95 and 1.04 µg/g Cr, respectively. In the 1st trimester, 4-OH-BP showed a significant correlation with AFD in total infants, decreasing 0.034 cm AFD per a log unit increase of 4-OH-BP. Within the male neonates, 4-OH-BP in the 1st and BP-8 in the 3rd trimester were significantly associated with head circumference and AFD increase, respectively. Among female neonates in the 3rd trimester, increasing 4-OH-BP and BP-3 concentration was correlated with a decrease in birth weight and AFD, respectively. This study demonstrated that all the target BP derivatives can influence normal fetal growth at any age of the pregnancy, nevertheless, to support these findings further studies are needed in a large and different group population.

Non-carcinogenic and cumulative risk assessment of exposure of kitchen workers in restaurants and local residents in the vicinity of polycyclic aromatic hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are often formed when organic substances do not burn completely. This study evaluates the non-carcinogenic and cumulative risks associated with PAHs levels by testing blood and urine samples in kitchen workers and residents near restaurants in Shiraz, Iran. Metabolites of PAH in the urine samples as well as clinical parameters in the blood samples were measured. The non-carcinogenic and cumulative risk assessments from exposure of the study groups to PAH metabolites were also evaluated. The highest average concentrations of PAH metabolites were related to kitchen workers (2126.7 ng/g creatinine (ng/g cr)). The metabolites of 1-Hydroxypyrene (1-OHP) and 9-Phenanthrene (9-OHPhe) had the highest and lowest mean concentrations, respectively. A direct correlation was observed between the levels of PAH metabolites with malondialdehyde (MDA) and total antioxidation capacity (TAC) levels (p < 0.05). Hazard Index (HIi) was obtained less than one (HIi < 1), indicating low-risk negative health impacts on the target groups. Nevertheless, conducting more studies to determine the health status of these people is quite evident.

Urinary levels of potentially toxic elements (PTEs) in female beauticians and their association with urinary biomarkers of oxidative stress/inflammation and kidney injury.

The present research was aimed to assess the urinary levels of potentially toxic elements (PTEs) in female beauticians and its correlation with oxidative stress/inflammation and kidney injury. To this end, the urine samples were collected from 50 female beauticians from beauty salons (exposed group) and 35 housewives (control group), and then, the level of PTEs was determined. The mean levels of the sum of urinary PTEs (∑PTEs) biomarkers in before and after exposure and control group were 83.55, 114.27 and 13.61 µg/L, respectively. Results also showed that the urinary level of PTEs biomarkers is significantly higher in women occupationally exposed to cosmetics compared to control group. The urinary levels of arsenic (As), cadmium (Cd), lead (Pb), and chromium (Cr) biomarkers have high correlation coefficients with early oxidative stress effects such as 8-Hydroxyguanosine (8-OHdG), 8-isoprostane and Malondialdehyde (MDA). Moreover, As and Cd biomarker levels were positively and significantly associated with kidney damages such as urinary kidney injury molecule-1 (uKIM-1) and tissue inhibitor matrix metalloproteinase 1 (uTIMP-1) (P < 0.01). Therefore, women who working in beauty salons can probably be categorized as high - exposure and high-risk workers in terms of DNA oxidative and kidney damages.

Polycyclic aromatic hydrocarbon (PAH) leachates from post-consumption waterpipe tobacco waste (PWTW) into aquatic environment- a primary study.

Post-consumption waterpipe tobacco waste (PWTW) is an unrecognized type of hazardous waste that is produced and released in large quantities into the aquatic environment. It may contain high amounts of various pollutants including PAH, and to date, there has been no research on the potential for contamination by PAH from PWTW leaching into aquatic environments. In this study, the concentrations of PAH via PWTW of fruit-flavored and traditional tobacco leachate into three water types, including distilled water (DW), tap water (TW) and sea water (SW) at different contact times were evaluated. There were significantly higher concentration levels of Æ©PAH in waters with leachates from fruit-flavored PWTW than traditional tobacco (P-value<0.05). The concentration levels of Æ©PAH in DW, TW and SW at a total contact time of two months ranged from 0.13 to 3.51, 0.12 to 3.63 and 0.11-3.64 µg/L, respectively. Lower molecular weight PAH such as naphthalene (Naph), acenaphthylene (Acen) and fluorine (Flu) were detected in leachates immediately after a short contact time of 15 min. Higher molecular weight PAH including benzo [a]anthracene (BaA), benzo [b]fluoranthene (BbF), benzo [k]fluoranthene (BkF), chrysene (Chr), and benzo [a]pyrene (BaP) were detected after one month contact time, while indeno [1,2,3-cd] pyrene (Indp), benzo [ghi]perylene (BghiP) and dibenz [a,h]anthracene (DahA) were only observed at the contact time measurement of two months. By adding sodium azide as an antimicrobial agent and chemical preservative to SW samples, higher concentrations of PAH including IP, DahA and BghiP were observed. The concentration levels of PAH in water samples after two months contact time were higher than water quality standards provided by the World Health Organization (WHO) and other international organizations.

Using biomonitoring as a complementary approach in BTEX exposure assessment in the general population and occupational settings: a systematic review and meta-analysis.

Hazardous organic compounds such as benzene, toluene, ethylbenzene, o-xylene, m-xylene, and p-xylene (known as BTEX) found at work and at home can cause adverse health effects of human beings throughout their lives. Biological monitoring, an exposure assessment method, considers all exposed organic and non-organic compounds. Our goal was to perform a systematic review and a statistical analysis (meta-analysis) of peer-reviewed publications to assess urinary concentrations of BTEX biomarkers in both occupationally-exposed population and the general population. Several major electronic databases, including Scopus, Embase, Medline, Web of Science, and Google scholar (grey literature), were searched for biomonitoring studies of BTEX. Overall, 33 studies met the eligible criteria for the systematic review and six met the full inclusion criteria for meta-analysis. For meta-analysis, we included studies in which unmetabolized BTEX compounds were measured in urine samples. Due to insufficient data, studies that measured BTEX metabolites in urine samples and unmetabolized BTEX compounds in blood samples were excluded from the meta-analysis but were analyzed in the qualitative synthesis. Most studies showed increased urinary concentrations of BTEX in exposed individuals (mainly workers) compared to unexposed individuals. The results showed that the highest total BTEX concentrations were recorded in painters and policemen. This study showed that the undoubted associations between lifestyle and environmental factors and urinary levels of BTEX or its metabolites have not yet been confirmed in current biomonitoring studies. This is attributed to the few studies reported in this research area, the lack of homogeneous information, and the disagreement in the published results of the studies.

Modeling and optimization approach for phytoremediation of formaldehyde from polluted indoor air by Nephrolepis obliterata plant.

This study aimed to model the removal of formaldehyde as an indoor air pollutant by Nephrolepis obliterata (R.Br.) J.Sm. plant using response surface methodology (RSM) and artificial neural network (ANN) models, and optimization of the models by particle swarm optimization algorithm (PSO). The data obtained in pilot-scale experiments under a controlled environment were used in this study. The effects of parameters on the removal efficiency such as formaldehyde concentration, relative humidity, light intensity, and leaf surface area were empirically investigated and considered as model parameters. The results of the RSM model, with power transformation, were in meaningful compromise with the experiments. A multilayer perceptron (MLP) neural network was also designed, and the mean of squared error (MSE), mean absolute error (MAE), and R2 were used to evaluate the network. Several training algorithms were assessed and the best one, the Levenberg Marquardt (LM), was selected. The PSO algorithm proved that the highest removal efficiency of formaldehyde was obtained in the presence of light, maximum leaf surface area and relative humidity, and at the lowest inlet concentration. The empirical system breakthrough occurred at 15 mg/m3 of formaldehyde, and the maximum elimination capacity was about 0.96 mg per m2 of leaves. The findings indicated that the ANN model predicted the removal efficiency more accurately compared to the RSM model.

The concentration of potentially toxic elements (PTEs) in drinking water from Shiraz, Iran: a health risk assessment of samples.

The existence of potentially toxic elements (PTEs) in water bodies has posed a menace to human health. Thus, water resources should be protected from PTEs, and their effect on the exposed population should be investigated. In the present investigation, the concentrations of PTEs such as lead (Pb), mercury (Hg), manganese (Mn), and iron(Fe) in the drinking water of Shiraz, Iran, were determined for the first time. In addition, hazard quotient, hazard index, cancer risk, and sensitivity analysis were applied to estimate the noncarcinogenic and carcinogenic impacts of Pb, Hg, Mn, and Fe on exposed children and adults through ingestion. The mean concentrations (µg/L) of Pb, Hg, Mn, and Fe were 0.36, 0.32, 2.28, and 8.72, respectively, in winter and 0.50, 0.20, 0.55, and 10.36, respectively, in summer. The results displayed that Fe concentration was more than the other PTEs. PTE concentrations were lower than the standard values of the Environment Protection Agency and World Health Organization. Values of the degree of contamination and heavy metal pollution index for lead, mercury, manganese, and iron were significantly low (< 1) and excellent (< 50), respectively. Based on the Spearman rank correlation analysis, positive and negative relationships were observed in the present study. The observations of the health risk assessment demonstrated that mercury, lead, iron, and manganese had an acceptable level of noncarcinogenic harmful health risk in exposed children and adults (hazard quotients < 1 and hazard index < 1). The carcinogenic risk of lead was low (< E - 06), which can be neglected. Monte Carlo simulation showed that water intake rate and mercury concentration were the most critical parameters in the hazard index for children and adults. Lead concentration was also the most crucial factor in the cancer risk analysis. The results of the present study proved that the drinking water of Shiraz is safe and healthy and can be confidently consumed by people.

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.

Simultaneous removal of fluoride and nitrate from synthetic aqueous solution and groundwater by the electrochemical process using non-coated and coated anode electrodes: A human health risk study.

Co-presence of fluoride (F-) and nitrate (NO3-) in water causes numerous health complications. Thus, they should be eliminated by an appropriate method like the EC process. In this research, simultaneous removal of F- and NO3- from synthetic aqueous solution and groundwater has been considered by the EC technique under operational parameters like anode materials (un-coated (Al and Fe) and synthesized coated (Ti/TiRuSnO2 and Ti/PbO2)), cathode materials (Cu, St, and Gr), current density (12, 24, and 36 mA/cm2), inter-electrode distance (0.5, 1, and 2 cm), pH (5.5, 7, and 8.5), NaCl concentrations (0.5, 1, and 1.5 g/L), electrolysis time (15, 30, 45, 60, 90, and 120 min), NO3- concentrations (75, 150, and 225 mg/L), and F- concentrations (2, 4, 6, and 8 mg/L) for the first time in this research. The results proved that Al as non-coated anode and Cu as cathode electrodes were more effective in the co-removal of F- and NO3-. The maximum removal efficiencies of 94.19 and 95% were observed at the current density of 36 mA/cm2, 1 cm of inter-electrode distance, pH 7, 1 g/L of NaCl, and 90 min electrolysis time by Al-Cu electrode for F- (2 mg/L) and NO3- (75 mg/L), respectively. The higher efficiency of Al-Cu electrodes was due to the simultaneous occurrence of electrocoagulation, electroreduction, and electrooxidation processes. Al-Cu electrode application considerably diminished f- and NO3- concentrations in the groundwater. Health risk assessment proved that HQ of F- was significantly decreased after treatment by the Al-Cu electrode. Thus, the EC process using an appropriate and effective electrode is a promising technique for treating aqueous solutions containing F- and NO3-.