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.

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.

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.

Biomonitoring of BTEX in primary school children exposed to hookah smoke.

Hookah smoking is one of the major indoor sources of benzene, toluene, ethylbenzene, and xylenes (BTEX). This study aimed to investigate the potential exposure to BTEX among primary school children, particularly those exposed to hookah smoke. This cross-sectional study was conducted in Khesht, one of the southwestern cities in Iran, in mid-June 2020. Totally, 50 primary school children exposed to hookah smoke were chosen as the case group and 50 primary school children were selected as the control group. Urinary un-metabolized BTEX was measured by a headspace gas chromatography mass spectrometry (GC-MS). Additionally, a detailed questionnaire was used to gather data and information from the students' parents. The mean levels of urinary benzene, toluene, ethylbenzene, m,p-xylene, and o-xylene were 1.44, 5.87, 2.49, 6.93, and 7.17 µg/L, respectively in the exposed children. Urinary BTEX was 3.93-folds higher in the case group than in the controls (p<0.05). Household cleaning products, the floor on which the house was located, children's sleeping place, and playing outdoors were found to be important factors in predicting urinary BTEX levels. Overall, it was found necessary to avoid indoor smoking to prevent the emission of BTEX compounds via exhaled mainstream smoke and to protect vulnerable non-smokers, especially children, from exposure to second-hand and third-hand smoke.

Exposure assessment of children living in homes with hookah smoking parents to polycyclic aromatic hydrocarbons: urinary level, exposure predictors, and risk assessment.

Children are extremely liable to indoor air pollutants as their physiology and a few metabolic pathways are different from those of adults. The present cross-sectional study aimed to assess exposure of children living with parents who use hookah tobacco smoke to polycyclic aromatic hydrocarbons (PAHs) using a biomonitoring approach. The study was conducted on 25 children (7-13 years of age) exposed to hookah smoke at home and 25 unexposed age-matched children. Urinary levels of five metabolites of PAHs were quantified via headspace gas chromatography-mass spectrometry (GC-MS). Urinary malondialdehyde (MDA) was measured, as well. Information regarding the sociodemographic and lifestyle conditions was collected through interviews using managed questionnaires. The urinary 1-OH-NaP and 9-OH-Phe concentrations were respectively 1.7- and 4.6-folds higher in the case samples compared to the control group (p < 0.05). In addition, urinary MDA levels were 1.4 times higher in the exposed children than in the unexposed group, but the difference was not statistically significant (p > 0.05). Increasing the consumption of grilled and meat food in the diet increased the participants' urinary 2-OH-Flu and 1-OH-Pyr levels, respectively. Moreover, sleeping in the living room instead of the bedroom at night was a significant predictor of high 1-OH-NaP and 2-OH-NaP concentrations in the children's urine. Overall, the findings confirmed that children living in their homes with hookah-smoking parents were significantly exposed to naphthalene and phenanthrene. Hence, implementing protective measures is critical to reduce the exposure of this group of children.

Comparative photo-oxidative degradation of etodolac, febuxostat and imatinib mesylate by UV-C/H2O2 and UV-C/S2O82- processes: Modeling, treatment optimization and biodegradability enhancement.

The pharmaceutical contamination in aquatic environment has arisen increasing concern due to its potentially chronic toxicity. In recent years, HO° and SO4°- based advanced oxidation processes (AOPs) have been widely applied in water and wastewater treatments due to their highly efficiency on contaminant removal. Here, the response surface modeling (RSM) was used to investigate the degradation of three typical pharmaceuticals (i.e., etodolac (ETD), febuxostat (FBU) and imatinib mesylate (IMT)) by UV/H2O2 and UV/S2O82- processes. Based on the multiple regression analysis on full factorial design matrix and calculated reaction rate constants, the RSM was built. The experimental rate constants under optimal conditions were quite close to those obtained from the model, implying the good fit of the RSM. In addition, the RSM results indicated that UV/S2O82- process was less sensitive to pH in comparison to the UV/H2O2 process on target contaminant removal. Finally, it showed that UV/S2O82- process was superior to the UV/H2O2 process to on the enhancement of target contaminant biodegradability.

A new computer-based index for swimming pools' environmental health assessment in big data environment by consensus-based fuzzy group decision-making models.

Swimming pools are popularly used for sport and recreational purposes worldwide. These places influence swimmers' health as they are considered public places. This study attempted to introduce a process mining framework which analyzes the environmental health status in swimming pools. In this context, a new numerical index namely Swimming Pool Environmental Health Index (SPEHI) was developed through which, big data extracted from checklists of environmental health inspection of swimming pools were analyzed in fuzzy environment. The methodology comprises MCDM (Multi- Criteria Decision-Making) approach including fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy OWA (Ordered Weighting Average). The performance of this index was evaluated through an applied example on 12 swimming pools in Shiraz, Iran that was run for a three-year sequence from 2015 to 2017. Among 30 evaluation criteria used in this index, the greatest (0.61) and lowest (0.35) group weights were dedicated to "Residual chlorine biological water quality" and "existence of drinking water facilities", respectively. For the study area, SPEHI showed a wide range of environmental health conditions between 37.8 (Relatively good) to 98.19 (Excellent). The extended index could shrink swimming pool's big data to concise values which are interpretable for health experts and managers of sport sector. It helps figuring out the trends of hygiene conditions in a swimming pool over the time and easy access to compare a city's swimming pools as well. The methodology is flexible in structure and thus, it could be applied for other sporting places.

Assessing BTEX concentrations emitted by hookah smoke in indoor air of residential buildings: health risk assessment for children.

Hookah smoke is one of the major indoor sources of Volatile Organic Compounds (VOCs), including Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX). The present study aimed to investigate potential exposure to BTEX compounds among primary school children whose parents smoked hookah at home. BTEX concentrations in indoor air were measured in 60 residential buildings of Khesht, southwestern Iran (case = 30 and control = 30). Target compounds were sampled by charcoal tubes, and the samples were then analyzed by GC-FID. Monte Carlo simulation was used to assess the carcinogenic and non-carcinogenic risks of BTX exposure for the children aged 7-13 years. The concentrations of benzene (7.19 ± 3.09 vs. 0.82 ± 0.5 µg/m3), toluene (1.62 ± 0.69 vs. 0.3 ± 0.22 µg/m3), and xylenes (2.9 ± 1.66 vs. 0.31 ± 0.22 µg/m3) were considerably higher in the indoor air of the case houses compared with the control houses (p < 0.05). The Incremental Lifetime Cancer Risk (ILCR) of benzene for non-smoking and smoking houses were estimated 1.8 × 10-6 and 15 × 10-6, respectively, exceeding the recommendations of the World Health Organization (WHO) and the Environmental Protection Agency (EPA) (1 × 10-6). Moreover, Hazard Quotients (HQs) of all BTX compounds were < 1. The indoor benzene concentration was significantly influenced by the floor at which families lived and type of the kitchen. In order to prevent children's exposure to BTX emitted by hookah, banning indoor smoking is the only way to eliminate these compounds in the indoor air.

The effects of exogenous application of melatonin on the degradation of polycyclic aromatic hydrocarbons in the rhizosphere of Festuca.

The study aimed to assess the effects of melatonin, a plant growth regulator, on the degradation of phenanthrene (Phe) and pyrene (Py), in the rhizosphere of the Festuca grass. The experiments were divided into the following groups: 1) soil contaminated with Phe and Py, without the Festuca, 2) contaminated soil + Festuca, 3-5), contaminated soil + Festuca + the application of melatonin in three separate doses: 10, 50, or 100 µM. After 90 days, the effects of melatonin supplementation on the degradation of polycyclic aromatic hydrocarbons (PAHs) were analyzed by evaluating the rate of PAHs degradation, the expression of genes encoding salicylaldehyde dehydrogenase (SDH) and glutathione peroxidase (GPX) enzymes in Pseudomonas putida, as well as by measuring the total activity of dehydrogenase and peroxidase enzymes. Our results have shown that in soil contaminated by 300 mg kg-1 PAHs, application of melatonin (10, 50, 100 µM), resulted in the following increase in the dehydrogenase and peroxidase activity in all three applied doses (19% and 5.7%), (45.3% and 34.3%), (40.9% and 14.3%), respectively in comparison to the control group. The experiment showed that soil supplementation with melatonin at 50 µM, resulted in the highest removal rate of PAHs. According to our results, melatonin demonstrated a potentially favorable role in enhancing plant biomass, as well as an increase in soil bacterial population, and the activity of antioxidative enzymes in P. putida, causing all tested parameters of the soil and the expression of desired genes to be advantageously altered for the degradation of the chosen PAHs.

4-chlorophenol removal by air lift packed bed bioreactor and its modeling by kinetics and numerical model (artificial neural network).

4-chlorophenol (4-CP) is a hazardous contaminant that is hardly removed by some technologies. This study investigated the biodegradation, and physical 4-CP removal by a mixed microbial consortium in the Airlift packed bed bioreactor (ALPBB) and modeling by an artificial neural network (ANN) for first the time. The removal efficiency of ALPBB was investigated at 4-CP(1-1000 mg/L) and hydraulic retention time (HRT)(6-96 hr) by HPLC. The results showed that removal efficiency decreased from 85 at 1 to 0.03% at 1000 mg/L, with increasing 4-CP concentration and HRT decreasing. BOD5/COD increased with increasing exposure time and concentration decreasing, from 0.05 at 1000 to 0.96 at 1 mg/L. With time increasing, the correlation between COD and 4-CP removal increased (R2 = 0.5, HRT = 96 h). There was a positive correlation between the removal of 4-CP and SCOD by curve fitting was R2 = 0.93 and 0.96, respectively. Moreover, the kinetics of 4-CP removal follows the first-order and pseudo-first-order equation at 1 mg/L and other concentrations, respectively. 4-CP removal modeling has shown that the 2:3:1 and 2:4:1 were the best structures (MSE: physical = 0.126 and biological = 0.9)(R2allphysical = 0.999 and R2testphysical = 0.999) and (R2allbiological = 0.71, and R2testbiological = 0.997) for 4-CP removal. Also, the output obtained by the ANN prediction of 4-CP was correlated to the actual data (R2physical = 0.9997 and R2biological = 0.59). Based on the results, ALPBB with up-flow submerged aeration is a suitable option for the lower concentration of 4-CP, but it had less efficiency at high concentrations. So, physical removal of 4-CP was predominant in biological treatment. Therefore, the modification of this reactor for 4-CP removal is suggested at high concentrations.

A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.

BACKGROUND: Proper Health-Care Waste Management (HCWM) and integrated documentation in this sector of hospitals require analyzing massive data collected by hospital's health experts. This study presented a quantitative software-based index to assess the HCWM process performance by integrating ontology-based Multi-Criteria Group Decision-Making techniques and fuzzy modeling that were coupled with data mining. This framework represented the Complex Event Processing (CEP) and Corporate Performance Management (CPM) types of Process Mining in which a user-friendly software namely Group Fuzzy Decision-Making (GFDM) was employed for index calculation. FINDINGS: Assessing the governmental hospitals of Shiraz, Iran in 2016 showed that the proposed index was able to determine the waste management condition and clarify the blind spots of HCWM in the hospitals. The index values under 50 were found in some of the hospitals showing poor process performance that should be at the priority of optimization and improvement. CONCLUSION: The proposed framework has distinctive features such as modeling the uncertainties (risks) in hospitals' process assessment and flexibility enabling users to define the intended criteria, stakeholders, and number of hospitals. Having computer-aided approach for decision process also accelerates the index calculation as well as its accuracy which would contribute to more willingness of hospitals' experts and other end-users to use the index in practice. The methodology could efficiently be employed as a tool for managing hospitals' event logs and digital documentation in big data environment not only for the health-care waste management, but also in other administrative wards of hospitals.

Photocatalytic degradation of atrazine herbicide with Illuminated Fe+3-TiO2 Nanoparticles.

BACKGROUND: Atrazine is a herbicide that is widely used to control broadleaf and grassy weeds for growing many crops especially in maize production. It is a frequently detected herbicide in many groundwater resources. This study aimed to assess the feasibility of using ultraviolet radiation UV and fortified nanoparticles of titanium dioxide (TiO2) doped with trivalent iron to remove atrazine from aqueous phase and determin the removal efficiency under the optimal conditions. RESULTS: The results of this study demonstrated that the maximum atrazine removal rate was at pH = 11 in the presence of Fe+ 3-TiO2 catalyst =25 mg/L and the initial concentration of atrazine equal to 10 mg/L. As the reaction time increased, the removal rate of herbicide increased as well. Atrazine removal rate was enhanced by the effect of UV radiation on catalyst activation in Fe+3-TiO2/UV process. It was also revealed that pH has no significant effect on atrazine removal efficiency (p > 0.05). CONCLUSION: Based on the data obtained in this study, atrazine removal efficiency was increased by increasing pH, initial atrazine concentration, catalyst, and contact time. The results also showed Fe+3-TiO2/UV process was an appropriate method to reduce atrazine in contaminated water resources. In conclusion, Fe+3-TiO2/UV process may enhance the rate of atrazine reduction in highly polluted water resources (more than 99%).

Optimization of DRASTIC method by artificial neural network, nitrate vulnerability index, and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain, Iran.

BACKGROUND: Extensive human activities and unplanned land uses have put groundwater resources of Shiraz plain at a high risk of nitrate pollution, causing several environmental and human health issues. To address these issues, water resources managers utilize groundwater vulnerability assessment and determination of protection. This study aimed to prepare the vulnerability maps of Shiraz aquifer by using Composite DRASTIC index, Nitrate Vulnerability index, and artificial neural network and also to compare their efficiency. METHODS: The parameters of the indexes that were employed in this study are: depth to water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, hydraulic conductivity, and land use. These parameters were rated, weighted, and integrated using GIS, and then, used to develop the risk maps of Shiraz aquifer. RESULTS: The results indicated that the southeastern part of the aquifer was at the highest potential risk. Given the distribution of groundwater nitrate concentrations from the wells in the underlying aquifer, the artificial neural network model offered greater accuracy compared to the other two indexes. The study concluded that the artificial neural network model is an effective model to improve the DRASTIC index and provides a confident estimate of the pollution risk. CONCLUSIONS: As intensive agricultural activities are the dominant land use and water table is shallow in the vulnerable zones, optimized irrigation techniques and a lower rate of fertilizers are suggested. The findings of our study could be used as a scientific basis in future for sustainable groundwater management in Shiraz plain.

Degradation of atrazine by microbial consortium in an anaerobic submerged biological filter.

Atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) (ATZ) is one of the components of S-triazine. Due to its certain characteristics, ATZ causes pollution in various ecosystems and has been of concern for its probable carcinogenic effects on humans. Researchers have used chemical and physical methods for removing ATZ from the environment. Although these methods are quick, they have not been capable of complete mineralization. Therefore, researchers are looking for methods with lower energy consumption and cost and higher efficiency. In this study, biodegradation of ATZ by microbial consortium was evaluated in the aquatic environment. The present study aimed to evaluate the efficiency of ATZ removal from aqueous environments by using an anaerobic submerged biological filter in four concentration levels of atrazine and three hydraulic retention times. The maximum efficiencies of ATZ and soluble chemical oxygen demand (SCOD) were 51.1 and 45.6%, respectively. There was no accumulation of ATZ in the biofilm and the loss of ATZ in the control reactor was negligible. This shows that ATZ removal in this system was due to biodegradation. Furthermore, the results of modeling showed that the Stover-Kincannon model had desirable fitness (R² > 99%) in loading ATZ in this biofilter.

Atrazine removal from aqueous solutions using submerged biological aerated filter.

Atrazine is widely used in the agriculture as an herbicide. Due to its high mobility, Atrazine leaks into the groundwaters, surface waters, and drinking water wells. Many physical and chemical methods have been suggested for removing Atrazine from aquatic environments. However, these methods are very costly, have many performance problems, produce a lot of toxic intermediates which are very harmful and dangerous, and cannot completely mineralize Atrazine. In this study, biodegradation of Atrazine by microbial consortium was evaluated in the aquatic environment. In order to assess the Atrazine removal from the aquatic environment, submerged biological aerated filter (SBAF) was fed with synthetic wastewater based on sucrose and Atrazine at different hydraulic retention times (HRTs). The maximum efficiencies for Atrazine and Soluble Chemical Oxygen Demand (SCOD) removal were 97.9% and 98.9%, respectively. The study findings showed that Stover-Kincannon model had very good fitness (R2 > 99%) in loading Atrazine in the biofilter and by increasing the initial concentration of Atrazine, the removal efficiency increased. Aerobic mixed biofilm culture was observed to be suitable for the treatment of Atrazine from aquatic environment. There was no significant inhibition effect on mixed aerobic microbial consortia. Atrazine degradation depended on the strength of wastewater and the amount of Atrazine in the influent.