Developing an artificial intelligence-based WRRF nitrous oxide mitigation road map: The Eindhoven N 2 O mitigation case study

Transcription

1 Developing an artificial intelligence-based WRRF nitrous oxide mitigation road map: The Eindhoven N 2 O mitigation case study J. Porro 1,2 ; G. Bellandi 3,2 ; I. Rodriguez-Roda 4,5 ; A. Deeke 6 ; S. Weijers 6 ; P. Vanrolleghem 7 ; J. Comas 4,5 ; I. Nopens 2 1 Cobalt Water Global 2 BIOMATH, Ghent University 3 University of Florence, Department of Civil & Environmental Engineering 4 LEQUIA, University of Girona 5 ICRA, Catalan Institute for Water Research 6 Waterboard De Dommel 7 modeleau, Département de génie civil et de génie des eaux, Université Laval

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4 WATER RECLAMATION FACILITY

5 Artificial Intelligence (AI) Techniques for for Online WRRF Supervision and Control Mimic human perception, learning and reasoning to solve complex problems (Chen et al., 2008) KB or expert system Case-based reasoning Neural networks Statistical / Data mining Machine Learning Deep learning Agent technology + Fuzzy logic

6 Vision AI Framework for for Online WRRF Supervision and Control

7 N 2 O Risk Model

8 Relevant pathways for N 2 O production in activated sludge systems

9 N 2 O Risk Knowledge Base

10 Eindhoven WRRF N 2 O Risk Assessment Nitrification Denitrification Summer compartment denitrification O2 Air compressor NH4 Location sensor: nitrification - Dry sloids - Ammonium - Phosphate - Oxygen (summer) O2 Winter compartment Location sensor: - Nitrate (nitrification) influent Location sensor: - Nitrate (denitrification Location sensor: - Oxygen (winter)

11 WRRF N 2 O Mitigation Roadmap Start

12 WRRF N 2 O Risk Roadmap Start

13 Eindhoven WRRF overall N 2 O risk aerobic zone Significant risk for significant portion of time? Yes Go to Step 2

14 WRRF N 2 O Risk Roadmap Start

15 Eindhoven WRRF individual N2O risk aerobic zone Overall risk was comprised of both Low DO risk and High DO risk Therefore both AOB pathways implicated

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17 Eindhoven WRRF N2O risk + process conditions aerobic zone 1. after a period of Low DO risk, ammonia goes up 2. after ammonia increases to a peak concentration, DO increases 3. N 2 O risk immediately transitions to High DO risk 4. ammonia peaks come down 5. Pattern repeats Opportunity to stabilize DO, ammonia, and risk got to Step 4 for mitigation plan

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19 Eindhoven WRRF detailed N 2 O risk diagnosis 3 key questions to answer from measurements and detailed diagnosis: 1. Is N 2 O being produced under Low DO and High DO conditions? 2. What is the ammonia concentration versus actual N 2 O concentrations? 3. Is there room to mitigate N 2 O production and emission, while still satisfying nitrogen removal objectives?

20 Eindhoven WRRF N 2 O risk diagnostic measurements Potential remedy: increase DO where you see increasing ammonia and Low DO risk, so that ammonia peaks and N2O peaks are minimized, and High DO peaks are minimized because DO is already higher at start of ammonia peak 1. after a period of Low DO risk, ammonia goes up 2. after ammonia increases to a peak concentration, DO increases 3. N 2 O risk immediately transitions to High DO risk 4. ammonia peaks come down 5. Repeats

21 Eindhoven WRRF detailed N 2 O risk diagnosis

22 Eindhoven WRRF detailed N 2 O risk diagnosis Liquid N 2 O measurements

23 Eindhoven WRRF detailed N 2 O risk diagnosis Liquid and off-gas N 2 O measurements Peaks in liquid coincide with peaks in off-gas Confirms actual production of N 2 O during previously identified risk conditions and peaks in off-gas N 2 O

24 Eindhoven WRRF detailed N 2 O risk diagnosis Risk versus measured N 2 O Confirms periods of N 2 O production during Low DO risk and High DO risk; if we eliminate risk peaks, we eliminate N 2 O peaks

25 N 2 O data via cloud two noticeable N2O peaks each evening (also at 19:55 and 4:55) 25 May 30 May

26 Eindhoven WRRF N 2 O Mitigation Strategy Indicates times when 3 mg/l DO may be enough to lower ammonia

27 Eindhoven WRRF N 2 O Mitigation Control Test Morning: same as current control (lower DO during lower ammonia) Afternoon: increase DO to 3 mg/l at around 12:00 before peak, until 8:00am the next morning when ammonia peak has fully subsided If ammonia exceeds high-high setpoint, override and go to normal DO control override should always be active

28 Eindhoven WRRF N 2 O Mitigation Control Test

29 Eindhoven WRRF N 2 O Mitigation Control Test

30 WRRF N 2 O Mitigation Roadmap END

31 Off-gas and liquid N 2 O measurements Confirmed emissions (kg/d) Proven mitigation strategy Preliminary mitigation strategy Measured GHG reductions and reduction projection Optional calibrated plantwide model for more robust decision support Is there Risk - yes or no

32 Conclusions Elimination of N 2 O peaks, which equal approximately 40 percent of maximum total N 2 O and WRRF electricity GHG emissions Elimination of peaks in ammonia Elimination of periods of over aeration NO 3- not substantially higher, but DO set point should be fine-tuned. N 2 O in anoxic needs to be checked. Needs coordination with other objectives before incorporating into permanent control AI-based N 2 O risk roadmap has proven to be an effective and practical approach for using expert knowledge for mitigating N 2 O

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