Programme Filires Biologiques

Trying to see through the black-box observation and data collection for modeling a biofiltration process

Pascal BoissonModel-based optimization of biofilm systems 29/05/09

2Context

Attached biomass processes are : Diverse (MBBR, BAF, MABR, etc.) Complex

High level of heterogeneities Quantitatively important interactions of qualitatively different

phenomenon

And they combine several advantages : Compact and intensive (BAF) Ease of wwtp upgrade options (IFAS) Interesting features (e.g. solids residence time)

Central treatment process in present and future wwtpdesign

3Context

Nevertheless :Much of the knowledge is either

Theoretical and as such, essentially orientedtoward fundamental problems

Operational and essentially empirical Biofilm / Biofilm reactors

This not completely satisfying

Observation and data collection for modeling a biofiltration process

General outlineExperimental based model development

5Experimental approach overview

Two different approaches: Treatment efficiency figures

i) What is the maximum treatment efficiency that I canreach?

ii) What are the required operational conditions for thismaximum?

iii) Is it an economic optimum? That the engineering way It leads to operational decision but not a full

description of the process itself thats a black box

6Experimental approach overview

Then, the question we are adressing: How to understand a process with very limited

internal observation possibilities? How to access a precise estimation of key

internal fluxes (growth, hydrolysis, ammonification, etc.)?

How to reduce uncertainty Then basically two approaches:

Steady state mass balancing and routing Dynamic temporal and spatial approach

7Context

Integrating knowledge about already known fundamental processes acquire robust predictive capacities identify limiting processes to focus innovation efforts on these

aspects

Biostyr (upflow biological aeratedfilters) systems: have been chosen as a model

process should serve as a first step for

methods development (to beapplied to other biofilm process)

Observation and data collection for modeling a biofiltration process

Mass Balance over a Biostyr

Back to basics

9Mass balance - Concepts

Based on simple and robust hypothesis Steady state Conserved quantities (water flows, CHONP, charges,

COD) Composition data (biomass, substrate, )

mass balancing leads to different and important possibilities: Data reconciliation Internal flux estimation

See e.g. Meijer et al 2002,Puig et al 2008 for more discussion on data reconciliationSee Ekama 2009, Iwa GMP 2008, and Lavoisier 1789 for mass balance

10

Mass balance - Estimation of the internal fluxes

Compartiments Flux Bilan

In and Out Conversions

Influent Effluent Backwash In Gas Out Gas H Aer Gr H Ano Gr A Aer Gr

Q g/j Vin - Vout - Vlav 0,0 P gP/j TPin - TPout - TPlav 0,0

TN gN/j TNin - TNout - TNlav (non mesur) (non mesur) - N2 produit 0,0

NOx- gN/j NOx- in - NOx- out - NOx- lav - NOx- consomm + NOx- produit 0,0 dO2 gO/j - O2 out O2 in - O2 cons - O2 cons - O2 cons 0,0

DCO gDCO/j DCOin - DCOout - DCOlav - DCOcons - DCOcons + DCOprod 0,0 TC/CO2 gC/j TCin - TCout - TClav CO2 in - CO2 out - CO2 produit - CO2 produit + CO2 consomm 0,0

Estimated from stochiometry

Measured values,Deduced from mass balance,

11

Mass balance - Concepts

Can we go deeper? Based on elemental cycles (COD, N, TC) Based on basic fractionation Based on ASM conceptual models

Other transformations process are accessible Hydrolysis (and decay) Ammonification

12

Mass Balance Undertsanding the cycles

-1

40-9-15

-32

140-37

Oxydation Nitrification

Dnitrification

-40

-12

TN-130

-50

200

Hydrolysis

Nitrogen Flux (gN/cycle)

NH4+

NOx-4

20

40 1

37

-4

4

-12

-80-15

-8

Ammonification

44

-44

-39

39

OK

OK

OK

OK

Norgsoluble

Norgparticulaire

-28

13

Mass Balance - Conclusion

Why is this approach that important on biofiltration process: Global process intensities over a filtration cycle

Interest for a modelling a biofilm reactor

Trial and error is not an option!

So many unknowns that one should at least calculate all the quantities that he is able to evaluate from a simple mass balance:

There are still many things to play with afterward: Initial state Kinetics and laws Biofilm specific process (thickness, boundary layers, filtration, etc.)

14

Mass Balance - Conclusion

interesting (I hope) and light approach on pilot scale calibrated flowmeters common lab analysis (possible with minikits only ) gaz analyser for a few days

is only global (in time and space) assumes homogeneity over the process aggregates the filtration cycle as a steady state process

and forget about variations in time Then what should be done :

Evaluate other functionning points Loop with the filter profiles approach Integrate this results in a biofilter model

Fate of suspended solids

Profiles and kineticsA bit deeper

16

Profils methods

Liquid sampling Media sampling

17

Bulk concentration profiles

CODt

0

100

200

300

400

500

ED P1 P2 P3 P4 P5 P6 EF

Sampling point

C

O

D

t

(

m

g

/

L

)

DCOt -12hDCOt -15h

MES

020406080

100120140

ED P1 P2 P3 P4 P5 P6 EF

Sampling point

M

E

S

(

m

g

/

L

)

MES -12hMES -15h

CODs

0

50

100

150

200

ED P1 P2 P3 P4 P5 P6 EF

Sampling point

C

O

D

s

(

m

g

/

L

)

DCOs -12hDCOs -15h

CODp

0

50

100

150

200

250

ED P1 P2 P3 P4 P5 P6 EF

Sampling point

C

O

D

p

(

m

g

/

L

)

DCOp -12hDCOp -15h

d_DCOt

-15,00

-10,00

-5,00

0,00

5,00

P1->P2

P2->P3

P3->P4

P4->P5

P5->P6

Sampling point

C

O

D

t

(

k

g

/

m

^

3

/

j

)

d_DCOt - 12h

d_DCOt - 15h

Bilan demasse

d_DCOs

-8,00

-6,00

-4,00

-2,00

0,00

2,00

P1->P2

P2->P3

P3->P4

P4->P5

P5->P6

Sampling point

r

(

k

g

/

m

^

3

/

j

)

d_DCOs -12hd_DCOs -15hBilan demasse

d_DCOp

-12,00

-8,00

-4,00

0,00

4,00

P1->P2

P2->P3

P3->P4

P4->P5

P5->P6

Sampling point

r

(

k

g

/

m

^

3

/

j

)

d_DCOp -12hd_DCOp -15hBilan demasse

d_MES

-6,00

-4,00

-2,00

0,00

2,00

P1->P2

P2->P3

P3->P4

P4->P5

P5->P6

Sampling point

r

(

k

g

/

m

^

3

/

j

)

d_MES - 12h

d_MES - 15h

Bilan demasse

Concentrations profiles Reaction rate profiles

18

Discussion

This is nice and obvisously needed: Estimation of the reaction rates Estimation of the filtration behavior

but This can lead to very long lab days This need special equipement

Pilot plant is the correct scale This leads to very very long lab days

19

Limits

After some tests with a model, it appearsthat: Air transfer is one of the most important

operational parameter as it influence everythingand what is published is clearly not enought

Results are also very sensitive to the physicalfiltration model that we choose

And that is where we should focus next

Any questions ?

Thanks for you attentionand have a nice day