Deliveries in a sustainable way: A mapping of emissions, documentation, and follow-up. : Presentation of sustainability work done by delivery partners of ByggDialog
Bibliographic record
Abstract
The construction industry is currently playing a significant role in climate change worldwide. With contributions to emissions from several stages of construction, the industry is responsible for one fifth of Sweden’s total emissions. From these emissions one quarter can be linked to transportation. With goals and requirements to live up to, such as Fossil Free Sweden, the Paris Agreement and Agenda 2030, construction companies today need to work together to reduce their emissions. This study is based around the construction company ByggDialog, which acts as a turnkey contractor for projects throughout Sweden. The company specializes in partnering, and focuses primarily on projects in the public sector. This study examines four anonymous suppliers who are all recurring partners of ByggDialog. The study deals mainly with emissions, documentation, and follow-up. The starting point during the study's execution period shows that several of the companies are already well on their way to reducing their emissions through, among other things, a change of fuel. A change from diesel to HVO100 does not require new engines or other modifications and can reduce emissions from about 2.6 kgCO2 / litre to 0.52 kg CO2 / litre, which is an improvement of as much as 80%. With a focus on large cities, this transition has already begun and the opportunities for completely fossil-free transport already exist today but comes with an additional cost. Saving one tonne of CO2 using fossil-free HVO100 is estimated to cost just under 3 000 SEK with current fuel prices from the study's execution period. The companies in the study also raise the importance of reducing the number of transports through planning. From ByggDialogs point of view, early planning and coordinated orders can remove superfluous transport, which in turn saves anything from 2 kg of CO2 up to 50 kg of CO2 depending on in which transport is saved. In the near future, the companies in the study hope to have developed better digital tools for collecting and processing transport data. Data that will make it easier for ByggDialog to track their emissions. Along with this, procedures for follow-up need to be developed so that production managers and purchasing managers will have a better insight into the requirements that are set and the effect they have.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".