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Modeling removal of volatile sulfur compounds in a full‐scale biological air filter
Author(s) -
Liu Dezhao,
Feilberg Anders,
Hansen Michael Jørgen,
Pedersen Claus Lunde,
Nielsen Anders Michael
Publication year - 2016
Publication title -
journal of chemical technology and biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 117
eISSN - 1097-4660
pISSN - 0268-2575
DOI - 10.1002/jctb.4696
Subject(s) - methanethiol , biofilter , chemistry , sulfur , biodegradation , filter (signal processing) , mass transfer coefficient , mass transfer , partition coefficient , environmental chemistry , environmental science , biological system , chromatography , environmental engineering , organic chemistry , computer science , computer vision , biology
BACKGROUND H 2 S and methanethiol, which are important odorants from pig facilities, were unsatisfactorily removed in field biological air filters with short residence time. For a better understanding of the process, this study established a dynamic model for simulation of H 2 S and methanethiol removal in a three‐stage biological air filter (two stages of biotrickling filter and one stage of biofilter), based on experimental determined mass transfer coefficients and partition coefficients from previous studies. RESULTS The maximum biodegradation rates for both H 2 S and methaetniol were estimated to be relatively low, with differences observed for different stages. Further, H 2 S removal was also observed to be limited by mass transfer, while other parameters such as active water content, biofilm thickness and diffusion coefficient were also shown to affect model performance, indicating the relevance of proper estimation of these parameters. For methanethiol, on the other hand, the model is mainly limited by maximum biodegradation rate. CONCLUSION Overall, the established model can properly simulate the performance of the field biological air filter for the removal of volatile sulfur compounds. Calibration of model parameters in field conditions may further improve the model precision and robustness for predicting performance of the field biological air filter. © 2015 Society of Chemical Industry