| Literature DB >> 30781741 |
Besma Khiari1, Marwa Moussaoui2, Mejdi Jeguirim3.
Abstract
This paper is part of a sustainable development approach, the aim being to develop a thermochemical energy recovery path while reducing the amount of tomato waste issued from agro-industrial units. The thermal process may contribute to an environmentally friendly management and help tomato processing industries creating new economic profitable circuits in an increasingly competitive context. The adopted approach was to follow the operating conditions needed for a complete thermal degradation through a thermal and kinetic analyses. The results of the tomato waste characterization confirmed their suitability to a thermochemical processing with high volatiles and fixed carbon and interesting high heating values comparable to sawdust biomass. We were able to isolate of the decomposition domains and extract kinetic parameters. Three kinetic models were applied; Flynn⁻Wall⁻Ozawa (FWO) simulated the best the combustion process. Calculated curves were validated by the first order (n = 1) model except for the slow heating rate of 5 °C/min which was fitted by the contracted cylinder model. The conclusions of this paper could help in optimizing the combustion process in order to achieve high energy recovery from tomato residues. Obtained kinetic data would help in the design of combustion reactors.Entities:
Keywords: combustion; kinetics; thermal analysis; tomato waste
Year: 2019 PMID: 30781741 PMCID: PMC6416722 DOI: 10.3390/ma12040553
Source DB: PubMed Journal: Materials (Basel) ISSN: 1996-1944 Impact factor: 3.623
Physical and chemical properties of tomato waste.
| Parameter | Jeguirim et al. [ | Kraiem et al. [ | Jeguirim et al. [ | Mangut et al. [ | Yargıç et al. [ |
|---|---|---|---|---|---|
| Moisture (%, wb) | 10 | 10 | 8 | 4.22 | 7.18 |
| Ash (%, db) | 11 | 11 | 8 | 4.58 | 4.49 |
| CF (%, db) | - | - | 8 | 12.51 | 10.98 |
| Volatiles (%, db) | - | - | 76 | 78.68 | 77.35 |
| ρ (kg·m−3) | 52.2 | 52.2 | 50 | - | - |
| HHV (MJ·kg−1) | 19.5 | 19.5 | 19.5 | 22.4 | 20.47 |
| Energy density (GJ·m−3) | 10.2 | 10.2 | 9.75 | - | - |
| N (%, db) | 1.5 | 1.5 | 1.6 | 2.41 | 3.78 |
| S (%, db) | 0.29 | 0.3 | 0.35 | 0.038 | - |
| K (%, db) | 0.03 | 0.03 | - | - | - |
| C (%, db) | - | 54.2 | 59.4 | 49.52 | 49.69 |
| H (%, db) | - | 7 | 7.6 | 6.74 | 7.43 |
| O (%, db) | - | 20.2 | 23.4 | - | 39.1 |
| Cl (g·kg−1) | 5.75 | - | - | - | - |
| Ca (g·kg−1) | 1.45 | 8.1 | - | - | - |
| Si (g·kg−1) | 0.19 | 1.067 | - | - | - |
| Na (g·kg−1) | 0.35 | 1.932 | - | - | - |
| P (g·kg−1) | 0.93 | 5.1919 | - | - | - |
| Mg (g·kg−1) | 0.59 | 3.311 | - | - | - |
| Al (g·kg−1) | 0.12 | 0.641 | - | - | - |
| Fe (g·kg−1) | 0.10 | 0.556 | - | - | - |
| Mn (g·kg−1) | 0.09 | 0.05 | - | - | - |
Fatty acid Composition of biomass, obtained by mechanical extraction (%W/W db).
| Fatty Acid Composition | Tomato Seeds [ | Olive Seeds [ | Grape Seeds [ |
|---|---|---|---|
| Palmitic acid C 16:0 | 14 | 11.5 | 6.6–11.6 |
| Stearic acid C 18:0 | 5 | 2.5 | 3.5–5.4 |
| Oleic acid C 18:1 | 21 | 75.5 | 14.0–20.9 |
| Linoleic acid C 18:2 | 57 | 7.5 | 61.3–74.6 |
| Linoleinic acid C 18:3 | 1 | 1 | 0.3–1.8 |
| Myristic acid C 14:0 | - | 0 | 0–0.17 |
| Anarchic acid C 20:0 | - | 0.5 | 0.1–1.7 |
| Others | 2 | - | - |
Standard methods of physical and chemical characterization.
| Parameter | Analytical Method |
|---|---|
| Sample Preparation | UNI EN 14780:2011 |
| Moisture content | UNI EN 14774:2009 |
| Ash | UNI EN 14775:2010 |
| HHV, LHV | UNI EN 14918:2010 |
| C, H, N, S, O | UNI EN 15104:2011 |
Examples of kinetic models f(X) and their integral forms g(X).
| Model | f(X) | g(X) |
|---|---|---|
| 1st order | 1 − X | −ln(1 − X) |
| Pseudo nth order | (1 − X)n | [1/(n−1)][(1 − X)(1−n) − 1] |
| Contracted cylinder | 2(1 − X)1/2 | 1 − (1 − X)1/2 |
| Contracted Sphere | 3(1 − X)2/3 | 1 − (1 − X)1/3 |
| Energy law | νX(ν−1)/ν | X1/ν |
| Avrami-Erofe’eve | p(1 − X)[−ln(1 − X)](p−1)/p | [−ln(1 − X)]1/p |
| Extended Prout-Tompkins | (1 − X)nXm | No analytical solution |
| 1D diffusion | ½X − 1 | X² |
| 2D diffusion | [−ln(1 − X)]−1 | (1 − X)ln(1 − X) + X |
| 3D diffusion (Jander) | [3/2(1 − X)2/3][1 − (1 − X)1/3]−1 | [1 − (1 − X)1/3]2 |
| 3D diffusion (G–B) | 3/2[(1 − X)−1/3− 1] | 1 − 2X/3 − (1 − X)2/3 |
g(X) is the integral function of
Isoconversional Kinetic methods used in evaluating activation energy study.
| Method | Expression | Plots | Ref |
|---|---|---|---|
| Friedman |
| [ | |
| FWO |
| [ | |
| KAS |
| [ |
Proximate analysis, ultimate analysis and energy content.
| Water Content (%) | Volatiles (%) | Fixed Carbon (%) | Ash (%) | ρ (kg/m3) | LHV (MJ/kg) | Energy Density (MJ/m3) | C (%) | H (%) | O (%) | N (%) | S (%) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 8 | 76 | 8 | 8 | 50 | 19.5 | 975 | 54.2 | 7 | 20.2 | 1.5 | 0.3 |
Figure 1Profiles of tomato waste combustion for different heating rates.
Figure 2FWO, KAS and Friedman kinetic linear diagrams.
Activation energies Ea (kJ/mol) and correlation coefficients R² calculated by KAS, FWO and Friedman models.
| Model | KAS | FWO | Friedman | |||
|---|---|---|---|---|---|---|
| X | Ea | R² | Ea | R² | Ea | R² |
| 10 | 132.53 | 0.95 | 125.18 | 0.96 | 134.30 | 0.88 |
| 15 | 145.79 | 0.88 | 146.78 | 0.80 | 168.80 | 0.92 |
| 20 | 155.50 | 0.82 | 156.10 | 0.84 | 148.15 | 0.84 |
| 25 | 152.14 | 0.81 | 149.98 | 0.83 | 170.05 | 0.86 |
| 30 | 174.77 | 0.88 | 186.46 | 0.83 | 169.62 | 0.89 |
| 35 | 206.93 | 0.84 | 190.40 | 0.87 | 194.37 | 0.91 |
| 40 | 195.81 | 0.94 | 195.15 | 0.94 | 195.67 | 0.99 |
| 45 | 156.14 | 0.80 | 128.68 | 0.81 | 125.58 | 0.64 |
| 50 | 165.27 | 0.86 | 150.52 | 0.93 | 186.08 | 0.99 |
| 55 | 492.12 | 0.96 | 449.40 | 0.99 | 500.48 | 0.83 |
| 60 | 494.97 | 0.84 | 480.89 | 0.84 | - | - |
| 65 | 447.47 | 0.63 | 437.32 | 0.85 | - | - |
| 70 | 380.93 | 0.79 | 372.82 | 0.80 | - | - |
| 75 | 200.77 | 0.98 | 201.59 | 0.98 | - | - |
| 80 | 112.88 | 0.99 | 118.22 | 0.99 | - | - |
| 85 | 85.38 | 0.96 | 92.38 | 0.97 | - | - |
| Average | 231.21 | 223.87 | 199.31 | |||
Figure 3Activation energy variation according to KAS, FWO and Friedman models.
Figure 4Mass loss fraction validation profiles.
Figure 5Model validation for 5 °C/min heating rate with n = 1/3 and n = 1 kinetic models.