Measurement-Informed Methane Inventories for Colorado’s Upstream Oil and Gas Sector: Two Independent Modeling Approaches
Year: 2026
Type: preprint
Abstract: The state of Colorado is recognized as a leader in regulating oil and gas methane emissions, with Colorado requirements often influencing subsequent federal policy. Building on existing efforts, Colorado published a greenhouse gas intensity verification rule in 2023, requiring upstream operators to either create their own measurement-informed emissions inventory or multiply their bottom-up inventory by a state-developed default factor. This factor is intended to address known deficiencies in bottom-up emissions reporting by increasing the bottom-up inventory to match measured emissions. In this paper, we describe the aerial measurement campaign and subsequent modeling approaches used to create the 2026 default factor. Three aerial technology vendors (Bridger Photonics, GHGSat, and Insight M) performed over 30,000 scans of production facilities across Colorado, covering roughly 94% of the state’s oil and gas production facilities that were operating or partially operating. Using these aerial measurements as inputs, two independent models were developed to estimate state-wide annual methane emissions. One model uses a discrete event simulation tool, Mechanistic Air Emissions Simulator (MAES), to estimate total emissions, while the other model, referred to as the statistical model, is purely data-driven and estimates a facility-level emission rate distribution from the measurement data. MAES and the statistical model estimate upstream oil and gas emissions of 38.7 (35.3, 44.6) and 97.7 (84.4, 114.7) Gg/y, respectively, which are 1.47 (1.34, 1.69) and 3.70 (3.19, 4.34) times higher than the state’s bottom-up inventory.
Source: ChemRxiv
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7204785032