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Integration of complete elemental mass-balanced stoichiometry and aqueousphase chemistry for bioprocess modelling of liquid and solid waste treatment systems – Part 4: Aligning the modelled and measured aqueous phases


G.A. Ekama
C.J. Brouckaert
B.M. Brouckaert

Abstract

Completely mass-balanced biological, physical and chemical process stoichiometry ensures that the CHONPS material and charge content entering and exiting bioprocess system models is conserved, which is a requirement for pH prediction in integrated physical, chemical and biological process models. Bioprocesses transform the material content from reactants to products, exchanging material between the aqueous, gaseous and solid phases, which cause pH changes in the aqueous phase. By measuring the material content of the aqueous phase, the progress of bioprocesses can be monitored. Alkalinity is an important aqueousphase property that can be used to track aqueous-phase changes caused by physical, chemical and biological processes. Alkalinity is a stoichiometry property of the components in solution (i.e., a linear function of the amounts present). Its uptake from, and release to, the aqueous phase can both be modelled with bioprocess stoichiometry, and measured in physical bioprocess systems, and so aid in linking the modelled and measured aqueous-phase compositions. Changes in the concentrations of components containing the elements C, H, O, N, P and S result in changes in six weak acid/bases systems in the aqueous phase, all of which affect the total alkalinity. These are: inorganic carbon (IC), ortho-phosphate (OP), free and saline ammonia (FSA), volatile fatty acids (VFA), free and saline sulphide (FSS) and the water itself. Characterization of the aqueous phase to quantify the material content of the aqueous phase containing these six weak acid/base systems using the 5-point titration method is described. While several alkalinity titration based methods are available for anaerobic digestion bioprocess monitoring, only the 5-point titration is sufficiently accurate for aqueousphase characterization to quantify the aqueous-material content for pH prediction in bioprocess models.


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eISSN: 1816-7950
print ISSN: 0378-4738