Comparison of Regression Model and Modified Monod kinetic Model to Predict the Removal of Formaldehyde in Trickling Biofilter

Author(s):
Abstract:
Introduction
Formaldehyde is a toxic, mutagen and probably carcinogen compound that can be released to air by world different industries. The present study aimed to investigate the kinetic parameters of a trickling bio-filter as well as to present a simple regression model.
Methods
The data of previous studies on formaldehyde vapor removal by bio-trickling filter in a laboratory scale was used to determine rmax and Km. Moreover, the data were applied to develop a simple regression model.
Results
Formaldehyde removal efficiency in different input concentrations was predicted by both regression and kinetic models. All results were compared with actual data in the pilot study.
Conclusion
The results of the present study revealed that although regression model has a high precision, it only could predict the mean of bio-filter efficiency in formaldehyde removal. Kinetic model demonstrated some extent of error in predicting, though it has a good alignment with the actual data, and thus, the results of this model can approximately predict ups and downs of system navigation.
Language:
Persian
Published:
Tolooe Behdasht, Volume:15 Issue: 1, 2016
Pages:
198 to 207
magiran.com/p1550752  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!