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23 April 2014
Challenge the future
Delft University of Technology
Biomass Energy Addressing the rate limiting step
Prof.dr.ir. Jules B. van Lier
2
Biomass COD is created by the photosynthetic reduction of
CO2.
Biomass Energy: how does it start?
CODtheo. = 8(4n+a-2b-3d)/(12n+a+16b +14d) mg COD/mg CnHaObNd
CnHaObNd + ¼ (4n+a-2b-3d) O2 nCO2 + ½(a-3d)H2O + dNH3
+ Energy!!!!
CO2 CnHaObNd
N, P, K
3
Energy Recovery? Anaerobic Digestion!!
(heat, carriers, electricity)
Anaerobic
conversions COD
“heat”
Sludge
Reduced liquid
compounds: VFA,
alcohols, LCFA,
alkanes??*
*Zengler et al., ’99, Nature 401,
266-269: alkanes→CH4
Electrons:
MFC/BES
Energy content
biomass:
13.5 MJ/kg COD
3.8 kWh*/kg COD
(theoretical)
“Conservation of electrons”
Reduced gases:
CH4, H2, (H2S)
4
Drivers and Application of AD
• Most widespread AD application worldwide: manure & slurry digestion:
• Biogas
• Fertiliser
•Most frequently applied scale: farm-scale digestion / domestic biogas
plants. E.g. India, China, Nepal:
• Nepal: 50,000 digesters
• China: > 30 million domestic biogas plants
• Current growing interest: industrial size biogas plants for green energy
generation and waste stabilisation
5
EU success developed in Denmark: spread out over Europe!
Germany, Austria, Sweden are leading (Germany > 3.000 manure digesters)
Note: China: > 25.000 large scale digesters for agricultural wastes!
Centralised manure (co-)digestion /
energy crops Holsworthy plant (UK),
commissioned in 2002
(Courtesy: Nova Energie).
Bio-Energy Production!
6
Crop /
residue
High value feed/
chemicals
Bioethanol/Biodiesel
Food
Biogas
Fertilizer/ Soil
conditioner Residues
valorization
Biorefinery Energy Food Industry
Anaerobic Digestion
(Pabon et al., 2013)
Role of AD for energy crops (residues)
in the bio-based economy
“Biomass cascading”
7
What energy can we expect?
Assessing the biomethane potential
Oxitop: measuring P increase:
AMPTS: Online CH4 production:
See e.g. Angelidaki et al, 2008: IWA Task group
Large volume batch digesters:
8
Manure
OFMSW
Industrial
waste
Crop
residues
Aerobic
sludge
Substrate BMP
(L CH4/ g VS)
Methane yield
(m3 CH4/ton ww)
Slaughterhouse waste 0.57 150
OFMSW 0.5-0.6 100-150
Energy crops 0.30-0.50 30-100
Straws, sugar beet
tops 0.2 - 0.4 36-145
Pig manure 0.29 - 0.37 17-22
Cow manure 0.11 - 0.24 7-14
Energy
crops
Biomethane Potential (BMP) of organic
substrates
(Lehtomaki et al, 2005)
BMP range: 0.1 - 0.6 L CH4/gVS
9
• Substrate (1): exact species, time of harvest
• Substrate (2): pre-treatments (particle size, storage,
blending)
• Inoculum: Type (source, structure), age, concentration (S/I)
• Buffer solution: type, concentration
• Macronutrients and trace elements: accessibility
• Equipment: type of bioassay (batch, continuous)
• Operating conditions: temperature, pH, sampling frequency.
(Hansen et al , 2004);(Rozzi and Remigi, 2004);
(Muller, 2004);(Colleran et al. 1992)
Intrinsic values?
Large variability in BMP literature data:
(PhD thesis Claudia Pabon (2009)) EU Cropgen project
(Banks, Univ. South., UK)
10
Up to 31%
difference in
BMP
0,41
0,35
0,31
0,34
0,31
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
Mixture S/I 0.5 Mixture S/I 1.5 Mixture S/I 2.5 Granular S/I 0.5 Granular S/I 2.5
BM
P (
l C
H4
ST
P/g
VS
)BMP: Impact Substrate/Inoculum
ratio and inoculum type: Inoculum type:
Digested primary sludge
Methanogenic granular sludge S/I ratios: 0.5 – 1.5 – 2.5
(Pabon-Pereira et al, WST 2012)
sludge mixture methanogenic
granular sludge
11
101% 100%
85%
78%
86% 100%
69% 73%
0.00
0.20
0.40
0.60
0.80
1.00
1.20
5 mM 20 mM 30 mM 50 mM
BM
P (
l C
H4 -
ST
P/g
VS
0%
20%
40%
60%
80%
100%
120%
BMP not corrected blank BMP
BMP: Impact phosphate buffer
concentration..!
Max. conc.: 20 mM
Also blank test was
impacted…
(Pabon-Pereira et al, WST 2012)
12
BMP: Impact substrate pre-treatment
Increase in BMP:
Freezing: No
significant influence
Blending: Up to 40%
Dry grinded: Up to
50%
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Mustard Endive Green beans
BM
P (
l C
H4 -
ST
P/g
VS
)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Fib
er
co
nte
nt
(%V
S)
Fresh 1 cm Frozen 1 cm Frozen blended Dry grinded Fiber content
Impact blending and
grinding apparently
dependent on fibre
content
(Pabon-Pereira et al, WST 2012)
13
BMP: impact drying and grinding
depends on fibre content:
-10%
0%
10%
20%
30%
40%
50%
60%
70%
Braken Mustard Spartina Triticale Winter
bean
Endive Green
beans
% B
MP
in
cre
ase
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Lig
nin
+C
ell
ulo
se (
g/g
VS
)
Dry grinded
Lignin+cellulose
(Pabon-Pereira et al, WST 2012)
14 14
First step AD conversion process (extent determines BMP)
Generally the overall rate limiting step
Conversion of polymeric compounds into soluble monomeric or
dimeric substrates.
Extra-cellular conversion by hydrolytic enzymes excreted by microbs
(dissolved compounds are taken up by biomass). Rate dependent
on surface availability and presence of refractory fibres!
Generally modeled using first order kinetics
Hydrolysis of particulate organic
substrates; “recap”
Batch digestion:
P= P0.e-kh.t
ln(P/P0)= -kh.t
CSTR digestion:
-kh.P + (P0-P)/SRT=0
(P0-P)/P= kh.SRT
dP/dt = -kh.P
(Eastman and Ferguson, 1991;
Hobson 1983; Noike et al. 1985).
15 15
Lignin: 15-25%
- Complex aromatic structure
- high energy content
- anaerobic non-biodegradable
Hemi-cellulose: 23-32%
- Polymer of C5 and C6 sugars
- easy to hydrolyse
Cellulose: 38-50%
- Polymer of glucose
- easy to hydrolyse
Fibres limiting hydrolysis:
Ligno-cellulosic matter
16
kh vs total fibre CROPGEN 2
y = -0,7915x + 0,8224
R2 = 0,695
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7
Total fiber (g/gVS)
-kh
kh vs lignin CROPGEN 2
y = -2,0655x + 0,6689
R2 = 0,8589
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0 0,05 0,1 0,15 0,2 0,25
lignin (g/gVS)
-kh
kh vs lignin + cellulose CROPGEN 2
y = -0,9537x + 0,7879
R2 = 0,7932
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0 0,1 0,2 0,3 0,4 0,5 0,6
lignin + cellulose (g/gVS)
-kh
Slope R2
Total fibre - 0.79 0.695
Lignin+cellulose - 0.95 0.793
Lignin -2.06 0.858
Impact fibre content hydrolysis rate
(Claudia Pabon, PhD thesis, 2009)
(EU-Cropgen)
Batch digestion:
ln(P/P0)= -kh.t
17
CSTR; hydrolysis is rate limiting; COD: 100g/l; BMP=80%
Impact hydrolysis rate on CH4
production at fixed SRT/HRT
Effect hydrolyis rate on CH4-production
0
5
10
15
20
25
0 20 40 60 80 100 120
HRT (days)
CH
4-p
rod
ucti
on
(m
3/m
3)
kh=0,05/daykh=0,2/dayBMP
G. Zeeman, WUR
CSTR digestion:
(P0-P)/P= kh.SRT
18
Observed problems in industrial
scale digesters:
• Less biogas than expected
• Production of non-stabilised digestates
• pH drops with energy rich substrates
• High effluent VFAs
ΔCH4 /Δt determined by BMP of substrate and SMA of methanogenic
biomass. Possible retardation caused by:
- inadequate mixing (drop in SMA)
- substrate overloading (drop in SMA)
- presence of refractory fibres (drop in BMP)
- inhibition of hydrolysis step (drop in BMP)
Angelidaki (2005): evaluation of 18 centralised scale biogas plants:
A large residual CH4 potential remains in main reactor…
19
Pretreatment of lignocellulose
Improved AD by pre-treating lignocellulosic biomass
- Improved accessibility of (hemi-)cellulose (higher BMP)
- Digestion of additional intermediates formed during pre-treatment (VFA,
aldehydes)
- Possibility to apply AD at high solid concentrations; no product inhibition.
Figure 1: Bonding of cellulose, hemicellulose and lignin (Keeton
et al., 1994)
(e.g. Moisier et al, 2005)
Thermo-chemical
20
A novel approach for bio-methanation
of agro-industrial residues:
Enzymatic pretreatment and subsequent high-rate bio-
methanation in EGSB reactors
Hydrolysis Simple
organic
compounds
Enzyme
addition
BSG = Brewer’s spent grain
BSG hydrolysate:
85 g COD/L!
15-20 g sugars/L
Haoyu et al., 2013, 2014
21
Start-up of EGSB reactor with pre-
hydrolysed BSG: risk of overloading!
VFA accumulation, sludge wash-out
Haoyu et al., 2013, 2014
22
Two-stage versus one-stage BSG
methanation: granule conservation
• HRT: 8h
• pH: 4.3~4.9
Influent
Pre-acidification
tank
Recyclin
g
Effluent
EGSB
Influent
One-stage, Day 16
One-stage, Day 55
One-stage, Day 70
Two-stage, Day 16
Two-stage, Day 55
Two-stage, Day 70
Haoyu et al., 2013, 2014
23
End of One-stage
Two-stage versus one-stage BSG
methanation: max. OLR 5-7 times CSTR
loading capacities
Haoyu et al., 2013, 2014
24
Sugar VF
A
CH4 Fibre
H A M
lignin
cellulose
Hemi-
cellulose
Hydrolysis rate assessed by analysing
fermentation products and biogas
Hydrolysis inhibition causing
disappointing CSTR performances?
25
0
2
4
6
8
10
12
14
16
18
20
9 10 11 12
HRT (days)
Hyd
roly
sis
(%)
Cow manure
0
2
4
6
8
10
12
14
16
18
20
0 1000 2000 3000 4000 5000 6000
NH4 (mg N/l)
Hyd
roly
sis
(%
)
1000 mg NH4+-N >4000 mg NH4
+-N
Hydrolysis at different NH4+-N
manure digestion in CSTR systems (mesophilic)
HRT = 10 days
(Zeeman,1991)
26
Lipid hydrolysis rates in relation to
NH4+
0
20
40
60
80
100
0 1 2 3 4
Time (days)
H (%
)
2000 mg NH4+-N 7000 mg NH4
+-N
Digestion of Tributyrin at
varying [NH4+]
Increase of [NH4+] did not
decrease hydrolysis rate
27
0
10
20
30
40
50
60
0 2000 4000 6000 8000 10000
Inert dissolved COD (mg/l)
Hyd
roly
sis
(%
)
Cow manure HRT 10 days
Pig manure 1 HRT 15 days
Pig manure 2 HRT 10 days
Pig manure 2 HRT 15 days
Relation between inert dissolved COD
and Hydrolysis?
Ligno-cellulosic
biomass
limiting
hydrolysis??
28
What are humic compounds: humic acids (HA) and fulvic
acids (FA)? End product of the biological decay of biota residues
• Hardly degradable organic acids
• Behave like weak polyelectrolytes
• HA higher MW than FA
• HA soluble at pH > 3.5
• FA soluble at all pH
(Engebretson & Wandruszka, 1994)
(Schulten and Schnitzer,1993) C308H328O90N5
MW = 5540Da
A closer look to humic compounds:
29
Reactivity of humic compounds? - Bind cations and other molecules
- Oxygen containing functional groups responsible for reactivity
O
OH R
OH
OH
OH
O
O
O
O
OH
O
R’ R O R R`
Phenolic & Carboxyl
Main source of binding
Humic compounds’ reactive groups:
30
Humic & Fulvic acids extraction
Fresh cow manure silage energy maize
HA FA
Fernandes et al., 2010
31
-1
1
3
5
7
0 25 50 75 100 125 150Time (hours)
Hy
dro
lysi
s (%
)
0 g/l
0.5 g/l
1 g/l
2.5 g/l
5 g/l
HA manure
-1
1
3
5
7
0 50 100 150 200 250Time (hours)
Hy
dro
lysi
s (%
)
0 g/l
0.5 g/l
1 g/l2.5 g/l
5 g/l
HA maize
Cellulose Hydrolysis
Humic Acids affecting cellulose hydrolysis
Results:
Fernandes et al., 2010 - Cellulases
- Fibrobacter succinogenes
- pH = 7
32
-1
1
3
5
7
0 25 50 75 100 125 150 175 200
Time (hours)
Hy
dro
lysi
s (%
)
0 g/l
0.5 g/l1 g/l
2.5 g/l5 g/l
FA manure
-1
1
3
5
7
0 5 10 15 20 25Time (hours)
Hyd
roly
sis
(%)
0 g/l0.5 g/l1 g/l2.5 g/l5 g/l
FA maize
Cellulose Hydrolysis
Fulvic Acids affecting cellulose hydrolysis
Results:
Fernandes et al., 2010
33
0
20
40
60
80
100
0 10 20 30 40 50Time (hours)
Hyd
roly
sis
(%)
0 g/l
0.5 g/l
1 g/l
2.5 g/l
5 g/l
HA manure
0
20
40
60
80
100
0 25 50 75 100 125Time (hours)
Hy
dro
lysi
s (%
)
0 g/l 0.5 g/l
1 g/l 2.5 g/l
5 g/l
HA maize
Tributyrin Hydrolysis
Humic Acids affecting tributyrin hydrolysis
Results:
Fernandes et al., 2010
34
What is the possible effect?
C
O
O-
O-
enzyme
cellulose
Ca 2+ Ca2+
- Cellulolytic enzymes scavenged by reactive functional
groups of humic substances (hydrolysis inhibition)
- Bivalent cations (Ca2+) mitigate inhibiting effect ? (Brons et
al., 1985; Ladd & Butler, 1970)
Effect of humic compounds on the
hydrolysis of lignocellulosic biomass?
35
How humic acid interfere cellulolytic
activity? (current research)
May Inhibit
Microbial Activity
May Inhibit Enzymatic
Activity
May Inhibit Functional
Gene Expression
May cover substrate to prevent microbial adhesion
Only hydrolysis? or more methanogenic subpopulations??
36
Turning biomass energy into a
gaseous fuel:
37
Na+ (CH3COO-)
CH4 HCO3
-
CO2
Na+
CO32-
Long live Henry’s law!!
Autogenerative high pressure digestion
(AHPD): Integrate biogas upgrading with
digestion in a single step
r = % of non-dissolved biogas
n = stoichiometric coefficient
P in bar
R = 8.3145*10-2 L Bar K-1mol-1
4 2( )* * *( )
lr
t l
VP nCH nCO R T
V V
Ralph Lindeboom, PhD thesis, 2014
38
Pre
ssure
(bar)
4
0
5
10
15
20
25
30
0 20 40 60 80 100 120
hours
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
7.8
Pressure pH
Which pressures are needed?
Lindeboom et al, 2012
Production of high pressure CH4 gas:
- Negligible water vapor
- Little CO2 (> 5 bar < 10%)
- Little if any H2S
- Injection in gas grid ? !!
39
Pre
ssure
(bar)
4
0
5
10
15
20
25
30
0 20 40 60 80 100 120
hours
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
7.8
Pressure pH
With active inoculum:
- 30 bars within few days
- Methanogenesis up to 100 bar!
Which pressures are needed?
Lindeboom et al, 2012
Production of high pressure CH4 gas:
- Negligible water vapor
- Little CO2 (> 5 bar < 10%)
- Little if any H2S
- Injection in gas grid ? !!
40
Pre
ssure
(bar)
4
0
5
10
15
20
25
30
0 20 40 60 80 100 120
hours
6
6.2
6.4
6.6
6.8
7
7.2
7.4
7.6
7.8
Pressure pH
With active inoculum:
- 30 bars within few days
- Methanogenesis up to 100 bar!
Which pressures are needed?
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200
Time (h)
Pre
ss
ure
(b
ar)
NaAc as feed
Lindeboom et al, 2012
Production of high pressure CH4 gas:
- Negligible water vapor
- Little CO2 (> 5 bar < 10%)
- Little if any H2S
- Injection in gas grid ? !!
41
Limiting factor: acidification (CO2)…
• Digestion of neutral, non-acidified compounds: pH ↓ • C6H12O6 + 2H2O 2CH3COO- + 2H+ + 4H2 + 2CO2
• VFA production and CO2 accumulation both lowers pH!
‘normal pH range CH4
production: 6-8 !’
pCO2 acidification
VFA acidification
Lindeboom et al, 2012, 2013
42
pH control using natural minerals
In-situ mineral
weathering
No need for NaOH dosing!
Wollastonite:
CaSiO3
Olivine:
Mg1.8Fe0.16Ni0.04SiO4
Lindeboom et al, 2013
4
5
6
7
8
0 24 48 72 96 120 144
pH
Time (h)
43
Addition of silicate minerals
88% CH4 + 12% CO2
50% CH4+ 50% CO2
Acetic acid
Glucose
CaSiO3(s)
Ca2+ + SiO2
CaCO3(s)
-H+
-CO2
Lindeboom et al, 2013
44
- influent feed pomp? - ΔP for membrane processes - ‘free’ injection in gas grid - etc.
Zagt et al., H2O, 2010-4
Pressure as additional energy source?
45
Conclusions
Maximising BMP requires better understanding hydrolysis
Cellulolytic and methanogenic (?) activity retarded by humic compounds
High pressure digestion technological feasible for biogenic CH4 production
AD technology world wide accepted for biomass energy recovery
Thanks for your attention!!
46
Acknowledgement
Claudia Pabon
Ralph Lindeboom
Tania Fernandes
Grietje Zeeman
Environmental Technology Lettinga Associates
Fondation
The TU Delft Group:
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