Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes

Abstract

This paper proposes a series of extensions to functionally upgrade the IWA Anaerobic Digestion Model No. 1 (ADM1) to allow for plant-wide phosphorus (P) simulation. The close interplay between the P, sulfur (S) and iron (Fe) cycles requires a substantial (and unavoidable) increase in model complexity due to the involved three-phase physico-chemical and biological transformations. The ADM1 version, implemented in the plant-wide context provided by the Benchmark Simulation Model No. 2 (BSM2), is used as the basic platform (A0). Three different model extensions (A1, A2, A3) are implemented, simulated and evaluated. The first extension (A1) considers P transformations by accounting for the kinetic decay of polyphosphates (XPP) and potential uptake of volatile fatty acids (VFA) to produce polyhydroxyalkanoates (XPHA) by phosphorus accumulating organisms (XPAO). Two variant extensions (A2,1/A2,2) describe biological production of sulfides (SIS) by means of sulfate reducing bacteria (XSRB) utilising hydrogen only (autolithotrophically) or hydrogen plus organic acids (heterorganotrophically) as electron sources, respectively. These two approaches also consider a potential hydrogen sulfide ( [Formula: see text] inhibition effect and stripping to the gas phase ( [Formula: see text] ). The third extension (A3) accounts for chemical iron (III) ( [Formula: see text] ) reduction to iron (II) ( [Formula: see text] ) using hydrogen ( [Formula: see text] ) and sulfides (SIS) as electron donors. A set of pre/post interfaces between the Activated Sludge Model No. 2d (ASM2d) and ADM1 are furthermore proposed in order to allow for plant-wide (model-based) analysis and study of the interactions between the water and sludge lines. Simulation (A1 - A3) results show that the ratio between soluble/particulate P compounds strongly depends on the pH and cationic load, which determines the capacity to form (or not) precipitation products. Implementations A1 and A2,1/A2,2 lead to a reduction in the predicted methane/biogas production (and potential energy recovery) compared to reference ADM1 predictions (A0). This reduction is attributed to two factors: (1) loss of electron equivalents due to sulfate [Formula: see text] reduction by XSRB and storage of XPHA by XPAO; and, (2) decrease of acetoclastic and hydrogenotrophic methanogenesis due to [Formula: see text] inhibition. Model A3 shows the potential for iron to remove free SIS (and consequently inhibition) and instead promote iron sulfide (XFeS) precipitation. It also reduces the quantities of struvite ( [Formula: see text] ) and calcium phosphate ( [Formula: see text] ) that are formed due to its higher affinity for phosphate anions. This study provides a detailed analysis of the different model assumptions, the effect that operational/design conditions have on the model predictions and the practical implications of the proposed model extensions in view of plant-wide modelling/development of resource recovery strategies.

Resource Recovery from Wastewater by Biological Technologies: Opportunities, Challenges, and Prospects

“…Bivalent and trivalent metals can interact with accumulated poly-P decreasing the inherent toxicity of these compounds to PAOs. These processes may be accounted for in the Fe-S-P nexus in aerobic and anaerobic wastewater technologies, linking to the expanded ADM1 model but in heavy metals-bearing effluents (Flores-Alsina et al, 2016). …”

Model‐based analysis and optimization of a full‐scale industrial high‐rate anaerobic bioreactor

“…Finally, the content of C and N of S I and biomass had to be adjusted to match CO 2 , NH x , and H X PO 4 3− X profiles, as well as the P content of lipids and bacteria. All other parameters were left at their default values (Batstone, Keller et al, ; Flores‐Alsina et al, ). It is important to highlight that the addition of reject water during the second period (#D2) substantially changed influent biodegradability (see Figure ).…”

“…The operational temperature is constant at 35°C (mesophilic conditions). The default implementation is upgraded to include P‐, S‐, and Et‐OH‐related conversion processes as published in Batstone, Keller, and Steyer (), Soda, Wada, Okuda, and Ike (), and Flores‐Alsina et al (). P is modeled using a source‐sink approach assuming a predefined elemental (C, H, N, P, O) composition (de Gracia, Sancho, Garcia‐Heras, Vanrolleghem, & Ayesa, ).…”

Towards Quality by Design and process analytical technology for enhanced nutrient recovery from wastewaters

“…This first available NRM library has recently been implemented in the widely applied WEST software platform (DHI) and will be made available for use by industry, municipalities and consultants worldwide. Other attempts to include physicochemical concepts in wastewater treatment process models are reported, for example, by Flores-Alsina et al, 28 Lizarralde et al, 29 Mbamba et al 30 and Solon. 31 However, these studies focus mainly on conventional wastewater treatment processes with limited attention to the optimization of nutrient recovery treatment trains and end-product quality.…”