Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling

Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibil...

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Autores principales:	Arianna Catenacci, Matteo Grana, Francesca Malpei, Elena Ficara
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ADM1 anaerobic co-digestion waste sludge modelling parameter estimation input characterization Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/81cda7cfc90d4b76a6ccf97cfa9d50a3
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spelling	oai:doaj.org-article:81cda7cfc90d4b76a6ccf97cfa9d50a32021-11-11T19:57:15ZOptimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling10.3390/w132131002073-4441https://doaj.org/article/81cda7cfc90d4b76a6ccf97cfa9d50a32021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/3100https://doaj.org/toc/2073-4441Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.Arianna CatenacciMatteo GranaFrancesca MalpeiElena FicaraMDPI AGarticleADM1anaerobic co-digestionwaste sludgemodellingparameter estimationinput characterizationHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3100, p 3100 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ADM1 anaerobic co-digestion waste sludge modelling parameter estimation input characterization Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	ADM1 anaerobic co-digestion waste sludge modelling parameter estimation input characterization Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Arianna Catenacci Matteo Grana Francesca Malpei Elena Ficara Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
description	Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.
format	article
author	Arianna Catenacci Matteo Grana Francesca Malpei Elena Ficara
author_facet	Arianna Catenacci Matteo Grana Francesca Malpei Elena Ficara
author_sort	Arianna Catenacci
title	Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
title_short	Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
title_full	Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
title_fullStr	Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
title_full_unstemmed	Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
title_sort	optimizing adm1 calibration and input characterization for effective co-digestion modelling
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/81cda7cfc90d4b76a6ccf97cfa9d50a3
work_keys_str_mv	AT ariannacatenacci optimizingadm1calibrationandinputcharacterizationforeffectivecodigestionmodelling AT matteograna optimizingadm1calibrationandinputcharacterizationforeffectivecodigestionmodelling AT francescamalpei optimizingadm1calibrationandinputcharacterizationforeffectivecodigestionmodelling AT elenaficara optimizingadm1calibrationandinputcharacterizationforeffectivecodigestionmodelling
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Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling

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