CALCULATING THE CARBON FOOTPRINT OF A CHEMICAL PLANT: A CASE STUDY OF AKZONOBEL
Bibliographic record
Abstract
Reduction of greenhouse gas emissions is one of the key requirements for sustainable production and consumption, but while the Canadian chemical industry has been very successful in reducing emissions to water and air, and while non- CO 2 greenhouse gas emissions have been minimised as well, reduction of CO 2 emissions has been less successful. The industry itself forecasts that further reduction of CO 2 emissions will be minimal. On the other hand concerns about global warming are increasing, while at the same time the chemical industry increases its commitment to sustainability. Determining the carbon footprint of a chemical plant and of its products will help to identify more emissions reduction possibilities and is a necessary step for the further reduction of the chemical industry's environmental impact. Carbon footprint determination is a corporate goal for AkzoNobel, an international coatings and specialty chemicals company, but the carbon footprint is not yet established for many products, and the information available from the chemical industry is scarce. This paper presents a case study of AkzoNobel's Saskatoon Plant and its attempt to calculate and analyse the carbon footprint of the plant and its main products which are used in the potash industry.
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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) | 0.000 | 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 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".