https://scholars.lib.ntu.edu.tw/handle/123456789/449177
Title: | Modeling nitrogen dynamics in a waste stabilization pond system using flexible modeling environment with MCMC | Authors: | Mukhtar H. YU-PIN LIN Shipin O.V. Petway J.R. |
Keywords: | Flexible modeling environment; Global uncertainty; GLUE; MCMC; Nitrogen dynamic; Parameterization; Sensitivity; Waste stabilization pond | Issue Date: | 2017 | Journal Volume: | 14 | Journal Issue: | 7 | Source: | International Journal of Environmental Research and Public Health | Abstract: | This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH3-N and NO3-N. Results indicate that the integrated FME-GLUE-based model, with good Nash-Sutcliffe coefficients (0.53-0.69) and correlation coefficients (0.76-0.83), successfully simulates the concentrations of ON-N, NH3-N and NO3-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH3-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO3-N simulation, which was measured using global sensitivity. © 2017 by the authors. Licensee MDPI, Basel, Switzerland. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/449177 | ISSN: | 1661-7827 | DOI: | 10.3390/ijerph14070765 | SDG/Keyword: | nitrogen; nitrogen; denitrification; Markov chain; Monte Carlo analysis; nitrogen; numerical model; parameterization; sensitivity analysis; uncertainty analysis; wastewater treatment; Article; concentration (parameters); correlation coefficient; denitrification; growth rate; Markov chain; Monte Carlo method; nitrogen dynamics; Nitrosomonas; nonhuman; sensitivity analysis; simulation; uncertainty; waste management; waste stabilization pond system; analysis; growth, development and aging; Markov chain; Monte Carlo method; pond; sewage; software; theoretical model; water pollutant; Nitrosomonas; Markov Chains; Models, Theoretical; Monte Carlo Method; Nitrogen; Nitrosomonas; Ponds; Software; Uncertainty; Waste Disposal, Fluid; Water Pollutants, Chemical |
Appears in Collections: | 生物環境系統工程學系 |
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