Ultimate and Proximate Analyses of Bamboo Samples

Ultimate and Proximate Analyses of Bamboo Samples



Sa.

Ultimate A. / wt-%

Proximate A. / wt-%

HHV

So.

C

H

N

S

O

M

Ash

VM

FC

MJ/kg

1

44.83

5.96

0.35

0.15

40.08

7.14

1.49

74.35

17.02

-

[1]

 

Sa.

Ultimate A. (wet free) / wt-%

Proximate A. (wet free) / wt-%

HHV

So.

C

H

N

S

O

M

Ash

VM

FC

MJ/kg

2

39.81

5.68

3.26

- 

31.32

- 

20.02

71.67

8.31

17.76

[2]

3

51.50

5.05

0.40

0.04

42.10

- 

0.90

81.60

17.50

19.69

[3]

4

48.76

6.32

0.20

- 

42.77

11.50

1.95

86.80

11.24

20.55

[4]

 

Sa.

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

Proximate A. / wt-%

HHV

So.

C

H

N

S

O

M

Ash

VM

FC

MJ/kg

5

50.52

6.04

0.58

0.09

42.80

6.14

1.95

77.16

14.75

-

[5]

6

45.67

5.32

0.35

0.28

48.38

9.45

1.84

73.42

15.29

-

[6]

7

42.80

6.30

0.35

- 

50.65

7.20

1.62

68.15

23.92

-

[6]

 

Sa.

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

Proximate A. (wet free) / wt-%

HHV

So.

C

H

N

S

O

M

Ash

VM

FC

MJ/kg

8

39.00

6.10

0.60

 -

54.30

 -

2.80

77.60

19.60

-

[7]

9

44.62

5.54

8.76

 -

41.08

16.86

8.12

76.43

15.46

-

 


[1] C. Chen, Y. Jin, Y. Chi. Effects of moisture content and CaO on municipal solid waste pyrolysis in a fixed bed reactor. Journal of Analytical and Applied Pyrolysis. 110. 2014.
[2] K. Phichai, P. Pragrobpondee, T. Khumpart, S. Hirunpraditkoon. Prediction Heating Values of Lignocellulosics from Biomass Characteristics. International Journal of Chemical and Molecular Engineering. 7, 7. 2013.
[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] S. A. Channiwala, P. P. Parikh. A unified correlation for estimating HHV of solid, liquid and gaseous fuels. Fuel. 81. 2002.
[5] A. O. Oyedun, T. Gebreegziabher, D. K. S. Ng, C. W. Hui. Mixed-waste pyrolysis of biomass and plastics waste – A modelling approach to reduce energy usage. Energy. 75. 2014.
[6] Mian Hu, Zhihua Chen, Shengkai Wang, Dabin Guo, Caifeng Ma, Yan Zhou, Jian Chen, Mahmood Laghari, Saima Fazal, Bo Xiao, Beiping Zhang, Shu Ma. Thermogravimetric kinetics of lignocellulosic biomass slow pyrolysis using distributed activation energy model, Fraser–Suzuki deconvolution, and iso-conversional method. Energy Conversion and Management. 118. 1-11. 2016.
[7] L. E. Hernandez-Mena, A. B. A. Pecora, A. L. Beraldo. Slow pyrolysis of bamboo biomass: Analysis of biochar properties. Chem Eng Trans 2014;37:115–20.

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