مجله محیط زیست و مهندسی آب
سال دهم شماره 1 (بهار 1403)

In this research, the biological adsorption process of lead heavy metal was investigated using brown algae Nizimuddinia zanardini and green algae Ulva rigida. Optimum adsorption conditions by measuring pH, the amount of adsorbent, time, and the concentration of lead ion were investigated. Langmuir, Freundlich, and Temkin isotherms were used to investigate surface adsorption. Adsorption kinetics were investigated according to pseudo-first and second-order kinetic equations. Examining the pH results, it was found that brown algae at pH = 5 and green algae at pH = 6 could reach the maximum adsorption of lead. Examining the time-related results, it was found that the best adsorption time for both algae was 60 min. The results of the adsorbent dosage showed that the two bioadsorbents of brown and green algae have the highest amount of adsorption in the amounts of 0.5 and 0.7 g, respectively, and in the initial concentration of metal ions, the highest efficiency was obtained in the dosage of 2 mg/l. The results of the isotherm model showed that lead adsorption by brown algae corresponds to the Langmuir isotherm and green algae to the Freundlich isotherm. Also, according to the kinetic results, both adsorptions follow second-order kinetics.

Phosphorus (P) is considered the leading cause of eutrophication in natural waters and has received considerable attention recently from the scientific community. In this study, P removal from aqueous solutions was investigated using bentonite, kaolinite, calcite, and zeolite mineral adsorbents modified with extract of walnut shell and wheat straw, chitosan, sodium carboxymethyl cellulose (CMC), and malic acid. Phosphorus sorption was evaluated using adsorption isotherms equations. Modified adsorbents with chitosan obtained the maximum sorption capacity of P. The results showed that P sorption capacity by Chitosan-adsorbents (bentonite (0.35 mg/g), calcite (2.09 mg/g), kaolinite (0.41 mg/g) and zeolite (0.43 mg/g)) was improved by ~ 129, 102, 128 and 119%, respectively compared to unmodified adsorbents (bentonite (0.27mg/g), calcite (2.04 mg/g), kaolinite (0.32 mg/g) and zeolite (0.36 mg/g). Langmuir and Freundlich models were used to simulate the sorption of P on modified adsorbents. The double layer model (DLM) could predict P adsorption by modified adsorbents over a wide pH range and varying ionic strength. Thermodynamic parameters showed that the nature of P adsorption by these adsorbents was non-spontaneity nature.

The temperature difference between the pure and impure water on the two sides of a membrane can lead to water purification. The asymmetry of molecular kinetic energy on both sides of the membrane causes pure water to move from the hot side to the cold one. In this research, a carbon nanotube membrane filtration system based on the temperature difference between water sources has been investigated by the molecular dynamics simulation method. The effect of various factors has been investigated. The simulation results confirm the possibility of using a thermal driving force for water purification with carbon nanotubes. The results show that by increasing the hot source temperature, the water passage and the purification speed increase. Such that increasing the temperature difference between sources from 15 to 60 K increases the water purification rate by 30%. Simultaneously, the possibility of impurities passing through the nanotube also increases. Increasing the impurity concentration slows down the purification process. Increasing the diameter of the nanotube up to 15 Å increases the water purification rate. In nanotubes with a diameter of less than 15 Å, 100% of impurities are removed. Among the examined nanotubes, the best performance was obtained for the armchair carbon nanotube.

To investigate the effect of different levels of vermicompost and irrigation on the yield and irrigation water efficiency of Quinoa, this experiment was conducted as a split plot based on a randomized complete block design in the research field of the University of Kurdistan located in Dehgolan in 2021. The experimental factors included four levels of irrigation water 50, 75, 100, and 125% of the water requirement of the quinoa crop and the variable included four levels of vermicompost fertilizer to 0, 5, 10, and 15 tons/ha, respectively. The irrigation method used in this experiment was a drip-strip irrigation system. The amount of irrigation water was measured by a volumetric meter installed on the main pipe. The highest yield of quinoa seed equaled 2375 kg/ha was observed in the treatment of 125% of the water requirement and 15 tons/ha of vermicompost and a biological yield of 5560 kg/ha in the treatment of 100% of the water requirement and 15 tons/ha vermicompost. The highest values of water consumption efficiency and water use efficiency were observed in the treatment of 50% water requirement. The application of 15 tons/ha vermicompost caused a significant increase in water use efficiency compared to the control treatment. The highest quinoa harvest index was observed in the treatment of 125% of the crop water requirement.

Plastic pollution is an important emerging environmental problem with possible impacts on biodiversity and human health. Although the majority of the scholarly attention in this field has been directed to oceans, plastic pollution has not been fully elucidated in freshwater ecosystems. Hence, this study aimed at investigating the spatial distribution and macro- and meso-characteristics of sedimentary plastic waste items along the Zayandeh-Rud River course. 400 types of anthropogenic debris were collected from 21 sampling sites consisting of macroplastic 58.3% (233 items), mesoplastic 18% (72 items), and other waste 23.8% (94 items). Bags (polyethylene), food packs (mainly polypropylene and polystyrene), and bottles (polyethylene terephthalate) were the dominant plastics. The Clean-Coast index was used to determine the river's cleanliness, showing that most parts of the river are clean. The Clean-Coast Index revealed useful implications in evaluating the continuity and success of protective measures such as educational, media, and enforcement actions to reduce river pollution.

Preparation of flood zoning maps is one of the primary and necessary measures in the management of flood prone areas. In this study, analytic hierarchy process, and geographic information system were used to assess and zoning the flood potential map in Kurdistan province, Iran. The factors involved in flooding including rainfall, slope, distance from river, drainage density, land use and topographic wetness index were used for zoning and providing flood maps. Effective criteria, except for land use and rainfall, were prepared using the digital elevation model, and each factor was weighted by Expert Choice software. The results showed that rainfall, slope, and distance from the river with weights of 0.409, 0.295, and 0.134 were the most important factors, respectively. In terms of flood potential zoning, different areas of the province were placed in five categories: very low (0.1%), low (1.9%), medium (43%), high (52%) and very high (3%). The flood potential at the outlet of the watersheds limited to the downstream and low-slope areas of main rivers in the western and central parts of the province was very high.

In this research work, two machine learning models including Least Squares Support Vector Machines (LS-SVR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to predict the scour depth around the bridge piers. For this purpose, 240 data series including pier geometry, flow condition, sediment characteristics, and some dimensional parameters were used. Dimensional and no dimensional parameters were considered. The performance of the models was evaluated using root mean square error (RMSE), mean absolute percentage error (MAPE), and Nash–Sutcliffe efficiency (NSE) criteria. The results showed that in both models, the use of dimensional parameters for prediction leads to high prediction accuracy. The comparison between the models also showed that the LS-SVR algorithm with the criteria RMSE=46.84, MAPE=38.03, NSE=0.62 for the test data of the first model and RMSE=28.62, MAPE=38.97, NSE=0.67 for the test data results of the second pattern are more accurate than the ANFIS algorithm. This research indicates that machine learning models are a suitable alternative to empirical models in predicting scour depth of bridge piers.

This research was conducted to investigate the effect of planting densities on some morphophysiological characteristics of sports turfgrass under low water stress conditions. The experiment was carried out in the form of split plots, based on a randomized complete block design with three replications. Treatments included low water stress at three levels of 90 (control), 60 and 30% of field capacity (FC), and planting density of 20, 30, and 40 g seed/m2. Seeds were planted according to the desired densities in plots measuring 2×3 m2. Two months after planting, low water stress was applied for three weeks. The results showed that the treatments had a significant effect on the evaluated traits. The highest fresh and dry weight of the aerial part, leaf length, and total chlorophyll content was observed in 90% FC and the density of 20 g seed/m2 treatment. The highest root fresh and dry weight, root volume, and total carbohydrates were obtained in 30% FC and density of 20 g seed/m2 treatment. Moreover, the highest proline content was in 30% FC and density of 40 g seed/m2 treatment. According to the results, the planting density of 20 g seed/m2 and 90% FC had a more favorable effect on the vegetative and physiological indicators of sport turfgrass.

One of the significant issues in hydraulic engineering is reducing erosion in rivers by using groynes to preserve soil. The purpose of this study is to investigate numerically the groynes' presence on the sedimentary flow parameters using FLOW-3D software. For this purpose, groynes were examined at angles 30°, 60°, and 90° under 10 scenarios in various discharge and hydraulic conditions. Here, the mesh block with dimensions of 5 mm was chosen as the optimal mesh block for simulating models. In addition, Large Eddy Simulation (LES) turbulence model was used for simulations. In the scenarios where two blades are used scouring is observed in the first blade, while the sedimentation phenomenon was observed in the groyne after the first groyne in the direction of the flow. In the two blades with a distance of 0.60 m from each other, 48 mm erosion occurred. The highest amount of scour is related to the arched groyne (LLeft-Q285) with 45 mm. Discharges have an increased effect on scouring, so by comparing the scenarios with one groyne (I-Q285, I-Q200, and I-Q350), the lowest amount is with the value of 5.5mm corresponding to I-Q200. The insufficient erosion in the angled groynes corresponds to the smaller angle scenario.

Constant and proper mixing of water in fish farms is essential for creating maximum uniformity, minimizing stagnant areas, properly distributing oxygen, and removing solid waste from the bottom of the ponds. The effect of the inflow installation mode and inflow momentum force in octagonal ponds was examined on the hydrodynamic flow mixing by laboratory modeling. For this purpose, the inflow was analyzed in three modes with angles of 90, 60, and 30° and the inflowing force at four levels with values of 0.004, 0.009, 0.013, and 0.018 N by the residence time distribution curve and hydraulic efficiency of octagonal ponds. The laboratory modeling results revealed that the inflow at the 90° mode for all four-momentum forces does not form an eddy current and short circuit in the pond's flow, as the result of which the hydraulic efficiency of the pond falls in the weak range. To improve the hydraulic efficiency of the pond, the inflow was installed at 60 and 30° modes; the results demonstrated 2.68 and 3.26 times higher efficiency than the 90° mode. Moreover, for all three inflow installation modes, the hydraulic efficiency had an inverse relationship with the inflow momentum force.