Calibration and statistical analysis of a simplified model for the anaerobic digestion of solid waste
Modelling is increasingly used for optimizing environmental treatment processes such as anaerobic digestion. It allows problems such as instability of the process to be solved by predicting various scenarios. The anaerobic digestion model No. 1 (ADM1) is accepted worldwide as the standard model for...
| Veröffentlicht in: | Environmental technology. - 1998. - 30(2009), 14 vom: 14. Dez., Seite 1575-84 |
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| Weitere Verfasser: | , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2009
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| Zugriff auf das übergeordnete Werk: | Environmental technology |
| Schlagworte: | Journal Article Industrial Waste Sewage |
| Zusammenfassung: | Modelling is increasingly used for optimizing environmental treatment processes such as anaerobic digestion. It allows problems such as instability of the process to be solved by predicting various scenarios. The anaerobic digestion model No. 1 (ADM1) is accepted worldwide as the standard model for the description of anaerobic digestion. However, it is sophisticated and complex, so it is not user friendly. Therefore, a mathematical method was developed that allows the calculation of the reactor pH, as well as the biogas flow rate (Q) and composition (expressed as the CO2 partial pressure, pCO2), based on a small number of widely available analyses such as chemical oxygen demand and total organic carbon. Furthermore, the ADM1 model was originally designed for anaerobic digestion of wastewater. In this work, the ADM1 model is evaluated for the first time for application in the modelling of solid waste digestion. This evaluation was performed in two steps. First, a list of experimentally available lab-scale data (pH and Q) was grouped according to the composition and origin of the treated solid waste (e.g. manure or vegetable waste). For each group the developed model for the calculation of pH, Q and pCO2 was calibrated with this lab-scale data. After calibration, the model was validated with additional experimental results. It could be demonstrated statistically that the model was able to predict the experimental results, although the confidence region was rather large |
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| Beschreibung: | Date Completed 02.04.2010 Date Revised 26.02.2010 published: Print Citation Status MEDLINE |
| ISSN: | 0959-3330 |
| DOI: | 10.1080/09593330903358278 |