Comparative assessment of modeling and experimental data of ammonia removal from pre-digested chicken manure.

Autor: Pekyavas G; Department of Environmental Engineering, Istanbul Technical University, Maslak, Istanbul, Turkey., Dereli RK; Department of Environmental Engineering, Istanbul Technical University, Maslak, Istanbul, Turkey.; School of Chemical and Bioprocess Engineering, University College Dublin, Belfield, Dublin 4, Ireland., Yangin-Gomec C; Department of Environmental Engineering, Istanbul Technical University, Maslak, Istanbul, Turkey.
Jazyk: angličtina
Zdroj: Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering [J Environ Sci Health A Tox Hazard Subst Environ Eng] 2020; Vol. 55 (11), pp. 1333-1338. Date of Electronic Publication: 2020 Jul 20.
DOI: 10.1080/10934529.2020.1794206
Abstrakt: The aim of this study was to interpret the development of Anammox activity by a mathematical model in an UASB reactor -originally inoculated with methanogenic granules- at which Anammox progress has been also experimentally observed while treating chicken manure digestate. Since ammonium is derived from anaerobic degradation of nitrogenous compounds in chicken manure similar to any other nitrogen-rich organic wastes; the reactor was operated intentionally at favorable conditions [i.e.; with external nitrite source for NH 4 + :NO 2 - ≅1.0] in order to make Anammox process to prevail as operation continued. Results indicated significant ammonia removals (60% on average) although influent concentration was gradually increased up to 200 mg L- 1 . A modeling exercise has been undertaken to investigate the performance of the laboratory scale UASB reactor. In this scope, the experimental results were modeled by using Mantis2 model within GPS-X 6.5 simulation software that included several built in libraries. Accordingly, effluent chemical oxygen demand (COD) and total ammonia nitrogen (TAN) concentrations could be predicted with reasonably good accuracy demonstrating successful calibration. The regression coefficient ( R 2 ) and mean relative absolute error (MRAE) parameters were found as 0.66 and 16% and 0.70 and 19%, respectively.
Databáze: MEDLINE
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