مدل‌سازی سینتیکی حذف آلاینده سولفید در بیوراکتور لجن فعال با حضور نانوذرات سیلیکا و گرافن اکساید

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه مهندسی شیمی، دانشکده مهندسی شیمی و مواد، دانشگاه صنعتی شاهرود، شاهرود، ایران

2 کارشناس، گروه مهندسی شیمی، دانشکده مهندسی شیمی و مواد، دانشگاه صنعتی شاهرود، شاهرود، ایران

چکیده

امروزه حضور ترکیبات گوگردی در محیط آبی به‌دلیل سمیّت زیاد آنها به یکی از مخاطرات جدی محیط‌زیستی تبدیل شده است. از‌این‌رو انتخاب و ارزیابی یک روش مناسب و کارآمد به‌منظور کاهش یا حذف این آلاینده‌ها امری ضروری است. در این پژوهش، به‌منظور بررسی و پیش‌بینی حذف بیولوژیکی آلاینده سولفید، یک مقایسه جامع بین مدل‌های سینتیک رشد مخصوص زیست‌توده در بیوراکتورهای مختلف انجام شد. برای این کار سه نوع سیستم بیوراکتور شامل لجن فعال بدون حضور نانوذره، در حضور نانوذرات سیلیکا و نانوصفحات گرافن اکساید استفاده شد. آزمایش‌های فرایند ناپیوسته برای بررسی اثر غلظت‌های مختلف آلاینده سولفید بر روی سرعت رشد مخصوص زیست‌توده و همچنین بررسی رشد زیست‌توده در طی 14 روز برای هر سه نوع سیستم بیوراکتور انجام شد. علاوه بر آن، مدل‌های سینتیکی مختلفی از جمله معادلات مونود، هالدان، اندرو و نواک، یانو و کوگا و وب توسط داده‌های آزمایشگاهی به‌دست آمده در فرایند ناپیوسته رشد لجن فعال مقایسه شدند. مطابق نتایج به‌دست آمده بیشینه سرعت رشد مخصوص برای سیستم‌های بیوراکتور EM، SS و GO به‌ترتیب برابر با 1817/0، 1667/0 و 1277/0 1-روز بود. مدل سینتیک غیرخطی یانو و کوگا با ضرایب تعیین 954/0، 965/0 و 941/0 به‌ترتیب برای بیوراکتور EM، SS و GO، نسبت به سایر مدل‌ها برازش بهتری از داده‌های سرعت رشد مخصوص در سراسر محدوده غلظت سولفید را ارائه داد. همچنین تحلیل توابع خطاهای مختلف SSE، ARE، HYBRID و MPSD نشان داد که بیوراکتور لجن فعال حاوی نانوذرات SiO2 نسبت به سایر سیستم‌ها بهترین عملکرد را دارد. توسعه و استفاده از این مدل‌های سینتیکی و روش‌های پیش‌بینی‌کننده به‌دلیل تحلیل‌پذیری و بررسی پارامترهای عملیاتی مؤثر در فرایند حذف بیولوژیکی آلاینده‌ها می‌تواند بسیار مفید و کارآمد باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Kinetic Modeling of the Sulfide Pollutant Removal in the Activated Sludge Bioreactor in the Presence of Silica Nanoparticles and Graphene Oxide

نویسندگان [English]

  • Jafar Abdi 1
  • Seyyed Hamid Esmaeili-Faraj 1
  • Ehsan Naghdbishi 2
1 Assist. Prof., Dept. of Chemical Engineering, Faculty of Chemical and Materials Engineering, Shahrood University of Technology, Shahrood, Iran
2 BSc., Dept. of Chemical Engineering, Faculty of Chemical and Materials Engineering, Shahrood University of Technology, Shahrood, Iran
چکیده [English]

Nowadays, the presence of sulfurous compounds in aqueous media has become one of the most serious risks due to their high toxicity. Therefore, selecting and assessing a suitable and efficient method for decreasing or eliminating these pollutants is a vital issue. In this study, a comprehensive comparative analysis among various specific growth kinetic models of biomass were carried out to investigate the biological removal of sulfide pollutant in different bioreactors. For this aim, three types of bioreactor systems, including activated sludge without nanoparticles, in the presence of silica nanoparticles, and graphene oxide nanosheets were employed. Batch process experiments were performed to investigate the effect of different concentration of sulfide pollutant on the specific growth rates of biomass and also to study the growth of biomass during 14 days for all three bioreactor systems. Moreover, different biokinetic models, such as Monod, Haldane, Andrews and Noack, Yano and Koga and Webb were compared using obtained experimental data in a batch activated sludge process. According to the results, the maximum specific growth rates of EM, SS and GO bioreactor systems were mmax= 0.1871, 0.667, and 0.1277/ day-1, respectively. The Yano and Koga kinetic model had better fit with the experimental specific growth rate data than the other models thorough sulfide concentrations ranges with the correlation coefficients (R2) of 0.954 0.965 and 0.941 for EM, SS and GO bioreactor systems, respectively. In addition, the analysis of different error functions including, SSE, ARE, HYBRID and MPSD, showed that the bioreactor containing SiO2 nanoparticles has the best performance towards the other systems. Development and using these kinetic models and predictive methods can be considerably useful and efficient due to their analyzability and investigation of different operational parameters in the biological process of pollutants removal.

کلیدواژه‌ها [English]

  • Activated Sludge System
  • Bio-Kinetic Modelling
  • Sulfide Removal
  • Silica Nanoparticle
  • graphene oxide
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