JOURNAL OF ENVIRONMENTAL HEALTH ENGINERING
Year:2018 | Volume:6 | Issue:1 |Papers Count:8

Background & Objectives: Waste processing is one of the most important elements responsible for Municipal Solid Waste (MSW). The present study aimed to investigate the characteristics of Tabriz urban solid waste and, finally, assess the environmental impacts of proposed scenarios for the management of MSW in Tabriz in 2017. Methods: In this descriptive study, the required data were collected from field observations, collecting library data, physical analysis with 4 sampling steps in 4 seasons in accordance with ASTM standard method. 4 scenarios (energy generation and composting, energy generation, composting, current status) were proposed and environmental impact assessment of proposed scenarios with Iranian leopold matrix. Results: An average of 1438 tons per day of MSW is collected from the city of Tabriz and the average per capita waste production for this city is 0. 804 kg per person per day. . The average thermal energy generated from the total waste of Tabriz city is 7965 Kj/Kg. The results of the evaluation using the Leopold matrix showed that Scenario 1 (energy generation and composting) with a score of 171 was considered as the best scenario and scenario 4 (current status) with 212 points was the worst management scenario. Conclusion: In the present situation, planning and adopting appropriate measures to reduce negative environmental impacts, composing and energy generation can be appropriate for the management of MSW in Tabriz.

Background and Purpose: The alphamethrin and cypermethrin insecticides are a common source of Pyrotyroid poisons, which means that it is useful for insects and targeted insects. The use of ultrasonic process for decontamination of contaminants in water and sewage is one of the advanced oxidation processes. The present study aims to determine the efficiency of elimination of alphamethrin and cypermethrin toxins by ultrasonic technology and electrodialysis with each other, simultaneous use of technologies, comparison and best practice for remove these toxins in a sewage sludge cake. Materials and methods: In this study, an ultrasonic bath of 25 kHz with temperature and time variables along with electrodialysis process was used. Specifications of the ultrasonic device: length 151 and width 137 mm and depth 143 mm. The device is a device of the Russian Federation and model of the device Y3B-3/200-TH-Pɜ π PTEK. It has the ability to adjust the temperature and time. The test time is 20 minutes and the temperature is 25 degrees Celsius and at voltages of 10 and 28 (30) volts and in currents of 0. 02 and 0. 1 amps. Results: The removal efficiency for the alphamethrin poison in the conditions of 10 volts and the current of 0. 20 amperes and in the presence of ultrasonics is about 58% and for the cypermethrin acid in the same conditions about 42%. And in the case of a voltage of 28. 1 and a current of 0. 1 amperes, they have an efficiency of 47% and 40% respectively. Conclusion: The ultrasonic and electrodialysis processes have the advantage of eliminating the effective removal of toxins that are used to remove insecticides in urban sewage networks. And has about two to three times more power removal than electrodialysis alone.

Background & Objectives: Nickel toxicity and its bioaccumulation potential in organisms at high concentrations, the use of cost-effective and environmental friendly remediation methods is necessary for the removal of nickel from polluted water and wastewaters. Bacterial biofilm be able to remove heavy metals from aqueous solutions and accumulate them in their cell structure. Therefore, the purpose of this study was to evaluate the nickel removal efficiency by biofilms of Pseudomonas aeruginosa supported on clinoptilolite. Methods: In this study, a strain of Pseudomonas aeruginosa as a biofilm coating supported on clinoptilolite. To ensure the establishment of biofilms, scanning electron microscopy was used. The effect of concentration, pH, support medium dosage, temperature and contact time were evaluated in 5 levels, and finally, the results were assessed by adsorption isotherm models. Results: The findings indicated that the maximum removal efficiency by biofilms of Pseudomonas aeruginosa supported on clinoptilolite (99/47%) was achieved in optimal condition containing 900 mg. L-1of nickel concentration, pH of 9, supporting medium dosage (clinoptilolite) 2. 36 g. L-1, temperature of 25 ° C and the contact time of 45 days. The fitness of data in Freundlich adsorption isotherm model revealed that the heterogeneity of adsorbent surface. Conclusion: This study indicates that the use of biofilm coating on the surface of clinoptilolite, can be a good candidate to remove the nickel from the aqueous media.

Background and objective: Wastewaters including dyes produced by various industries have serious destructive effects on the environment. Therefore, proposing analytical and numerical mathematics methods simulating dye removal process from industrial wastewaters are great of importance. Methods: In this research, the Fe3O4-activated carbon magnetic nanocomposite was synthesized and its crystalline structure, surface, and magnetic properties were characterized by XRD, SEM, and VSM techniques. Efficiency of the composite adsorbent for decolorization of Reactive Red dye in different conditions was investigated. Then, an artificial neural network was constructed by using Matlab program to predict the removal efficiency of dye onto magnetic activated carbon and the number of neurons in a hidden layer was optimized. pH, contact time, initial dye concentration, and temperature as input parameters and dye removal percentage as an output parameter were considered. Performance of network after its training was evaluated based on the correlation factor. The experimental data were analyzed by pseudo-first-order, pseudo-second-order, and intra-particle diffusion kinetics models. The Langmuir and Freundlich models were used to describe the sorption equilibrium isotherms. Results: . The high correlation factor for testing data showed that artificial neural network model can estimate the experimental data. The intra-particle diffusion kinetics and Freundlich isotherm models best describe the experimental data for the uptake of dye. A relatively low activation energy (34. 6 kJ mol-1) suggests that the adsorption involve physio sorption. Maximum adsorption capacity decreased with increasing temperature. Conclusion: Use of network prediction resulted to eliminate experiments and to improve dye removal percentage.

Background: In today's world, the main issue is the safeguarding of the human resources employed in the economic sectors. But still, it's still yearly Lots of manpower employed Due to human economic activities are destroying. The purpose of this research is to identify hazard points and potentials and risk assessment and provide management solutions to reduce or eliminate these risks in the acid recovery unit of the Abadan Oil Refining Company as one of the most active and important sectors in the oil industry. Methods: To this end, the William fine method was used in 2016. Results: Based on the results of this method, 100 hazard and health risks were identified in the acid recovery unit, which included 25 abnormal risks, 2 emergencies and 73 natural risks. The highest RPN in the William fine method with a score of 300 is for the inhalation of acid neutralization gases, and the lowest with a score of 2. 5 is the risk of falling from the height. Similarly, of the identified risks, 67% of the risks are at a low level. Conclusion: Regarding all mentioned points, the acid recovery unit of ABADAN Oil Refining Company has been identified as medium-average unit. Given the risk management practices, especially the training of personnel in different sectors, the formation of an accident investigation team and the scientific analysis of accidents and pseudo-events will play an important role in reducing the overall system risk.

Background & objective: Identification of ground waters contaminated by arsenic using surface soil parameters and modeling this relationship in two models including artificial neural network and multiple linear regression can be useful in managing the water resources of the region. Material & methods: The purpose of the present study was to estimate the potential of arsenic pollution in the Sanandaj ground waters using multiple linear regression (MLR) and artificial neural network (ANN) models. In this regards, 35 number of wells were selected among the permissible wells with considering watershed area, appropriate distribution, and different geological structure. The water samples stored in polyethylene bottles and kept at 4° C until transferred to the laboratory. For consideration of the relationship between the soils characteristics around the wells and ground water, the soil samples were collected from 0-20 cm of topsoil with composite sampling technique. The soil samples were air-dried and prepared for analysis. For long term storage of water samples nitric acid were added and the concentration of arsenic in water samples were measured by graphite furnace atomic absorption analyzer. Physical and chemical characteristics of the soil samples including: arsenic, arsenate, arsenite, phosphate, nitrate, total iron, amorphous iron, total manganese, amorphous manganese, clay, sand, silt, organic matter, pH and CEC were measured. Then all water and soil data were normalized and finally, accuracy of the MLP and ANN models was assessed to investigate the relationship between arsenic of water and soil parameters. Results: Results showed that the arsenic concentration of ground waters were lower than the standard level in the study area. This can be due to high concentration of arsenate in the study area soils compared arsenite and increasing the cationic exchange capacity of soil under the influence of clay particles, organic matter and free iron oxides. Conclusion: Compression of models accuracy result showed that ANN model with R=0. 835, RMSE=0. 156 and MAE =0. 118 in the training phase and R =0. 816, RMSE=0. 177 and MAE=0. 158 in the testing phase has higher accuracy and lower errors in the estimation of ground waters arsenic contamination than MLP model.

Background: Development of communities, population growth, and enhancement of the health indicators has led to a significant increase in dairy and meat consumption, and consequential growth in the livestock industry. As the result, the environmental problems which cause by such industrial wastewater has increased. Livestock wastewater considered as a very non-biodegradable and polluted wastewater. In this study, the performance of livestock wastewater pre-treatment, by using coagulation and flocculation method, in order to reduce the pollutants concentration and improve wastewater properties were investigated. Methods: In the experimental methods, the Jar test unit was used as a batch reactor; FeCl3, PAC, and Alum as coagulants; and two polyelectrolytes: Zetafloc and Megafloc as cationic and anionic flocculants. The effects of coagulant dosage and type, flocculant type, and pH on the removal of COD and turbidity from wastewater were investigated in three stages. The wastewater with initial COD and turbidity of 12250 mg/L and 7125 NTU, respectively, was collected from a livestock unit. Results: The optimum conditions in the coagulation and flocculation process to achieve the maximum removal efficiency for COD (29. 6%) and turbidity (52. 8%) were obtained in an experiment with FeCl3 at a concentration of 400 mg/L, pH=8, and using an anionic flocculant. Conclusion: The results of the present study showed that the coagulation and flocculation process can be an effective method for livestock wastewater pre-treatment.

Background: Laccase enzyme is capable of oxidizing many resistant and non-biodegradable environmental pollutants, so it has been studied frequently in recent years and is widely used in biodegradation of contaminants. Despite its abundant applicability, due to its short life span, nonrecovery, thermal instability and instability in organic environments, its widespread use is very limited. The present study aimed to increase the stability of laccase by immobilizing it on silica coated iron oxide nanoparticles. Materials and Methods: Fe3O4 nanoparticles were synthesized based on the co-precipitation method and after coating with silica, their surface was modified by amine groups. The enzyme was then immobilized by covalent binding using glutaraldehyde. Specifications of synthesized nanoparticles and immobilized enzyme were investigated using X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), and Energy-dispersive X-ray spectroscopy (EDX). Results: Results of successful laccase immobilization on nanoparticles showed that laccase immobilization significantly increased storage and thermal stability, maintaining activity in a wider range of temperature and pH than free laccase. Conclusion: The immobilization of laccase on silica-coated iron oxide nanoparticles can reduce the barriers and challenges of various enzymes by increasing its efficiency and stability.