Production of versatile char via lignite coal and leonardite pyrolysis
Bibliographic record
Abstract
The effects of climate change due to anthropogenic activities have generated discussions on controlling greenhouse gas emissions. As a result, coal is predicted to lose prominence in power generation due to the greenhouse gas emissions associated with its combustion. Therefore, this research investigates char production from coal to provide alternate applications for coal postcombustion. Lignite coal and leonardite from the Poplar River mine in Saskatchewan, Canada, were characterized using proximate and ultimate analyses, pore structural analyses, X-Ray Fluorescence (XRF), Scanning Electron Microscope (SEM), and Fourier Transform Infrared (FTIR) spectroscopy to establish their physical and chemical properties. They were then used as feedstocks in the pyrolysis experiments to produce versatile char for different applications. Temperature and time were varied from 450 °C to 850 °C, and 30 minutes to 120 minutes, respectively, and their effects on the products’ distribution and characteristics were investigated. The results were subjected to statistical analysis using a two-way analysis of variance and pairwise multiple comparison tests to validate the observed trends. The catalytic effects of potassium, calcium, and iron on lignite and leonardite pyrolysis and their product characteristics were also investigated. The investigations were capped off with a kinetic study using the Coats-Redfern model-fitting approach. The ultimate and XRF analyses showed that lignite and leonardite possess similar elemental compositions. However, their proximate results revealed significant differences between them. Lignite possessed higher fixed carbon, 29.32 wt%, than leonardite, 16.65 wt% (air-dry basis), while leonardite had a higher volatile matter, 40.12 wt%, than lignite, 32.26 wt% (air-dry basis), which was attributed to the oxidation process leading to leonardite formation. The structures of lignite and leonardite were similar under the scanning electron microscope, while the FTIR and pore analysis also revealed similar identities. The product distribution showed that the chars produced from lignite and leonardite maximized at 450 °C and decreased as the temperatures increased due to higher thermal energies, allowing the various pyrolysis reactions to initiate and intensify. Consequently, the gas yields increased with temperature and maximized at 850 °C. The liquid yields peaked at 650 °C and decreased thereafter when the temperatures were increased due to the predominance of depolymerization reactions at lower temperatures, and cracking reactions at higher temperatures, respectively. The effect of time on the products’ yields was not very significant, especially at higher temperatures, because the reactions were faster. The analysis of variance (ANOVA) and multiple comparison test revealed that char properties, including pore volume, surface area, volatile matter, fixed carbon, H/C, and O/C ratios, significantly depended on temperature and time. Additionally, the structure of the chars, analyzed with Raman spectroscopy, revealed the evolution of the char’s structure into a more aromatic structure with temperature and time. Preliminary catalytic studies conducted using K, Ca, and Fe catalysts showed that K increased char yields in both lignite and leonardite, while Ca and Fe increased gas yields in leonardite and lignite, respectively. However, the Ca and Fe catalysts reduced the activation energies at high temperatures, while the K catalyst increased the activation energy, thereby acting as an inhibitor. The kinetic studies on the non-catalytic pyrolysis showed that the activation energy increased with the order of reaction. However, the first-order approximation best predicted the devolatilization rates in both lignite and leonardite, with absolute average deviations (AADs) less than 2%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".