Item based CO2 emission calculation method
Bibliographic record
Abstract
Global warming is one of the main threats to the Earth, caused by the release of greenhouse gases. Gases are measured by their global warming potential (GWP), which is an air pollutant’s relative potency to contribute towards global warming compared to CO2 during a 100-year time period in the atmosphere. The related unit is CO2e (CO2-equivalent), and it commonly accounts for seven greenhouse gases, measured in kgCO2e/kg. GWP and the related CO2e are common climate metrics used in management and policies. \n \nTeknikum Oy is a provider of polymer technologies, selling rubber and plastic components and products, used for example in agricultural, mining and railway industries. Teknikum Oy has opted into Science Based Targets initiative (SBTi), as such they have undertaken a full companywide CO2e assessment in 2020 following the Greenhouse Gas (GHG) Protocol. Since the GHG Protocol does not provide product specific CO2e factors, which are needed for process optimization and requested by clients, another tool is needed. \n \nTeknikum Oy’s item based CO2e tool accounts for the cradle-to-gate emissions and is utilizing the data collected for the GHG Protocol calculation. CO2e is calculated on a case-by-case basis for each item and customer. The tool was tested with a case calculation for a rubber component. \n \nWith the growing interest in environmental effects, reaching reduction targets, along with pressure from the public and governments, the demand for CO2e accounting is increasing. CO2e assessments provide additional marketing bene-fits, help in emission reduction, and provide basis for the analysis. A smaller CO2e value indicates more effective processes. \n \nThis thesis acts as the theory and validation of a such tool, and manual for the transparency and use of the tool. A tool such as this is tailored by the consultant to meet the needs of the client based on their unique company processes. Whilst a tool can provide a relatively reliable calculation, limited datasets can hinder accuracy and how the result is validated needs to be reported. The accounting results can both guide and imply, but a thorough environmental analysis requires multiple impact categories, and some of them could be qualitative. Overall, shifting from the dependency of the use of fossil fuels is key.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.059 | 0.023 |
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".