Abstract
ISO 14083:2023 was introduced to guide the calculation of greenhouse gas emissions within the logistics industry. Under this standard, the uncertainty of reported emissions values can, at best, be inferred from whether the value is based on measurements, generated by modeling or using industry default values. This makes it difficult to gauge the uncertainty of emissions figures used in decision-making. This work aims for transparency through explicit quantification of uncertainty. Large corporations are required to report on their emissions, including those made on their behalf. However, road haulage is dominated by small companies that are exempt from emissions reporting, and many do not provide their customers with emissions data. This paper considers the position of small road haulage companies that can take measurements, as opposed to companies that subcontract logistic operations. For simplicity, the paper only considers direct CO2 emissions. This work provides an analysis of the uncertainty that would arise from collecting data on fuel usage, cargo weights, and distances,
method has low computational overheads and generates bounds that are not inflated by the propagation mechanism when applied in the context of ISO 14083:2023. Since this methodology is applicable across the logistic industry, similar analysis performed in a different part of the industry should reach comparable conclusions.
method has low computational overheads and generates bounds that are not inflated by the propagation mechanism when applied in the context of ISO 14083:2023. Since this methodology is applicable across the logistic industry, similar analysis performed in a different part of the industry should reach comparable conclusions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 36th European Safety and Reliability Conference |
| Editors | Jose C. Matos, Paulo B. Lourenco, Michael Beer, Daniel Oliveira, Edoardo Patelli |
| Number of pages | 8 |
| Publication status | Accepted/In press - 13 May 2026 |
Funding
This research is funded by the University of Strathclyde’s StrathDRUMS centre for doctoral training and also partly funded by Mavarick.ai.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 13 Climate Action
Keywords
- Interval arithmetic
- Uncertainty quantification
- Greenhouse gas emissions
- logistics
- road haulage
Fingerprint
Dive into the research topics of 'Interval uncertainty propagation on CO2 emission calculations in road haulage'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver