Aerial LiDAR Based, Source Resolved Methane Emissions Inventory: Permian Basin Case Study for Benchmarking U.S. Emissions

Reducing methane emissions is one of the quickest ways to slow near-term warming, yet building accurate inventories to track progress towards reduction targets remains challenging. We present a 2024 source-resolved methane inventory for the Permian Basin built from quarterly aerial LiDAR scans that supports benchmarking and provides a scalable framework for operator-level OGMP 2.0 reporting. We combined public infrastructure records with machine learning identification of non-producing sites to define the facility population and generate representative sampling plans, then deployed Bridger Photonics’ Gas Mapping LiDAR to scan 51,770 sites across four quarters. Sources were localized to within 2 m and attributed to equipment identified in aerial photography acquired during the scans. The instruments achieved an average 90% probability of detection at 1.16 kg/h under campaign field conditions. We detail a Monte Carlo framework that propagates quantification, extrapolation, sampling, and detection sensitivity uncertainty and weights spatial extrapolation by observed equipment counts, avoiding bias from over or under sampling of large facilities. The workflow yields a facility inventory comprehensive of source-level emission rates down to 0.4 kg/h. After adding gathering pipeline and sub-0.4 kg/h emissions estimates from prior studies, the basin total was 5,133 kt CH₄ (95% CI: 4,070–6,337 kt). Seasonal variation in emissions was observed, with winter up to 17% higher than summer. Non-producing facilities contributed 38% of facility emissions, and tanks (31%) and compressors (28%) dominated equipment-level totals. The basin-wide methane loss rate was 3.13%. Texas emitted 4,038 kt CH₄ with a 3.60% loss rate, while New Mexico emitted 1,095 kt CH₄ with a 2.10% loss rate, placing New Mexico near its 2026 target of 2%. At the operator level, most large operators outperformed the basin average intensity by a wide margin, attributable to newer facilities, higher production, and active leak detection and repair programs indicating that facility design and operating practices are stronger drivers of emissions performance than geography, geology or regulatory environment.