A high performance biological degradation of trimethylamine: Experimental study and mathematical modeling. Issue 5 (October 2019)

• Record Type: Journal Article
• Authors: Raj, Ishan; Gupta, Ankit; Pandharipande, S.L.; Bansiwal, Amit; Vaidya, A.N.
• Is Part Of: Journal of environmental chemical engineering. Volume 7:Issue 5(2019)
• Publication Date: 2019-10
• Subjects: Trimethylamine -- Biodegradation -- Biotrickling filter -- Shock loads -- Response surface method and artificial neural network; Chemical engineering -- Environmental aspects -- Periodicals; Environmental engineering -- Periodicals; Chemical engineering -- Environmental aspects; Environmental engineering; Periodicals; 660.0286
• DOI: 10.1016/j.jece.2019.103292
• Languages: English
• ISSNs: 2213-2929

Abstract

Graphical abstract: Highlights: A continuous packed bed filter shows good performance at high TMA loading rate. Filter bed undergoes different shock loads and shows a good resilience capacity. A maximum of 100% removal efficiency was observed by Ochrobactrum and Agromyces sp. Highest elimination capacity of 175.2 g m −3 h -1 was achieved. RSM and ANN models have shown a good fit with experimental data. Abstract: A bench scale Biotrickling filter (BTF) packed with polyurethane foam seeded with potential TMA degrading bacterial strains ( Agromyces and Ochrobactrum sp.) was tested to eliminate TMA from ambient air. BTF was functioned constantly for a period of 125 days at retention time of 180 s and 90 s corresponding to the different loading rate of 14.4–232 g m −3 h -1 . The maximum elimination capacity attained in the study was 160 g m −3 h -1 with the removal efficiency above 95%. Low, medium and high shock loads of higher concentration were applied to the BTF during the operational period. The BTF has recuperated its performance after each shock loads which shows its good resilience capacity. The performance of the BTF was modeled first time using RSM and ANN algorithm to predict the outlet concentration, elimination capacity and removal efficiency of TMA. Both the algorithm can efficiently be employed to model the BTF performance for degrading TMA.