Development and optimization of pyrolysis biochar production systems towards advanced carbon management
Bibliographic record
Abstract
About 10% of the 60 Petagram (Pg)-Carbon fixed annually through worldwide photosynthetic activity ends up in agricultural residues. Through a heat-induced chemical conversion process such residues can be converted to biochar, a form of carbon that can be employed as a soil amendment, thereby providing long-term storage of carbon in soil. In this application, it has the ability to both reduce GHG emissions and enhance soil structure, moisture and nutrient retention, thereby also addressing global food security issues by improving soil fertility and crop yields.Dealing with several aspects of carbon management and resulting mitigation of GHG emissions, the current project sought to maximize biochar yield from microwave-assisted pyrolysis of maple (Acer L.) wood biomass. Microwave-assisted heating processes are known to be faster and more energy-efficient, yielding higher quality products than conventional methods. Volumetric, spectral and thermodynamic analysis of biochar developed through microwave-assisted pyrolysis showed it to exhibit greater porosity, lower reflectance and greater exothermic energy, and therefore greater overall quality than conventionally-produced biochar. This study also showed this microwave-assisted process to be capable of both producing high quality char and synthesize value-added carbon products. A three-dimensional finite element numerical model developed to optimize the primary parameters was instrumental in optimizing microwave pyrolytic process parameters so as to maximize biochar yields. The influence of selective heating phenomena on pyrolysis conditions was an important factor maximizing biochar yields arising from microwave-assisted pyrolysis of biomass. The application of a doping agent (i.e., microwave receptor) such as char enhanced the severity of the pyrolysis process by better temperature distribution within the biomassBased on numerical models and simulation data, the design of a microwave-assisted pyrolysis reactor affording optimal performance in terms of biochar yields was experimentally validated in a custom-built lab-scale unit. Biochar yield decreased with increasing pyrolysis temperature and time while doping ratio had no significant effect on biochar yields. The maximum predicted yield occurred for an microwave-assisted pyrolysis process optimized at the pyrolysis temperature of 250°C, reaction time of 1 min and doping ratio of 16%.The biochar resulting from microwave-assisted pyrolysis was characterized through various physical and chemical analyses: hyper-spectral imaging, pycnometry, proximate analyses, Scanning Electron Microscopy, Fourier Transform Infrared Radiation and Differential Scanning Calorimetry. The biochar's structural development was directly influenced by the pyrolysis conditions of temperature, residence time and doping ratio.In light of GHG emission balances and the economic feasibility of biochar production, a life cycle analysis was important in estimating the benefits of biochar systems over a wide range of biomass, process and application scenarios. The life cycle analysis determined the sustainability — in terms of reducing the undesired effects of pyrolysis biochar systems — of the proposed process for different types of agricultural residues in Quebec, Canada. This would help farmers to assess the economic vs. environmental benefits of employing this technology to put the agricultural waste they generate to optimal use. The economic viability of the pyrolysis-biochar system was found to be largely dependent on the costs of feedstock production, pyrolysis, and the value of carbon offsets. Therefore, the conclusions drawn from such a life cycle analysis would represent a useful tool in assessing the potential of biochar systems worldwide.
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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) | 0.000 | 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".