Sensitivity analysis for the SimpleTreat model to simulate fate of chemicals in sewage treatment plants
SimpleTreat 3.1 predicts the distribution and elimination of chemicals by sewage treatment. The model is used as the default calculation in EUSES 2.0 to estimate exposure concentration in the receiving water, soil and air. A sensitivity analysis was performed to rank input parameters according to th...
| Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 63(2011), 9 vom: 27., Seite 2052-60 |
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| Auteur principal: | |
| Autres auteurs: | |
| Format: | Article |
| Langue: | English |
| Publié: |
2011
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| Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't Anti-Infective Agents, Local Sewage Triclosan 4NM5039Y5X |
| Résumé: | SimpleTreat 3.1 predicts the distribution and elimination of chemicals by sewage treatment. The model is used as the default calculation in EUSES 2.0 to estimate exposure concentration in the receiving water, soil and air. A sensitivity analysis was performed to rank input parameters according to their influence on model predictions. Triclosan was selected for the base case. The sewage flow, degradation rates and parameters describing the raw sewage were shown to be the most sensitive inputs. The pH and dissociation constant are very sensitive parameters when working with ionisable compounds. Variation in certain input parameters was propagated through the model to yield greater variation in output parameters with a maximum ratio of 4.0. SimpleTreat 3.1 is a steady state model describing a highly non-steady system. A large variability in the most sensitive parameters is expected within a single sewage plant and parameters should therefore be selected to cover this variability |
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| Description: | Date Completed 27.09.2011 Date Revised 18.09.2019 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |