نشریه علوم و مهندسی آب و فاضلاب
سال هشتم شماره 3 (پاییز 1402)

Proper plant nutrition plays a crucial role in enhancing the quality and quantity of agricultural products. Phosphorus, a vital nutritional element, is often in short supply, severely limiting plant growth. The growing population and the consequent demand for more food have led farmers to use phosphorus-based fertilizers to boost production. However, this practice results in an excess of phosphorus entering agricultural drains and contaminating groundwater sources. To address this issue, the use of biological reactors for treating agricultural drainage water and removing elements like phosphorus has been explored. In this study, wheat straw and stubble were chosen as the substrate and content of the bioreactor due to their cost-effectiveness and widespread availability across Iran. Three galvanized iron boxes, each 1 m in length, width, and height, were used to simulate farm conditions. Each box was equipped with an outlet and an inlet for injecting drainage water and three points for collecting wastewater. The collection points were set at depths of 1, 6 and 16 cm from the bottom of the box. The boxes were filled with compacted wheat stubble up to a height of 20 cm from the floor, weighing 39 kg. The study was conducted over 51 days with four replications, using an effluent containing approximately 14 mg of phosphate per liter. All measurements were taken on-site using a 7100 photometer. The results showed that phosphate concentration decreased over time, with a minimum reduction of 48% and a maximum reduction of 97%, indicating the bioreactor’s satisfactory performance. Statistical tests such as the t-test and variance test revealed no difference in the reduction of element concentration (bioreactor performance) after 51 days of wheat straw and stubble life. The initial concentration was neutralized in this research due to the potential impact of temperature and initial concentration on the results. A covariance test was conducted to investigate the effect of temperature on the lifespan of straw and stubble, which showed no significant impact of temperature.

Given that, observational data have different uncertainties, the calibration of water distribution networks based on a definite value can affect the results of the calibrated model. In this research, the calibration of water distribution networks by considering the uncertainty of nodal pressure has been investigated. For this purpose, first, by generating a series of nodal pressure data using the Monte Carlo method, the Hazen-Williams coefficients of the network have been obtained. Then, by producing a series of Hazen-Williams coefficients, the nodal pressure values have been calculated and the results of the two pressures have been compared. The calibration model was performed using the particle swarm optimization algorithm by linking the EPANET simulator in MATLAB. The proposed method has been implemented on the two-loop sample network and real water distribution network of Sufian city. The results show that the application of node pressure uncertainty in network nodes leads to multiple sets of solutions for Hazen-Williams coefficients of pipes with different variation ranges and standard deviations, which according to the average absolute error of 4 and 3.8 percent between the average nodal pressure in the sample and the real network in the non-deterministic mode with the deterministic mode, the proposed method, can be a more accurate method for calibrating networks. However, it should be noted that there are challenges in the modeling and execution time of calibration models.

For the effective qualitative management of drinking water, it is necessary to estimate the level of water pollution. In this research, to calculate the quality index of drinking water from the chemical parameters of Total Hardness, Alkalinity, Electrical Conductivity, Total Dissolved Solids, Calcium, Sodium, Magnesium, Potassium, Chlorine, Carbonate, Bicarbonate, and Sulfate in the hydrometric station of Bagh Kelayeh, Qazvin province used in the statistical period of 23 years (1998-2020). According to the calculated numerical values ​​and existing standards, water quality classified into two classes, good and excellent. To predict the quality class of drinking water based on chemical parameters, different combinations of parameters were considered in the form of several scenarios. In this regard, correlation and relief algorithms were used to select different scenarios. Hoeffding tree was used as a basic model for classifying water quality based on different combinations of parameters. Also, the performance of the combined Dagging approach in improving the results was evaluated. The results showed that the combined Dagging improves the water quality classification results. Scenario 6 Dagging with Hoeffding tree base algorithm, including HCO3, Ca, SO3, TDS, EC and TH parameters, with Kappa = 1, was introduced as the best method which is able to classify test samples correctly.

Iran is facing limited water resources and all production and service processes require the use of water, so it is very important to evaluate the state of water consumption of activities and provide methods for its optimization. So, the aim of the present study is to evaluate the water consumption in the production of each kilowatt hour of electricity and to examine the virtual water situation in the process of exporting and importing electricity in Iran. For this purpose, two methods of structural path analysis and technical-basic approach have been used. The results showed that the country's power plants directly consume 1.5 liters of water per kilowatt hour of electricity production. Also, according to the results of the structural path analysis method, in the electricity production chain before reaching the power plant, 2.5 liters of water is indirectly consumed per kilowatt hour of electricity, and therefore the entire chain consumes 4 liters of water per kilowatt hour. Of the total water consumed in the electricity production chain, which is more than one billion cubic meters, 38% of it was consumed directly in power plants and the other 62% in the production chain.

The pulp and paper industries are one of the largest water-consuming industries in the world. The high organic load of wastewater makes conventional treatment methods like biological and coagulation, ineffective for making the discharge effluent meet environmental standards. Advanced oxidation processes have been considered a promising solution due to their high oxidation power and low operating cost compared to other methods. These processes based on the type of radical production have different types, which are divided into two main categories of hydroxyl radicals and sulfate radicals, which are selected depending on the conditions and their purpose. In this research, by using the Response Surface Method (RSM) experiment design, sulfate radical efficiency, the initial oxidizing concentration and pH were optimized. To investigate the effect of factors, Chemical Oxygen Demand (COD) removal was measured at the end of each experiment as an index for organic pollutant removal. In the maximum state whit this method, 75% of the initial COD can be removed. In the economic optimal mode, with the initial dimensionless peroxy-disulfate dose = 0.407 and initial pH = 8.37, COD removal% = 53.53% is demonstrated.

The use of porous asphalt has been the subject of many inventions and innovations during the last decade. The most obvious characteristics of this asphalt is its drainage ability, which is due to the presence of a high percentage of empty space and pores and connections between these pores. Therefore, it is very important to pay attention to environmental issues such as the reduction of pollutants in porous environments such as asphalt, and therefore the purpose of the research is to investigate the effect of different concentrations of nanomaterials such as nano copper oxide (CuO) and nano zinc oxide (ZnO) on resistance and absorption. The pollutant was in porous asphalt. In this study, durable porous asphalt pavement with the ability to absorb pollutants from water was introduced, and it was built for dynamic creep testing in the asphalt laboratory, and the state of pollutants was investigated in the chemical laboratory. The results of the dynamic creep test showed that the addition of CuO nano oxide to the porous asphalt mixtures significantly increased the bearing capacity and Mental Number (FN), which was useful for rutting resistance. The FN values ​​of porous asphalt mixtures increased by an average of 15% in all loads, and in all loads, asphalt samples modified with 6% copper nano oxide had higher FN values, but insignificant changes were observed in asphalt samples containing ZnO nano oxide. Also, the comparison of the qualitative results regarding the effectiveness of zinc oxide and copper nanomaterials in reducing pollution showed that zinc oxide (ZnO) had the role of reducing pollution in all qualitative parameters, and the biggest reduction was in phosphate, TSS and sulfate. Finally, in the mechanical test section, the asphalt sample containing copper nanooxide with a concentration of 6%, and in the environmental section, the asphalt sample containing zinc nanooxide with a concentration of 8% had the best performance.