Application of ADM1 model for simulation of organic solid waste

Parameters

Middle

Minimum Maximum

Stand. Dev.

Num. samples

Sludge

pH

7.3

6.7

7.9

0.34

36

NH4+ (mg N/l)

3.9

1

13

4

24

TKN (mg N/l)

43.1

31.2

49.9

8.23

16

COD (mg COD/l)

670.7

596.8

748

44.49

16

Ptot (mg P/g TS)

603.4

241.7

770.6

149.73

10

TS (g/l)

35.6

26.6

47.5

4.67

36

TVS (g/l)

23.1

17.2

31.1

3.05

36

TVS sludge (%ST)

64.8

58.3

80.9

4.35

36

Flow (m3/ day)

0.019

0.019

0.019

0.00

45

Waste

TKN (mg N/l)

33.3

21.9

53.5

8.30

13

TCOD (mg COD/l)

996.2

829.7

1124.4

78.26

16

Ptot (mg P/g ST)

831.1

183.3

1540.9

411.99

11

TS (g/l)

160.2

72

269.9

56.42

38

TVS (g/l)

141.6

61.5

245.5

51.07

38

TVS (%TS)

89.4

73.7

94.7

4.28

38

Flow (m3/ day)

0.0032

0.0023

0.0036

0.00

45

Waste mixed with sludge

TKN (mg N/l)

41,7

29,9

50,4

TCOD (mg COD/l)

717,6

630,3

802,2

Ptot (mg P/g ST)

636,2

233,3

881,5

TS (g/l)

53,5

33,1

79,5

TVS (g/l)

40,2

23,6

62,0

TVS (%TS)

68,3

60,5

82,9

Waste (m3/day)

0.0032

0.0023

0.0036

Table 2. Influent characteristics

Parameters

Middle

Minimum

Maximum

Stand. Dev.

Num. samp

pH

7.84

7.6

8.1

0.10

44

NH4+ (mg N/l)

1022.1

900

1140

70

24

TKN (mg N/l)

37.8

28.7

49.1

5.45

9

TCOD(kg COD/m3)

22.2

18.3

24.7

1.92

16

SCOD (kg COD/m3)

4,6

2

7

2.07

5

Ptot (mg P/g ST)

752.2

383

1080.8

181.22

12

TS (g/l)

33.1

26.3

52.3

5.01

40

TVS (g/l)

18.9

15.5

26.8

2.18

40

TVS (% TS)

57.2

50

64.3

3.82

40

VFA (mg COD/l)

50.7

7.0

110.3

26.47

36

TA at pH 6 (mg CaCO3/l)

2466.7

2181.5

2911

186.67

44

TA at pH 4 (mg CaCO3/l)

4005.5

3806.4

4356

135.07

44

effluent flow (m3/day)

0.0225

0.0225

0.0225

0.00

45

Table 3. Effluent characteristics

Parameters
Biogas volume
(m3/day)

Подпись: Middle Minimum Maximum Stand. Dev. Num. samp 0.431 0.153 0.728 0.16 31 0.51 0.26 1.06 0.16 29 0.96 0.34 1.62 0.35 31 60.6 55 65 2.22 40 39.4 35 45 2.22 40 0.3 0.09 0.44 0.10 31 0.17 0.06 0.28 0.06 31 440 200 1044 204.91 31 SGP (m3 biog/kg TVS)
GPR

(m3 biogas/m3 day)

% CH4 (%)

% CO2 (%)
Volume of CH4
(m3/day)
Volume of CO2
(m3/days)

H2S (ppm)

Kinetic

Names

Units

Initial values

Initial

Estimate

parameter

used in

values

d values

s

ADM1

Kdis

Disintegration constant

Day-1

0.5b

0.7

0.7

Khyd. Ch

Carbohydrate hydrolysis

Day-1

10b

1.25a

1.0

Khyd. Pr

constant

Day-1

10b

0.5a

0.7

Khyd. Li

Proteins hydrolysis

Day-1

10b

0.4a

1.0

Table 4. Characteristics of biogas production

constant

Lipids hydrolysis

constant

a Middle values obtained from (Mata-Alvarez, 2003) b Values obtained from (Batstone and Keller, 2003)

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Table 5. Initial and estimated values of kinetic parameters

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Fig. 8. Comparison between the simulation and the experimental TVFA

However the simulated results of SCOD are somehow underestimated in comparison with the experimental ones. This may be explained by the fact that the substrate distribution between proteins, carbohydrates and lipids was not measured but default model values were adopted for this parameter.

The simulated TVFA results show good digester stability and are in good agreement with the experimental ones as well.

Figure 9 shows variation of the experimental and simulated results of total biogas volume produced, which depends on the nature, the composition and the biodegradability of solids. In this case, mass loading fluctuate as shown by the ORL, it should be underlined that the main objective of these experiments was to increase the ORL to the practical limits in order to treat a maximum quantity of solid waste however it was difficult to maintain it constant. Consequently these variations condition the tendency of biogas volume produced variation. The limitations of ADM1 imply that the simulated biogas production follows an average course; therefore, the simulated data overlaps partially the experimental values.

Figure 10 shows the experimental and simulated results of biogas production. The biogas is composed principally of methane and carbon dioxide and a small percentage of hydrogen. It can be noticed that the simulated results are in good agreement with the experimental ones. A similar remark concerning the average course of the curve can be held as well. Moreover, they show a good stability in the operating of the reactor

To have a clear picture of what is happening within the system, inorganic carbon (IC) and inorganic nitrogen (IN) as well as pH, were represented on the same graph as presented in Figure 11.

Since pH is approximately equal to 8, IC represents alkalinity. Any variation in alkalinity is due to neutralisation of VFA, if accumulated. Furthermore, alkalinity or IC is more sensitive to VFA accumulation than pH and therefore more reliable.

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4

 

It is noted that in this study, the simulated results show an acceptable fit for Total chemical oxygene demand (COD), biogas volume and composition, pH and inorganic nitrogen (IN). However, for inorganic carbon (IC), the simulated results do not show a good fit. It was confirmed that IC or bicarbonate alkalinity is a very sensitive parameter to volatile fatty acids (VFA) accumulation, compared to pH variations and hence it can be used as a monitoring parameter.