Lube Oil Recycling: Environmental and Economic Implications
Bibliographic record
Abstract
This study presents a practical investigation on the reuse of spent lubricating oil as its indiscriminate disposal by the various users daily constitutes a serious pollution problem in the environment. In carrying out this work, samples of various used lubricating oil collected at different locations were analyzed for their physical and chemical composition, to ascertain their suitability for use as fuel in the cement factory. The examined parameters gave average values of 9.4686 kcal/kg, 96 oC, 18.48, 24 oC and 7834.5 kg/m3 for caloric value, flash point, viscosity, pour point and ash content respectively. The results were compared with those of low fuel oil, used in the cement factories. Consequently, a trial burn was conducted which gave mean values of 133.7 mg/m3, 1.7 ppm, 112.3 mg/m3, ﹤25.0 mg/m3, 20.0 mg/m3, ﹤0.1 mg/m3, ﹤6.8 mg/m3 and 371.2 ppm for SPM, CO, THC, SO3, NO3, H2S, NH3 and CO3 respectively. The results obtained clearly showed that the used lubricating oil has chemical composition, calorific value and other physical properties that are comparable to those of low pour fuel oil. The results obtained from the trial burn conducted in the various cement factories, reveal that, the use of used lubricating oil as fuel in cement factories is environmental friendly and economically viable technique of disposing used lubricating oil.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".