Plant-wide modelling of phosphorus transformations in wastewater treatment systems: Impacts of control and operational strategies

Abstract

The objective of this paper is to report the effects that control/operational strategies may have on plant-wide phosphorus (P) transformations in wastewater treatment plants (WWTP). The development of a new set of biological (activated sludge, anaerobic digestion), physico-chemical (aqueous phase, precipitation, mass transfer) process models and model interfaces (between water and sludge line) were required to describe the required tri-phasic (gas, liquid, solid) compound transformations and the close interlinks between the P and the sulfur (S) and iron (Fe) cycles. A modified version of the Benchmark Simulation Model No. 2 (BSM2) (open loop) is used as test platform upon which three different operational alternatives (A, A, A) are evaluated. Rigorous sensor and actuator models are also included in order to reproduce realistic control actions. Model-based analysis shows that the combination of an ammonium ( [Formula: see text] ) and total suspended solids (X) control strategy (A) better adapts the system to influent dynamics, improves phosphate [Formula: see text] accumulation by phosphorus accumulating organisms (X) (41%), increases nitrification/denitrification efficiency (18%) and reduces aeration energy (E) (21%). The addition of iron ( [Formula: see text] ) for chemical P removal (A) promotes the formation of ferric oxides (X, X), phosphate adsorption (X, X), co-precipitation (X, X) and consequently reduces the P levels in the effluent (from 2.8 to 0.9 g P.m). This also has an impact on the sludge line, with hydrogen sulfide production ( [Formula: see text] ) reduced (36%) due to iron sulfide (X) precipitation. As a consequence, there is also a slightly higher energy production (E) from biogas. Lastly, the inclusion of a stripping and crystallization unit (A) for P recovery reduces the quantity of P in the anaerobic digester supernatant returning to the water line and allows potential struvite ( [Formula: see text] ) recovery ranging from 69 to 227 kg.day depending on: (1) airflow (Q); and, (2) magnesium ( [Formula: see text] ) addition. All the proposed alternatives are evaluated from an environmental and economical point of view using appropriate performance indices. Finally, some deficiencies and opportunities of the proposed approach when performing (plant-wide) wastewater treatment modelling/engineering projects are discussed.

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

“…As the sulfate concentrations in this study are below 1 g S/L, a more viable option would be adsorption on limestone (Silva, et al ). In a WWTP, removal of dissolved H 2 S in the AD can be achieved by dosing iron salts in a tank before the AD reactor (Ge, Zhang, Batstone, Keller, & Yuan, ; Solon et al, ). Influent pH and dissolved CO 2 (influent alkalinity). The content of inorganic carbon in the influent can be reduced by recycling part of the effluent stream into a smaller tank before the main anaerobic digester.…”

“…As the sulfate concentrations in this study are below 1 g S/L, a more viable option would be adsorption on limestone (Silva, et al 2012). In a WWTP, removal of dissolved H 2 S in the AD can be achieved by dosing iron salts in a tank before the AD reactor (Ge, Zhang, Batstone, Keller, & Yuan, 2013;Solon et al, 2017).…”

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

“…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.…”

“…Due to the complex and variable nature of waste materials, finding the optimal combination of unit processes in treatment trains for nutrient (and energy) recovery and the optimal operating conditions that maximise resource recovery at minimal cost and environmental impact is challenging. 31 Vaneeckhaute et al 14 recently developed a novel method using the NRM models and global sensitivity analysis to set up optimal resource recovery treatment train configurations. The developed models and method may be applied as a cost-effective tool for optimisation of single unit processes, for selection of optimal unit process combinations, and for optimisation of holistic valorisation chains.…”

“…Every new product and process has an associated optimal design and control strategy, while treatment train interactions must also be considered. 31 To tackle these challenges, the use of model-based integrated design and control strategies, i.e., methods that implement control at the design stage, to ensure that products of desired quality are produced consistently, is proposed. Integrated design and control may lead to cost savings of up to 50% compared to sequential design and control approaches.…”