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selecting the optimal WWTP confjguration including resource recovery units Živko Južnič-Zonta*, Albert Guisasola, Juan Antonio Baeza GENOCOV. Department of Chemical, Biological and Environmental Engineering, Universitat Autònoma de Barcelona, Catalonia, Spain 7th International Conference on Sustainable Solid Waste Management – 26 th June 2019 *Presenting author HERAKLION2019-SSWM

Funded by the Horizon 2020 Framework Programme of the S cale-up of low-carbon footprint European Union MA terial R ecovery T echniques for under grant agreement No upgrading existing WWTP 690323 DSS for selecting the optimal HERAKLION2019-SSWM 2 WWTP confjguration including resource recovery units

MAIN GOAL REDUCE energy and environmental footprint RECOVER valuable materials (water, cellulose, biopolymers, nutrients) PRODUCE products exploitable in construction, chemical and agriculture DSS for selecting the optimal HERAKLION2019-SSWM 3 WWTP confjguration including resource recovery units

Started Juny 2016 Ends in Juny 2020 S cale-up of low-carbon footprint MA terial R ecovery T echniques for upgrading existing WWTP DSS for selecting the optimal HERAKLION2019-SSWM 4 WWTP confjguration including resource recovery units

Total EC funding 7,5M€ S cale-up of low-carbon footprint MA terial R ecovery T echniques for upgrading existing WWTP DSS for selecting the optimal HERAKLION2019-SSWM 5 WWTP confjguration including resource recovery units

Partners 26 S cale-up of low-carbon footprint MA terial R ecovery T echniques for upgrading existing WWTP DSS for selecting the optimal HERAKLION2019-SSWM 6 WWTP confjguration including resource recovery units

SMARTech pilot-plants 7 DSS objective Advise the potential stakeholders on how to implement the SMART - Plant Technologies for their specifjc wastewater treatment problem DSS for selecting the optimal HERAKLION2019-SSWM 7 WWTP confjguration including resource recovery units

SMARTech process models • Complex dynamics (ASM2d, ADM1) • Discrete events (SBR) • Complex control systems • Large system of difgerential- algebraic equations (DAE) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 8 WWTP confjguration including resource recovery units

Dynamic fjne-screen and post- processing of cellulosic sludge (ST1) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 9 WWTP confjguration including resource recovery units

Polyurethane-based anaerobic digestion bio-fjlter (ST2a) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 10 WWTP confjguration including resource recovery units

Short-Cut Enhanced Phosphorus and PHA Recovery (SCEPPHAR) main-stream process (ST2b) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 11 WWTP confjguration including resource recovery units

Tertiary hybrid ion exchange for N and P nutrients recovery (ST3) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 12 WWTP confjguration including resource recovery units

Short-Cut Enhanced Nutrient Abatement (SCENA) and ordinary digestion side-stream process (ST4a) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 13 WWTP confjguration including resource recovery units

SCENA and CAMBI-enhanced digestion side-stream process (ST4b) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 14 WWTP confjguration including resource recovery units

SCEPPHAR side-stream process (ST5) Biopolym Energy ers Cellulose Nutrients DSS for selecting the optimal HERAKLION2019-SSWM 15 WWTP confjguration including resource recovery units

Which plant confjguration is best for me? Try our hyper-tech solution Decision Support System! DSS for selecting the optimal HERAKLION2019-SSWM 16 WWTP confjguration including resource recovery units

STEP1: Design problem set-up • New design or retrofjt • Geo-location (weather) • PE, legal limits, etc. DSS for selecting the optimal HERAKLION2019-SSWM 17 WWTP confjguration including resource recovery units

Mayor rain event Infjltration Weekend Week STEP2: Wastewater infmow generation • Dry weather model • Wet weather model • Sewer model DSS for selecting the optimal HERAKLION2019-SSWM 18 WWTP confjguration including resource recovery units

Pre-treatment Activated Sludge Digestion STEP3: Superstructure generation and simulation DSS for selecting the optimal HERAKLION2019-SSWM 19 WWTP confjguration including resource recovery units

STEP3: Superstructure generation and simulation • Conventional A2O process • Redeclare Stage3 with ST2b • Automatic built-up of WWTP confjgurations! DSS for selecting the optimal HERAKLION2019-SSWM 20 WWTP confjguration including resource recovery units

STEP4: Objective values estimation • Effmuent Quality Index (EQI) Compute for all • Frequency Effmuent Violations (FEV) possible WWTP design • Net Present Value (NPV) confjgs! • GreenHouse Gas (GHG) emissions DSS for selecting the optimal HERAKLION2019-SSWM 21 WWTP confjguration including resource recovery units

STEP5: Design confjguration sorting Multi Criteria Decision Making (MCDM) based on user preferences Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) DSS for selecting the optimal HERAKLION2019-SSWM 22 WWTP confjguration including resource recovery units

STEP6: Design parameter optimization Minimize NPV optimizing Volume, S/L separation capacity, etc. Constraints on FEV, HRT, SOR, etc. Decrease confjgurations to optimize with MCDM DSS for selecting the optimal HERAKLION2019-SSWM 23 WWTP confjguration including resource recovery units

STEP7: Uncertainty analysis Input and parameter uncertainty Sensitivity analysis given the optimal design DSS for selecting the optimal HERAKLION2019-SSWM 24 WWTP confjguration including resource recovery units

Conclusions • Design is based on dynamic and static process models • Effmuent limits fully accounted • Design of discrete event processes (e.g. SBR) • Design integrates the WWTP control system • Infmuent model for Europe For future work • Test global optimization strategies for design optimization • Build user friendly web-interface • Perform simulations in a distributed computing environment • Integrate other resource recovery technologies • Increase the range of application of the infmow model to North America • Integrate Life Cycle Analysis frameworks DSS for selecting the optimal HERAKLION2019-SSWM 25 WWTP confjguration including resource recovery units

Questions? DSS for selecting the optimal HERAKLION2019-SSWM 26 WWTP confjguration including resource recovery units

selecting the optimal WWTP confjguration including resource recovery units Živko Južnič-Zonta*, Albert Guisasola, Juan Antonio Baeza GENOCOV. Department of Chemical, Biological and Environmental Engineering, Universitat Autònoma de Barcelona, Catalonia, Spain 7th International Conference on Sustainable Solid Waste Management – 26 th June 2019 *Presenting author HERAKLION2019-SSWM