How to show scope and uncertainty in carbon data

Add source, scope, method and confidence limits to every data line.

2 October 2024Updated 23 September 2026

Short answer

For each line, state activity data, period, unit, boundary, allocation method and emission-factor source. Label data measured, derived or assumed and show gaps and estimate impacts. If reporting uncertainty as a range, explain the method; compare results only under matching boundaries and methods. Prioritise replacing high-impact assumptions with actual records.

A carbon result is derived from activity data and a chosen method. Credibility starts by showing the source and coverage of each input.

Leave a trail for every data line. Record source file, period, unit, vehicle/route boundary, whether empty running is included, allocation method and emission-factor version. Make unit conversions visible.

Mark inputs measured, derived or assumed. For estimates, explain their basis, plausible range and effect on the total; show scenarios using different assumptions separately.

For year or carrier comparisons, keep boundary, method and factor scope consistent. Identify assumptions with the largest effect and replace them with actual records in the next data cycle.

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Topics:Sustainability and carbon Measurement and traceability

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