FEAST 3.0: Incorporating New Technologies Into Methane Mitigation Policies

State and federal governments throughout North America recently introduced statutes requiring periodic leak detection surveys of natural gas infrastructure to reduce methane emissions. Typically, these regulations specify that the surveys use optical gas imaging (OGI) as part of the detection protocol. New technologies including drones and novel algorithms promise lower cost, faster detection systems that may improve regulatory outcomes if permitted. However, there has been no systematic framework to determine equivalence between these new technologies and existing protocols. In this work, we adapt the Fugitive Emission Abatement Simulation Toolkit (FEAST) framework to explore measures of equivalency between leak detection and repair (LDAR) programs. FEAST simulates the time evolution of emissions at the component-level at natural gas facilities using a Markov process. Leaks, vents, and anomalous emission events are represented in the model at hourly time-steps using a combination of publicly available data and state-level regulatory filings. We parametrize technology properties such as leak detection probability using the results from controlled-release tests at the Methane Emissions Technology Evaluation Center (METEC). By integrating the results from METEC tests with facility emission profiles established by recent measurement campaigns, FEAST compares LDAR programs based on avoided methane emissions and cost of mitigation. The LDAR programs simulated include traditional OGI surveys, automated drone mounted sensors and tiered detection methods. Tiered detection methods modeled in this work consist of a high-speed aerial survey used to locate facilities with large emissions followed by a precise OGI survey to pinpoint the source. Accurate modeling of new LDAR programs will enable regulators to approve new LDAR programs that provide equivalent emission mitigation at lower cost.