Influence of Intrinsic Physicochemical Properties of Agroforestry Waste on Its Pyrolysis Characteristics and Behavior
Abstract
:1. Introduction
2. Materials and Methods
2.1. Feedstock Preparation and Characterization
2.2. Pyrolysis Experiments and Thermogravimetric Analysis
2.3. Kinetic Analysis
2.4. Mechanism Model f(α) Prediction
2.5. Data Analysis
3. Results and Discussion
3.1. Intrinsic Physicochemical Properties of Samples
3.2. TG and DTG Curves
3.3. Pyrolysis Characteristics
3.4. Correlation between the Intrinsic Physicochemical Properties and Thermal Characteristics
3.5. Kinetic Parameter Analysis
3.5.1. Ea Analysis
3.5.2. Pre-Exponential Factors (A) Analysis
3.5.3. Estimation of the Reaction Mechanism [f(α)]
4. Conclusions
- (1)
- There were significant differences in the intrinsic physicochemical properties of the three agroforestry wastes. The rich lignocellulose content; low moisture, ash, and N element content; and good thermophysical properties indicate that the agroforestry waste has good prospects for pyrolysis.
- (2)
- The intrinsic physicochemical properties of agroforestry waste have a significant influence on their pyrolysis characteristics. Moisture is positively correlated with the weight loss in the first stage. The second stage is the main stage of pyrolysis, and the pyrolysis characteristics are influenced by the combination of several intrinsic physicochemical properties. The content of fixed carbon was positively correlated with Prate. WL2 was positively correlated with C and cellulose content and negatively correlated with O content. R2 was positively correlated with the sum of cellulose and lignin content. RSS was positively correlated with lignin content. In addition, C0 and D also had an effect on Prate, but not significantly at the lower heating rate conditions. This indicates that the intrinsic physicochemical properties of the biomass on the pyrolysis characteristics are also influenced by pyrolysis conditions.
- (3)
- The Ea[min] values were significantly positively correlated with C0 and negatively correlated with D. The Ea[mean] and Ea[max] were significantly positively correlated with the sum content of cellulose and lignin, indicating that the contents of cellulose and lignin determine the energy required for the pyrolysis process of agroforestry waste.
- (4)
- Vast variations in A value and several reaction models (diffusion model, growth model, and geometrical contraction model) involved in the pyrolysis process indicate that the pyrolysis of agroforestry waste is a complex process due to the heterogeneity of its intrinsic physicochemical properties.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Kinetic Models | f(α) | g(α) | |
---|---|---|---|
Nucleation models or growth model | |||
Power law | P2 | ||
P3 | |||
P4 | |||
Avarami–Erofeev | A2 | ||
A3 | |||
A4 | |||
Diffusion model | |||
One-dimensional diffusion | D1 | ||
Two-dimensional (Valensi model) | D2 | ||
Diffusion control (Jander model) | D3 | ||
Diffusion control (Ginstling model) | D4 | ||
Order-based model | |||
First order | F1 | ||
Second order | F2 | ||
Third order | F3 | ||
Geometrical contraction model | |||
Contracting area | R2 | ||
Contracting sphere | R3 |
Samples | RS | ATB | PS | |
---|---|---|---|---|
Proximate analysis (%) | water | 5.01 ± 0.08 a | 2.63 ± 0.12 b | 2.24 ± 0.33 b |
ash | 3.49 ± 0.03 a | 2.32 ± 0.02 b | 1.55 ± 0.02 c | |
volatile matter | 80.02 ± 0.54 b | 80.0 ± 0.42 b | 82.72 ± 0.39 a | |
fixed carbon | 11.47 ± 0.23 c | 15.04 ± 0.17 a | 13.49 ± 0.16 b | |
Ultimate analysis (%) | C | 42.24 ± 0.02 c | 46.19 ± 0.08 b | 51.27 ± 0.07 a |
H | 5.52 ± 0.03 c | 5.69 ± 0.06 b | 6.55 ± 0.01 a | |
O | 47.79 ± 0.05 a | 45.25 ± 0.17 b | 40.33 ± 0.06 c | |
N | 0.97 ± 0.01 a | 0.55 ± 0.01 b | 0.30 ± 0.02 c |
Samples | RS | ATB | PS | |
---|---|---|---|---|
Lignocellulosic contents (%) | cellulose | 41.08 ± 2.26 c | 46.22 ± 1.30 b | 54.69 ± 2.01 a |
hemicellulose | 27.95 ± 5.13 a | 16.68 ± 0.55 b | 11.08 ± 2.65 c | |
lignin | 16.05 ± 3.08 c | 30.73 ± 0.97 a | 26.43 ± 1.22 b | |
Thermophysical properties | K (W·m−1·°C−1) | 0.112 ± 0.005 a | 0.110 ± 0.005 a | 0.116 ± 0.004 a |
C0 (MJ·m−3·°C−1) | 0.539 ± 0.013 b | 0.652 ± 0.027 a | 0.606 ± 0.017 a | |
D (m2·s−1) | 0.208 ± 0.006 a | 0.168 ± 0.005 c | 0.191 ± 0.002 b |
Pyrolysis Stages | RS | ATB | PS | |||||||
---|---|---|---|---|---|---|---|---|---|---|
5 | 10 | 15 | 5 | 10 | 15 | 5 | 10 | 15 | ||
The initial stage | FT1 (°C) | 176 | 178 | 190 | 165 | 170 | 180 | 160 | 162 | 172 |
R1 (°C) | 146 | 148 | 160 | 135 | 140 | 150 | 130 | 132 | 142 | |
WL1 (%) | 10.39 | 8.34 | 6.46 | 7.16 | 4.35 | 3.4 | 6.79 | 6.69 | 2.34 | |
The second stage | FT2 (°C) | 353 | 362 | 380 | 373 | 380 | 395 | 378 | 380 | 402 |
R2 (°C) | 177 | 184 | 190 | 208 | 210 | 215 | 218 | 218 | 230 | |
WL2 (%) | 54.06 | 55.28 | 58.3 | 57.3 | 57.62 | 58.88 | 62.2 | 63.37 | 64.69 | |
PT (°C) | 295.99 | 306.45 | 304.91 | 335.84 | 342.43 | 343.79 | 351.28 | 358.62 | 358.12 | |
Prate (%/°C) | 0.9 | 1.77 | 2.6 | 0.68 | 1.25 | 1.76 | 0.79 | 1.46 | 2.23 | |
The final stage | R3 (°C) | 447 | 438 | 420 | 427 | 420 | 405 | 422 | 420 | 398 |
WL3 (%) | 25.27 | 20.62 | 23.94 | 14.28 | 13.34 | 11.57 | 12.35 | 11.01 | 10.42 | |
WLtotal (%) | 90.15 | 84.25 | 88.71 | 78.75 | 75.31 | 73.85 | 81.34 | 81.07 | 77.45 | |
RSS (%) | 9.85 | 15.75 | 11.29 | 21.24 | 24.69 | 26.15 | 18.66 | 18.93 | 22.55 |
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Liu, H.; Zhao, B.; Zhang, X.; Zhang, Y. Influence of Intrinsic Physicochemical Properties of Agroforestry Waste on Its Pyrolysis Characteristics and Behavior. Materials 2023, 16, 222. https://doi.org/10.3390/ma16010222
Liu H, Zhao B, Zhang X, Zhang Y. Influence of Intrinsic Physicochemical Properties of Agroforestry Waste on Its Pyrolysis Characteristics and Behavior. Materials. 2023; 16(1):222. https://doi.org/10.3390/ma16010222
Chicago/Turabian StyleLiu, Hui, Baowei Zhao, Xin Zhang, and Yin Zhang. 2023. "Influence of Intrinsic Physicochemical Properties of Agroforestry Waste on Its Pyrolysis Characteristics and Behavior" Materials 16, no. 1: 222. https://doi.org/10.3390/ma16010222