A unified Python workflow for mobile downwind quantification of methane emissions from active landfill cells: implementing Gaussian and tracer-release methods

In the UK, the waste sector accounted for approximately 31.7% of national CH₄ emissions in 2023 (National Atmospheric Emissions Inventory – NAEI 2023), with landfills contributing for nearly 80% of these sectoral emissions, or ≈ 25.4% of national CH₄ emissions. This reality, combined with marked spatial and temporal variability in surface fluxes, requires rigorous measurement protocols and explicit quantification of uncertainties.

As part of the MOMENTUM and DEFRA-funded programmes, mobile measurement campaigns were carried out for multiple active landfill cells. Downwind of each cell, ≥10 road transects were completed, with each group of transects run at a constant vehicle speed (typically 20–60 km h⁻¹), using an instrumented mobile laboratory (Toyota RAV4 hybrid) measuring CH₄, CO₂, C₂H₆ and δ¹³C-CH₄ with cavity-enhanced analysers; acquisition protocols were harmonised to maximise comparability.

Flux quantification applies two established methods to the same downwind datasets: (i) Gaussian plume dispersion modelling with Monte-Carlo uncertainty propagation to produce probabilistic emission estimates; and (ii) a tracer-dispersion method using controlled releases of ethane (C₂H₆) during transects, with CH₄ emissions estimated from integrated C₂H₆/ CH₄ plume ratios. Survey results are employed illustratively to explore how external factors, meteorological inputs, atmospheric stability conditions, downwind distance from emission points, tracer placement and measurement routing can influence method outputs and uncertainty characterisation.

The objective of this work was to develop and validate a reproducible Python-based post-processing routine for mobile surveys downwind of landfill cells, implemented as a unified workflow that enables the consistent and traceable application of Gaussian-plume dispersion modelling (with uncertainty propagation) and tracer-release quantification methods to identical downwind datasets. The workflow standardises data ingestion and time synchronisation, quality filtering, baseline treatment, plume and peak selection, and execution of both calculation routes, producing comparable methane flux estimates with associated uncertainty characterisation.

Applied across multiple landfills, this common processing environment enables systematic, like-for-like method evaluation and targeted sensitivity analyses, linking variability in estimated fluxes to meteorological conditions and sampling configuration. It facilitates identification of dominant sources of uncertainty and highlights methodological choices that would benefit from standardisation, providing a robust basis for harmonised mobile CH₄ quantification and the development of best-practice guidance for inventories and mitigation planning.