Regional methane emissions estimates in northern Pennsylvania gas fields using a mesoscale atmospheric inversion system

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 4 February 2014: 4:45 PM
Room C113 (The Georgia World Congress Center )
Thomas lauvaux, Pennsylvania State University, University Park, PA; and A. Deng, B. Gaudet, S. J. Richardson, N. L. Miles, J. N. Ciccarelli, and K. J. Davis

Shale gas development has been accompanied by concerns regarding the overall greenhouse gas (GHG) footprint of this energy source. Estimates of total methane (CH4) leakage from shale wells to point of use have ranged from about 1% to more than 7% of production, with the greatest variability due to estimates of leakage in the production phase, which accounts for 1-4% leakage in these estimates. Government accounting of shale gas emissions has changed frequently and by large amounts. We present here the first regional emissions estimates of CH4 from shale gas production activities using a mesoscale inverse system at high resolution. Two CH4 CRDS analyzers were deployed in the North East of Pennsylvania (Susquehanna county) and near Windsor, New York during June and July of 2013 measuring continuously the CH4 atmospheric concentrations. Using the PennState WRF-FDDA modeling system coupled to a Lagrangian particle dispersion model, we simulated the atmospheric transport at 1km resolution. The regional CH4 emissions over northeastern Pennsylvania were quantified using a Bayesian atmospheric inversion system, using alternatively one of the two sites as our background CH4 atmospheric concentration, depending on the wind direction. We also present an analysis of the temporal variability and the amplitude of signals in the observed concentrations, with several peaks of a few ppm occurring over short periods of time and the systematic enhancement of CH4 concentrations at the downwind site over longer periods of time. We show here that surface networks of high accuracy CH4 analyzers are able to detect atmospheric signals due to CH4 emissions in shale gas production areas and could be used in regional atmospheric inversion systems to quantify CH4 emissions from gas production activities.