Issue 4

Water is the most important substance. Drinking water in the industry comes from raw water and is treated through a heating process. The results of laboratory tests on raw water used for drinking water are 41 MPN/100ml, so it is necessary to process raw water into drinking water using Reverse Osmosis (RO) membrane technology. The purpose of this study is to determine the difference in the decrease in the total amount of Coliform in drinking water based on variations in water pressure on the Reverse Osmosis membrane in the canteen of X Industry. This type of research is an experiment with the design used is pre-test post-test without control, the sampling technique used is grab sampling, and the total sample is 36 samples with a volume of 3600 ml. The decrease in the total number of Coliforms was analyzed using univariate and bivariate tests. The results of total Coliform in drinking water after treatment with Reverse Osmosis membranes are the average results for a pressure of 1 bar is 0 MPN/100 ml, a pressure of 1.5 bar is 2.81 MPN/100 ml, and a pressure of 2 bar is 5.3 MPN/100 ml. This study concludes that there is a difference between the pressure of 1 bar, 1.5 bar, and 2 bar on the decrease in the total Coliform content in the canteen of X Industry with a p-value of 0.001, and the most effective pressure to reduce total coliform in drinking water in the canteen of X Industry is a pressure of 1 bar with a 100% percentage. Suggestions for further research to carry out the saturated condition of the Reverse Osmosis membrane.

The Conversion of SO2 by Hydrogen Oxidation Branching Chain Reaction A.A. Arutyunyan Institute of Chemical Physics after A.B. Nalbandyan NAS of The Republic of Armenia, 5/2 Paruyr Sevak St., Yerevan 0014, Republic of Armenia E-mail: harhasmik@mail.ru The process of SО2 conversion in the hydrogen combustion mode at the following conditions T=500 oC and P<200 Torr (H2:O2:SO2:N2=10:1:1:0.5) has been studied. It is shown that at τк<4.5s the process is characterized by pulsating flames along with the consumption of hydrogen, oxygen and SО2. When leaving the reactor, free sulfur is precipitated on the cold part. The structural features of precipitated sulfur were studied with the help of electron microscopy and X- ray diffraction phase analysis. Key words: sulfur, sulfur dioxide, pulsating flames, free radicals, combustion.

Recycling of wastewater is an important issue as it is used for many important applications such as industries, agriculture, household applications and due to water scarcity across the different countries. Wastewater treatment is an important activity as it protects human being and the ecosystem from harmful and toxic elements present in wastewater. Performance evaluation of wastewater treatment technologies being complex Multi-criteria Decision Making (MCDM) problem that has contradictory evaluation factors. This paper is focused on the analysis of factors that affect evaluation of wastewater treatment technologies and their impact by developing a model which combine Analytical Hierarchy Process (AHP) and Grey Relational Analysis (GRA) for the assessment and ranking wastewater treatment technologies (WWTTs) respectively. The best WWTT is chosen based on data acquired through a case study. AHP is applied for computing criteria weights based on comparative significance while Grey Relational Analysis method is applied for ranking and selecting the wastewater treatment technologies. Sensitivity analysis is performed to show the impact of grey relational scores of alternatives in line with variations of distinguished coefficients.

This study emphasis on draining and slowing runoff volumes in arid and semi-arid lands regions using HEC-HMS model linked with various Best Management Practices (BMPs) alternatives. The proposed methods may help significantly in reducing flash flood precipitation and improving instream water quality. It provides facilities to increase flood retention times and infiltration rates. Recently, flash flooding in arid lands is occurring on almost every two-year basis and is threatening human lives and damaging properties. Modern urbanization of the cities has great impacts on flooding schemes, it increases peak streamflows and it reduces the time to peak. Eventually, major cities experienced newly developed areas to accommodate the increase of population, and thus surface runoff volumes would increase substantially. In addition to outflows from surrounding high desert lands which form a significant portion of flash flood volumes. This study proposed a modern and progressive flash flood management scheme that would emphasize on enhancing soil infiltration and runoff attenuation by construction facilities that would absorb runoff water. We formulated five proposals for flood mitigation derived from BMP techniques for the purposes of stormwater management. Rainfall-runoff natural disaster modeling was simulated using HEC-HMS (Hydrological Modeling Systems). The Geographic Information System (GIS) coupled with HEC-HMS was employed in this study to delineate the watershed line and to simulate streams discharges. Results for investigating the construction of dry dams' option showed a significant reduction in both peak volumes and time to peak and consequently, the mitigated flood spreads longer. Furthermore, downstream calculations prove the contributions of other events on increasing flood hazards downstream. Outlet bottom size and storage capacity are the major parameters that control flood hazards. Outcomes of this study would help water resources managers and decision-makers who need immediate action plans and operational responses when floods occur. Discharge outflow rates were assessed using HEC-HMS and CN methods, and modeling the studied area using Geographic Information Systems (GIS). This study reveals runoff volumes ranges of 0.04 to 0.77 cm/hr. Also, results shows that the HEC-HMS model is capable of simulating runoff based event.

The present paper carries for novel modeling that are often used for evaluate the kinetic performance of groundwater reverse osmosis (GWRO) desalination system by empirical correlation with dimensionless parameters. About three hundred dimensionless empirical correlationshave been proposed and validated for the calculation of three cumulative dimensionless volumes: alimentation, permeate and rejection as a function of the dimensionless filtration time and vice versa. This correlation has obtained by inspiration of the models already proposed in the literature from four unitary operation processes: filtration, adsorption, drying and extraction. The experimental data consists of 2561 points taken during the lifetime of 66 organics RO membranes. The interpreting of regression and residual results is validated by four statistical criteria: reduced chi-Sqr, residual sum of residual, r-square (COD) and adj. R-square (R²) and with two criteria in ANOVA analysis: sum of squares, mean square. Results show that 95 dimensionless empirical correlations (DEC) among 192 are highly capable to describe the separation kinetics on reverse osmosis desalination system curve with a least R2 was around 0.970 in comparison to the best correlation (DEC 1) with R2 of 0,998, 0,995 and 0,993 for alimentation, permeate and rejection, respectively, with negligible errors and perfect alignment of correlation with RO kinetic separation according to statistical criteria.

Estimation of annual peak flood flow has considerable financial influence, as this can pave numerous ways for water resources planning, design of hydraulic structures, and sustainable management of these valuable resources at an optimum benefit. Six standard plotting position methods coupled with Linear Log-regression Model (LLM) are employed for the Return Period (RP) of 15, 20, 25, 30, 60, and 1000 years to forecast peak flood flow magnitudes and for this daily annual peak flood flow data for the periods of 24 years were used to illustrate the proposed methods. Another method, Gumbel's Analytical Approach (GAA), is also used to forecast the peak flood flow magnitude for the same RP, and it was taken as the benchmark to compare all the six methods of plotting position. The degree of accuracy of the plotting position is based on the coefficient of determination R2. The R2 values for Adamowski, Hazen, Beard, Chegodajev, Tukey, and Benard, are 0.9073, 0.9284, 0.9119, 0.9111, 0.9135, and 0.9111, respectively. Out of the six-plotting position methods, Hazen method predicted a very closer value in comparison with GAA. It is advantageous to have the additional method to forecast peak flood flow for longer RP. The achieved result assuredly facilitates effective planning, regulation, and maintenance of huge reservoirs across the frequent occurrence of floods in river basin areas, considering safety and particularly downstream inhabited areas to save loss of human life, animals, damages to properties, and an impair of cultivated crops.

Growing environmental awareness coupled with stricter regulations has pushed various industries to look for appropriate technologies to treat wastewater. Natural coagulants have recently been used as part of water and wastewater technologies due to their performance, cost-effectiveness when compared to chemical coagulants, they produce less sludge and are safer for humans. A huge effort has also been taken to find new plant species and ingredients that may be used as natural coagulants, and hence improve the efficacy of existing plant-based natural coagulants. The purpose of this research is to assess the progress of various natural coagulants used for water and wastewater treatment. Besides, several plant-based natural coagulants are also summarized and reviewed. The results reveal that natural coagulants are more successful than chemical coagulants at removing heavy metals and suspended particles from wastewater, with better removal efficiency exceeding chemical coagulants and being more environmentally friendly.

The majority of nitrate (NO3‾) pollutants come from a different type of industries. Even if present in low amounts, these nitrates are harmful to humans and aquatic systems. This research investigated the utilisation of Tamarind Fruit shell (TFS) as biosorbent in the removal of Nitrate from aqueous solution. TFS shell was modified by soaking it with distilled water. Many remediation strategies are available, but they are both costly and ineffectual. However, it has been discovered via significant research that waste materials such as tamarind bark, eggshells, and agricultural wastes are well suited to removing nitrate from waste water using the biosorption process (Panida, et.al., 2010). Biosorption is a nitrate removal process that is both environment friendly and cost-effective. The equilibrium distribution of NO3‾ onto the surface of the TFS can be best explained by Freundlich isotherm. Based upon the reaction of the thermodynamic study the TFS- NO3‾ interaction is an endothermic (Amardeep, et.al., 2013). A substantial chance in the NO3‾ - TFS interaction is expected because of the significant gain in the translational entropy by the displaced synchronised water molecules. Than the Chemiluminescence Analysing techniques Spectroscopic studies shows the biosorption capacity of TFS shows a little variation between 1.25 mg/g for 1 mm size and 2.14 mg/g for 0.13 mm size.

Rapid urbanization has given us many benefits in terms of giving us a better standard of life, but it sure has brought a lot of problems with it. Solid waste management is a major issue that has been in the forefront of the issues caused by urbanization. It has brought a lot of domains together namely social, environmental, and climate together. Technology has been used occasionally but has not made significant advances in this domain. This domain is relatively new in terms of deep learning. This is due to some of the issues like lack of proper dataset, effective architecture to classify multiple objects and so on. The goal is to build multi-class dataset in this domain and perform detection and classification using both single stage and two stage object detection networks. The single stage network that is to be implemented is YOLOv5 and the two stage network that is to be implemented is Faster Region based CNN using Resnet50. The single object dataset used is TrashNet dataset and the multi-object dataset used is Waste-mart self-built dataset. The result obtained shows mAP around 0.84 for the two-stage network and mAP around 0.98 with IoU threshold placed at 0.5 for both the systems.