4. Biofilters

  1. Christian Kennes and
  2. María C. Veiga
  1. Eldon R. Rene,
  2. María C. Veiga and
  3. Christian Kennes

Published Online: 13 MAR 2013

DOI: 10.1002/9781118523360.ch4

Air Pollution Prevention and Control: Bioreactors and Bioenergy

Air Pollution Prevention and Control: Bioreactors and Bioenergy

How to Cite

Rene, E. R., Veiga, M. C. and Kennes, C. (2013) Biofilters, in Air Pollution Prevention and Control: Bioreactors and Bioenergy (eds C. Kennes and M. C. Veiga), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118523360.ch4

Editor Information

  1. Department of Chemical Engineering, University of La Coruña, Spain

Author Information

  1. Department of Chemical Engineering, University of La Coruña, Spain

Publication History

  1. Published Online: 13 MAR 2013
  2. Published Print: 19 APR 2013

ISBN Information

Print ISBN: 9781119943310

Online ISBN: 9781118523360

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Keywords:

  • Biofilter;
  • biofilter modelling;
  • odour;
  • unsteady-state;
  • volatile compounds;
  • waste gas

Summary

Biofilters have proven to be efficient in treating low to moderately high concentrations of pollutants (<5 gm-3) over a rather wide range of gas-flow rates. In this chapter we present a broad overview on the design, operation and process parameters affecting the performance of a biofilter. The following parameters that affect biofilters performance have been discussed in detail based on the most recent literature: pollutant load, composition of waste-gas, filter bed, temperature, pH, oxygen availability, nutrient availability, moisture content and relative humidity, polluted gas flow direction, carbon dioxide generation rates, pressure drop, and biomass accumulation. During their operation, biofilters do often undergo periodic variations in gas-flow rates and inlet concentrations, and it is often necessary to assess biofilters performance under transient-state conditions. A separate section of this chapter discusses the different patterns of shock-loads that a biofilter is expected to receive, and the reactors response to such conditions. The application of on-line monitoring devices and intelligent control devices to monitor and control biofilters has not yet been fully explored. A few examples on the application of such intelligent devices in biofiltration is briefly mentioned. The emergence of Artificial Intelligence (AI) tools such as Artificial Neural Networks (ANNs), and Fuzzy Logic/Fuzzy Neural Networks can also be considered as an efficient modeling alternative for performance prediction for performance prediction, optimization and design of a biofilter. This chapter also outlines the step-wise procedure followed to formulate a suitable ANN-based model for a biofilter, and suggests the different scopes and strategies for considering fuzzy logic-based tools to model a biofilter′s performance.