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Biosystems engineering, 2020-03, Vol.191, p.85-95
2020
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Autor(en) / Beteiligte
Titel
Model-based evaluation of ammonia removal in biological air scrubbers
Ist Teil von
  • Biosystems engineering, 2020-03, Vol.191, p.85-95
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2020
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • A mechanistic model for ammonia removal in a countercurrent biological air scrubber was set up. This model was used to study the effect of the influent characteristics – air temperature, ventilation rate and ammonia load, on ammonia removal efficiency. Besides mass balances of the components participating in the biological conversions, the water mass balance and the heat balance were considered. The effects of the pH and the concentration of the nitrogen components on the driving force for mass transfer were examined. The model output was compared against experimental data from a pig housing facility. Simulations were performed to assess the usefulness of pH control and to investigate the effect of inflow air conditions on the ammonia removal efficiency. The study found out that although pH control affected the nitrogen component distribution in the washing water, it hardly affected the ammonia removal efficiency. Thus, pH control for biological air scrubbers is not recommended in practice, however, an on/off pH control system adding only acid at critical moments (pH above 7.5) could be considered. The variations in the ammonia removal efficiency are mainly caused by a changing ventilation rate rather than air temperature fluctuations or ammonia load. •A mechanistic model for a biotrickling filter for ammonia removal was developed.•pH control affected the nitrogen component distribution in the washing water.•Changing ventilation rate mainly caused variations in ammonia removal efficiency.•Simulation results agreed with experimental data from a pig housing facility.
Sprache
Englisch
Identifikatoren
ISSN: 1537-5110
eISSN: 1537-5129
DOI: 10.1016/j.biosystemseng.2019.12.011
Titel-ID: cdi_crossref_primary_10_1016_j_biosystemseng_2019_12_011

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