Mathematical modeling and sensitivity analysis of xylene removal in a scoria‐compost biofilter. Issue 6 (17th April 2019)

• Record Type: Journal Article
• Authors: Heidari, Mohsen; Rahimi, Amir; Amin, Mohammad M.; Bina, Bijan; Sami, Samaneh; Nourmoradi, Heshmatollah; Mohammadi‐moghadam, Fazel; Norouzi, Samira
• Is Part Of: Environmental progress & sustainable energy. Volume 38:Issue 6(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-17
• Subjects: biofilter -- mathematical modeling -- sensitivity analysis -- xylene; Environmental engineering -- Periodicals; Sustainable engineering -- Periodicals; Environmental chemistry -- Periodicals; 333.7
• DOI: 10.1002/ep.13235
• Languages: English
• ISSNs: 1944-7442

Abstract

Abstract: Mathematical modeling of biofiltration systems improves our understanding and design of such complex systems. This study focused on the theoretical and technical aspects of the modeling of xylene biofiltration in the absence and presence of a nonionic surfactant. In this regard, a mathematical model was developed based on mass balance principles in gas and biofilm phases. The developed model was calibrated and validated using the experimental data obtained from a lab‐scale scoria‐compost biofilter, which operated for 151 days in the absence and presence of Tween‐20, a nonionic surfactant. First, the model was calibrated using the experimental data obtained at empty bed retention time (EBRT) of 90 s and then validated with the data obtained at two other EBRTs. The biofilter provided maximum elimination capacities (ECmax ) of 97.5 and 93.6 g m −3 hr −1, respectively, in the absence and presence of the surfactant at EBRT of 90 s. The corresponding predicted ECmax values were 99.9 and 95.7 g m −3 hr −1, respectively. Both model output and experimental data revealed that the nonionic surfactant improved the performance of the biofilter at moderate inlet loading rates. Various statistical measures, including fractional bias, average absolute relative error, and coefficient of determination ( R 2 ), showed good agreement between experimental data and estimated model predictions. Sensitivity analysis of the model showed that the specific surface area and bioreactor length affected strongly the results of the model. In general, the results of this study would in turn form the design basis for engineering purposes.