Next Article in Journal
Progress Evaluation for the Restaurant Industry Assessed by a Voluntary Marketing-Mix and Choice-Architecture Framework That Offers Strategies to Nudge American Customers toward Healthy Food Environments, 2006–2017
Previous Article in Journal
Day-Ahead PM2.5 Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessFeature PaperArticle
Int. J. Environ. Res. Public Health 2017, 14(7), 765; https://doi.org/10.3390/ijerph14070765

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

1
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
2
Environmental Engineering and Management Program, School of Environment, Resources and Development, Asian Institute of Technology, Pathum Thani 12120, Thailand
*
Author to whom correspondence should be addressed.
Academic Editor: Jason K. Levy
Received: 19 May 2017 / Revised: 2 July 2017 / Accepted: 9 July 2017 / Published: 12 July 2017
(This article belongs to the Section Environmental Science and Engineering)
View Full-Text   |   Download PDF [5808 KB, uploaded 18 July 2017]   |  

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. View Full-Text
Keywords: flexible modeling environment; waste stabilization pond; nitrogen dynamic; parameterization; sensitivity; MCMC; GLUE; global uncertainty flexible modeling environment; waste stabilization pond; nitrogen dynamic; parameterization; sensitivity; MCMC; GLUE; global uncertainty
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Mukhtar, H.; Lin, Y.-P.; Shipin, O.V.; Petway, J.R. Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC. Int. J. Environ. Res. Public Health 2017, 14, 765.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top