Optimizing Wastewater Treatment Efficiency at North Esfahan WWTP Using GPS-X Simulation: Enhancing Aeration Strategies

سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: فارسی
مشاهده: 20

فایل این مقاله در 19 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_WWJ-35-6_001

تاریخ نمایه سازی: 25 مهر 1404

چکیده مقاله:

This study utilizes GPS-X simulation software to enhance the wastewater treatment processes at the North Esfahan Wastewater Treatment Plant, which handles an average inflow of ۴۴,۰۰۰ m³/day. The facility utilizes a conventional activated sludge aeration process, and this research focuses on improving effluent quality through optimized aeration strategies and effective management of dissolved oxygen levels. GPS-X software was used to model the aeration process, adjusting kinetic and stoichiometric parameters, such as heterotrophic yield, to match the plant’s wastewater characteristics. The aeration tank was divided into four sections to simulate various air distribution scenarios, including dynamic DO control and creating anoxic zones for denitrification. Sensitivity analysis identified key parameters, and the model was calibrated using real operational data. Fourteen aeration scenarios were tested to evaluate their impact on treatment efficiency. Key findings indicate that the treatment system is particularly sensitive to heterotrophic yield, with kinetic and stoichiometric parameters adjusted from an initial value of ۰.۶۶ to ۰.۷۵ to align the model with the specific wastewater characteristics. The study emphasizes the significance of dynamic aeration control and the establishment of anoxic zones to facilitate denitrification, which ultimately enhances effluent quality. The research revealed that achieving a uniform DO distribution in the aeration tank significantly boosted overall treatment efficiency, with chemical oxygen demand and total suspended solids removal rates reaching ۹۲% and ۹۳%, respectively. In other words, COD decreases from ۶۹۱ to ۵۹ mg/L and TSS decreases from ۳۳۶ to ۲۵ mg/L. Furthermore, the introduction of an anoxic zone within the aeration process proved effective for denitrification, reducing total nitrogen in the effluent to ۳۵ mg/L, compared to ۴۲ mg/L in the current condition (with an influent TN of ۸۷ mg/L). Furthermore, the study highlights the significant impact of influent quality fluctuations and temperature variations on wastewater treatment performance. Sensitivity analyses under optimal aeration conditions showed that a ±۱۰% change in influent COD and TSS concentrations directly affects effluent quality, with COD increasing to ۱۱۰ mg/L and TSS rising to ۶۳ mg/L during a ۱۰% shock. This research highlights the potential of simulation tools like GPS-X in optimizing wastewater treatment operations, providing valuable insights for enhancing environmental sustainability and public health. Future studies are encouraged to explore additional operational variables and their effects on treatment efficiency, thereby promoting sustainable practices in wastewater management throughout Iran.

نویسندگان

محمدرضا فدائی تهرانی

Assist. Prof. and Faculty Member, Esfahan Higher Education and Research Complex, Niroo Research Institute (NRI), Isfahan, Iran

میلاد ایرج پور

MSc. Student in Environmental Civil Engineering at Daneshpajoohan Pishro University, Isfahan, Iran

محبوبه سیدبرزانی

Postgraduate in Civil Engineering-Environmental, Isfahan University of Technology (IUT), Isfahan, Iran

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Aguilar, M. I., Lloréns, M., Fernández-Garrido, J. M., Pérez-Marín, A. ...
  • Akter, J., Lee, J. and Kim, I., ۲۰۲۲. A fixed-film ...
  • Insel, G., Güder, B., Güneş, G. and Ubay Cokgor, E., ...
  • Kandare, G. and Nevado Reviriego, A., ۲۰۱۱. Adaptive predictive expert ...
  • نمایش کامل مراجع