مجله محیط زیست و مهندسی آب
سال هشتم شماره 4 (زمستان 1401)

In this study, the adsorption of methylene blue (MB) from an aqueous solution on copper-alginate (Cu(II)-A) granules containing activated carbon derived from polyethylene terephthalate (PEtAC) with different experimental conditions was investigated. The composition and structure of the granules were characterized by SEM and BET methods. The effect of various variables including dye concentration, pH, adsorbent amount, and contact time was investigated by batch method. Equilibrium data were evaluated using Langmuir, Freundlich, and Temkin isotherms. The adsorption isotherm fits well with the Langmuir model (0.9973), which shows that the MB dye adsorption on the granules is homogeneous. The maximum adsorption capacity under optimal conditions for the removal of MB was 86.96 mg/g. Kinetic data were analyzed using the first-order and second-order Lagergren equations. The quasi-second-order model showed the best fit for the synthetic studies (R2 = 0.9997). In addition, no obvious decrease was observed after up to five adsorption cycles, indicating that the PETAC/Cu (II) -A adsorbent has good stability and reusability. Overall, the results show that the prepared granules can be used an am efficient adsorbent for the treatment of colored effluents.

Ibuprofen is one of the most widely used drugs in the world, which affects the health of living organisms by causing pollution in water sources. Therefore, this study was conducted with the aim of determining the effectiveness of modified carbon of straw and sesame stubble in removing ibuprofen from aqueous solutions. For this purpose, ammonium chloride, zinc chloride, and phosphoric acid were used to optimize the adsorbent. Also, the changes in the absorbent surface and its characteristics were studied using a scanning electron microscope (SEM) and infrared spectroscopy (FTIR) technique. After determining the optimal conditions of pH variables, contact time, temperature, and adsorbent dose, the surface adsorption process was investigated under three Langmuir, Freundlich, and Dubinin-Radoshkevich models. On the other hand, first-order and pseudo-second-order kinetic models were used to process the adsorption data. The results showed that the surface adsorption process followed the Freundlich isotherm model pseudo-second-order kinetics. pH, contact time, initial concentration of ibuprofen, and optimal adsorbent dose were 3, 120 min, 50 mg/l, and 0.10 g/l respectively at 25°C. The results of this study showed that agricultural residues such as straw and sesame stubble can be used as effective and cost-effective adsorbents to remove the remaining pharmaceutical compounds from aqueous solutions.

The use of natural processes, including the physiological potential of plants, is a suitable solution. In this study in order to assess the effect of waste leachate and industrial wastewater on the absorption of heavy metals by the Vetiver plant, two separate factorial experiments were performed in the crop year 2020-2021 as a completely randomized design. Experiment treatments factors included waste leachate and industrial wastewater use separately on 5 levels (0, 25, 50, 75, and 100%) in three replications (B1, B2, B3) and two irrigation periods of 5 and 10 days (A5, A10). The amount of iron, zinc, copper, manganese, potassium, and sodium measured in vetiver showed waste leachate had a significant effect at the level of 5% (P <0.05). Meanwhile, the use of industrial wastewater had a significant effect on the amount of iron, zinc, copper, manganese, and sodium absorbed by the vetiver at the level of 5% (P <0.05) but it had no significant effect on the potassium amount (P> 0.05). R4A1 and W5A1 treatments showed a relatively good response with a decrease in biomass production below 10% compared to the control treatment. According to the results, the Vetiver species has relatively high compatibility in the absorption of heavy metals with unconventional waters and can have a special application for soil and water protection.

Pharmaceutical contaminants are one of the most important environmental problems that must be cleared of aqueous environments before they enter the environment. Adsorption method is operationally easy and cost-effective if the adsorbent is not expensive. The purpose of this study is optimization the process of removal of tetracycline from aqueous solutions by nanoclay adsorbent and investigation the kinetics and adsorption isotherms. In this study, after preparing the nanoclay, optimization of parameters was done with Design Expert software. The parameters effect of pH, initial concentration and amount of adsorbent were investigated and SEM, XRD and FTIR analyzes were done to identify nanoclay properties. The optimal values ​​of parameters were pH equal to 9.5, adsorbent amount equal to 1.2 g and initial concentration equal to 21.15 mg /l at 25 °C, time of 30 min and stirring speed of 1000 rpm. The study of kinetic models and equilibrium isotherms showed that the adsorption follows the Pseudo-second Order (R2=0.999(   and   the Langmuir model, respectively. Under optimal condition, nanoclay as a low cost and environmentally friendly adsorbent has a good ability to adsorb tetracycline from aqueous solutions.

The study of sediments as one of the reservoirs for absorbing environmental pollutants and especially heavy metals is of particular importance. Therefore, this research was conducted with the aim of identifying and evaluating the contamination of arsenic, cadmium, nickel, and vanadium elements in the sediments of Farahabad coast of the Caspian Sea in 2018. In this study, after collecting 36 sediment samples from 12 selected stations, the values ​​of pH, EC, organic matter, and texture of sediments were determined. The concentrations of elements were determined by inductively coupled plasma optical spectroscopy. In addition, in order to evaluate the pollution of sediments, environmental toxicology criteria were calculated, including indicators of pollution coefficient, enrichment, and pollution load. In order to identify the potential sources of elements and their grouping in the sediment samples, multivariate statistical methods were used, namely principal component analysis and hierarchical clustering. For statistical processing of the results, one-way analysis of variance, one-sample t-test, and Pearson's correlation coefficient were used in the SPSS software. The average concentration of arsenic, cadmium, nickel, and vanadium was 12.7, 0.191, 35.0, and 31.9 mg/kg, respectively. The output results of PCA, HCA models, EF index values, ​​and coefficient of variation, as well as Pearson's correlation matrix, showed that arsenic probably originates from man-made sources and cadmium, nickel, and vanadium elements have natural sources.

The gas production operation in the gas refinery, in addition to creating special and ordinary wastes, also leads to the production of industrial wastes. Failure to properly manage special waste in such refineries will cause environmental hazards and threaten the workforce’s health. This research aimed to identify, differentiate and prioritize industrial wastes in this refinery to eliminate or reduce environmental risks. After collecting waste information, 19 cases of industrial waste were identified in process units and facilities. Then the data was analyzed through documentation, expert theory and Delphi method, and according to the importance of multi-criteria decision-making method for ranking and waste management, TOPSIS method was used for prioritization. The findings showed waste Sulfur with an amount of 86%, has the highest priority of relative proximity to high-risk waste and mixed laboratory containers, with an amount of 20%, have the least priority of relative proximity to low-risk waste among industrial wastes. Also, based on the percentage distance of the relative closeness of the residues to each other, 5 groups (about 26%) are at the high level, 6 groups (about 32%) are at the medium level and 8 groups (about 42%) are at the low level of industrial wastes were placed.

Industrial and agricultural processes have resulted in the release of cadmium metal into the ecosystem. One way to remove this heavy metal is adsorption. This research aimed to determine the efficiency of magnetic nanographene for removing cadmium ions from aqueous solution., This research was done in a discontinuous system at a laboratory scale. For this purpose, the effect of effective parameters such as pH, concentration, contact time, ambient temperature, adsorbent dose, and other factors was investigated. The results showed that the maximum amount of cadmium absorption occurred in the conditions of pH=6, concentration 100 mg/l, contact time 120 min, ambient temperature 45 ° C and adsorbent dose 0.01 g.  Thermodynamic parameters showed that the absorption process of cadmium metal was spontaneous and endothermic in the temperature range of 288 to 318 K The pseudo-second-order model with adsorption rate constant (K2 = 0.0092) and coefficient of determination (R2 = 0.99) showed that it describes the laboratory data better. Also, the examination of adsorption isotherms showed that the Freundlich isotherm (R2 = 0.96) was more suitable for describing the adsorption process and was more consistent with the laboratory data. According to the results of this research, magnetic oxide nanographene adsorbent with 92.8% efficiency can be used to remove cadmium from aqueous solutions.

The most important goal in the planning and optimal operation of the reservoir system is to determine the various operating policies that can operate properly Under the drought condition and existing uncertainties. In this study, a combination of the Horse herd optimization algorithm (HOA) and WEAP simulator model was used to extract the optimal reservoir exploitation policies in the form of specific optimization and objective functions were calculated based on the results of the implementation of each scenario and the total operating period for Maroon and Jarreh reservoir dams. The results showed that the average error of the optimal rules extracted from the support vector machines relative to the output of the HOA algorithm in the validation stage is less than 17%, which indicates the high efficiency of this method in predicting the optimal pattern of the dam control curve in real-time. Moreover, evaluation of different scenarios showed that agricultural development in areas 1, 4, and 5 of Ramhormoz will be reduced by an average of 50% and also a 10% reduction in inflow to Marun and Jarreh dams will have negative effects on Shadegan wetland.

Nowadays, machine learning models are able to make good predictions based on pattern extraction between data. In this study, a neural-fuzzy network (ANFIS) was used to predict the inflow to the reservoirs of a dam namely, the Mahabad dam located in the northwestern part of Iran. A new Harris Hawk (HHO) optimization algorithm was also used to improve the ANFIS (HHO-ANFIS) structure. Monthly precipitation and temperature and inlet flow data to the reservoir one to three months ago were used as input parameters as 6 different input patterns. About 70% of the data was used for training and 30% to test the models. The results showed that the ANFIS model has good accuracy in training data although, for test data, its accuracy was greatly reduced. The development of the HHO-ANFIS model improved the accuracy of the prediction. The patterns with all input parameters had the highest prediction accuracy. In this pattern, values ​​of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Nash Sutcliffe Efficiency coefficient (NSE) for test data were 3.9 MCM, 2.41 MCM, and 0.86, respectively. Due to the good performance of the model used, it can be recommended for time series predictions.

Because direct measurement of evapotranspiration is costly and time-consuming, researchers have turned to the estimation of evapotranspiration via indirect approaches. The aim of this study is to investigate the capability of kernel-based, tree-based, bagging-based data-driven, and empirical models to estimate reference evapotranspiration. For this purpose, data related to meteorological parameters such as average temperature, hours of sunshine, maximum and minimum temperature, wind speed, precipitation, and relative humidity were collected over a period of 39 years. A correlation matrix, relief algorithm, and trial and error based on the author’s own experience were used to select input scenarios. The performance of these methods was evaluated using correlation coefficient (R2), root mean square error (RMSE), scattering index (SI), Nash Sutcliffe (NS), and Wilmot indexes (WI). Based on the results, scenario 13 includes maximum temperature and monthly time index based on the relief algorithm was selected as the best scenario, also on the other hand the random tree model with R=0.99, RMSE=0.04 mm/day, and SI=0.01 was selected as the superior method. Thus, the maximum temperature was defined as the efficient meteorological parameter for the reference evapotranspiration modeling.

Here, the contraction coefficient, discharge coefficient, hydraulic jump length, and relative energy dissipation in which the gate acts as a supercritical flow generator were investigated at different openings. The maximum value of the contraction coefficient is related to the gate with the lowest amount of opening. The amount of gate opening is inversely related to the discharge coefficient. At a certain discharge, increasing opening leads to a decrease in relative energy dissipation. Moreover, with increasing Froude number, relative energy dissipation increases. Here, the amplitude of the Froude number changed from 2.2 to 14.2, which has a direct effect on the hydraulic jump length, and with increasing opening, the Froude number and jump length decreased. The amount of opening is inversely related to the upstream water depth and the hydrodynamic force applied to the gate. Regression nonlinear polynomial relationships were presented to predict relative energy dissipation and discharge coefficient with appropriate statistical indicators of root mean square error and Kling Gupta. For the discharge coefficient, mdecreasedore than 78% of the data have an error of less than ±1.5%. In addition, for energy dissipation relative to the upstream and downstream, more than 88% of the data have a relative error of less than ±5 and ±1%, respectively.

FSM-16 mesoporous silica modified with metformin (FSM-16-Met) is known as a suitable additive for membrane modification in order to obtain a modified membrane with anti-fouling capability for highly efficient oily wastewater treatment. In this research, the production of polyether sulfone microfiltration membranes was done using an efficient modification process. The modified membrane with FSM-16-Met nanoparticles showed excellent fouling resistance, while maintaining a high net water transfer efficiency of more than 150 kg/m2.h without significant oil infiltration. The optimal modified membrane PES/FSM-16-Met had a high net water flux of 156.07 kg/m2.h and a low contact angle compared with the unmodified membrane (respectively 79.8 and 46.25 for the unmodified and was the modified optimum). Also, the flux recovery ratio is more than 97% and the ability to resist clogging is Rir = 79.58 and Rir = 2.13%, respectively, for unmodified and modified membranes during filtration at different concentrations of oily feed (300 and 500 mg/l). It was one of the features obtained in this study. Overall, this work provides insight into efficient polymer membrane modifications with very low oil cake layer formation on the membrane surface, which shows great potential for industrial-scale oily wastewater treatment in the future.

Acoustic Doppler velocimetry (ADV) is one of the most suitable devices for measuring flow characteristics. Determination of measurement frequency and duration, in a way that the results are calculated with the lowest error, is very important. The goal of this study was to determine the optimum measurement frequency and duration to save money and time. 3D instantaneous subcritical flocharacteristicsts are measured at 200, 100, 25, and 5Hz frequencies for a duration of 3 minutes, in a laboratory flume with an aspect ratio of less than 5. Then, 3D averaged velocities, shear velocity, turbulence intensity, and Reynolds shear stress are calculated. Results show that the reduction of error is independent of the number of measured data and its dependence is on the data collection duration and frequency. For measurements of 3D averaged velocity components, the appropriate measurement frequency and duration are 1Hz and 50 seconds, respectively. To determine the shear velocity, using logarithmic law, reducing the frequency and duration, results in a maximum error of 13%. For calculation of turbulence flow characteristics, like turbulence intensity and Reynolds shear stress, the measurement frequency, and duration of up to 25Hz and 50-70sec, respectively, results in an error of less than 10%.

This study was conducted with the general purpose of explaining the behavior of agricultural water conservation among farmers in Bavi County. The statistical population of this study consisted of all farmers in Bavi County of Khuzestan province. Using Cochran formula sampling and the stratified proportional sampling method, 190 persons were selected as the study sample. The data collection tool of the study was a questionnaire whose validity was confirmed by a panel of experts, and its reliability was established by calculating Chronbach's Alpha Coefficient (α > 0.7). Data analysis was done by SPSSwin18 and Smart Pls software. In this research, the theory of planned behavior was used for the research framework. The results of structural equation modeling showed that the variables of attitude, subjective norm, perceived behavior control, and inclination are able to explain 60.5% of water conservation behavior. In general, the results of this study can provide new insights for policymakers in this field, because in previous studies, more emphasis has been placed on incentives and limitations for water conservation, and attention has not been paid to environmental psychological studies.

Water resources are limited in arid and semi-arid regions. Hirmand catchment is one of the arid and semi-arid regions of the country. The agricultural sector is the largest consumer of water in the Hirmand catchment. In recent years, water shortages in the Hirmand catchment have hampered water supply for agriculture, the environment and drinking water. Therefore, integrated water resources management in this area is important. In this research, the aim is to simulate and optimize water consumption in order to integrate water resources in the Hirmand catchment. For this purpose, a water evaluation and planning model (WEAP) was used to simulate the water resources system of Helmand catchment and a multi-objective linear programming technique was used to optimize water consumption. In the reference scenario, water demand in the Helmand catchment is 1400 million cubic meters per year, which increases over time due to population growth in the drinking sector. The agricultural sector is responsible for the highest amount of water consumption in the Hirmand catchment. 75.18% of water consumption in Hirmand catchment is related to agriculture, 19.44% is related to the environment and 38.5% is related to drinking. The highest water shortage is related to the agricultural sector. 35.21% of the total water demand in Hirmand catchment is not met. The agricultural and environmental sectors are facing water shortages. 50.12% of water demand in the environmental sector and 31.63% of water demand in the agricultural sector is not met. If the current situation continues for the next 20 years, the problem of fine dust in the region will be inevitable. After optimization, water consumption in the Hirmand catchment area will be reduced to 382.82 million cubic meters and 93.60 and 89.03% of water demand in agriculture and environment will be met. In the reference scenario, the amount of water shortage in agriculture and the environment in summer is 170.562 and 90.535 million cubic meters and the amount of water supply is 95.407 and 0.010 million cubic meters. After optimization, the amount of water shortage in summer in agriculture and the environment will reach 18.090 and 4.302 million cubic meters and the amount of water supply will increase to 151.940 and 86.059 million cubic meters. In the reference scenario, the net profit of farmers in the agricultural sectors of Sistan, Zahak and Miankangi is 6365.506, 6390.649 and 3499.895 billion rials, respectively. With the optimization of the agricultural pattern, the net profit of farmers in the agricultural sector of Sistan has increased by 139.46%, the agricultural sector of Zahak has increased by 10.66% and the agricultural sector of the middle class has increased by 52.50%. After optimizing onion, sesame, tomato and garden crops were removed from the cultivation pattern of the region. Wheat, barley, herbs, sorghum, legumes, alfalfa and cucumber were selected as the most optimal crops. The area under cultivation of medicinal plants due to lower water requirements and higher net profit than other crops had the highest percentage of increase in area under cultivation. Wheat is also one of the optimal products due to the existence of protectionist policies such as the guaranteed purchase policy by the government and the absence of price risk for this product. Sorghum crop is climatically compatible with the tropical region of Helmand catchment area and has a high yield per unit area and as a result, high profitability in the agricultural pattern of the region.