This document describes a methodology for estimating input parameters for the Anaerobic Digestion Model 1 (ADM1) using laboratory-scale batch testing of methane production. The methodology involves a two-stage process of biochemical fractionation using elemental analysis and kinetic fractionation by analyzing experimental methane production data. The parameters estimated include biomass composition and hydrolysis/fermentation kinetics. Testing of food waste and green waste showed that multiple fractions were needed to accurately model food waste kinetics while a single fraction sufficiently modeled green waste degradation kinetics. The goal is to validate the estimation procedure using continuous laboratory systems and co-digestion behaviors.

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Estimation of the ADM1 input parameters for
modelling the anaerobic digestion of waste
materials using laboratory scale batch testing
of methane production
International Conference on Advances in Energy
Research
10-12th December 2013
Indian Institute of Technology Bombay
Davide Poggio, Mark Walker, William Nimmo and Mohamed Pourkashanian
m.walker@leeds.ac.uk

2. Introduction

Anaerobic Digestion Model 1 (ADM1) is the current benchmark in modelling of
AD and biogas production

ADM1 is a large, complex model (35 states, 29 conversion processes, 100+
parameters) therefore feedstock characterisation and parameter estimation is
important for each application

Previous methods used;

Literature data for similar substrate,

direct analysis of the biochemical fractions (Carbohydrate, protein, fat…)

Kinetic based methods

In this paper a methodology for the estimation of the feedstock biomass
composition and hydrolysis/fermentation kinetics is presented

Method based on a hybrid biochemical and kinetic approach

Parameters estimated using statistical analysis of batch methane production
tests
Mark Walker, ICAER, 10-12th December 2013, IITB

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Methods

4. Outline
Mark Walker, ICAER, 10-12th December 2013, IITB

5. Kinetic Models
Model
Fractionation of COD and Kinetic Equations
1 Particulate
Increasing model
complexity
& 1 Soluble
•
More parameters
estimated
•
Better fit
•
1 Particulate
More uncertainty
2 Particulate
2 Particulate
& 1 Soluble
Mark Walker, ICAER, 10-12th December 2013, IITB

6. Biomass Feedstocks
Food Waste
(Source segregated)
TS = 30.1%
VS = 27.3%
Green Waste
(Source segregated)
TS = 39.8%
VS = 25.9%
Mark Walker, ICAER, 10-12th December 2013, IITB

7. Laboratory equipment
 15 x 0.5-litre
heated, stirred
reactors
 Automated gas
flow monitoring
 Carbon dioxide
absorption
Mark Walker, ICAER, 10-12th December 2013, IITB

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Results and Discussion

9. Biochemical Fractionation
FW
COD
(gCOD/gVS)
1.73
GW
1.55
Mark Walker, ICAER, 10-12th December 2013, IITB

10. Results
FW
GW
Cellulose
Mark Walker, ICAER, 10-12th December 2013, IITB

11. Kinetic Fractionation - GW
1 Particulate
Fraction
Model
1 particulate
X^2
0.058
1 Particulate & 1
Soluble Fraction
Std. Error
95% confidence
0.249
0.623
0.99 %
3.38 %
0.244 - 0.254
0.581 - 0.664
fd
fS
khyd
0.250
0.216
0.347
0.66%
3.42%
3.42%
0.799 - 0.820
0.285 - 0.326
0.345 - 0.395
fd
fXr
khyd,r
khyd,s
0.246
0.216
>20
0.336
NA
NA
unbounded
NA
NA
NA
unbounded
NA
0.040
2 Particulate
Value
fd
khyd
1 Particulate & 1
Soluble
Parameter
0.0

12. Kinetic Fractionation - GW
1 Particulate
1 Particulate & 1 Soluble
χ2 = 0.53
χ2 = 0.23
Max. Std. Error = 2.5%
Max. Std. Error = 3.4%
2 Particulate
2 Particulate & 1 Soluble
χ2 = 0.17
χ2 = 0.16
Max. Std. Error = 6.6%
Max. Std. Error = 23.2%
Mark Walker, ICAER, 10-12th December 2013, IITB

13. On-going work
Modelling Semi-Continuous AD
Food Waste
Green Waste
2 Particulate Fraction Model
1 Particulate & 1 Soluble
Fraction Model
Under-prediction of fast
kinetics (no soluble fraction)
Over-prediction of fast
kinetics (overestimated
soluble fraction)
Mark Walker, ICAER, 10-12th December 2013, IITB

14. Conclusion
 A Procedure for the Anaerobic Digestion Model 1 (ADM1) characterization of
a biomass feedstock has been described
 Two stage process;
 Biochemical fractionation using elemental analysis
 Kinetic fraction using experimental data methane production tests
 Biochemical fractionation of green waste samples resulted in high predicted
level of lipids → modification of the method required in high lignin samples
 Statistical analysis permitted the identification of the most appropriate model
and the relevant parameters to describe the anaerobic digestion process.
 Food wastes is a more complex substrate requiring at least two fractions to
describe the kinetics, while only one fraction gives a satisfactory description
for green waste degradation.
 Future works will include the validation of the procedure in laboratory
continuous systems and investigation into the co-digestion behaviour
Mark Walker, ICAER, 10-12th December 2013, IITB

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Thank you!
Any questions?