Environmental Study of Used Engine Oil Management in Dakar Region: Case of CFAO Motors, Bolloré Transport and Logistics, Eiffage and Dakar Dem Dikk (Senegal)
Bibliographic record
Abstract
In Senegal, the production of used motor oil is very high (between 4,000 and 4,800 tons per year). Despite their hazardous nature (relating to Annex I of the Basel Convention ratified by Senegal), these oils are poorly managed and few studies have been carried out in this area. This is the purpose of this research, which aims to contribute to the study of the management of used motor oils in certain companies, including CFAO Motors, Bolloré Transport, and Logistics, Eiffage, and Dakar Dem Dikk (Senegal). Documentary review, field study (semi-structured individual interviews, focus groups, informal interviews, field visits, and direct observation), data processing, and analysis using the triangulation technique were the methodological tools used. The results of this work reveal a significant production of more than 3,000 liters of used motor oil per month/company and storage of these oils in underground or overhead metal tanks. The recovery and/or collection of these oils is done free of charge by the Société de Régénération des Huiles (SRH), by Skysea for transformation into fuel or by SOCOCIM, a cement factory, for energy recovery. The companies surveyed manage their used oil according to the standards in force in Senegal, although the green register is notoriously absent. The various management actors are well aware of the hazardous nature of these oils, but the operational agents sometimes tend to minimize their impacts. A comparative analysis of management systems has allowed us to observe similarities in the management of used motor oils in France, Canada, and the United States compared to the management in Senegal, such as the responsibility of the author of the used oils from production to final disposal, as well as progress noted such as the priority given to regeneration (Directive 2006/12/EC) or the non-free collection of oils.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".