LogisticsAI

guide

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.

Audience

Logistics, sustainability, procurement, and data teams reviewing transport emissions outputs.

Problem

Emissions totals are difficult to trust when the calculation boundary, inputs, factor source, and fallback assumptions are hidden.

Product fit

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.

Frequently asked questions

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.

Related resources

Move from content to workflow

Use the public samples and tools to evaluate the workflow, then create a workspace or request async follow-up when real shipment data is ready.