Modelli matematici applicati ai processi di filtrazione a membrana — Mathematical modelling of MBR system Biomath, Ghent University, Belgium Tao Jiang

2 Overview of the presentation Modelling the biological performance of MBR Modelling of MBR fouling

3 Biological difference of MBR and TAS Complete retention of solids and partial retention of colloidal/macromolecular fraction Operational parameters Long SRT Short HRT

4 Colloidal fraction in MBR Colloidal: µm - 1µm MBR membrane pore size: µm non-settable flocs in TAS: < 5-10 µm Additional removal of solids by MBR Small flocs ( µm) Partial retention of colloids (pore size µm)

5 Colloidal concentration in MBR sludge TAS Effluent: mg/L MBR sludge (<0.45µm): mg/L MBR effluent (<pore size): 5-20 mg/L Membrane retention: 70-95%

6 Colloidal fraction is S or X? By size: Colloidal fraction < 0.45 µm  S By retention: 70-90% retention  X By biological degradation: Slow biodegradable  X

7 Colloidal fraction is X Colloidal fraction is X, although smaller than 0.45 µm No significant error in TSS measurement, if the colloidal fraction is missing (COD Col <<COD TSS )

8 Influence of long SRT and short HRT High MLSS concentration MLSS=SRT/HRT*….. Increased sensitivity of X (advantage of calibration) Inert particulate COD build up in MBR X I = SRT/HRT*X I,in Careful wastewater characterization Low active biomass fraction

9 Membrane model Simple option (BNR study) Point settler and include the colloidal fraction into X Complete option (membrane fouling study) Define new variable S_SMP (X) Define retention of S_SMP by membrane

10 Modelling of settler vs. membrane TAS (settler) Difficulty in calibrating settling model Possible biological processes in settlers MBR (Membrane) Point separation (no volume) No biological processes Complete retention of X Partial retention of colloidal fraction

11 Modelling of a lab-scale MBR Parameter /variable Reference values Influent rate108 L/day Aerobic17 min Anoxic mixing11 min Anoxic recirculation 12 min SRT17 days HRT6.4 hr MLSS7 g/L Filtration flux31.8 L/(m 2 h)

12 WEST – Configuration

13 WEST – Experimentation

14 Simulation results - Particulate

15 Simulation results - effluent

16 Simulation results - user defined

17 Objective of modelling MBR fouling Prediction of membrane fouling (TMP vs t) Facilitate integrated design, upgrading, operation Cost reduction …

18 Influence of biology on fouling Feed to membrane is activated sludge The composition of activated sludge is determined by the influent and operation of biological process How biology influence fouling What is the main foulant? Influence of MLSS, SRT, HRT, DO?

19 Foulant in MBRs The main foulant in MBRs is up to the influent composition, design and operation Particulate and colloidal can be the main foulant Colloidal fouling is getting more attention (soluble microbial products)

20 Identify the main foulant Quantify the amount of foulant and their fouling potential Estimate the deposit rate of foulant on/in the membrane Predict additional resistance due to the foulant Estimate the reversibility of foulant by backwashing and chemical cleaning Steps in the modelling of fouling

21 conclusion

22 Modelling the biolgical performance of MBR is simpler than TAS Modelling of MBR fouling, especially fouling prediction is extremely difficult and pre-mature