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ارزیابی اثرات زیست محیطی فرآیند تغییر و تبدیل پسماند جامد شهری تبریز Environmental Impacts Assessment of the Transformation of Municipal Solid Waste Process of Tabriz City 1 1 مقدمه: فرآیند تغییر و تبدیل از مهمترین عناصر موظف مدیریت پسماندهای شهری است. مطالعه حاضر با هدف ارزیابی اثرات زیست محیطی سناریوهای پیشنهادی تغییر و تبدیل پسماند شهری تبریز در سال 1396 انجام یافته است. روش کار: در این مطالعه توصیفی، جهت جمع آوری اطلاعات از بازدیدهای میدانی، جمع آوری اطلاعات کتابخانه ای، تعریف 4 سناریو (تولید انرژی و ،ASTM آنالیز فیزیکی با 4 مرحله نمونه برداری در 4 فصل مطابق با روش استاندارد کود، تولید انرژی، تولید کود، ادامه وضع موجود) و ارزیابی اثرات زیست محیطی سناریوهای پیشنهادی با ماتریس لئوپولد ایرانی انجام شد. یافته ها: روزانه به طور میانگین 1438 تن زباله از سطح شهر تبریز جمع آوری می گردد و میانگین سرانه تولید پسماند 0 کیلوگرم به ازای هر نفر در روز تعیین گردید . میانگین انرژی حرارتی تولیدی از کل پسماند / برای این شهر 804 7965 می باشد. نتایج ارزیابی با استفاده از ماتریس لئوپولد نشان داد که سناریو 1 (تولید Kj/Kg شهری تبریز برابر کود و انرژی) با امتیاز 171 - به عنوان سناریو برتر و سناریو 4 (ادامه وضع موجود) با امتیاز 212 - به عنوان بدترین گزینه انتخاب شد. نتیجه گیری: در وضعیت موجود با برنامه ریزی و با اتخاذ تمهیدات مناسب جهت کاهش اثرات منفی زیست محیطی، فرآیند تولید کود و انرژی، می تواند برای مدیریت پسماند شهری تبریز مناسب باشد. 2 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. 1 15 2018/12/29 1397/10/8 2018/12/29 1397/10/8 سعید لک Saeed Lak دانشجوی کارشناسی ارشد مهندسی بهداشت محیط، دانشکده بهداشت، ، دانشگاه علوم پزشکی اردبیل، اردبیل، ایران ایران saeedlak@gmail.com مرتضی عالیقدری Morteza Alighadri گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی اردبیل، اردبیل، ایران ایران m.alighadri@arums.ac.ir کوروش رحمانی Kourosh Rahmani گروه مهندسی بهداشت محیط، مجمتع آموزش عالی سلامت ممسنی، دانشگاه علوم پزشکی شیراز، شیراز، ایران ایران krahmanii@yahoo.com محمد حسن سربازان Mohammad Hasan Sarbazan سازمان مدیریت پسماند شهرداری تبریز HSE کارشناس ارشد محیط زیست آمایش سرزمین و مدیر پژوهش و ایران Environmental impact assessment Leopold Matrix Municipal solid waste Tabriz ارزیابی اثرات زیست محیطی ماتریس لئوپولد پسماند تبریز 1. Akhavan F, Abdoli MA, Vahidi H, Khalili I, editors. The need for lifecycle assessment studies in integrated waste management. Second Conference on Environmental Planning and Management; 2012. [in persian].##2. Rand T, Haukohl J, Marxen U. Municipal Solid Waste Incineration: a decision makers’ guide. Washington. D.C.: The World Bank; 2000.##3. White P, Dranke M, Hindle P. Integrated Solid Waste Management: A Lifecycle Inventory: Springer US; 2012.##4. Norpour A, Afrasibi H, Davoudi M. Investigating the Waste Management Process in the World and Iran:Center for Urban Studies and Planning in Tehran.2013;207. [in persian].##5. Mohee R, Simelane T. Future Directions of Municipal Solid Waste Management in Africa: Africa Institute of South Africa; 2015.##6. Panahandeh M, Abedinzadeh N, Ravanbakhsh M.Environmental impact assessment of compost plant in Yazd. J Environ Sci Technol. 2013;12(3): 87-99. [in persian].##7. El-Naqa A. Environmental impact assessment using rapid impact assessment matrix (RIAM) for Russeifa landfill,Jordan. Environ Geol. 2005;47(5): 632-9.##8. Kuitunen M, Jalava K, Hirvonen K. Testing the usability of the Rapid Impact Assessment Matrix (RIAM) method for comparison of EIA and SEA results. United States 2008.##9. Makhdoom M. Environmental Impact Assessment: Faculty of Environment, University of Tehran; 2001.##10. Monavari M. Environmental Impact Assessment. 2st ed.Tehran: Mitra Publishing Co. 2015: 65-110.##11. Alinezhad N, Zadeh SRA. Reviewing the Conventional Environmental Impact Assessment. The 8th National Conference and Environmental Engineering Exhibition; Tehran2016.##12. Valizadeh S, Shekari Z. Evaluation of Iranian Leopold Matrix application in the Environmenta Impact Assessment (EIA) of solid waste management options in Birjand city. Iran J Healt Environ. 2015;8(2): 249-62. [in persian].##13. Sajjadi SA, Aliakbari Z, Matlabi M, Biglari H, Rasouli S.Environmental impact assessment of Gonabad municipal waste landfill site using Leopold Matrix. Electron Physician. 2017;9(2): 3714-9.##14. ASTM International. Standard Test Metod for Determination of the Composition of Unprocessed Municipal Solid Waste. ASTM Designation: D5231-92 (Reapproved 2003) 2003.##15. Tchobanoglous G, Theisen H, Vigil SA. Integrated solid waste management: engineering principles and management issues: McGraw-Hill; 1993.##16. Alipanah A, Alighadri M. Evaluation of the Recovery Potential of Ardabil Municipal Wastes. J Healt. 2015;6(3): 337-44.##17. Schwarz VSC, Brunner CR. Energy and Resource Recovery from Waste: Noyes Data Corporation, Park Ridge; 1983.##18. Statistical Yearbook of Waste Management Organization of Tabriz Municipality. Design and planning deputy2016.[in persian].##19. Sharholy M, Ahmad K, Mahmood G, Trivedi RC.Municipal solid waste management in Indian cities – A review. Wast Manag. 2008;28(2): 459-67.##20. Zhang DQ, Tan SK, Gersberg RM. Municipal solid waste management in China: Status, problems and challenges. J Environ Manag. 2010;91(8): 1623-33.##21. Zhou H, Meng A, Long Y, Li Q, Zhang Y. An overview of characteristics of municipal solid waste fuel in China:Physical, chemical composition and heating value.Renewable Sustainable Energy Rev. 2014;36: 107-22.##22. Sipra AT, Gao N, Sarwar H. Municipal solid waste (MSW) pyrolysis for bio-fuel production: A review of effects of MSW components and catalysts. Fuel Process Technol. 2018;175: 131-47.##23. Chang N-B, Davila E. Municipal solid waste characterizations and management strategies for the Lower Rio Grande Valley, Texas. Wast Manag.2008;28(5): 776-94.##24. Tanner R. Die Entwicklung der Von RollMüllverbrennungsanlagen. Schweizerische Bauzeitung 1965;16.##25. Jabari V, Safari A, Ranaei A. Measuring the Heating value of municipal solid waste mixed with the output waste from processing facilities and comparing the results with Tanner triangle for assessment of combustibility of Waste (A case study on the garbage of Qazvin). J Res Environ Healt. 2015;1(4): 306-13.##26. Unnikrishnan S, Singh A. Energy recovery in solid waste management through CDM in India and other countries.Resour. Conserv Recycl. 2010;54(10): 630-40.##27. Zhao Y, Christensen TH, Lu W, Wu H, Wang H.Environmental impact assessment of solid waste management in Beijing City, China. Wast Manag.2011;31(4): 793-9.##28. Gautam S, Bundela PS, Pandey AK, Sarsaiya S.Composting of Municipal Solid Waste of Jabalpur City. 2013.##29. Mirzaei N, Nori J, Mahvi A, Masoud Y, Afshin M.Assessment of Environmental Impacts produced by Compost Plant in Sanandaj. Sci. J. Kurdistan Univ Med Sci.2010;14(4): 79-88. [in persian].##30. Gholamalifard M, Mirzaei M, Hatamimanesh M, Riyahi Bakhtiari A, Sadeghi M. Application of rapid environmental impacts assessment matrix and Iranian matrix in environmental impact assessment of solid waste landfill of Shahrekord. J Shahrekord Univ Med Sci. 2014;16(1): 31-46. [in persian].## ##

طراحی پایلوت تخریبی سموم آلفامترین و سایپرمترین در کیک لجن فاضلاب با استفاده از فناوری اولتراسونیک در مقایسه با الکترودیالیز Designing a Pilot for Alphamethrin and Cypermethrin Degradation in Sewage Cake Using Ultrasonic Technology Compared to Electrodialysis 1 1 زمینه و هدف: آلفامترین و سایپرمترین حشره کش جزء سموم پایروتیروئید گسترده ای هستند، بدان معنی است که حشرات مفید و نیز حشرات مورد هدف را می کشد. استفاده از فرایند اولتراسونیک برای تجزیه آلاینده ها در آب و فاضلاب یکی از فرایندهای اکسیداسیون پیشرفته است .پژوهش حاضر در جهت تعیین میزان راندمان حذف سموم آلفامترین و سایپرمترین توسط فناوری اولتراسونیک و الکترودیالیز با یکدیگر ، استفاده همزمان هر دو فناوری ، باهم مقایسه و بهترین روش برای حذف این سموم در کیک لجن فاضلاب است. مواد و روش ها: در این بررسی از حمام اولتراسونیک باقدرت 25 کیلوهرتز با متغیرهای دما و زمان به همراه فرآیند الکترودیالیز استفاده شده است. مشخصات دستگاه اولتراسونیک: طول 151 و عرض 137 میلی متر و عمق 143 میلی متر است. که قابلیت تنظیم دما و زمان را Y3B-3/200-TH-PɜπTEK است. سازنده دستگاه کشور روسیه و مدل دستگاه 30 ) ولتی و در جریان های ) 28/ دارد. زمان آزمایش را 20 دقیقه و دما را 25 درجه سانتی گراد و در ولتاژهای 10 و 1 0 آمپر انجام گرفته است. / 0/02 و 1 یافته ها: نتایج حاصل از این مطالعه نشان می دهد که راندمان حذف برای سم آلفامترین در شرایط ولتاژ 10 ولتی و 0 آمپر و در حضور اولتراسونیک حدود 58 % و برای سم سایپرمترین در همین شرایط حدود 42 % است ؛ و / جریان 02 0 آمپر به ترتیب دارای راندمان حذف 47 % و 40 % را دارا است. / 28 و جریان 1 / در شرایط ولتاژ 1 نتیجه گیری: فرآیند اولتراسونیک و الکترودیالیز نسبت به الکترودیالیز به تنهایی دارای راندمان حذف مطلوبی در حذف سموم پرکاربرد برای رفع حشرات موذی موجود در شبکه فاضلاب شهری داشته است؛ و دارای تقریباً 2 تا سه برابر دارای راندمان حذف بیشتری نسبت به الکترودیالیز به تنهایی دارد. 2 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-PɜπPTEK. 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. 16 26 2018/12/292018/12/29 1397/10/8 2018/12/292018/12/29 1397/10/8 حسین کیاشمشکی Hossein Kiashemshaki کارشناس ارشد، گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی مشهد، مشهد، ایران ایران sosha_shemshaki@yahoo.com Ultrasonic Electrodialysis Toxins اولتراسونیک الکترودیالیز سایپرمترین آلفامترین 1. J. V. The use of power ultrasound in biofuel production,bioremediation, and other applications. Power Ultrasonics. 2015:1095-122.##2. Mohseni. Benzaldehyde degradation using ultrasonic. JAC. 2012;3(12):57-62.##3. A M. Application of Ultrasonic Technology for Water and Wastewater Treatment. . Iranian J Publ Health.2009;38(2):1-7.##4. Kumar R YN RLaGM. Effect of Two Waves of Ultrasonic on Waste Water Treatment. CHEM ENG PROCESS. 2014;5(3).##5. V.O. Abramova OVA AEG, V.M. Kuznetsova, G.J. Priceb. . Ultrasonic intensification of ozone and electrochemical destruction of 1,3-dinitrobenzene and 2,4-dinitrotoluene. ULTRASON SONOCHEM. 2005;13(4):303-7.##6. Lisa A. Davies AD JRD, Michael E. Deary Use of 24 kHz ultrasound to improve sulfate precipitation from wastewater. ULTRASON SONOCHEM. 2015;23:424-31.##7. Afshari MGRMRMZZA. Destruction of Escherichia coli and Enterococcus faecalis using Low Frequency Ultrasound Technology. ISO: Health Scope | JCR:HEALTH SCOPE. 2014;3(1).##8. Jin Peia HY HW, Dan Shanb, Yichen Jiangc, Lanqianya Maa, Xiaohua Yua. Effect of ultrasonic and ozone pretreatments on pharmaceutical waste activated sludge’s solubilisation, reduction, anaerobic biodegradability and acute biological Bioresour Technol. 2015;192:418-23.##9. Guilherme L. Dotto JMC COC, Eduardo H. Tanabe ,Daniel A. Bertuol. Surface modification of chitin using ultrasound-assisted and supercritical CO2 technologies for cobalt adsorption. J Hazard Mater 2015;295:29-36.##10. Yangsheng Liua SK YL, Hui Zengb. Novel technology for sewage sludge utilization: Preparation of amino acids chelated trace elements (AACTE) fertilizer. J Hazard Mater. 2009;171:1159-67.##11. Jinchuan Deng XF XQ. Extraction of heavy metal from sewage sludge using ultrasound-assisted nitric acid. Chem Eng J. 2009;152:177-82.##12. R F. SONOCHEMICAL DEGDATION OF ORGANOPHOSPHORUS PESTICIDE IN DILUTE AQUEOUS SOLUTION. JEH. 2003;15(10):704-10.##13. VKaSI VS. Starch despersion in water under ultrasonic treatment. ChemChemTechnol; Сh&ChT. 2012;6(2):183-8.##14. Raf Dewila JB aRG. The Use of Ultrasonics in the Treatment of Waste Activated Sludge. Chinese J Chem Eng. 2006;14(1):105-13.##15. Xuejiang Wang JC XY, Xin Wang, Jing Zhang, Jiayu Huang,Jianfu Zhao. . Heavy metal chemical extraction from industrial and municipal mixed sludge by ultrasound-assisted citric acid. J IND ENG CHEM.2015;27:368-72.##16. Shengchun Yang XF LD, Shu Yang, Zirong Lei,Xiaodong Wen. Comparison of ultrasound-assisted cloud point extraction and ultrasound-assisted dispersive liquid liquid microextraction for copper coupled with spectrophotometric determination. Spectrochim Acta A Mol Biomol Spectrosc. 2015;148:72-7.##17. Zheng-Zhe Zhang Y-FC Y-HZ, Xiemuguli Buayi, Ren-Cun Jin. A novel strategy for accelerating the recovery of an anammox reactor inhibited by copper(II): EDTA washing combined with biostimulation via low-intensity ultrasound. Chem Eng J. 2015;279:912-20.##18. Seon-Suk Hwang J-SP aWN. Ultrasonic-Assisted Extraction to Release Heavy Metals from Contaminated Soil. J Ind Eng Chem. 2007;13(4):650-6.##19. Sridhar Pillia PB SY, R.J. LeBlancc, R.D. Tyagia, R.Y.Surampallid. Ultrasonic pretreatment of sludge: A review. ULTRASON SONOCHEM. 2011;18(1):1-18.##20. Seleem E. Gaber MSR MMY. Extraction of certain heavy metals from sewage sludge using different types of acids. Biokemistri. 2011;23(1):41-8.##21. M Khoobdel MS SG, M Abtahi, H Vatandoost, H Zeraatii, S Bazrafkan. Effectiveness of Ultrasound and Ultraviolet Irradiation on Degradation of Carbaryl from Aqueous Solutions. Iranian J Arthropod-Borne Dis. 2010;4(1):47-53.##22. D.Manariotisc SDVTKMHKKI. Aqueous phenanthrene toxicity after high-frequency ultrasound degradation. AQUAT TOXICOL. 2014;147:32-40.##23. Eleni Manousaki EP, Nicolas Kalogerakis, Dionissios Mantzavinos. Degradation of sodium dodecylbenzene sulfonate in water by ultrasonic irradiation. Water Res. 2004;38:3751–9.##24. Reza Shokohi AHM, Ziaeddin Bonyadi. Comparison efficiency of both sonochemical and sonochemical/hydrogen peroxide processes for cyanide removal from aqueous solutions. jmums. 2009;19(73):60-7.## ##

بهینه سازی پاکسازی نیکل از پساب شبیه سازی شده توسط بیوفیلم استقرار یافته باکتری سودوموناس آئروژینوزا بر روی کلینوپتیلولایت Optimization the Removal of Nickel from Simulated Wastewater by A Pseudomonas aeruginosa Biofilm Supported on Clinoptilolite 1 1 سابقه و هدف: سمیت و توانایی تجمع زیستی فلز نیکل در جانداران در غلظت های بالا، پاکسازی آب و فاضلاب آلوده از این عنصر با استفاده از روش های کم هزینه و دوستدار محیط زیست را امری مهم و ضروری ساخته است. بیوفیلم باکتری ها قادر به جذب فلزات سنگین از محیط آبی و تجمع آن در ساختمان سلولی خود است. بنابراین هدف پژوهش حاضر ارزیابی راندمان پاکسازی نیکل توسط بیوفیلم استقرار یافته باکتری سودوموناس آئروژینوز ا بر روی کلینوپتیلولایت بوده است. مواد و روش ها : در این مطالعه مقطعی، سویه ای از باکتری سودوموناس آئروژینوزا در قالب پوشش بیوفیلم بر روی کلینوپتیلولایت استقرار یافت. برای حصول اطمینان از استقرار بیوفیلم از مطالعات میکروسکوپ الکترونی روبشی مقدار بستر، دما و زمان تماس در 5 سطح مورد بررسی قرار گرفت و نهایتا نتایج ،pH ، استفاده شد. اثر عوامل، غلظت توسط مدل های همدمای جذب مورد ارزیابی قرار گرفت. 99 درصد توسط بیوفیلم استقرار یافته باکتری سودوموناس / یافته ها: یافته ها بیانگر حداکثر راندمان پاکسازی 47 2 گرم در /36 ، معادل 9 pH ، آئروژینوزا بر روی کلینوپتیلولایت در شرایط بهینه غلظت اولیه نیکل 900 میلی گرم در لیتر لیتر کلینوپتیلولایت، دمای 25 درجه سانتی گراد و زمان تماس 45 روز بود. برازش داد ه ها در مدل همدمای جذب فروندلیچ حاکی از عدم یکنواختی پوشش سطح جاذب است. نتیجه گیری: مطالعه حاضر نشان دهنده آن است که کاربرد پوشش بیوفیلم در سطح کلینوپتیلولایت، می تواند روش مناسبی برای پاکسازی نیکل از محیط های آبی باشد 2 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. 27 41 2018/12/292018/12/292018/12/30 1397/10/9 2018/12/292018/12/292018/12/30 1397/10/9 رقیه سادات صالح نژاد Roghayeh Sadat Salehnezhad گروه علوم خاک، دانشکده کشاورزی و منابع طبیعی، دانشگاه آزاد اسلامی واحد اصفهان (خوراسگان)، اصفهان، ایران ایران میترا عطاآبادی Mitra Ataabadi گروه علوم خاک و عضو مرکز تحقیقات پسماند و پساب، دانشگاه آزاد اسلامی واحد اصفهان (خوراسگان)، اصفهان، ایران ایران mitra_ataabadi@yahoo.com Nickel Clinoptilolite Biofilm Pseudomonas aeruginosa نیکل کلینوپتیلولایت بیوفیلم سودوموناس آئروژینورا 1. Akhondi A, Khodadadi Darban A, Ganjidoust H. The Effectiveness of Electrocoagulation process for the Removal of Cadmium from Water. J Water Wastewater 2013; 2: 86-93[In Persian].##2. 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Multimetal resistance and tolerance in microbial biofilms. Nat Rev Microbiol 2007; 5(12): 928–938.##8. Malik A. Metal bioremediation through growing cells. Environ Int 2004; 30(2): 261–278.##9. Quintelas C, Rocha Z, Silva B et al. Biosorptive performance of an Escherichia coli biofilm supported on zeolite NaY for the removal of Cr (VI), Cd (II), Fe (III) and Ni(II). Chem Eng J 2009; 152(1): 110-115.##10. Mangwani N, Shukla SK, Rao TS, Das S. Calciummediated modulation of Pseudomonas mendocina NR802 biofilm influences the phenanthrene degradation. Colloild surf B Biointerfaces 2014; 114(1): 301-309.##11. Comte S, Guibaud G, Baudu M. Biosorption properties of extracellular polymeric substances (EPS) towards Cd, Cu, and Pb for different pH values. J Hazard Mater 2008; 151(1): 185-193.##12. Eboigbodin KE, Biggs CA. Characterization of the extracellular polymeric substances produced by Escherichia coli using infrared spectroscopic, proteomic, and aggregation studies. 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Quintelas C, Tavares T. Removal of chromium (VI) and cadmium (II) from aqueous solution by a bacterial biofilm supported on granular activated carbon. Biotechnol Lett 2001; 23(16): 1349-1353.##19. Kang SY, Bremer PJ, Kim KW, McQuillan AJ. Monitoring metal ion binding in single layer Pseudomonas aeruginosa biofilm using ATR-IR spectroscopy. Langmuir 2006; 22(1): 286-291.##20. Yolmeh M, Habibi Najafi MB, Farhoosh R, Hosseini F. Application of response surface methodology to optimize Ultrasound-assisted extraction conditions of dye from annatto seeds. J Food Sci Technol. 2016; 13(50): 41-51.##21. Ataabadi M, Tahmourespour A, Hoodaji M, et al. The role of exopolysaccharides from a chromate reducing Pseudomonas aeruginosa in resistance to hexavalent chromium and antibiotics. J Shahrekord Univ Med Sci 2014; 16(4): 28-38 [In Persian]##22. Amoozegar MA, Ghazanfari N, Didari M. Lead and cadmium bioremoval by Halomonas sp., an exopolysaccharide-producing halophilic bacterium. 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بهینه سازی حذف رنگزای آنیونی روی نانوکامپوزیت مغناطیسی کربن فعال با استفاده از شبکه های عصبی مصنوعی -Fe3O4 Optimization of Removal Efficiency of An Anionic Dye Onto Magnetic Fe3O4-Activated Carbon Nanocomposite Using Artificial Neural Network 1 1 زمینه و هدف: پساب های حاوی رنگزاها که از صنایع مختلف تولید می شوند، اثرات و پیامدهای مخربی بر محیط زیست میگذارند. از این رو، ارائهی مدلهای ریاضی تحلیلی و عددی که قادر به شبیه سازی فرایند حذف رنگ از پسابهای صنعتی باشند، از اهمیت بسیاری برخوردار است. کربن فعال به روش هم رسوبی سنتز و ساختار -Fe3O مواد و روشها: در این پژوهش، ابتدا نانوکامپوزیت مغناطیسی 4 شناسایی شد. کارآیی جاذب VSM و ،SEM ،XRD بلوری و ویژگیهای سطحی و مغناطیسی آن با تکنیک های کامپوزیتی برای حذف رنگزای آنیونی ری اکتیو رد از محلول آبی در شرایط مختلف مورد بررسی قرار گرفت. سپس، یک شبکهی عصبی مصنوعی برای پیش بینی بازدهی حذف رنگزا به وسیله ی (Matlab) با استفاده از نرم افزار متلب زمان تماس، غلظت ،pH کربن فعال مغناطیسی طراحی و تعداد لایههای پنهان آن بهینه شد. بدین منظور، پارامترهای اولیهی رنگزا، و دما به عنوان ورودی، و درصد حذف رنگزا به عنوان خروجی شبکه ی عصبی در نظر گرفته شد. عملکرد شبکه پس از آموزش آن بر مبنای ضریب همبستگی مورد ارزیابی قرار گرفت. دادههای تجربی با مدل های سینتیکی شبه مرتبهی اول، شبه مرتبهی دوم، و نفوذ درون-ذرهای برازش شد. مدل های لانگمویر و فروندلیچ برای توصیف ایزوترمهای تعادلی جذب به کار برده شدند. یافته ها: ضریب بالای همبستگی برای دادههای آزمون ( 989530) نشان داد که مدل شبکه ی عصبی در پیش بینی /  داده های تجربی موفق است. مدل های سینتیکی درون-ذرهای و ایزوترم فروندلیچ با داده های تجربی انطباق بیشتری 34/6 ) نشان داد که جذب سطحی دارای ماهیت فیزیکی است. حداکثر kJ mol– داشتند. انرژی فعالسازی نسبتاً پایین ( 1 ظرفیت جذب با افزایش دما کاهش یافت. نتیجه گیری: استفاده از پیشبینی شبکه ی عصبی منجر به حذف آزمایش های تکراری و بهبود درصد حذف رنگزا می شود 2 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. 42 66 2018/12/292018/12/292018/12/302018/12/30 1397/10/9 2018/12/292018/12/292018/12/302018/12/30 1397/10/9 مریم فرزان Maryam Farzan تصفیه خانه ی آب و فاضلاب، شهرک صنعتی علیدره، فیروزکوه، ایران ایران مهساسادات میرعلینقی Mahsasadat Miralinaghi گروه شیمی، دانشکده علوم پایه، دانشگاه آزاد اسلامی، واحد ورامین- پیشوا، ورامین، ایران ایران msmiralinaghi@gmail.com nanocomposite adsorption artificial neural network Reactive dye نانوکامپوزیت جذب سطحی شبکهی عصبی مصنوعی رنگزای ریاکتیو 1. Gupta, V. K. & Suhas. Application of low-cost adsorbents for dye removal – A review. J. Environ. Manage. 90, 2313– 2342 (2009).##2. Yagub, M. T., Sen, T. K., Afroze, S. & Ang, H. M. Dye and its removal from aqueous solution by adsorption: A review. Adv. Colloid Interface Sci. 209, 172–184 (2014).##3. Adegoke, K. A. & Bello, O. S. Dye sequestration using agricultural wastes as adsorbents. Water Resour. 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ارزیابی ریسک ایمنی و بهداشت واحد احیای اسید شرکت پالایش نفت آبادان به روش ویلیام فاین Risk Assessment Health and Safety of Acid Recovery unit of Abadan Oil Refining Company by using William Fine 1 1 زمینه: در جهان امروز، موضوع اساسی، صیانت از نیروی انسانی شاغل در بخش های اقتصادی است. لیکن با این وجود هنوز سالانه تعداد زیادی از نیروی انسانی شاغل در اثر فعالیت های اقتصادی بشر رو به نابودی میباشند. هدف از انجام این تحقیق نیز شناسایی نقاط و پتانسیل های خطر و ارزیابی ریسک و ارایه راهکارهای مدیریتی جهت کاهش و یا حذف این خطرات در واحد احیاء اسید شرکت پالایش نفت آبادان به عنوان یکی از بخش های فعال و مهم در صنایع نفتی می باشد. مواد و روش: برای رسیدن به این هدف در سال 1395 از روش William fine استفاده گردید.  یافته ها: براساس نتایج این روش بر این اساس تعداد 100 مورد از ریسک های ایمنی و بهداشتی در واحد احیاء اسید در روش RPN شناسایی که 25 ریسک غیرطبیعی، 2 ریسک اضطراری و 73 ریسک طبیعی به دست آمد. بالاترین 2 مربوط به / با نمره 300 مربوط به استنشاق گازهای حاصل از خنثیسازی اسید و کمترین آن با نمره 5 William fine خطر سقوط از ارتفاع می باشد. همچنین از ریسک های شناسایی شده 67 درصد از ریسک ها در سطح پایین قرار گرفته اند. نتیجه گیری: با توجه به تمامی نکات ذکر شده واحد احیای اسید شرکت پالایش نفت آبادان جزء واحدهای با میانگین خطر متوسط شناسایی شده است. با توجه به روشهای مدیریتی کاهش ریسک به ویژه آموزش پرسنل در بخش های مختلف، تشکیل تیم بررسی حادثه و آنالیز علمی حوادث و شبه حوادث، نقش مهمی در کاهش ریسک کلی سیستم خواهد داشت 2 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 67 83 2018/12/292018/12/292018/12/302018/12/302018/12/30 1397/10/9 2018/12/292018/12/292018/12/302018/12/302018/12/30 1397/10/9 سلمان حافظی Salman Hafezi گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران salmanhafezi15@gmail.com سولماز دشتی Solmaz Dashti استادیار گروه محیطزیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران solmazdashti@gmail.com غلامرضا سبزقبایی Gholamreza Sabzghabaei استادیار گروه محیط زیست دانشگاه صنعتی خاتمالانبیاء بهبهان، بهبهان، ایران ایران grsabz1@gmail.com Risk Assessment Acid Reactivation Unit Abadan Oil Refining Company William Fine ارزیابی ریسک واحد احیاء اسید شرکت پالایش نفت آبادان ویلیام فاین 1. Ezejiofor T.I.N, Iwuala O.E, Nwigwe H.C. Risk assessment: Prevalent Occupational Hazards in Nigerian petroleum oil refining and distribution industry. J. Med. Invest. Pract. 2012; 8:24-829.##2. Li H, Dong K, Jiang H, Sun R, Guo X, Fan Y. Risk Assessment of China’s Overseas Oil Refining Investment Using a Fuzzy-Grey Comprehensive Evaluation Method. Sustainability 2017; 9: 1-18.##3. Osabutey D, Obro- Adibo G, Agbodohu W, Kumi P. Analysis of Risk Management Practices in the Oil and Gas Industry in Ghana. Case Study of Tema Oil Refinery (Tor), Eur. J. Bus. Manage. 2013; 5 (29): 139-149.##4. Navaie aznave Z, Omidvari M. Safety Risk assessment in Motor vehicle industries by using William fine and ANPDEMATEL. Iran. Occuo. Health. J. 2017; 14 (1): 57-70 [in Persian].##5. Abbaspour M, Nasiri P, Dana T, Totonchean S. HSE risk assessment and hazard identification in projects of oil and gas industries from construction to production (Case Study: Petro Pars Ltd). J. Environ. Sci. Technol. 2006; 11 (3): 1-13 [in Persian].##6. Ezejiofor T. Risk Assessment: Re-appraisals for Potential Hazards in the Operational Environment and Facilities of Petroleum Refining and Distribution Industry in Nigeria - Research and Review. Occup. Med. Health. Affa. 2014; 2:187.##7. Meknatjoo M, Omidvari M. Safety Risk Assessment by using William –Fine method with Compilation Fuzzy DEMATEL in Machining Process. Iran. Occuo. Health. J. 2015; 12 (5): 31-42 [in Persian].##8. Jozi S.A, Mirsalimi S.M. Environmental risk management of Madkansar Iron Ore Mine in Khorambid County using EFMEA and William Fine integrated approach. J. Manage. Syst. 2016; 1 (1): 19-27 [in Persian].##9. Ebrahimi M.H, Raei M. Conducting Risk assessment by William-Fine method in one of Kermanshah tile factory in 2014, J. Curr. Res. Sci. 2016; 1: 8-13 [in Persian].##10. Halvani G, Ehrampoush M H, Ghaneian M T, Dehghani A, Hesami Arani M. Applying Job Hazard Analysis and William Fine Methods on risks Identification and assessment of Jobs in Hot Rolling Steel, Iran. J. Mazandaran. Univ. Med. Sci. 2017; 26 (145): 293-303[in Persian].##11. Pirsaheb M, Yarmohammadi H, Rostami R, Sohrabi Y. The Evaluation of Safety, Health, and Environmental Risks in Waste Unit of Imam Reza Hospital in Kermanshah Based on William Fines Method, Int. J. Pharm. Technol. 2016; 8 (1): 10910-10917 [in Persian].##12. Jozi S.A, Ka'bzadeh Sh, Iran-Zakhai M. Safety, Health & Environmental Risk Assessment and Management of Ahwaz Pipe Manufacturing Company via William Fine Method. J. Ilam. Univ. Med. Sci. 2010; 18 (1): 1-8 [in Persian].##13. Ghale S, Khosravi M, Shalbaf M, Taghavi L. Health Safety and Environmental Risk Management cement plants. First International Conference of environmental crisis and its solutions, Kish Island, Science and Research Branch 2013: Islamic Azad University, Ahvaz, Iran: 1-9 [in Persian].##14. Samimi S, Yousefi H, Jafarzadeh N. Assessment and management of environmental risks Activities of an oil complex in Abadan Refinery. Proceedings of the 2nd National Conference on Environmental Researches in Iran, Hamedan, Shahid Mofateh University: 1-16 [in Persian].##15. Hataminzhad H. Demographic changes in Khuzestan. Jeo Sci. J. 2006; 1: 119-122 [in Persian].##16. www.arvandfreezone.com.##17. Nikeghbali sisakht N, Sekhavatjo M.S, Roozbehani B, Dadolahi A. Minimization of Air Pollutants Emission from FCCU by Scrubber in Abadan Oil Refinery, Farayandno 2014; 9 (46): 79-95 [in Persian].##18. Werner W, James R.W. The Manufacture of Sulfuric Acid. New York, Reinhold pub 1995: 1- 515.##19. Abadan Oil Refinery Engineering Department, 2011 [in Persian].##20. Jafari Nodoushan R, Kakaei Z, Rezaei H, Khodarahmi F, Kakaei H.A, Hajian N. Risk Assessment of Ilam Gas Refinery Based on William Fine Method in 2012. J. Commun. Health. Res. 2014; 3(1): 49-58 [in Persian].##21. Habibi A, Alizadeh M. Industrail Safety, 4th ed. Fanavaran publisher, Iran, Tehran, 2011:115-118 [in Persian].##22. Habibi A. Applied Safety and Performance Indicators in Industry. Second Edition, Tehran: Fanavaran Publishing House 2007: 1-385 [in Persian].##23. Pirsaheb M, Zinatizade A.A, Asadi F, Pourhaghighat S, Mohamadi A sharafi K. Assessment and risk, safety, health and environmental management of on shore drilling machines of National Iranian Drilling Company with the method of William Fine. Tech. J. Eng. Appl. Sci. 2015; 5 (3): 127-132 [in Persian].##24. Jozi A, Jafardzadehaghighifard N, Afzali behbahani N. Identify and Assess Environmental Risks Posed by High – Voltage Power Transmission Lines in Urban areas. J. Ilam. Univ. Med. Sci. 2014; 22 (2): 82-92[in Persian].##25. Jafari A.R, Razi Tabari H.R. Case study of risk assessment by William Fein in Power Plants of Abadan Oil Refining Company. The First International Conference on Inspection and Safety in Oil and Energy Industries 2010; Tehran, Iran. - Kimia Energy Conservatives; 1-8 [Persian].##26. Meknatjoo, M, Omidvari, M, 2015, Safety Risk Assessment by using William –Fine method with Compilation Fuzzy DEMATEL in Machining Process, Iran. Occuo. Health. J. Volume 12, Number 5, pp 31-42. [in Persian].## ##

برآورد پتانسیل آلودگی آرسنیک آب های زیرزمینی شهرستان سنندج با استفاده از مدل شبکه عصبی مصنوعی Estimation of Potential of the Ground Water Arsenic Contamination in Sanandaj Area Using Artificial Neural Network Model 1 1 زمینه و هدف: شناسایی آبهای زیرزمینی آلوده به آرسنیک با استفاده از پارامترهای سطحی خاک و مدلسازی این رابطه در دو مدل شبکه عصبی مصنوعی و رگرسیون خطی چندگانه میتواند در مدیریت منابع آبی منطقه مفید باشد. مواد و روشها: در این مطالعه برآورد پتانسیل آلودگی آرسنیک آب های زیرزمینی سنندج با استفاده از مدل های رگرسیون خطی چندگانه و شبکه عصبی مصنوعی مورد آزمون قرار گرفت. در این راستا از بین چاه ها ی مجوزدار شهرستان سنندج 35 چاه با در نظر گرفتن حوضه آبریز، پراکندگی مناسب و ساختار زمین شناختی متفاوت انتخاب 0- شدند. نمونه های آب هر چاه در ظرف های پلی اتیلنی و در دمای 4 درجه سانتیگراد و نمونه های خاک از عمق 20 سانتیمتری خاک سطحی بالادست چاهها به صورت مرکب جمع آوری و به آزمایشگاه منتقل شدند. در آزمایشگاه غلظت آرسنیک نمونه های آب با دستگاه جذب اتمی به روش کوره اندازه گیری گردید. ویژگی های فیزیکی و شیمیای خاک شامل: آرسنیک، آرسنات، آرسنیت، فسفات، نیترات، آهن کل، آهن بیشکل، منگنز کل، منگنز بیشکل، درصد رس، اندازه گیری شدند. در ادامه دقت مدل های رگرسیون چندگانه و CEC و pH ، درصد شن، درصد سیلت، ماده آلی خاک شبکه عصبی مصنوعی برای بررسی رابطه بین پارامترهای ذکر شده خاک و آرسنیک موجود درآب مورد آزمون قرار گرفت. یافته ها: نتایج نشان داد که غلضت آرسنیک آبهای زیرزمینی منطقه کمتر از حد استاندارد است که این می تواند به دلیل بالا بودن غلظت آرسنات خاک های منطقه نسبت به آرسنیت و افزایش ظرفیت تبادل کاتیونی خاک تحت تأثیر ذرات رس، ماده آلی و اکسیدهای آزاد آهن باشد. نتیجه گیری: مقایسه ی دقت مدل ها نیز نشان داد که مدل شبکه عصبی با 835MAE=0/ و 118 RMSE=0/ و 156 R=0/ در مرحله آزمون دارایی دقت بیشتر و خطای کمتری MAE=0/ و 158 RMSE=0/ و 177 R=0/ در مرحله آموزش و 816 در برآورد آلودگی آرسنیک آبهای زیرزمینی نسبت به مدل رگرسیون خطی چندگانه است. 2 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. 84 98 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/30 1397/10/9 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/30 1397/10/9 سامان مرادی Saman Moradi دانش آموخته کارشناسی ارشد، محیط زیست، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران ایران جمیل امان اللهی Jamil Amanoallahi استادیار، گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران ایران j.amanollahi@uok.ac.ir فرشید قربانی Farshid Ghorbani استادیار، گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران ایران Arsenic Groundwater Multiple linear regression Artificial neural network. Arsenate آرسنیک آبهای زیرزمینی رگرسیون خطی چندگانه شبکه عصبی. آرسنات 1. 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Suspended sediment flux modeling with artificial neural network: An example of the Longchuanjiang River in the Upper Yangtze Catchment. China Geo 2007; 84: 111-125.##38. Dastorani MT, Azimi Fashi K, Talebi A, Ekhtesasi MR. Estimation of Suspended Sediment Using Artificial Neural Network (Case Study: Jamishan Watershed in Kermanshah). J Watershed Manag Res 2012; 3(6): 61-74 [In Persian].##39. Demuth H, Beale M. Neural Network Toolbox (Version 4) For Use with Matlab. The Mathworks, Inc Available online at: ttps://wwwmathworkscom/help/pdf_doc/nnet/ nnet_ugpdf 1998.##40. Minasny B, McBratney A. The neuro-m method for fitting neural network parametric pedotransfer functions. Soil Sci Soc Am J 2002; 66: 352-361.##41. Back B, Back BJR. Financial statement planning in the presence of tax constraints. Euro J Oper Res 1995; 85: 66-81.##42. Missaghi.F, Mohammadi.k. Estimation of groundwater levels using conventional interpolation techniques and comparison with geostatistics technique. Twenty-first meeting on Earth Sciences Geo Survey and Min Explo of Country 2002: 588-590.##43. Hassani Pak AA. Geostatistics. Tehran University Press 1998: 328 [In Persian].##44. A MS, Abyaneh.H TZ. Evaluation of geostatistical methods for estimating electrical conductivity and pH of stream waters in Hamedan-Bahar plain. J Water Soil Conser 2009;16: 169-187.##45. Khodakarami L, Soffianian AR, Mohamadi T, Mirghafari NA. Study of heavy metals concentration Copper, Zinc and Arsenic soil using GIS and RS techniques (Case study: Kaboudarahang, Razan and Khonjin- Talkhab catchment in Hamedan province). Appl RS GIS Tech Nat Resour Sci 2011; 2(1): 79-89 [In Persian].##46. Giacomino A, Malandrino M, Abollino O, et al. An approach for arsenic in a contaminated soil: speciation, fractionation, extraction and effluent decontamination. Environ Poll 2010; 158: 416-423.##47. Wauchope R. Fixation of arsenical herbicides, phosphate, and arsenate in alluvial soils. J Environ Qual 1975; 4: 355-358.##48. 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بررسی عملکرد فرایند انعقاد و لخته سازی در پیش تصفیه شیمیایی فاضلاب گاوداری Investigation of Coagulation and Flocculation Process in Chemical Pre-Treatment of Livestock Wastewater 1 1 زمینه و هدف: با پیشرفت جوامع، افزایش جمعیت و ارتقا شاخص های سلامت، مصرف لبنیات و گوشت افزایش چشمگیری یافت، ولیکن با رشد صنعت دامداری مشکلات ناشی از فاضلاب این صنایع هم بیشتر شده است. فاضلاب دامداری به عنوان یک فاضلاب با زیستتخریبپذیری بسیار کم و آلایندگی بسیار بالا شناخته شده است. در این مطالعه عملکرد پیش تصفیه فاضلاب دامداری با استفاده از روش انعقاد و لختهسازی جهت کاهش آلاینده ها و بهبود خواص آن بررسی شد. مواد و روش ها: به این منظور از دستگاه جارتست بهعنوان یک سیستم پا یلوت منقطع، از 3به Alum و PAC ،FeCl  به عنوان لخته ساز کاتیونی و آنیونی استفاده شد و تاثیر Megafloc و Zetafloc عنوان منعقدساز و از دو پلیالکترولیت و کدورت در سه مرحله بررس ی شد . فاضلاب مورد COD در حذف pH میزان و نوع منعقدساز و نوع لختهساز و 7125 جمع آوری NTU 12250 و mg/L و کدورت او لیه به ترت یب برابر با COD آزمایش از یک واحد دامداری با گردید. یافته ها: شرایط بهینه در فرایند انعقاد و لخته سازی جهت دستیابی به بیشترین بازده حذف29 ) و کدورت /%6) COD  به همراه لخته ساز آنیونی ارزیابی گردید. pH= 400 و 8 mg/L در غلظت FeCl 52 ) در آزمایشی با حضور 3 /%8) نتیجه گیری: نتایج حاصل از این پژوهش نشان داد که فرآ یند انعقاد و لخته ساز ی م ی تواند روشی کارآمد در پیش تصفیه فاضلاب دامداری باشد. 2 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. 99 110 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/302018/12/30 1397/10/9 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/302018/12/30 1397/10/9 الهام عبداله زاده شرقی Elham Abdollahzadeh Sharghi استادیار گروه محیط زیست، پژوهشکده انرژی، پژوهشگاه مواد و انرژی، مشکیندشت، کرج، ایران ایران e.abdollahzadeh@merc.ac.ir فایزه یادگاری Faeze Yadegari دانش آموخته کارشناسی ارشد مهندسی انرژیهای تجدیدپذیر، پژوهشکده انرژی، پژوهشگاه مواد و انرژی، مشکین دشت، کرج، ایران ایران f.yadegari@merc.ac.ir لیلا داورپناه Leila Davarpanah استادیار گروه محیط زیست، پژوهشکده انرژی، پژوهشگاه مواد و انرژی، مشکین دشت، کرج، ایران ایران l.davarpanah@merc.ac.ir Livestock Wastewater physicochemical Treatment Coagulation and Flocculation COD Turbidity کدورت COD فاضلاب دامداری تصفیه فیزیکوشیمیایی انعقاد و لخته سازی 1. Xiaoyan W. Diffuse pollution from livestock production in China. Chin. J. eochem. 2005; 24(2):189-93.##2. LIVE.221 Characteristics and Volume of Effluent Produced by Livestock Vessels. Final Report prepared for MLA and LiveCorp by: Landline Consulting. Meat & Livestock Australia Ltd. 2003.##3. Harrington R, McInnes R. Integrated Constructed Wetlands (ICW) for livestock wastewater management. Bioresour. Technol. 2009; 100(22):5498-505.##4. Bernet N, Béline F. Challenges and innovations on biological treatment of livestock effluents Bioresour. Technol. 2009; 100(22):5431-6.##5. Chen X, Fukushi K. Development of a natural treatment system consisting of red ball earth and alfalfa for the post-treatment of anaerobically digested livestock wastewater. Water Sci. Technol. 2014; 70(5):795-802.##6. Pinedo-Hernandez J, Paternina-Uribe R, Marrugo-Negrete J. Alternative Electrocoagulation for Livestock Wastewater Treatment. Portugaliae Electrochim. Acta. 2016; 34(4):277-85.##7. Cressie N, Majure JJ. Spatio-temporal statistical modeling of livestock waste in streams. J. Agric. Biol. Environ. Sat.##8. Lee BH, Song WC. High concentration of ozone application by the DAF (Dissolved Air Flotation) system to treat livestock wastewater. WIT Trans. Eng. Sci. 2006; 95.##9. Lee H, Shoda M. Removal of COD and color from livestock wastewater by the Fenton method. J. Hazard. Mater. 2008; 153(3):1314-9.##10. Cho W. A study on the livestock wastewater treatment by the microscreening, chemical coagulation, and ozonation. J. Environ. Res, Korea, 2001; 1(1):137-43.##11. Burton CH. The potential contribution of separation technologies to the management of livestock manure. Livest. Sci. 2007; 112(3):208-16.##12. Zhang RH, Westerman PW. Solid-liquid separation of annual manure for odor control and nutrient management. Appl. Eng. Agric. 1997; 13(3):385-93.##13. Moller HB, Sommer SG, Ahring BK. Separation efficiency and particle size distribution in relation to manure type and storage conditions. Bioresour. Technol. 2002; 85(2):189-96.##14. Cocolo SG. Assessment of different solid-liquid separation techniques for livestock slurry. PhD Thesis, 2013.##15. APHA, AWWA, WEF. Standard Methods for the Examination of Water and Wastewater, 21st ed., American Public Health Association, Washington, DC, 2005.##16. Metcalf & Eddy. Wastewater Engineering: Treatment, Disposal and Reuse. McGraw – Hill Book Co, 2003##17. Bratby J. Coagulation and flocculation in water and wastewater treatment. IWA publishing; 2006 Oct 15.##18. Hanna M, Sievers DM, Fischer JR. Chemical coagulation of methane producing solids from flushing waste waters. In Proc. 5th Int’l. Symp. Agric. Wastes, 1985; 632-637. St. Joseph, Mich.: ASAE.##19. Powers WJ, Montoya RE, Van Horn HH, Nordstedt RA, Bucklin RA. Separation of manure solids from simulated flushed manures by screening or sedimentation. Appl. Eng. Agric. 1995; 11(3): 431-6.##20. Ming TT, Hyun KT, Myun JL. Characterization of livestock wastewater at various stages of wastewater treatment plant. Malays. J. Anal. Sci. 2007; 11:23-8.##21. Vanotti MB, Hunt PG. The use of polymers for nitrogen removal in swine wastewater: PAM and encapsulated nitrifier technologies. In Proc. Technical Conf. on Water Quality, 1996; 19-21 March, North Carolina State University, Raleigh, N.C., 116-120. Raleigh, N.C.: NCSU.##22. Piccinini S, Cortellini L. Solid-liquid separation of animal slurries. In Proc. 4th Int’l. CIEC Symp., Agricultural Waste Management and Environmental Protection, Braunschweig, Germany, 1987; 219-229. Braunschweig- Voelkenvode, Germany: International Scientific Center of Fertilizers (CEIC) and Federal Agric. Research Center (FAL).##23. Akbal F, Camcı S. Comparison of electrocoagulation and chemical coagulation for heavy metal removal. Chem. Eng. Technol. 2010; 33(10):1655–64.##24. Henriksen K, Berthelsen L, Matzen R. Separation of liquid pig manure by flocculation and ion exchange part 1: laboratory experiments. J. Agr. Eng. Res. 1998; 69(2):115-25.##25. Zhang RH, Lei F. Chemical treatment of animal manure for solid-liquid separation. Transactions of the ASAE. American Society of Agricultural Engineers. 1998; 41(4):1103-8.## ##

تثبیت آنزیم لکاز بر روی نانوذرات اکسید آهن پوشیده با سیلیس و مقایسه پایداری و فعالیت آنزیم لکاز آزاد و تثبیت شده Immobilization of Laccase Enzyme on Silica-Coated Iron Oxide Nanoparticles and Comparison of Stability and Activity of Free and Immobilized Laccase 1 1 زمینه و هدف : آنزیم لکاز قادر به اکسید کردن بسیاری از آلاینده های زیست محیطی مقاوم و غیرقابل تجزیه بیولوژیکی می باشد، به همین جهت در سالهای اخیر مورد مطالعات زیادی قرار گرفته است و به طور گسترده ای در زمینه تجزیه بیولوژ یکی آلاینده ها استفاده میشود. بهرغم قابلیت های کاربردی فراوان آن، به علت طول عمر کوتاه، عدم بازیابی، ناپایداری حرارت ی و ناپایدار ی در محیطهای آلی، استفاده گسترده از آنها بسیار محدود شده است. مطالعه حاضر، با هدف افزایش پایداری لکاز توسط تثبیت آن بر روی نانوذرات اکسید آهن پوششدار شده با سیلیس انجام پذیرفت. مواد و روشها: نانوذرات 4به روش همترسیبی سنتز شدند و پس از پوششدار شدن با سیلیس، سطح آنها توسط گروهها ی Fe3O  آمین اصلاح گردید. در ادامه تثبیت آنزیم به روش ایجاد پیوند کووالانسی با استفاده از گلوتارآلدهید انجام پذیرفت. مشخصات میکروسکوپ الکترونی گسیل میدانی ،(XRD) نانوذرات سنتز شده و آنزیم تثبیت شده به کمک تکنیک پراش اشعه ایکس بررسی شد. (EDX) و طیف سنجی تفکیک انرژی (FESEM) یافته ها : نتایج مطالعه تثبیت موفق لکاز بر روی نانوذرات را نشان داد ضمن اینکه تثبیت لکاز به طور چشمگیری سبب افزایش در مقایسه با لکاز آزاد گردید. pH پایداری ذخیره سازی و حرارتی، حفظ فعالیت در محدوده وسیعتری از دما و نتیجه گیری: تثبیت لکاز بر روی نانوذرات اکسید آهن پوششدار شده با سیلیس میتواند با افزایش کارآیی و پایداری آن، موانع و چالش های پیش روی کاربردهای متنوع این آنزیم را کاهش دهد. 2 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. 111 124 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/302018/12/302018/12/30 1397/10/9 2018/12/292018/12/292018/12/302018/12/302018/12/302018/12/302018/12/302018/12/30 1397/10/9 الهام رزمی Elham Razmi گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی ایران، تهران، ایران ایران e_razmi63@yahoo.com احمد جنیدی جعفری Ahmad Jonidi Jafari گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی ایران، تهران، ایران و مرکز تحقیقات تکنولوژی بهداشت محیط، دانشگاه علوم پزشکی ایران، تهران، ایران ایران علی اسرافیلی Ali Esrafili گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی ایران، تهران، ایران و مرکز تحقیقات تکنولوژی بهداشت محیط، دانشگاه علوم پزشکی ایران، تهران، ایران ایران عماد دهقانی فرد Emad Dehghanifard گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی البرز، کرج، ایران دانشگاه علوم پزشکی البرز، کرج، ایران ،(RCHSE) 4 مرکز تحقیقات بهداشت، ایمنی و محیط ایران روشنک رضایی کلانتری Roshanak Rezaei Kalantari گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی ایران، تهران، ایران و مرکز تحقیقات تکنولوژی بهداشت محیط، دانشگاه علوم پزشکی ایران، تهران، ایران ایران rezaei.r@iums.ac.ir Laccase Immobilization Silica-coated iron oxide nanoparticles Enzyme Activity لکاز تثبیت نانوذرات اکسید آهن پوششدار شده با سیلیس فعالیت آنزیم 1. Polaina J, MacCabe AP. Industrial enzymes: Springer; 2007.##2. Senthivelan T, Kanagaraj J, Panda R. Recent trends in fungal laccase for various industrial applications: an ecofriendly approach-a review. Bioprocess Eng. 2016;21(1): 19-38.##3. Xu R, Si Y, Wu X, et al. Triclosan removal by laccase immobilized on mesoporous nanofibers: strong adsorption and efficient degradation. Chem Eng J. 2014;255: 63-70.##4. Kunamneni A, Plou FJ, Ballesteros A, Alcalde M. Laccases and their applications: a patent review. Recent Pat. Biotechnol. 2008;2(1): 10-24.##5. Bautista LF, Morales G, Sanz R. Immobilization strategies for laccase from Trametes versicolor on mesostructured silica materials and the application to the degradation of naphthalene. Bioresour. Technol. 2010;101(22): 8541-8.##6. Datta S, Christena LR, Rajaram YRS. Enzyme immobilization: an overview on techniques and support materials. 3 Biotech 2013;3(1): 1-9.##7. Couto SR, Herrera JLT. 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