Self-Sustaining Smoldering Combustion: A Novel Remediation Process for Non-Aqueous-Phase Liquids in Porous Media
Bibliographic record
Abstract
Smoldering combustion, the slow burning process associated typically with porous solids (e.g., charcoal), is here proposed as a novel remediation approach for nonaqueous phase liquids (NAPLs) embedded in porous media. Several one-dimensional vertical smoldering experiments are conducted on quartz sand containing fresh coal tar at an initial concentration of 71 000 mg/kg (approximately 25% saturation) and employing an upward darcy air flux of 4.25 cm/s. Following a short-duration energy input to achieve ignition at the lower boundary, a self-sustaining combustion front is observed to propagate upward at 1.3 x 10(-2) cm/s. The process is self-sustaining because the energy released during NAPL smoldering is efficiently trapped and recirculated by the soil matrix, preheating the NAPL ahead of the reaction front. The smoldering process is observed to self-terminate when all of the NAPL is destroyed or when the oxygen source is removed. Pre- and post-soil analysis revealed that NAPL smoldering reduced the concentration of total extractable petroleum hydrocarbons (TPH) from 38 000 mg/kg to below detection limits (< 0.1 mg/kg) throughout the majority of the column. A comparable experiment in which conductive heating is applied in the absence of smoldering demonstrates a 6-fold reduction in the net energy in the system and residual TPH values of 2000-35 000 mg/kg. A further repeat in which the air supply is prematurely terminated demonstrated that the NAPL smoldering process can be extinguished via external control. A suite of 23 demonstration experiments shows that NAPL smoldering is successful across a range of soil types (including simple layered systems) and contaminants (including laboratory mixtures of dodecane, DCA/ grease, TCE/oil, vegetable oil, crude oil, and mineral oil) as well as field-obtained samples of materials containing coal tar, oil drill cutting waste, and oil sands.
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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".