Novel method to locate and quantify point-source methane emissions using time series of ground-based column observations

Abstract. Identifying and quantifying local methane emitters remains a major challenge for atmospheric monitoring. We present a novel top-down method to estimate both the upwind location and emission strength of an unknown atmospheric source from a time series of concentration observations. The approach employs backward trajectories from a Lagrangian Particle Dispersion Model (LPDM) to derive a characteristic transfer function for each potential source region. The transfer function that best reproduces the observed enhancement identifies the most likely source location. In a second step, the emission strength is inferred from the particle ensemble and its corresponding surface footprint. The method was developed and tested using data from a six-week measurement campaign in the San Francisco Bay Area, where six EM27/SUN near-infrared Fourier transform spectrometers were operated as part of a collaborative effort to quantify greenhouse gas emissions. At the UC Berkeley site, one instrument recorded a strictly periodic methane enhancement of approximately 10 ppb occurring every 12 minutes. Since co-emitted species showed no correlation with this pattern, the signal was attributed to a single, point-like, puff-emitting methane source. Favourable meteorological conditions enabled the analysis of several enhancement peaks. The retrieved average emission strength during the emission episodes was 0.8–78 g CH4 s-1 (equivalent to 2.1–190 metric tons yr-1). Although the exact source could not be identified in the field, the emission characteristics are consistent with periodic natural-gas venting from a heating system with an installed power output of approximately 500–1000 kW installed power. The study demonstrates the potential of this approach for detecting and characterising local methane emitters from ground-based remote-sensing observations.