Interval Uncertainty Propagation on $\mathrm{CO}_{2}$ Emission Calculations in Road Haulage

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, and characterises it using intervals. An exemplar road haulage scenario is then described. The proposed 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.

Keywords: Interval arithmetic, Uncertainty quantification, Greenhouse gas emissions, Logistics, Road haulage..