Guides
Transport emissions methodology: boundaries, factors, assumptions, and evidence
A credible transport emissions workflow should explain how numbers were produced, which assumptions were used, and what still needs review before external reporting.
Public
Logistics, sustainability, procurement, and data teams reviewing transport emissions outputs.
Problème
Emissions totals are difficult to trust when the calculation boundary, inputs, factor source, and fallback assumptions are hidden.
Ajustement du produit
LogisticsAI packages methodology notes with evidence artifacts so reviewers can see inputs, boundaries, assumptions, and data quality context.
Boundary selection
Transport emissions outputs should make the selected boundary visible, including whether the workflow is presenting well-to-wheel, tank-to-wheel, or another reviewed scope.
- Keep boundary labels visible in summaries and machine-readable exports.
- Separate planning estimates from reviewed shipment-data workflows.
- Avoid presenting an estimator result as a verified customer report.
Input hierarchy
Primary shipment data should be preferred when available. Fallbacks can be useful, but they should be documented so reviewers understand what changed the confidence level.
- Shipment date, mode, origin, destination, distance, cargo weight, and vehicle or fuel context improve review quality.
- Fallback assumptions should be named rather than hidden in a spreadsheet formula.
- Evidence notes should point back to source exports, invoices, or operational records where available.
Methodology statement
A methodology statement gives the reviewer a compact explanation of the calculation setup, assumptions, exclusions, and output limitations.
- State what the pack is intended to support.
- List known exclusions and data gaps.
- Keep certification and legal compliance claims out unless they are backed by an actual external process.
Explorez le flux de travail des preuves
Questions fréquemment posées
Does LogisticsAI certify transport emissions calculations?
No. LogisticsAI provides workflow artifacts and methodology context. Certification or external verification must come from a real qualified process.
Can methodology text be shared with customers?
Yes, the methodology artifact is intended to help customers understand boundaries, assumptions, and data quality. Teams should review it before external use.
Ressources connexes
Passer du contenu au workflow
Utilisez les échantillons et outils publics pour évaluer le flux de travail, puis créez un espace de travail ou demandez un suivi asynchrone lorsque les données réelles de l'expédition sont prêtes.