Ultimate and Proximate Analyses of Almond Shells Samples

Ultimate and Proximate Analyses of Almond Shells Samples




Sa.

Ultimate A. (wet free) / wt-%

Proximate A. (wet free) / wt-%

HHV

So.

C

H

N

S

O

M

Ash

VM

 FC

MJ/kg

1

44.09

5.59

0.15

2.96

45.98

2.27

1.23

78.29

20.48

-

[1]

2

44.98

5.97

1.16

0.02

42.27

- 

4.81

73.45

21.74

19.38

[2]

3

48.60

5.99

1.00

0.05

41.10

- 

3.30

74.90

21.80

19.42

[3]

4

49.30

5.97

0.76

0.04

40.64

6.93

3.29

76.00

20.71

19.49

[4]

 

Ultimate A. (wet and ash free) / wt-%

 

 

 

C

H

N

S

O

5

54.80

7.50

0.30

 

37.40

 

2.60

91.80

5.60

-

[5]

6

46.35

5.67

0.30

0.22

47.46

8.68

2.20

82.00

15.80

19.38

[6],[7]


[1] F. Kartal, U. Özveren. A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus. Energy. 209.2020.
[2] S. Gaur, T. B. Reed. Thermal Data for Natural and Synthetic Fuels. CRC Press. 2020.
[3] H. Qian, W. Zhu, S. Fan, C. Liu, X. Lu, Z. Wang, D. Huang, W. Chen. Prediction models for chemical exergy of biomass on dry basis from ultimate analysis using available electron concepts. Energy. 131. 2017.
[4] T. R. Miles, L. L. Baxter, R. W. Bryers, B. M. Jenkins, L. L. Oden. Alkali deposits found in biomass power plants: a preliminary investigation of their extent and nature.
[5] V. Dhyani, T. Bhaskar. A comprehensive review on the pyrolysis of lignocellulosic biomass. Renewable Energy. 2017.
[6] R. García, C. Pizarro, A. G. Lavín, J. L. Bueno. Spanish biofuels heating value estimation. Part I: Ultimate analysis data. Fuel. 117. 2014.
[7] R. García, C. Pizarro, A. G. Lavín, J. L. Bueno. Spanish biofuels heating value estimation. Part II: Proximate analysis data. Fuel. 117. 2014.

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