| 1. |
- Feldman, H, et al.
(author)
-
Modelling an industrial anaerobic granular reactor using a multi-scale approach
- 2017
-
In: Water Research. - : Elsevier BV. - 0043-1354. ; 126, s. 488-500
-
Journal article (peer-reviewed)abstract
- The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et−OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (XI) and methanogens (Xac) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (Xsu,Xaa, Xfa) and acetogens (Xc4,Xpro). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed.
|
|
| 2. |
- Saagi, R., et al.
(author)
-
A model library for simulation and benchmarking of integrated urban wastewater systems
- 2017
-
In: Environmental Modelling and Software. - : Elsevier BV. - 1364-8152. ; 93, s. 282-295
-
Journal article (peer-reviewed)abstract
- This paper presents a freely distributed, open-source toolbox to predict the behaviour of urban wastewater systems (UWS). The proposed library is used to develop a system-wide Benchmark Simulation Model (BSM-UWS) for evaluating (local/global) control strategies in urban wastewater systems (UWS). The set of models describe the dynamics of flow rates and major pollutants (COD, TSS, N and P) within the catchment (CT), sewer network (SN), wastewater treatment plant (WWTP) and river water system (RW) for a hypothetical, though realistic, UWS. Evaluation criteria are developed to allow for direct assessment of the river water quality instead of the traditional emission based metrics (for sewer overflows and WWTP discharge). Three case studies are included to illustrate the applicability of the proposed toolbox and also demonstrate the potential benefits of implementing integrated control in the BSM-UWS platform. Simulation results show that the integrated control strategy developed to maximize the utilization of the WWTP's capacity represents a balanced choice in comparison to other options. It also improves the river water quality criteria for unionized ammonia and dissolved oxygen by 62% and 6%, respectively.
|
|
| 3. |
- Solon, K., et al.
(author)
-
Plant-wide modelling of phosphorus transformations in wastewater treatment systems : Impacts of control and operational strategies
- 2017
-
In: Water Research. - : Elsevier BV. - 0043-1354. ; 113, s. 97-110
-
Journal article (peer-reviewed)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 (A1, A2, A3) 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 (SNHX ) and total suspended solids (XTSS) control strategy (A1) better adapts the system to influent dynamics, improves phosphate (SPO4 ) accumulation by phosphorus accumulating organisms (XPAO) (41%), increases nitrification/denitrification efficiency (18%) and reduces aeration energy (Eaeration) (21%). The addition of iron XFeCl3 ) for chemical P removal (A2) promotes the formation of ferric oxides (XHFO−H, XHFO−L), phosphate adsorption (XHFO−H,P, XHFO−L,P), co-precipitation (XHFO−H,P,old, XHFO−L,P,old) and consequently reduces the P levels in the effluent (from 2.8 to 0.9 g P.m−3). This also has an impact on the sludge line, with hydrogen sulfide production (GH2S) reduced (36%) due to iron sulfide (XFeS) precipitation. As a consequence, there is also a slightly higher energy production (Eproduction) from biogas. Lastly, the inclusion of a stripping and crystallization unit (A3) for P recovery reduces the quantity of P in the anaerobic digester supernatant returning to the water line and allows potential struvite (XMgNH4PO4 ) recovery ranging from 69 to 227 kg.day−1 depending on: (1) airflow (Qstripping); and, (2) magnesium (QMg(OH)2 ) 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.
|
|
