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اولویت بندی سناریوهای حذف ترکیبات آلی فرار از واحدهای R.O.P پالایشگاه نفت با استفاده از مدل شبکه عصبی مصنوعی (مطالعه موردی: پالایشگاه نفت آبادان) Prioritization of Air Pollutant Removal (VOC) Scenarios from Refinery R.O.P Units Using Artificial Neural Network Model (Case Study: Abadan Oil Refinery) 1 1 مقدمه و اهداف: نفت در بسیاری از صنایع اهمیت حیاتی دارد و مهم ترین منبع تامین انرژی در سطح بین المللی است و 32 درصد منبع تامین انرژی در اروپا و آسیا و بیش از 53 درصد در خاورمیانه را تشکیل میدهد. با توجه به جایگاهی که صنایع پتروشیمی امروزه پیدا کرده اند نباید از صدمات آن بر سلامت انسان و محیط زیست غافل بود. امروزه پالایشگاهها میلیون‌ها پوند آلاینده در هوا منتشر می‌کنند که خطری جدی بر سلامت انسان و محیط زیست محسوب می‌گردد و کیفیت زندگی افراد مجاور جوامع صنعتی را با آسیب‌های جدی رو به رو می‌کند. لذا در این پژوهش با بهره گیری از منطق و الگوریتم بکار رفته در مدل شبکه‌ی عصبی مصنوعی، به اولویت‌بندی وزنی استراتژی‌ها و پیش‌بینی شرایط آتی حاکم بر طرح، پرداخته است و در نهایت رتبه بندی نهایی با مدل TOPSIS صورت پذیرفت. روش کار: در این پژوهش، سنجش آلاینده‌های هوا با روش کروماتوگرافی گازی بود و با استفاده از شبکه عصبی مصنوعی ANN (Artificial Neural Networks) به بررسی اولویت بندی سناریوهای حذف آلاینده‌های آلی فرار از واحد تصفیه پساب نفتی ROP (Recovery Oil Compound) پالایشگاه نفت آبادان در سال 1398 پرداخته شد. روش به کار گیری شبکه عصبی مصنوعی در مطالعه حاضر روش پرسپترون چند لایه MLP (Multi Layer Perceptron)   بود. رتبه بندی نهایی با مدل  TOPSISصورت پذیرفت. یافته ها: بر اساس نتایج به دست آمده از سنجش آلاینده‌های هوای مجاور واحد  ROPپالایشگاه، بیشترین میزان انتشار ترکیبات آلی فرار نسبت به میزان اعلام شده توسط WHO متعلق به نشر بنزن با مقادیر  µg/m388/8865 در فصل بهار،  µg/m304/1701 در فصل تابستان،  µg/m3 72/8061  در فصل پاییز و  µg/m3 62/8447 در فصل زمستان بود. نتیجه گیری: بر اساس خروجی‌های مدل و رتبه بندی آن با مدل TOPSIS، کمینه سازی پساب تولیدی در کارخانه از طریق کنترل موثر تر مصرف آب، بهینه سازی فرآیندهای تولید، استفاده مجدد از آبهای کندانس مبدل‌های غیر مستقیم، کنترل نشت در اتصالات، شیرها و تجهیزات پالایشگاه با ضریب تاثیر با خلوص 1، اولین اولویت و ائده آل ترین حالت بود. پس از آن برگشت دادن لجن از مخزن هوادهی جهت فراهم سازی تعداد کافی میکروارگانیسم‌ها برای جلوگیری از بی هوازی شدن لجن فعال، همچنین افزایش زمان ماند هیدرولیکی فاضلاب هر دوساعت یکبار با 7798/0 اولویت دوم و بکارگیری حوض‌های یکنواخت سازی با 6964/0 به حالت ائده آل استراتژی سوم مشخص گردید. 2 Oil is vital in many industries and is the most important source of energy supply internationally, accounting for 32% of energy supply in Europe and Asia and more than 53% in the Middle East. Given the position that the petrochemical industry has found today, its damage to human health and the environment should not be overlooked. Refineries today emit millions of pounds of pollutants into the air, which poses a serious threat to human health and the environment, and seriously damages the quality of life of people living in industrial communities. Therefore, in this study, using the logic and algorithm used in the artificial neural network model, the weight prioritization of the strategies and the prediction of future conditions governing the plan have been done, and finally the final ranking was done with the TOPSIS model. Methods: In this study, air pollutants were measured by gas chromatography and using artificial neural network ANN (Artificial Neural Networks) to prioritize the scenarios of removal of volatile organic pollutants from ROP (Recovery Oil Compound) of Abadan Oil Refinery It was done in 2019 to 2020. The method of using artificial neural network in the present study was MLP (Multi Layer Perceptron). The final ranking was done with TOPSIS model. Results: Based on the results obtained from the measurement of air pollutants adjacent to the ROP unit of the refinery, the highest emission of volatile organic compounds compared to the amount announced by WHO belongs to benzene emission with values of 8865.88 µg/m3 in spring, 1701.04 µg/m3 in summer, 8061.72  µg/m3 in autumn and 8447.62 µg/m3 was in winter. Conclusion: Based on the model outputs and its ranking with the TOPSIS model, minimization of production effluent in the factory through more effective control of water consumption, optimization of production processes, reuse of condensate water of indirect converters, control of leakage in connections, valves and equipment The refinery with an impact factor of 1 purity was the first priority and the most ideal. hen return the sludge from the aeration tank to provide a sufficient number of microorganisms to prevent anaerobic activation of the sludge, as well as increase the hydraulic retention time of wastewater every two hours with 0.7798 second priority and use of uniformity ponds with 0.6964 to the ideal state. The third strategy was identified. 1 16 2020/08/11 1399/5/21 2020/11/1 1399/8/11 لادن خواجه حسینی Ladan Khajeh Hoseini گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران رضا جلیل زاده ینگجه Reza Jalilzadeh Yengejeh گروه مهندسی محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران مریم محمدی روزبهانی Maryam Mohammadi Rouzbahani گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران سیما سبزعلیپور Sima Sabz alipour گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران Volatile Organic Compounds Oil Refinery Air Pollution Artificial Neural Network ترکیبات آلی فرار پالایشگاه نفت آلودگی هوا شبکه عصبی مصنوعی 1. Barraza F, Uzu G, Jaffrezo J L, Schreck E, Budzinski H, Le Menach K, Dévier MH, Guyard H, Calas A, Perez M I, Villacreces L A, Maurice L. Contrasts in chemical composition and oxidative potential in PM10 near flares in oil extraction and refining areas in Ecuador. Atmospheric Environment 2020; 223_ 117302. doi:10.1016/j.atmosenv.2020.117302.##2. McGuire J B, Leahy J E, Marciano J A, Lilieholm R J, Teisl M F. Social acceptability of establishing forest-based biorefineries in Maine, United States. Biomass and Bioenergy2017;105: 155-163. doi:10.1016/j.biombioe.2017.06.015.##3. Mahmoudi E, Jodeiri N, Fatehifar E. Implementation of material flow cost accounting for efficiency improvement in wastewater treatment unit of Tabriz oil refining company.Journal of Cleaner Production 2017; 165: 530-536.doi: 10.1016/j.jclepro.2017.07.137.##4. Jakrawatana N, Pingmuangleka P, Gheewala S H. Material flow management and cleaner production of cassava processing for future food, feed and fuel in Thailand. Journal of Cleaner Production 2016; 134: 633-641. doi:10.1016/j.jclepro.2015.06.139.##5. Christ K L, Burritt R L. Material flow cost accounting: a review and agenda for future research. 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Tourism Management 2004;25(4): 499-506. doi:10.1016/S0261-5177(03)00120-1.##11. Hellsmark H, Mossberg J, Söderholm P, Frishammar J. Innovation system strengths and weaknesses in progressing sustainable technology. the case of Swedish biorefinery development, Journal of Cleaner Production 2016;131: 702-715. doi:10.1016/j.jclepro.2016.04.109.##12. Feng X, Li Q, Zhu Y, Hou J, Jin L, & Wang J. Artificialneural networks forecasting of pm2.5 pollution using air mass trajectory based geographic model and wavelet transformation.Atmospheric Environment 2015; 107 , 118 – 128##13. Aragonés-Beltrán P, Chaparro-González F, Pastor-Ferrando J P, Pla-Rubio A. An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy 2014; 66, 222-238. doi:10.1016/j.energy.2013.12.016.##14. Capecci E, Doborjeh Z. G, Mammone N, Foresta F L, Morabito F C, & Kasabov N. Longitudinal study of alzheimer’s disease degeneration through eeg data analysis with a neucube spiking neural network model. International Joint Conference on Neural Networks (IJCNN)2016; (pp. 1360–7201366).##15. Choudhary D, Shankar R. An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy 2012; 42(1): 510-521. doi:10.1016/j.energy.2012.03.010.##16. Ertay T, Ruan D, Tuzkaya U R. Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems. Information Sciences 2006; 176(3): 237-262.doi:10.1016/j.ins.2004.12.001.##17. Saeidi M, Abesi A, Sarpak M. Locating a suitable place to bury hazardouswaste using GIS rating and AHP: case report of Shahid RajaeePowerhouse. Environ Sci Tech 2009;11(1):231–241.##18. Kurttila M, Pesonen M, Kangas J, Kajanus M. Utilizing the analytic hierarchy process (AHP) in SWOT analysis — a hybrid method and its application to a forest-certification case.Forest Policy and Economics 2000; 1(1): 41-52. doi:10.1016/S1389-9341(99)00004-0.##19. Görener A, Toker K, Uluçay K. Application of Combined SWOT and AHP: A Case Study for a Manufacturing Firm, Procedia. Social and Behavioral Sciences 2012; 58, 1525-1534. doi: 10.1016/j.sbspro.2012.09.1139.##20. Cannon, A. J. 2017. monmlp r package: Multi-layer perceptron neural networkwith optional monotonicity constraints.##21. Kumari Muniyandi S, Johan S, Azman H, Siti SM. Converting non-metallicprinted circuit boards waste into a value added product. J Environ HealthSci Eng 2013; 11:2. doi:10.1186/2052-336X-11-2.##22. Fetros and Barzegar .Factors Affecting Air Pollution. First Conference of air pollution and its effects on health2005. ##23. Kaya, T .2011. 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بررسی میزان غلظت ترکیبات هیدروکربن‌های آروماتیک چند حلقه‌ای ( PAHs ) در هوای بیرونی و داخلی محیط‌های شهری (مطالعه موردی: شهر تهران، 1397-1396) Investigation of The Concentration of Polycyclic Aromatic Hydrocarbon Compounds (PAHs) in Indoor and Outdoor Air of Urban Areas (Case study: Tehran, 2017-2018) 1 1 سابقه و هدف: ترکیبات آلی فرار یکی از مهمترین آلاینده‌های هوای شهرهاست که ناشی از خودروها , صنایع شیمیایی و پتروشیمی می‌باشد. یک جزء بسیار مهم از ترکیبات آلی فرار مربوط به ترکیبات PAHs است که دارای ساختار آروماتیک هستند و در اثر بسیاری از فرایند‌های طبیعی و فعالیت‌های انسانی ایجاد می‌شوند. این ترکیبات به شکل وسیعی در محصولات و صنایع نفت و پتروشیمی، به عنوان حلال در صنایع رنگ سازی و چسب سازی مورد استفاده قرار گرفته و دارای اثرات بهداشتی مهمی بر روی انسان مانند ایجاد سرطان می‌باشند هدف از این مطالعه بررسی میزان هیدرو کربن‌های اروماتیک حلقوی ( PAHs ) در هوای بیرونی و داخلی د ردو فصل سرد و گرم می‌باشد مواد و روشها: نمونه‌برداری این مطالعه با انتخاب12 ایستگاه از شهر تهران انجام گرفت. نمونه‌برداری در یک دوره یکساله با استفاده از لوله‌های جاذب و پمپ نمونه‌بردار فردی با دبی 200 میلی لیتر در دقیقه در فاصله 2-5/1 متری از سطح زمین انجام شد. از هر ایستگاه سه نمونه در دوره گرم (خشک) و سه نمونه در دوره سرد (تر)،جمعاً72 نمونـه گرفتـه شـد. نمونـه‌های جمـع آوری شـده در یخچال نگهداری و سپس به آزمایشگاه منتقل شده و بعد از استخراج از سطح جاذب توسط دسـتگاه گازکارومـاتوگرافی قرائـت گردید. یافته‌ها: نتایج نشان داد در دوره نمونه‌برداری در محیط خشک هوای آزاد میانگین غلظت PAHsبرابر با 2/20 ppb و در محیط تر هوای آزاد میانگین غلظت PAHsبرابر با 6/23 ppb بوده است. همچنین در دوره نمونه‌برداری در محیط خشک هوای داخل میانگین غلظت PAHsبرابر با 6/20 ppb و در محیط تر هوای داخل میانگین غلظت PAHsبرابر با 8/23 ppb بوده است. نتیجه‌گیری: به طور کلی میانگین غلظت ترکیبـات PAHs در فصل سرد بیش از فصل گرم می‌باشد کـه دلیـل آن آلودگی مراکز خانگی و تجاری توأم با ایجاد اینورژن در شهر تهران در فصول سرد سال و افـزایش واکنش‌های فتوشیمیایی در فصل گرم و تبدیل شدن سریعتر این مواد به مواد دیگر می‌باشد. میزان ایـن ترکیبـات در قسـمت‌های پرترافیک و مرکز شهر بیش از سایر نقاط می‌باشد و با فاصله گرفتن از این نقـاط پرترافیـک از غلظـت ایـن ترکیبـات بـتدریج کاسته می‌شود. 2 Volatile organic compounds are one of the most important air pollutants in cities that are caused by cars, chemical and petrochemical industries. A very important component of volatile organic compounds is PAHs, which have an aromatic structure and are formed by many natural processes and human activities. These compounds are widely used in petroleum and petrochemical products and industries, as solvents in paint and adhesive industries and have important health effects on humans, such as cancer. The aim of this study was to investigate the amount of Poly Cyclic Aromatic Hydrocarbons (PAHs) in indoor and outdoor air during the hot and cold seasons. Materials and methods: Sampling of this study was performed by selecting 12 stations from Tehran in a one-year period using absorbent tubes and individual sampling pump with a flow rate of 200ml / min at a distance of 1-2.5 meters from the ground. From each station, three samples were taken in dry period and three samples in wet period (72 sample). The collected samples were stored in the refrigerator and then transferred to the laboratory and after extraction from the adsorbent surface were read by Gas Chromatographic. Results: The results showed that during the sampling period in dry in ambient air, the average concentration of PAHs was equal to 20.2 ppb and in wet outdoor environment( ambient air), the average concentration of PAHs was equal to 23.6 ppb. Also, in the sampling period in dry (indoor air), the average concentration of PAHs was equal to 20.6 ppb and in wet (indoor air), the average concentration of PAHs was equal to 23.8 ppb. Conclusion: In general, the average concentration of PAHs in the cold season(wet) is more than the hot season (dry), which is due to pollution of domestic and commercial canters with the creation of inversion in Tehran in the cold season and increased photochemical reactions in the hot season and become faster This material is to other materials. The amount of these compounds in high-traffic areas and the city centre is more than other places, and by moving away from these high-traffic points, the concentration of these compounds is gradually reduced. 17 30 2020/08/112020/08/15 1399/5/25 2020/11/12020/10/31 1399/8/10 حمید رضا حاجی آدینه Hamid Reza Haji Adineh گروه مهندسی محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران مریم محمدی روزبهانی Maryam Mohammadi Rouzbehani گروه محیط زیست، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران خوشناز پاینده Khoshnaz Payandeh گروه خاک شناسی، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران نوید قنواتی Navid Ghanavati گروه خاک شناسی، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران ایران Air Pollution Polycyclic Aromatic Hydrocarbons (PAHs) Dry and Wet Tehran آلودگی هوا هیدروکربن‌های آروماتیک چند حلقه ای ( PAHs) خشک و تر تهران 1. Ali-Taleshi M S, Moeinaddini M, Feiznia S, Squizzato S. Heavy Metal Pollution in Street Dust from Tehran in 2018: Metal Richness and Degree of Contamination Assessment. jehe. 2020; 7 (2) :179-194. [in Persian]##2. Fatma E, Yucel T, Siddik CS. Determination of mass transfer rates and deposition levels of polycyclic aromatic hydrocarbons (PAHs) using a modified water surface sampler. Atmospheric Pollution Research. 2010;1(3):177-83.##3. Yuan B, Shao M, Lu S, Wang B. Source profiles of volatile organic compounds associated with solvent use in Beijing, China. Atmospheric Environment. 2010 May 1;44(15):1919-26.##4. Brown SK, Sim MR, Abramson MJ, Gray CN. Concentrations of volatile organic compounds in indoor air–a review. Indoor air. 1994;4(2):123-34.##5. Van Winkle MR, Scheff PA. Volatile organic compounds, polycyclic aromatic hydrocarbons and elements in the air of ten urban homes. Indoor air. 2001;11(1):49-64.##6. Miller L, Xu X, Lemke LD, Wheeler AJ. 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Gas–particle concentration, distribution, and health risk assessment of polycyclic aromatic hydrocarbons at a traffic area of Giza, Egypt. Environmental Monitoring and Assessment. 2012 Jun 1;184(6):3593-612.##11. Naddafi K, Yunesian M, Faridi S, Rafiee A, Parmy S, Safari G, et al. Source identification of PM10-bound Polycyclic Aromatic Hydrocarbons (PAHs) of Tehran ambient air in year 2013. ijhe. 2017; 10 (1) :25-36. [in Persian]##12. Derakhshannezhad A S, Goodarzy R, Baneshi MM, Nazari Z. Investigation on the concentration of polyaromatic hydro carbons dibenzo (α, h) anthracen in Ahwaz ambient air Jundishapur Journal of Health Sciences 2012. [in Persian]##13. Freire C, Abril A, Fernández MF, Ramos R, Estarlich M, Manrique A, Aguirre A, Ibarluzea J, Olea N. Urinary 1-hydroxypyrene and PAH exposure in 4-year-old Spanish children. Science of the total environment. 2009 Feb 15;407(5):1562-9.##14. 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ارزیابی قابلیت زئولیت طبیعی در تثبیت و نامتحرک‌سازی سرب و کادمیم در خاک آلوده با استفاده از روش استخراج متوالی Investigation of Efficiency of Natural Zeolite on Immobilization/Stabilization of Pb and Cd in Contaminated Soil Using the BCR Sequential Extraction Method 1 1 زمینه و هدف: فلزات سنگین از جمله مهم‌ترین آلاینده‌های خاک هستند که کاهش زیست‌فراهمی و تحرک این عناصر در خاک برای کنترل میزان سمیت و اثرات حاد و مزمن آن‌ها از اهمیتی بسزا برخوردار است. لذا، این پژوهش با هدف بررسی قابلیت زئولیت طبیعی برای تثبیت شیمیایی سرب و کادمیم در یک نمونه خاک آلوده انجام شد. مواد و روش­ها: پس از آلوده کردن نمونه‌های خاک شاهد و تیمار حاوی %5 زئولیت طبیعی با مقادیر مشخصی از نمک‌های نیترات سرب (150، 500 و 1500 میلی‌گرم در کیلوگرم) و نیترات کادمیم (10، 30 و 100 میلی‌گرم در کیلوگرم) نسبت به تعیین مقادیر عناصر سرب و کادمیم در جزء‌های مختلف خاک شامل محلول در اسید، کاهشی، اکسایشی و باقی‌مانده نمونه‌های خاک آلوده شده به‌روش BCR و محاسبه نرخ تحرک‌پذیری عناصر در فواصل زمانی معین (1، 7، 14، 28 و  56 روز) اقدام شد. یافته­ها: نتایج نشان داد که نرخ تحرک‌پذیری سرب در تیمار حاوی زئولیت طبیعی حاوی 150، 500 و 1500 میلی‌گرم در کیلوگرم سرب افزوده به خاک با افزایش زمان انکوباسیون یعنی پس از طی 56 روز در مقایسه با تیمار شاهد به‌ترتیب %51، %23 و %15 کاهش یافته بود. از طرفی نرخ تحرک‌پذیری کادمیم نیز در تیمار حاوی زئولیت طبیعی حاوی 10، 30 و 100 میلی‌گرم در کیلوگرم کادمیم افزوده به خاک پس از طی 56 روز در مقایسه با تیمار شاهد به‌ترتیب %12، %9 و %5 کاهش یافته بود. نتیجه‌گیری: هرچند نتایج نشان داد که با افزایش محتوی افزوده سرب و کادمیم به خاک، کارایی زئولیت طبیعی در تثبیت و نامتحرک‌سازی این عناصر کاهش یافت، ولی می‌توان از زئولیت طبیعی بدلیل کارایی قابل قبول در جذب فلزات سنگین، قیمت مناسب، فراوانی و حداقل تاثیر منفی بر محیط‌زیست برای فرآیند تثبیت شیمیایی در خاک‌های آلوده به فلزات سنگین استفاده کرد. 2 Nowadays, soil contamination with heavy metals is among the main world concern, and therefore, special attention to protecting soil quality is vital. In this regard, the decrease of bioavailability and mobility of these elements in the soil are very important to control their toxicity and their acute and chronic effects. Therefore, this study was conducted to investigate the efficiency of natural zeolite for the immobilization/stabilization of lead and cadmium in a contaminated soil sample. Materials & Methods: In this study, first, the control and experimental (containing 5% of natural zeolite) soil treatments were contaminated with 150, 500 and 1500 mg/kg of Pb and 10, 30 and 100 mg/kg of Cd. Then the contents of Pb and Cd in the soil samples were determined in various fractions (i.e. exchangeable and acid-soluble fraction (F1), the reducible fraction (F2), the oxidisable fraction (F3) and the residual fraction (F4)) of both soil treatments were extracted using the BCR sequential extraction procedure and finally, the mobility rates of the elements were computed at different incubation periods (i.e. 1, 7, 14, 28 and 56 days). Results: The results showed that the mobility of Pb in the experimental treatment containing 150, 500 and 1500 mg/kg added lead was decreased 51%, 23% and 15% at 56th day of incubation compared to the control treatment. While, the mobility of Cd in the experimental treatment containing 10, 30 and 100 mg/kg added cadmium was decreased 12%, 9% and 5% at the 56th day of incubation compared to the control treatment. Conclusion: Based on the results obtained, although with increasing in the added amounts of Pb and Cd in the soil the efficiency of natural zeolite as an amendment agent in the immobilization and solidification of these elements was reduced, natural zeolite can be used for chemical fixation of heavy metal- contaminated soils due to its acceptable efficiency in heavy metal uptake, reasonable price, abundance and minimal adverse environmental impact. 31 49 2020/08/112020/08/152020/07/7 1399/4/17 2020/11/12020/10/312020/10/28 1399/8/7 فرزانه محمدظاهری Farzaneh Mohammad Zaheri دانش‌آموخته کارشناسی ارشد محیط‌زیست، دانشکده علوم پایه، واحد همدان، دانشگاه آزاد اسلامی، همدان، ایران ایران سهیل سبحان اردکانی Soheil Sobhanardakani دکترای تخصصی علوم محیط‌زیست، دانشیار گروه محیط‌زیست، دانشکده علوم پایه، واحد همدان، دانشگاه آزاد اسلامی، همدان، ایران ایران بهاره لرستانی Bahareh Lorestani دکترای تخصصی علوم محیط‌زیست، دانشیار گروه محیط‌زیست، دانشکده علوم پایه، واحد همدان، دانشگاه آزاد اسلامی، همدان، ایران ایران Soil contamination Soil amendment Mobility Heavy metals آلودگی خاک اصلاح کننده خاک تحرک‌پذیری فلز سنگین 1. 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ارزیابی شاخص خطر مصرف شیرینی‌جات سنتی کرمانشاه در سال 1397 با تاکید بر قابلیت خطرآفرینی سرب، کادمیم، کروم و مس Health risk Assessment of Traditional Pastries Marketed in City of Kermanshah in 2019 with Emphasis on Potential Risk of Pb, Cd, Cr and Cu 1 1 زمینه و هدف: شیرینی­ جات از فرآورده‌های غذایی مورد علاقه مردم در هر رده سنی و بویژه کودکانی است که آن‌ها را به مقدار زیاد مصرف می‌کنند. از آن‌جا که بواسطه آلودگی مواد اولیه و یا فرآیند تولید امکان آلودگی این قبیل محصولات به انواع ترکیبات خطرناک و بویژه فلزات سنگین محتمل است، این پژوهش با هدف ارزیابی مخاطره سلامت مصرف نان برنجی و کاک به‌عنوان پرمصرف‌ترین شیرینی‌جات سنتی کرمانشاه با تاکید بر قابلیت خطرآفرینی سرب، کادمیم، کروم و مس در سال 1397 انجام یافت. مواد و روش­‌ها: از هر نوع شیرینی، 21 نمونه از هفت برند پر فروش تهیه و نسبت به آماده­سازی و هضم اسیدی آن‌ها در آزمایشگاه اقدام شد. سپس غلظت عناصر مورد مطالعه در نمونه‌ها توسط دستگاه طیف‌سنج نشری پلاسمای جفت‌شده القایی خوانده شد. پردازش آماری نتایج نیز توسط نرم­افزار SPSS انجام یافت. یافته­ ها: میانگین غلظت عناصر سرب، کادمیم، کروم و مس (میلی‌گرم در کیلوگرم) در نمونه‌های نان برنجی به‌ترتیب برابر با 770/0، 034/0، 21/1 و 14/1 و میانگین غلظت این عناصر در نمونه‌های کاک نیز به‌ترتیب برابر با 200/0، 035/0، 02/1 و 23/1 بوده است. از طرفی میانگین غلظت سرب در نمونه‌های نان برنجی از بیشینه رواداری WHO بزرگ­تر بود. همچنین مقادیر شاخص خطر کل (TTHQ) نان برنجی برای کودکان و بزرگسالان به‌ترتیب با 2-10× 57/2 و 3-10× 29/5 و کاک نیز به‌ترتیب با 2-10× 10/1 و 3-10× 33/2 کوچک­تر آستانه خطر (یک) بود. نتیجه­ گیری: هرچند با استناد به مقادیر محاسبه شده شاخص خطر، استفاده از نان برنجی و کاک با نرخ مصرف فعلی عواقب مخاطره­آمیز بهداشتی برای افراد بدنبال ندارد، اما از آن‌جا که میانگین غلظت سرب در نمونه‌های نان برنجی از حد مجاز تجاوز کرده بود و در نظر گرفتن قابلیت پایداری و تجمع‌زیستی فلزات سنگین در بافت‌های بدن، نسبت به پایش مقادیر تجمع­یافته فلزات سنگین در مواد غذایی پرمصرف به­ منظور حفظ سلامت مصرف‌کنندگان و همچنین ایمنی غذایی توصیه می­شود.   2 Traditional pastries are the favorite common food items of people at all ages, especially children who consume them in large amounts. Since raw materials and manufacturing processes may be the main sources of contamination of foodstuffs by hazardous compounds particularly toxic heavy metals, this study was conducted to health risk assessment of Pb, Cd, Cr and Cu through consumption of two famous traditional pastries (i.e. "Nan-e Berenji" and "Kak") which marketed in city of Kermanshah in 2019. Materials and Methods: After the purchase of 21 samples of each pastry of seven popular brands and acid digestion of the samples according to standard methods, the content of studied elements was determined using inductively coupled plasma- optical emission spectrometer (ICP-OES) in 3 replicates. Also, all statistical analyses were performed using the SPSS software. Results: Based on the results the mean contents of Pb, Cd, Cr and Cu (mg/kg) in Nan-e Berenji samples were 0.770, 0.034, 1.21 and 1.14, respectively, while the mean contents of elements in Kak samples were 0.200 for Pb, 0.035 for Cd, 1.02 for Cr and 1.23 mg/kg for Cu. Besides, the results obtained showed that TTHQ values were 2.57 ⨯ 10-2 and 5.29 ⨯ 10-3 for children and adults, respectively, who consuming Nan-e Berenji and were 1.1 ⨯ 10-2 and also 2.33 ⨯ 10-3, respectively, for children and adults who consuming Kak. Also, the mean contents of Pb in Nan-e Berenji samples were higher than the WHO maximum permissible limits (MPL). Besides, THQ values were within the safe limits (THQ < 1), and there is no potential health risk for adults and children via the consumption of analyzed traditional pastries. According to the results of the current study, the controlled consumption of traditional pastries under the current consumption rate hasn't an adverse effect on the consumer's health. While, the mean contents of Pb in Nan-e Berenji samples were higher than the MPL, and due to the persistent and bioaccumulation potential of heavy metals in the body tissues, regular periodic monitoring of the content of toxic metals in popular foodstuffs for maintaining human health and achieve food security is recommended. 50 62 2020/08/112020/08/152020/07/72020/07/22 1399/5/1 2020/11/12020/10/312020/10/282020/09/19 1399/6/29 فاطمه فرخی Fatemeh Farrokhi دانش‌آموخته کارشناسی ارشد محیط‌زیست، گروه علوم و مهندسی محیط‌زیست، دانشکده منابع‌طبیعی و محیط‌زیست، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران، ایران سهیل سبحان اردکانی Soheil Sobhanardakani دکترای تخصصی علوم محیط‌زیست، دانشیار گروه علوم و مهندسی محیط‌زیست، دانشکده علوم پایه، واحد همدان، دانشگاه آزاد اسلامی، همدان، ایران ایران لعبت تقوی Lobat Taghavi دکترای تخصصی علوم محیط‌زیست، دانشیار گروه علوم و مهندسی محیط‌زیست، دانشکده منابع‌طبیعی و محیط‌زیست، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران ایران Food security Maximum permissible limits Target hazard quotient Traditional pastries Heavy metals ایمنی غذایی بیشینه رواداری شاخص خطر شیرینی‌جات سنتی فلز سنگین 1. 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Health risk assessment of citrus contaminated with heavy metals in Hamedan City, potential risk of Al and Cu. Environ Health Eng Manage J 2016; 3(3): 131-5. ##7. Sobhanardakani S, Jafari SM. Assessment of heavy metals (Cu, Pb and Zn) in different tissues of common carp (Cyprinus carpio) caught from Shirinsu Wetland, Western Iran. J Chem Health Risk 2014; 4(2): 47-54. ##8. Sobhanardakani S, Maanijou M, Asadi H. Investigation of Pb, Cd, Cu and Mg concentrations in groundwater resources of Razan Plain. Sci J Hamadan Univ Med Sci 2014; 21(4): 319-29 (In Persian).##9. Muhammad S, Tahir Shah M, Khan S. Health risk assessment of heavy metals and their source apportionment in drinking water of Kohistan region, northern Pakistan. Microchem J 2011; 98(2): 334-43. ##10. Özcan MM, AL Juhaimi FY. Determination of heavy metals in bee honey with connected and not connected metal wires using inductively coupled plasma atomic emission spectrometry (ICP–AES). Environ Monit Assess 2012; 184: 2373-5. ##11. Hosseini SV, Sobhanardakani S, Kolangi Miandare H, et al. Determination of toxic (Pb, Cd) and essential (Zn, Mn) metals in canned tuna fish produced in Iran. J Environ Health Sci Eng 2015; 13: 59. ##12. Sabzevari E, Sobhanardakani.S. Analysis of selected heavy metals in indoor dust collected from city of Khorramabad, Iran: A case study. Jundishapur J Health Sci 2018; 10(3): e67382. ##13. Aghelan N, Sobhanardakani S. Health risk assessment of consumption of tea marketed in Hamadan City, potential risk of As, Pb, Cd and Cr. Sci J Hamadan Univ Med Sci 2016; 23(1):65-74 (In Persian).##14. Bakirdere S, Yaman M. Determination of lead, cadmium and copper in roadside soil and plants in Elazig, Turkey. Environ Monit Assess 2008; 136(1-3): 401-10. ##15. Sobhanardakani S, Tizhosh M. Determination of Zn, Pb, Cd and Cu contents in raw milk from Khorram-Abad dairies. J Food Hyg 2016; 6(2):43-50 (In Persian).##16. Lee S, Kim Y-Y, Lee Y, et al. Rrice P1B-type heavy-metal ATPase, OsHMA9, is a metal efflux protein. Plant Physiol 2007; 145(3): 831-42. ##17. Hedayatifar R, Falahi E, Bbirjandi M. Determination of cadmium and lead levels in high consumed rice (Oryza Sativa L.) cultivated in Lorestan province and its comparison with national standards. Yafteh 2011; 12 (4): 15-22 (In Persian).##18. Sobhanardakani S. Heavy metals health risk assessment through consumption of some foodstuffs marketed in city of Hamedan, Iran. Caspian J Environ Sci 2019; 17(2): 175-83. ##19. Sobhanardakani S, Taghavi L. Non-carcinogenic risk assessment of As and Zn in citrus marketed in Hamedan City. J Res Environ Health 2016; 2(3): 237-44 (In Persian).##20. Zeng X, Wang Z, Wang J, et al. Health risk assessment of heavy metals via dietary intake of wheat grown in Tianjin sewage irrigation area. Ecotoxicology 2015; 24(10): 2115-24. ##21. Azarshab Z, Sobhanardakani S. Study of health risk assessment of Fe and Cr content in some spices marketed in Hamedan city in 2015. Razi J Med Sci 2016; 23(9): 28-34 (In Persian).##22. Varmazyar L, Sobhanardakani S. The risk assessment of Pb and Cd through consuming spices. Sci J Sch Pub Health Inst Publ Health 2017; 15(2): 185-95 (In Persian).##23. Azarshab Z, Sobhanardakani S.Health risk assessment of heavy metals (Zn and Cd) via consumption of cinnamon, black Pepper and chili marketed in city of Hamedan. Tabriz Univ Med Sci Health Serv 2018; 40(5): 7-14 (In Persian).##24. Guo J, Yue T, Li X, et al. Heavy metal levels in kiwifruit orchard soils and trees and its potential health risk assessment in Shaanxi, China. Environ Sci Pollut Res 2016; 23(14): 14560-6. ##25. Barki Vandi N, Sobhanardakani S, Cheraghi M. Health risk assessment of heavy metals (As, Al, Zn and Cu) in lemon balm and borage marketed in Hamedan City. J Sabzevar Univ Med Sci 2017; 24(4):265-71 (In Persian).##26. Kianpoor S, Sobhanardakani S. Health risk assessment of heavy metal concentrations in bread marketed in city of Hamedan. J Innov Food Sci Technol 2019; 11(3): 87-94 (In Persian).##27. Sobhanardakani S. Health risk assessment of As and Zn in canola and soybean oils consumed in Kermanshah, Iran. J Adv Environ Health Res 2016; 4(2): 62-7. ##28. Sobhanardakani S, Kianpour M. Heavy metal levels and potential health risk assessment in honey consumed in west of Iran. Avicenna J Environ Health Eng 2016; 3(2): e7795. ##29. Sobhanardakani S, Shiravand S, Jameh Bozorgi S. Health risk assessment of heavy metals (Cd, Cu, Pb and Zn) in soybean marketed in Hamedan City, Iran. Ann Mil Health Sci Res 2016; 14(3): e11464. ##30. Sobhanardakani S, Shahmoradi B, Jahangard A. Assessment of contents and health risk of aluminum and copper through consumption of commercial fruit juices. Ann Mil Health Sci Res 2017; 15(4): e68743. ##31. Ghafari HR, Sobhanardakani S. Contamination and health risks from heavy metals (Cd and Pb) and trace elements (Cu and Zn) in dairy products. Iran J Health Sci 2017; 5(3): 49-57. ##32. Sobhanardakani S. Tuna fish and common kilka: Health risk assessment of metal pollution through consumption of canned fish in Iran. J Consum Prot Food Saf 2017; 12(2): 157-63. ##33. Liang Y, Yi X, Dang Z, et al. Heavy metal contamination and health risk assessment in the vicinity of a Tailing Pond in Guangdong, China. Int J Environ Res Publ Health 2017; 14(12): 1557.##34. Mohammadi MJ, Yari AR, Saghazadeh M, et al. A health risk assessment of heavy metals in people consuming Sohan in Qom, Iran. Toxin Rev 2018; 37(4): 278-86. ##35. Sobhanardakani S. Analysis of contamination levels of Cu, Pb and Zn and population health risk via consumption of processed meat products. Jundishapur J Health Sci 2018; 10(1): e14059. ##36. Sobhanardakani S, Tayebi L, Hosseini SV. Health risk assessment of arsenic and heavy metals (Cd, Cu, Co, Pb, and Sn) through consumption of Caviar of Acipenser persicus from Southern Caspian Sea. Environ Sci Pollut Res 2018; 25(3): 2664-71. ##37. Abellan GB, de Santiago IG, Marquina AD, et al. Macroelements content in nougat, A traditional Spanish sweet. J Food Compos Anal 2000; 13: 265-73. ##38. Gopalani M, Shahare M, Ramteke DS, et al. Heavy metal content of potato chips and biscuits from Nagpur City, India. Bull Environ Contam Toxicol 2007; 79: 384-7.##39. Mohammadi P, Poursadeghiyan M, Yarmohammadi A, et al. Evaluation of lead and cadmium levels of Iranian and imported rice in Kermanshah, 2016 (Iran). Arch Hyg Sci 2018; 7(2): 106-111. ##40. Iwegbue CMA, Nwozo SO, Overah CL, et al. Concentrations of selected metals in some ready-to-eat-foods consumed in Southern Nigeria: Estimation of dietary intakes and target hazard quotients. Turk J Agri Food Sci Technol 2013; 1(1): 1-7. ##41. Salama AK, Radwan MA. Heavy metals (Cd, Pb) and trace elements (Cu, Zn) contents in some foodstuffs from the Egyptian market. Emir J Food Agr 2005; 17(1): 34-42.##42. Naqvi II, Saeed Q, Farrukh MA. Determination of trace metals (Co, Cu, Cd, Pb, Fe, Ni and Mn) in selected sweets of different shops of Karachi City by atomic absorption spectroscopy. Pak J Biol Sci 2004; 7(8): 1355-9.##43. Cuadrado C, Kumpulainens J, Carbajal A, et al. Cereals contribution to the total dietary intake of heavy metals in Madrid, Spain. J Food Compos Anal 2000; 13: 495-503. ##44. Ghasemkhani H, Sobhanardakani S, Cheraghi M. Health risk assessment of consumption of commercial fruit juices marketed in Hamedan City based on potential risk of Zn and Cd. J Neyshabur Univ Med Sci 2016; 4(2): 32-40 (In Persian).##45. Sobhanardakani S, Hosseini SV, Tayebi L. Heavy metals contamination of canned fish and related health implications in Iran. Turk J Fish Aquat Sci 2018; 18(8): 951-7. ##46. Karimi M, Tayebi L, Sobhanardakani S. Pb and Cd in medicinal plants (Case study: Shirazi thyme, sweet violet, pennyroyal and jujube). J Kermanshah Univ Med Sci 2016; 20(3): 111-6. ##47. Miri M, Akbari E, Amrane A, et al. Health risk assessment of heavy metal intake due to fish consumption in the Sistan region, Iran. Environ Monit Assess 2017; 189: 583. ##48. Sobhanardakani S. Human health risk assessment of Cd, Cu, Pb and Zn through consumption of raw and pasteurized cow's milk. Iran J Publ Health 2018; 47(8): 1172-80.## ##

تعیین مهمترین عوامل موثر بر عملکرد ایمنی کارگران در صنعت ساخت و ساز با استفاده از روش تحلیل سلسله مراتبی‌ (مطالعه موردی در یک نیروگاه سیکل ترکیبی) Evaluation of the Most Important factors Affecting the Safety Performance of Workers in the Construction Industry Using Hierarchical Analysis Method (Case Study in A Combined Cycle Power Plant) 1 1 زمینه و اهدف : ساخت و ساز یکی از پرخطرترین صنایع شناخته شده در دنیا می­باشد و بهبود ایمنی آنها یکی از دغدغه­های مسئولین این حوزه می باشد. این مطالعه با هدف بررسی علل رفتارهای ناایمن در نیروگاه  سیکل ترکیبی انجام شده است. روش کار: مطالعه توصیفی-تحلیلی و مقطعی حاضر با استفاده از پرسشنامه میان 300 نفر از کارگران نیروگاه سیکل ترکیبی صورت پذیرفت. سپس اطلاعات بدست آمده بصورت معیار و زیرمعیار تاثیرگذار بر علل رفتارهای ناایمن تقسیم بندی شد. معیارها و زیرمعیارها بصورت پرسشنامه مقایسه زوجی در بین 19 نفر از نفرات شاغل در حوزه ایمنی توزیع شد و از آنها خواسته شد بر اساس تجربیات و همچنین مقیاس فاصله­ای وزن­دهی کنند. معیارها و زیرمعیارها به روش تحلیل سلسله مراتبی (Analytic hierarchy process) (AHP) و با استفاده از نرم افرار Expert Choice‌ رتبه­بندی شد. یافته‌ها: نتایج نشان داد معیار ویژگی­های فردی با 34 ٪ امتیاز، موثرترین عامل در بروز رفتارهای ناایمن است. بعد از آن به ترتیب کارفرما (22 ٪)، آموزش (15 ٪)، تحصیلات (12 ٪)، تخصص و تجربه (8/7 ٪)، سن (6/7 ٪)، ویژگی­های شغل (3 ٪) و شرایط جوی (2 ٪) بر عملکرد ناایمن کارگران تاثیرگذار بوده­اند. نتیجه‌گیری: مهمترین زیرمعیار ویژگی­های فردی، استعداد حادثه پذیری افراد می­باشد. با مشخص کردن استعداد حادثه پذیری کارگران می­توان با به کار گماشتن افراد حادثه­پذیر در مشاغل کم­خطر­تر از بروز رفتارهای ناایمن جلوگیری کرد. 2        Background and objectives: Construction is one of the most dangerous industries in the world and one of the authorities’ concerns of officials in this area is to improve their safety. This study was carried out so as to investigate the causes of unsafe behaviors in a combined cycle power plant. Materials and Methods: In this cross-sectional study, a questionnaire for 300 workers of the combined cycle power plan were used. The obtained information was divided into criteria and sub-criteria affecting the causes of unsafe behaviors. Criteria and sub-criteria were distributed as a pairwise comparison questionnaire among 19 people who worked on the safety and they were supposed to answer based on their experiences as well as the distance scale. Criteria and sub-criteria were ordered by Analytic Hierarchy Process (AHP) and using Expert Choice‌ software. Results: the results showed that the criterion of individual characteristics (34 %) is the most effective factor for unsafe behaviors and followed by employer (22%), teaching 915%), education (12%), specialization and experience (7.8%), age (7.6%), job characteristics (3%), and weather condition (2%) respectively. Conclusion: the most important sub-criterion of individual characteristics is a one's susceptibility to accident. Hence, it is necessary to prevent unsafe behaviors by employing vulnerable people in less dangerous occupations.   63 73 2020/08/112020/08/152020/07/72020/07/222020/09/1 1399/6/11 2020/11/12020/10/312020/10/282020/09/192020/12/9 1399/9/19 محمد نوری سپهر Mohammad Noorisepehr مرکـــز تحقیقـــات بهداشـــت، ایمنـــی و محیط (RCHSE)، دانشگاه علـوم پزشـکی البرز، کرج، ایران - گروه مهندسی بهداشت محـیط، دانشـکده بهداشت، دانشگاه علوم پزشکی البرز، کرج، ایران ایران مهدی سالاری Mehdi Salari گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران ایران محمد درویش متولی Mohammad Darvishmotevalli مرکـــز تحقیقـــات بهداشـــت، ایمنـــی و محیط (RCHSE)، دانشگاه علـوم پزشـکی البرز، کرج، ایران ایران علیرضا بهشتی Alireza Beheshti گروه بهداشت، ایمنی و محیط زیست (HSE)، دانشکده بهداشت، دانشگاه علوم پزشکی زنجان، زنجان، ایران ایران Unsafe behavior Construction Hierarchical analysis Combined cycle power plant اعمال ناایمن ساخت و ساز تحلیل سلسله مراتبی نیروگاه سیکل ترکیبی 1. 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A research framework for investigating the relationship between safety climate and safety performance in the construction of multi-storey buildings in Pakistan. Procedia Eng 2015;118:581-9.##25. Asadi Z, Akbari H, Ghiyasi S, et al. Survey of unsafe acts and its influencing factors in metal smelting industry workers in Kashan in 2016. J Occup Health 2018;15(1):55-64.##26. Malchaire J. Occupational heat stress assessment by the Predicted Heat Strain model. Ind. Health 2006;44(3):380-7.## ##

بررسی خصوصیات پسماند شهرک‌های صنعتی اوره و شجاع آباد Investigation the Characteristics of Industrial Solid Waste in Ure and Shoja Abad 1 1 زمینه و هدف: نظر به توسعه صنعت در سالهای اخیر و اهمیت تولید پسماندهای صنعتی و خطرات ناشی از آن برای محیط زیست، آگاهی از کمیت و کیفیت پسماندها مسئله ای حائز اهمیت می‌باشد. بنابراین مطالعه حاضر نیز با هدف بررسی خصوصیات پسماند‌های تولیدی از واحدهای صنعتی اوره و شجاع آباد انجام شد. روش کار: این مطالعه به صورت توصیفی مقطعی در سال 1397 انجام شد. پرسشنامه ای جهت بررسی کمی و کیفی پسماندهای صنعتی استفاده شد. بدین منظور پس از مراجعه به واحدهای صنعتی و تکمیل پرسشنامه ها، داده‌ها مورد تجزیه و تحلیل قرار گرفت و وضعیت پسماندهای صنعتی مشخص گردید. یافته‌ها: مقدار کل پسماند تولیدی در شهرک صنعتی اوره و شجاع آباد به ترتیب 59730 و 168620 تن در سال می‌باشد. پسماندهای حاصل از کانی‌های غیر فلزی بالاترین میزان کل پسماند تولیدی به میزان به ترتیب 29460و 151490 تن در سال را در شهرک‌های اوره و شجاع آباد به خود اختصاص داده اند. بازیافت در محل در صنایع شهرک‌های اوره و شجاع آباد به ترتیب با میزان 74/1212 و 91/434 تن در سال عمده ترین روش مدیریت پسماند را به خود اختصاص داده است. نتیجه‌گیری: مطابق نتایج به دست آمده، روش غالب دفع پسماند تولیدی صنایع، بازیافت در محل می‌باشد. کانی‌های غیر فلزی به میزان بیشتری نسبت به سایر پسماند تولیدی در شهرک‌های صنعتی اوره و شجاع آباد در فرآیند تولید مورد استفاده و بازیافت قرار می‌گیرند. 2 Background & Objective: Considering the development of industries and the importance of industrial waste production and its environmental hazards, it is important to survey the quantity and quality of waste. Therefore, the present study was conducted with the aim of properties investigation of waste produced from industrial units in Ure and Shoja Abad. Materials and Methods: This descriptive cross-sectional study was performed in 2018. A questionnaire was used for quantitative and qualitative survey of industrial waste. For this purpose, after referring to the industrial units and completing the questionnaires, the data were analyzed to determine the status of industrial waste. Results: A total of 59730 and 168620 tons per year of industrial waste are respectively produced in Ure and Shoja Abad. Waste from non-metallic minerals has the highest amount of total production waste at 29460 and 151490 tons per year in Ureh and Shoja Abad, respectively.On-site recycling in the industries of Urea and Shoja Abad towns with 1212.74 and 434.91 tons per year, respectively, is the main method of waste management. Conclusion: According to the results the main method of industrial waste management is on-site recycling. Non-metallic minerals are used and recycled in the production process to a greater extent than other production wastes in Urea and Shojaabad industrial plants. 74 82 2020/08/112020/08/152020/07/72020/07/222020/09/12020/06/18 1399/3/29 2020/11/12020/10/312020/10/282020/09/192020/12/92020/11/5 1399/8/15 حسین موحدیان عطار Hossein Movahedian Attar گروه مهندسی بهداشت محیط، دانشکده بهداشت مرکز تحقیقات محیط زیست، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران ایران مریم مرادنیا Maryam Moradnia کمیته تحقیقات دانشجویی، دانشکده بهداشت، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران ایران حمیدرضا پورزمانی Hamid Reza Pourzamani گروه مهندسی بهداشت محیط، دانشکده بهداشت مرکز تحقیقات محیط زیست، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران ایران مجید هاشمی Majid Hashemi کمیته تحقیقات دانشجویی، دانشکده بهداشت، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران ایران فاطمه نجفی Fatemeh Najafi گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی کرمان، کرمان، ایران ایران فاطمه محمدی خواه Fatemeh Mohammadi khah گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی کرمان، کرمان، ایران ایران Industrial waste hazardous waste quantitative qualitative investigation زباله‌های صنعتی زباله‌های خطرناک خصوصیات کمی و کیفی 1. Abdoli MA. Municipal solid waste management in south coastline of the Caspian Sea. Environ Health 2007;70:34-7. [in Persian]##2. Karami M, Farzadkia M, Jonidi A, Nabizadeh R, Gohari M, Karimaee M. Quantitative and qualitative investigation of industrial solid waste in industrial plants located between Tehran and Karaj. Iran Occup Health 2011;8(2):12-0. [in Persian]##3. Rhyner CR, Schwartz LJ, Wenger RB, Kohrell MG. Waste management and resource recovery: CRC Press; 2017.##4. Lara ER, De la Rosa JR, Castillo AIR, de Jesús Cerino-Córdova F, Chuken UJL, Delgadillo SSF, et al. A comprehensive hazardous waste management program in a Chemistry School at a Mexican university. J Clean Prod 2017;142:1486-91.##5. Waste FH. Hazardous waste management. 2018.##6. Blackman Jr WC. Basic hazardous waste management: Crc Press; 2016.##7. Casares M, Ulierte N, Mataran A, Ramos A, Zamorano M. Solid industrial wastes and their management in Asegra (Granada, Spain). Waste Manage 2005;25(10):1075-82.##8. Nabizadeh R. Qualification of hazardous solid waste in Esfahan [dissertation]. Tehran: Tehran University of Medical Sciences. 1994. [in Persian]##9. M.Feyzipour, M.Dehghani, Karbasi AR. Qualitative and quantitative classification of industrial waste in the number two industry town of Bandar Abbas. The First Conference on Health, Environment & Sustainable Development; 10 March; Bandar Abbass, Iran; 2010:1 ##10. Shahbazi A, Soffianian AR. Investigating the Quantitative and Qualitative Characteristics and Management of Industrial Waste in Industrial Units of Isfahan Province. Environ Dev J 2015;11:13-18. [in Persian]##11. Abedinzadeh F, Monavari S. Study of solid waste management in industrial estate of Rasht. 2007.[in Persian]## ##

مدل سازی و بهینه سازی جذب متیلن بلو از محیط‌های آبی توسط پامیس براساس روش‌های RSM-CCD و ANN-GA Modeling and Optimization of Methylene Blue Adsorption from Aqueous Solution by Pumice Based on RSM-CCD and ANN-GA Methods 1 1 زمینه و هدف: تخلیه حجم بالایی از فاضلاب‌های رنگی به منابع آب پذیرنده سبب نگرانی‌های گسترده ای در سرتاسر جهان شده است. هدف این مطالعه، بررسی کارایی جاذب پامیس در حذف متیلن بلو (MB) از محلول‌های آبی می باشد. همچین فرآیند جذب توسط روش‌های سطح پاسخ-طراحی مرکب مرکزی (RSM-CCD) و شبکه عصبی مصنوعی- الگوریتم ژنتیک (ANN-GA) مدل‌سازی و بهینه‌سازی شد. روش کار: پارامترهای ورودی به مطالعه شامل pH (3-11)، زمان تماس ( 10-50 دقیقه)، دوز جاذب (2/0-1 گرم در لیتر) و غلظت MB (20-100 میلی گرم در لیتر) بود. اثر این پارامترها بر کارایی پامیس در جذب MB توسط روش‌های RSM-CCD و ANN-GA مدل سازی و بهینه سازی شد. جهت سنجش غلظت باقی مانده MB در محلول از دستگاه اسپکتروفتومتر در طول موج 620 نانومتر استفاده شد. یافته‌ها: نتایج نشان داد که روش RSM-CCD قابلیت توسعه مدل چند جمله درجه دوم با اعتبار بالا (9997/0 = R2) برای فرآیند جذب دارد. بطور مشابه روش ANN-GA به خوبی با دیتا آزمایشگاهی برای توسعه مدل با اعتبار بالا (9978/0 = R2) فیت شد. نتایج بهینه سازی فرآیند توسط روش‌های RSM-CCD و ANN-GA، بالاترین راندمان جذب را در 11 = pH، زمان = 50 دقیقه، دوز جاذب = 1 گرم در لیتر و غلظت MB = 20 میلی گرم در لیتر نشان داد. راندمان جذب با pH، زمان تماس و دوز جاذب ارتباط مستقیم و با غلظت آلاینده رابطه عکس نشان داد. اثر خطی متغیرهای غلظت آلاینده و دوز جاذب بیشترین تاثیر را بر کارایی جذب داشتند. نتیجه‌گیری: در این مطالعه مشاهده شد که پامیس بعنوان جاذب ارزان قیمت و در دسترس می تواند بعنوان گزینه مناسبی جهت جذب آلاینده‌های رنگی از محیط‌های آبی در نظر گرفته شود. همچنین می توان از دو روش RSM-CCD و ANN-GA جهت مدل سازی و بهینه سازی فرآیند‌های جذب استفاده نمود. 2   Background: The discharge of a large volume of colored wastewater into receiving water sources has caused widespread concern around the world. The aim of this study was to investigate the efficiency of pumice as an adsorbent in removing methylene blue (MB) from aqueous solution. The adsorption process was also modeled and optimized by the methods as follows: central composite design-central composite design (RSM-CCD) and artificial neural network-genetic algorithm (ANN-GA). Methods and Materials: The independent variables in the study were included pH (3-11), contact time (10-50 minutes), adsorbent dose (0.1-2 g/L), and MB concentration (20-100 mg/l). The effect of these parameters on the efficiency of pumice in MB uptake was modeled and optimized by RSM-CCD and ANN-GA methods. A spectrophotometer at 620 nm was used to measure the residual MB concentration in solution. Results: The results showed that the RSM-CCD method has the ability to develop a quadratic polynomial model with high validity (R2 = 0.9997) for the adsorption process. Similarly, the ANN-GA method fitted well with experimental data to develop a model with high validity (R2 = 0.9978). The results of optimization process by RSM-CCD and ANN-GA methods obtained the highest adsorption efficiency at pH = 11, contact time = 50 minutes, adsorbent dose = 1 g/L, and concentration MB = 20 mg/L. Adsorption efficiency shows a direct relationship with pH, contact time and adsorbent dose and inversely with contaminant concentration. The linear effect of pollutant concentration and adsorbent dose variables had the greatest effect on adsorption efficiency. Conclusion: In this study, it was observed that pumice as a cheap and available adsorbent can be considered as a suitable choice for absorbing dye pollutants from aqueous media. RSM-CCD and ANN-GA methods can also be used to model and optimize adsorption processes. 83 98 2020/08/112020/08/152020/07/72020/07/222020/09/12020/06/182020/08/3 1399/5/13 2020/11/12020/10/312020/10/282020/09/192020/12/92020/11/52020/12/7 1399/9/17 قربان عسگری Ghorban Asgari گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران ایران محمد درویش متولی Mohammad Darvishmotevalli مرکـــز تحقیقـــات بهداشـــت، ایمنـــی و محیط (RCHSE)، دانشگاه علـوم پزشـکی البرز، کرج، ایران ایران علیرضا بهشتی Alireza Beheshti گروه بهداشت، ایمنی و محیط زیست (HSE)، دانشکده بهداشت، دانشگاه علوم پزشکی زنجان، زنجان، ایران ایران مهدی سالاری Mehdi Salari گروه مهندسی بهداشت محیط، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران ایران Methylene blue Pumice Adsorption Aqueous solution متیلن بلو پامیس جذب محیط‌های آبی 1. Sharifpour E, Ghaedi M, Nasiri Azad F, et al. Zinc oxide nanorod‐loaded activated carbon for ultrasound‐assisted adsorption of safranin O: Central composite design and genetic algorithm optimization. Appl Organomet Chem 2018;32(2):4099.##2. Huang T, Yan M, He K, et al. Efficient removal of methylene blue from aqueous solutions using magnetic graphene oxide modified zeolite. J Colloid Interface Sci 2019;543:43-51.##3. Gao H, Zhao S, Cheng X, et al. Removal of anionic azo dyes from aqueous solution using magnetic polymer multi-wall carbon nanotube nanocomposite as adsorbent. Chem Eng J 2013;223:84-90.##4. Mikac L, Marić I, Štefanić G, et al. Radiolytic synthesis of manganese oxides and their ability to decolorize methylene blue in aqueous solutions. Appl Surf Sci 2019;476:1086-95.##5. Chan YJ, Chong MF, Law CL, et al. A review on anaerobic–aerobic treatment of industrial and municipal wastewater. Chem Eng J 2009;155(1-2):1-18.##6. Tuppurainen K, Asikainen A, Ruokojärvi P, et al. Perspectives on the formation of polychlorinated dibenzo-p-dioxins and dibenzofurans during municipal solid waste (MSW) incineration and other combustion processes. Acc Chem Res 2003;36(9):652-8.##7. Daneshvar N, Khataee A. Removal of azo dye CI acid red 14 from contaminated water using Fenton, UV/H2O2, UV/H2O2/Fe (II), UV/H2O2/Fe (III) and UV/H2O2/Fe (III)/oxalate processes: a comparative study. J Environ Sci Heal A 2006;41(3):315-28.##8. Tyagi VK, Lo S-L. Application of physico-chemical pretreatment methods to enhance the sludge disintegration and subsequent anaerobic digestion: an up to date review. Rev Environ Sci Biotechnol 2011;10(3):215.##9. Ranjan D, Talat M, Hasan S. Biosorption of arsenic from aqueous solution using agricultural residue ‘rice polish’. J Hazard Mater 2009;166(2-3):1050-9.##10. Sulaymon AH, Mohammed AA, Al-Musawi TJ. Removal of lead, cadmium, copper, and arsenic ions using biosorption: equilibrium and kinetic studies. Desalin Water Treat 2013;51(22-24):4424-34.##11. Sepehr MN, Allani F, Zarrabi M, et al. Dataset for adsorptive removal of tetracycline (TC) from aqueous solution via natural light weight expanded clay aggregate (LECA) and LECA coated with manganese oxide nanoparticles in the presence of H2O2. Data Brief 2019;22:676-86.##12. Mansourian N, Javedan G, Darvishmotevalli M, et al. Efficiency evaluation of zeolite powder, as an adsorbent for the removal of nickel and chromium from aqueous solution: isotherm and kinetic study. J Chem Technol Biotechnol 2016;8(2):13891-907.##13. Zazouli MA, Balarak D, Mahdavi Y, et al. Adsorption rate of 198 reactive red dye from aqueous solutions by using activated red mud. Iran J Med Sci 2013;1(1):36-43 [In persian].##14. Samarghandi MR, Tarlaniazar M, Mehranpoor R, et al. Survey the Efficiency of Iron-Coated pumice in Fluoride Removal from Aqueous Solutions. J Environ Health Sci 2015;2(2):128-40 [In persian].##15. Kitis M, Kaplan S, Karakaya E, et al. Adsorption of natural organic matter from waters by iron coated pumice. Chemosphere 2007;66(1):130-8.##16. Mohammadi H, Alinejad A, Khajeh M, et al. Optimization of the 3D electro‐Fenton process in removal of acid orange 10 from aqueous solutions by response surface methodology. J Chem Technol Biotechnol 2019;94(10):3158-71.##17. Osouleddini N, Heydari M, Motevalli MD, et al. Application of artificial neural networks and response surface methodology for analysis of malachite green removal from aqueous solution using phosphoric acid–modified pumice powder: kinetic and isotherm studies. Desalin Water Treat 2020;178:296-311.##18. Shokoohi R, Salari M, Safari R, et al. Modelling and optimisation of catalytic ozonation process assisted by ZrO2-pumice/H2O2 in the degradation of Rhodamine B dye from aqueous environment. Int J Environ Anal Chem 2020:1-25.##19. Darvishmotevallia M, Salarib M, Moradniaa M, et al. Evaluation of magnetic ZSM-5 composite performance in 2, 4 dichlorophenol removal from synthetic solutions: response surface method (RSM) modeling and isotherm, kinetic and thermodynamic studies. Desalin Water Treat 2019;164:249-62.##20. Asgari G, Shabanloo A, Salari M, et al. Sonophotocatalytic treatment of AB113 dye and real textile wastewater using ZnO/persulfate: Modeling by response surface methodology and artificial neural network. Environ Res 2020:109367.##21. El Qada EN, Allen SJ, Walker GM. Adsorption of methylene blue onto activated carbon produced from steam activated bituminous coal: a study of equilibrium adsorption isotherm. Chem Eng J 2006;124(3):103-10.##22. Derakhshan Z, Baghapour MA, Ranjbar M, et al. Adsorption of methylene blue dye from aqueous solutions by modified pumice stone: kinetics and equilibrium studies. Health Scope 2013;2(3):136-44.##23. Sarı A, Tuzen M. Equilibrium, thermodynamic and kinetic studies on aluminum biosorption from aqueous solution by brown algae (Padina pavonica) biomass. J Hazard Mater 2009;171(1-3):973-9.##24. Qadri S, Ganoe A, Haik Y. Removal and recovery of acridine orange from solutions by use of magnetic nanoparticles. J Hazard Mater 2009;169(13):318-23.##25. Wu J, Yu H-Q. Biosorption of 2, 4-dichlorophenol from aqueous solution by Phanerochaete chrysosporium biomass: Isotherms, kinetics and thermodynamics. J Hazard Mater 2006;137(1):498-508.## ##

بررسی مقطعی روند تغییرات کیفی آب دریاچه سد کلان ملایر (مطالعه موردی : 1397-1396) Cross-Sectional Study of Water Quality Changes in Lake of Kalan Malayer Dam (Case Study: 2017-2018) 1 1 زمینه و هدف: استفاده بهینه از منابع آب در دسترس، محافظت و ‌‌‌‌‌‌‌‌‌‌‌‌پایش منابع آب امری ضروری و حیاتی می‌باشد. هدف این مطالعه بررسی تغییرات کیفی آب در دریاچه سد کلان شهر ملایر در استان همدان در طول سال 1396-1397 بوده است. مواد و روش‌ها: با استفاده از نرم‌افزار GIS و نقشه‌های کاربری اراضی، محل‌های دقیق نمونه برداری در دریاچه سد انتخاب شدند. در نمونه‌های گرفته شده از فصول مختلف پارامترهای pH و EC و غلظت Ca, Mg, Cl, SO4, PO4, NO3, TDS, TSS, DO, BOD, COD, TOC, و کدورت و همچنین غلظت سموم کشاورزی رایج استفاده شده در منطقه، اندازه‌گیری شد. یافته‌ها: نتایج تحقیق نشان داد که مطابق با رهنمون WHO، کدورت در اردیبهشت ماه و هدایت الکتریکی، BOD و COD در کل زمان‌های نمونه‌برداری، برای مصارف شرب محدودیت ایجاد می‌کنند. میانگین غلظت BOD و COD در ایستگاه‌های ورودی آب به سد بیشتر بود و از میانگین غلظت آن‌ها در دریاچه و ایستگاه‌های نزدیک دیواره سد کاسته شد که دلیل اصلی این پدیده به تخلیه و راه‌یابی آلاینده‌ها در بالادست رودخانه که سبب افزایش میزان اکسیژن‌خواهی زیست شیمیایی و اکسیژن خواهی شیمیایی می‌شود، ارتباط دارد. مقدار نوترینت‌ها (NO3, Cl, SO4, Na) در تمامی نمونه‌ها در محدوده غلظت مجاز تعیین شده توسط WHO قرار داشت. نتیجه‌گیری: آب در فصل زمستان به دلیل افزایش حجم دبی رودخانه و آب ذخیره شده در پشت سد، کاهش دما و کاهش فعالیت‌های کشاورزی، از کیفیت مطلوب‌تری برخوردار بوده است. 2   Background: Using available water resources, protection and monitoring of water resources is essential and vital. The aim of this study was to investigate the changes in water quality in Lake of Kalan Malayer Dam in Hamedan province during the year 2017-2018. Methods: Using GIS software and land use maps, sampling locations in the dam lake were selected. In samples was carried out on 5 occasions, pH, EC, Ca, Mg, Cl, SO4, PO4, NO3, TDS, TSS, DO, BOD, COD, TOC, Turbidity and concentration of common pesticides used in the area were measured. Results: The results showed that according to WHO guidline, turbidity in May and electrical conductivity, BOD and COD in all sampling times, limit the consumption of drinking water. The average concentration of BOD and COD was higher in the primary stations and decreased from the average concentration in the lake and stations near the dam wall, that be related to the discharge and route of pollutants upstream of the river, which increases the amount of biochemical and chemical oxygen demand. Nutrient concentrations (NO3, Cl, SO4 and Na) in all samples were within the allowable range determined by WHO. Conclusion: Water in winter was of better quality due to increased river flow and water stored behind the dam, lowering the temperature and reducing agricultural activities. 99 116 2020/08/112020/08/152020/07/72020/07/222020/09/12020/06/182020/08/32020/07/6 1399/4/16 2020/11/12020/10/312020/10/282020/09/192020/12/92020/11/52020/12/72020/12/7 1399/9/17 بهاره لرستانی Bahare Lorestani دانشیار گروه محیط زیست، دانشگاه آزاد اسلامی واحد همدان، همدان، ایران ایران هاجر مریخ پور Hajar Merrikhpour استادیار علوم خاک، گروه کشاورزی، دانشگاه سید جمال الدین اسدآبادی، اسدآباد، ایران ایران مهرداد چراغی Mehrdad Cheraghi دانشیار گروه محیط زیست، دانشگاه آزاد اسلامی واحد همدان، همدان، ایران ایران Dam Lake Water quality Dissolved Oxygen Total Dissolved Solids دریاچه سد؛ کیفیت آب؛ اکسیژن محلول؛ غلظت کل جامدات محلول 1.Erfanmanesh MA, M. Environmental Pollution (Water, Soil, and Air). 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