A toolbox to find the best mechanistic model to predict the behavior of environmental systems

Journal Article (2016)
Author(s)

A.G. van Turnhout (TU Delft - Geo-engineering)

Robbert Kleerebezem (TU Delft - BT/Environmental Biotechnology)

Timo Heimovaara (TU Delft - Geo-engineering)

Geo-engineering
Copyright
© 2016 A.G. van Turnhout, R. Kleerebezem, T.J. Heimovaara
DOI related publication
https://doi.org/10.1016/j.envsoft.2016.05.002
More Info
expand_more
Publication Year
2016
Language
English
Copyright
© 2016 A.G. van Turnhout, R. Kleerebezem, T.J. Heimovaara
Geo-engineering
Volume number
83
Pages (from-to)
344-355
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Reliable prediction of the long-term behavior of environmental systems such as Municipal Solid Waste (MSW) landfills is challenging. While many driving forces influence this behavior, characterization of them is limited by measurement techniques. Therefore, a model structure for reliable prediction needs to optimally combine all measured information with suitable mechanistic information from literature. How to get such an optimal model structure? This study presents a toolbox to find and build the model structure that describes an environmental system as close as possible. The toolbox combines environmental frameworks to include all suitable mechanistic information; it fully couples kinetic and equilibrium reactions and contains multiple resources to obtain biogeochemical parameters. Several possible optimal model structures are quickly built and evaluated with objective statistical performance criteria obtained via Bayesian inference. By applying the novel methodology, we select the best model structure for anaerobic digestion of MSW in full scale landfills.

Files

ENVSOFT_D_15_00385R3.pdf
(pdf | 1.28 Mb)
- Embargo expired in 01-10-2018