Presentation on the PhD course „Biohydrogen. System analysis” (project No 28-02 Biohydrogen) April 18-22, 2005, Riga

1. Microcalorimetric
Monitoring of Anaerobic
Treatment Process
Anne Menert, PhD
Stockholm Environment Institute Tallinn Centre
Tallinn University of Technology

2. Why calorimetry?
Calorimetry is an extremely appropriate method
for studying the anaerobic processes.
Thermal power-time curves are influenced by
the metabolic activity and can be related to the
different physiological states of bacteria (Kemp
and Lamprecht, 2000).
From microcalorimetric data the thermodynamic
(∆H) as well as kinetic ( =dX/(X dt))
parameters of a process can be calculated.
Biohydrogen and System Analysis
April 18 -22, 2005 Riga Technical University

3. Ice calorimeter of Lavoisier-Laplace
The quantities of heat that are
produced or absorbed are proportional
to the extent of the processes
involved.
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April 18 -22, 2005 Riga Technical University

4. Isothermal calorimeter
Very intensive
thermal process
Reaction in calorimetric container is
accompanied by a temperature
difference ∆T which produces a flow
of heat Φ.
Intensive thermal
process
No thermal
process
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April 18 -22, 2005 Riga Technical University

5. Thomas Johann Seebeck
born 9 April 1770 in Tallinn, Estonia, Russion Empire
died 10 December 1831 in Berlin, Prussia (now Germany)
In 1821 Estonian-German physicist Seebeck
showed the presence of electric potential between
the junction of two different metals, the
temperatures of which are different. This
thermochemical effect is known in physics as
Seebeck’s effect. This is the underlying principle of
working the thermocouple and it is considered to be
the most precise temperature measuring method.
Seebeck published his findings about
thermomagnetism in 1822-1823 as "Magnetische
Polarisation der Matalle und Erze durch
Temperatur-Differenz. Abhandlungen der
Preussischen Akad, Wissenschaften, pp 265-373."
Thomas Johann Seebeck,
undated engraving
German Muuseum, Munich
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April 18 -22, 2005 Riga Technical University
http://chem.ch.huji.ac.il/~eugeniik/history/seebeck.html

6. Seebeck‘s instrument
Seebeck’s effect
The “thermomagnetic effect”
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April 18 -22, 2005 Riga Technical University
http://chem.ch.huji.ac.il/~eugeniik/history/seebeck.html

7. Heat flow rate and heat production rate
Φ = G · ∆T, where (1)
Φ - heat flow rate over the entire area of container (W)
G - thermal conductance of materials between the container
and the heat sink (J s-1 K-1)
Heat production rate in any process in the calorimetric container is not
equal to the heat flow rate as part of the applied thermal power is lost for
the temperature increase in the container:
P = Φ + Cp d∆T/dt, where
∆ (2)
P – heat production rate (W)
Cp – total combined heat capacity of the reaction vessel and its content (W K-1)
At the beginning of the experiment all the thermal power is used to
increase the temperature in the container while when d∆T/dt → 0,
/dt
P = Φ:
Biohydrogen and System Analysis
April 18 -22, 2005 Riga Technical University

8. /dt
P = Φ+ Cp/G · (dΦ/dt) (3)
The quotient of Cp and G controls the response properties of
the instrument and is called time constant:
constant:
τ = Cp/G (4)
/dt
P = Φ + τ dΦ/dt (5)
Isothermal calorimetry can also be used for measuring the
total amount of released heat Q:
d∆T 
t2

Q = ∫ Φ + C p dt (6)
t1  dt 
t2
If ∆T(t1) ≅ ∆T(t2), Q = ∫ Φdt (7)
t1
Biohydrogen and System Analysis
April 18 -22, 2005 Riga Technical University

9. In isothermal heat conduction calorimetry the signal that is
measured directly is not the heat output rate P (µW) but rather a
potential U (µV) from the thermoelectric plates. The heat output
rate and the potential U can be related receiving the Tian
equation:
P = ε (U+ τ dU/dt) (8)
In practice the calorimetric signal is not collected as U but as
digital units on the computer that are proportional to the potential
U. The instrument output data are presented as heat production
rate P (µW). Another characteristic instrumental constant is the
practical calibration constant ε
ε = G/(kd · n · e) (9)
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10. Solvent activity meter at Lund University, 1997

11. Isothermal
microcalorimeter
2277 TAM
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12. General advantages of calorimetry
low specificity
good reproducibility
non-destructive analysis
continuous registration of processes
possibility to analyze turbid or coloured samples
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13. Multichannel calorimeters
TAM Air TAM III System
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14. http://www.thermometric.se
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15. Thermal Activity Monitor TAM 2277
Combination measuring unit

16. Three types of power-time curves
depending on the state of anaerobic process
c
150
120
Power / µW cm -3
5.0
90
60
30
4.0 0
-3
0 5 10 15 20
Time / h
Volatile fatty acids / g dm
3.0
b
a 60
120 50
Power / µW cm -3
2.0 100
Power / µW cm -3
40
80
30
60
20
40
20 10
1.0 0 0
-20 0 5 10 15 20 0 5 10 15 20
Time / h Time / h
0.0
0 20 40 60 80 100 120 140 160 180 200
Experiment time / d
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April 18 -22, 2005 Riga Technical University

17. IWA Anaerobic Digestion Model No 1
Biochemical steps
(Batstone et al., 2001 )
• Disintegration from homogeneous particulates to
carbohydrates, proteins and lipids;
• Extracellular hydrolysis of these particulate
substrates to sugars, amino acids, and long chain
fatty acids (LFCAs), respectively;
• Acidogenesis from sugars and amino acids to
volatile fatty acids (VFAs) and H2;
• Acetogenesis of LFCAs and VFAs to acetate;
• Separate methanogenesis steps from acetate and
H2/CO2.

18. IWA Anaerobic Digestion Model No 1
(Batstone et al., 2001 )
Complex particulate waste and inactive biomass
Inert particulate
Carbohydrates Proteins Lipids
Inert soluble
Sugars Amino acids Long chain fatty acids (LCFA)
Propionate Valerate, acidogenesis from sugars
Butyrate
acidogenesis from amino acids
acetogenesis from LCFA
acetogenesis from propionate
acetogenesis from butyrate
and valerate
Acetate H2
acetotrophic methanogenesis
hydrogenotrophic
methanogenesis
CH4

19. Cultivation of sulfate reducing bacteria (SRB) isolated from yeast
wastewater treatment plant in batch culture
Without preparation Biotreat 100 With supplement of Biotreat 100
-1
-1
Sulfides / mg L-1
S ulfides / mg L
-1
Sul fa tes / mg L
Sulfates / mg L
-1
-1
-1
-1
dQ/dt / µ W mL
Number of cells mL
dQ/dt / µW mL
Number of cells mL
600 600
1E8 1E8
50 50
6000 500 6000 500
1E7 40 1E7 40
400
400
100000 0 30 4000 100000 0 30 4000 300
300
10000 0 10000 0 200
20 20
200
2000 2000
100
10000 10 10000 10
100
0
10 00 0 0 0 1000 0 0
0 10 20 30 40 0 10 20 30 40
Time / h Time / h
Symbols _ thermal power, - cell count, ∆ - sulfates, - sulfides.
Pyruvate-+0.2 SO42-+ 0.15 H2O + 0.33 H+ CO2 + 0.95 acetate-+ 0.05 ethanol + 0.087 H2S + 0.113 HS- + 0.1 H2 ∆Hcat (KJ mol-1)=-70.2
Lactate-+ 0.37 SO42-+ 0.56 H+ CO2 + 0.98 acetate- + 0.02 ethanol + 0.16 H2S + 0.215 HS-+ 0.5 H2O + 0.48 H2 ∆Hcat (KJ mol-1)=-36.4
2 Lactate- + SO42- + 3H+ 2 acetate- + 2 CO2 + 2 H2O+HS- ∆G’0cat (KJ mol-1)=-74.5
Propionate- + 0.75 SO4 2- + acetate- + HCO3- + 0.75 HS- + 0.25 H+ ∆G’0cat (KJ mol-1)=-37.7
Propionate- + 1.75 SO42- + 3 HCO3- + 1.75 HS- + 0. 5 H+ + 0.25 OH- ∆G’0cat (KJ mol-1)=-88.9
Acetate- + SO4 2- HCO3 - + HS- ∆G’0cat (KJ mol-1)=-47.6
Acetate- + SO42- + 3H+ 2CO2 + HCO3- + HS- ∆G’0cat (KJ mol-1)=-57.0

20. Power-time curves of cultures of
sulfate reducing bacteria
200
Thermal power / µW
1
150
2
Batch experiments on 100 3
Postgate C at +35°C
4
with various amounts of
growth regulator 50
Biotreat. 1 - 0 mg L-1; 2
- 50 mg L-1; 3 - 500 mg
L-1; 4 - 5000 mg L-1. 0
0 20 40
Time / h

21. Adaptation of biofilm to yeast industry waste in
the first stage (AF)
100
day 61, gas 4.08 L/day
90 day 72, gas 5.51 L/day
day 83, gas 7.54 L/day
80
70
Thermal power /µW mL-1
60
50
40
30
20
10
0
0 10 20 30 40 50 60 70
Time /h

22. Calculation of specific growth rate µ
• In exponential growth phase dX/dt = µX (1)
• If the stoichiometry of biomass growth does not change during the growth
(dX/dt) is proportional to dQ/dt and
(X-X0) is proportional to Q.
• The rate of biomass increase is proportional to the rate of increase in the heat
production (where YQ is the proportionality factor):
dX/dt = YQ * dQ/dt (2)
• From definition of specific growth rate (Eq. 1) and replacing it into Eq. 2 we get the
relationship between µ and dQ/dt:
µX = YQ * dQ/dt (3)
• The increase of biomass in the exponential growth phase is an exponential
function: X = X0 * eµt (4)
• Replacing X from Eq. (4) into Eq. (3) µ * X0 * eµt = YQ * dQ/dt (5)
dQ/dt = 1/YQ * µ * X0 * eµt (6)
• After integrating :ln (dQ/dt) = ln (dQ/dt)t=0 + µt (7)
where ln (dQ/dt)t=0 = ln (1/YQ * µ * X0 * eµ).

23. Biomass growth rate is proportional to the heat production rate
(in exponential phase)
Specific growth rate of X
Ansorbance
microorganisms µ Cellcount
Biomass ln X
dX/dt = µX µ=(lnXt-lnX0)/t
µ=1/X*dX/dt
Xt=X0*eµt lnXt =lnX0 + µt Time
q
dQ/ Qs1 my1
Q µ
µW/mL µJ/mL 1/h
dt 2.5e+06 0.50
150
6 5
5 ln dQ/dt = 0.648 + 0.272 t
µmax = 0.272 h-1 3
120 2e+06 0.40 4
3
1
90 1.5e+06 0.30 2
ln dQ/dt
1
ln Q
0 5 10 15 20
-1
0
60 1e+06 0.20
0 5 10 15 20
-1
ln Q = - 3.382 + 0.254 t -3
-2 µmax = 0.254 h-1
30 500000 0.10
-3 -5
hours -4
0 0 0
0 4 8 12 16 20 -5 -7
time Time / h
Region for calculation of maximum
specific growth rate
ln (dQ/dt) = ln (dQ/dt)t=0 + µt

24. Comparison of growth characteristics determined
by microcalorimetry and ATP measurements
N umber of cells by ATP
1.00E+09
-1
N umbe r of ce lls mL
1.00E+08
1.00E+07
1.00E+06
1.00E+05
1.00E+04
0 10 20 30
N umber of cells by calorimetry 40 50
1.00E+09 Time / h
-1
1.00E+08
Numbe r of ce lls mL
1.00E+07
1.00E+06
1.00E+05
1.00E+04
0 10 20 30 40 50
Time / h
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April 18 -22, 2005 Riga Technical University

25. Growth rates of sulfate reducing bacteria
determined by ATP and thermal power
Conc. of Biotreat 100 (mg L-1) max(ATP) (h-1) max(dQ) (h-1)
0 0.220 0.150
50 0.195 0.153
500 0.171
5000 0.184
Average max 0.207±0.013 0.165±0.008
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26. Heat production as a function of biomass
(on the example of SRB isolated from yeast waste treatment plant)
3.0
y = 1 2.009x
-1
2.5 R 2 = 0 .9631
He at production Q / J mL
2.0
1.5
1.0
0.5
0.0
0.00 0.05 0.10 0.15
-1
0.20 0.25
B iomas s / mg mL

27. Influence of thermophilic anaerobic pre-treatment
(t = +65 C) on the thermal power of sludge
P,µW ...20012005sm2 ...20012005sm3 P,µW ...20012005sm1 ...20012005sm4
I: 7.735 J I: 6.535 J I: 4.085 J I: 3.797 J
I: 7.749 J I: 6.542 J I: 4.088 J I: 3.800 J
300 300
200 200
100 100
0 0
0 15 30 45 Time,hour 0 15 30 45 Time,hour
Raw sludge Mesophilic digestion without pretreatment
Pre-treated (t=65° sludge
C) Mesophilic digestion with pretreatment
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28. Acetogenesis, methanogenesis and heat production
Power-time curve of coculture of two types of Kinetics of formation and degradation of
bacteria – a sulfidogen (Desulfovibrio vulgaris products during lactate fermentation by
Hildenborough (NCIB 8303)) and a methanogen coculture of D. vulgaris Hildenborough
(Methanosarcina barkeri (DSM 800)) (NCIB 8303) and M. barkeri (DSM 800).
A - growth of D. vulgaris using sulfate as electron Symbols ∆ - lactate, - CO2, + - CH4, -
acceptor acetate, - H2 (Traore et al. 1983).
B – growth of the coculture when M. barkeri acted
as the H acceptor (from Traore et al., 1983).
2

29. Influence of thermophilic anaerobic pre-treatment
(t = +70 C) on the thermal power of sludge
exothermic region endothermic region
I II
60
a 0
-1
-1
50
Thermal power µW mL
Thermal power µW mL
0 5 10 15 20
40 -100
IV
30 I
III
II III -200
20
IV
10
-300
0 b
0 5 10 15 20
-10 -400
Time / h Time / h
I - raw sludge, II - pre-treated (t = +70 C) sludge, III - sludge after mesophilic digestion
(t = +35 C), I stage, IV - sludge after mesophilic digestion (t = +35 C), II stage.
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30. Production of acetate, H2 and CO2 by OHPAs
2 ethanol + 2 H2O → 2 acetate- + 2 H+ + 4 H2
∆G0' = +19.3 kJ/reaction (1)
2 butyrate- + 4 H2O → 4 acetate- + H+ + 4 H2
∆G0' = +96.2 kJ/reaction (2)
4 propionate- + 12 H2O → 4 acetate- + 4 HCO3- + 4 H+ + 12 H2
∆G0' = +304.6 kJ/reaction (3)
acetate- + 4 H2O → 2 HCO3- + 4 H2 + H+
∆G0' = +104.6 kJ/reaction (4)
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31. Formation of metabolites in the anaerobically pre-
treated (t = +65 C, 15 h) sludge
60 0.8 60 0.8
50 50
Concentration / mg mL -1
Concentration / mg mL -1
-1
0.6 0.6
Thermal power / J mL
-1
40 40
Thermal power / J mL
30 0.4 30 0.4
20 20
0.2 0.2
10 10
0 0.0 0 0.0
0 5 10 15 20 0 10 20 30 40 50
Time / h
Time / h
 thermal power, - pyruvate, - lactate, - propionate, - acetate.
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32. Quantitative characteristics of microbial growth
Type of sludge
Raw sludge Pre-treated sludge After mesophilic conditions
Parameter For 70°C
For For At For Single Tallinn WWTP
+65°C +70°C +65°C At +70°C +65°C stage (as after II stage
a conrol) I stage II stage (as a control)
Heat production, Q/ J -1.729 -0.858 -1.562 -0.601 -0.740 -0.954 +1.372 -0.193 -0.902
mL-1
Biomass, X/ mg ml-1 0.0899 0.0446 0.0812 0.0313 0.0385 0.0496 0.0114* 0.0136 0.0469
Cell count, NQ /107 8.99 4.46 8.12 3.13 3.85 4.96 1.14* 1.36 4.69
cells mL-1
Specific growth rate , 0.106 0.268 0.337 0.422 0.197 0.347 0.180 low bact. 0.073
-1
max /h activity
Solubilized COD / mg 9 400 8 800 15 200 9 800 7 300 12 000 5 000 4 300 -**
O2 L-1

33. Microcalorimetry is a suitable analysis method for
monitoring of anaerobic processes:
• Nonspecific, reproducible, nondestructive, continuous
monitoring, allows turbid samples, not laborious
• Can be used for quantitative characterization of growth (Q,
µmax, YQ), incl monitoring bacterial growth in wastewater or
residual sludge; no need to isolate microorganisms as pure
cultures!
• To describe the microbial consortium more precisely, the
products of metabolism are determined by chemical analysis
or chromatography.
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34. Thank you for
your attention!
attention!