Evaluation of the Solid and Hazardous Wastes Generated by the Automotive Industry in Turkey
Bibliographic record
Abstract
Development of the automotive industry not only facilitated our daily lives, but also introduced environmental stress. The automotive industry consists of both the original equipment manufacturers (OEMs), and a great variety of suppliers that support this industry. Most of the published studies focus on the environmental impacts of the OEMs; the impacts of suppliers were generally neglected. The objective of this study was to evaluate the types and amounts of solid and hazardous wastes generated by the automotive industry especially in relation to the supplier companies supporting the automotive manufacturers in Turkey. A survey was conducted with representative numbers of automotive manufacturers and suppliers located in Bursa, Turkey to obtain data on resource usage, waste types, and waste amounts generated. One hundred and five different parts of an automobile were examined in the framework of the study. Interviews were also conducted with the suppliers about the details on each item produced. Resource usage, solid and hazardous waste generation during the production of each component of an automobile were calculated. The environmental burden of the automotive industry in Turkey was roughly calculated in terms of waste generation and resource usage based on energy and water. It was seen that of the items constituting an automobile, which are provided by the suppliers, 47% is made of plastics, 31% is made of textile, and 21% is made of metals. The amounts of water and electricity used for all the items by the suppliers were found as 0.60 m 3/vehicle and 190 kWh/vehicle, respectively. Water and electricity usage by OEMs were 3.47 m3/vehicle and 1763 kWh/vehicle, respectively. Solid and hazardous waste generated by OEMs were found as48.97 kg/vehicle and 7.04 kg/vehicle, respectively, and by suppliers were 5.71 kg/vehicle and 0.6 kg/vehicle, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".