This task will develop models to determine equivalence between survey type technologies and CMS using the Fugitive Emissions Abatement Simulation Tool (FEAST) framework. The analysis, to be conducted using the model sites used by EPA in its Supplemental Proposal, will demonstrate how a site operator could determine the number and sensitivity of sensors required to deliver emission reductions equivalent to periodic OGI LDAR surveys.

Previous work by the EEMDL team has developed algorithms for CMS sensor placement at single sites. This task will expand that work to networks of sites. Sensor placement algorithms will be developed such that a sensor network would achieve an emissions detection efficiency greater than a minimum specified value at every site and achieve a desired level of overall network emission detection efficiency with a minimum number of sensors deployed. This algorithm will be tested using a CMS network deployed in the Permian Basin (www.projectastra.energy).

CMS network design/sensor placement algorithms, CMS data analytics systems, and methods for reconciliation of CMS data with annual emissions estimates all rely on dispersion modeling, yet few data sets exist for evaluating the performance of dispersion models at oil and natural gas supply chain facilities. Expanding recent work by the EEMDL team, this task will develop a study design for deploying state of the art methane sensors at the METEC site in a testing system that will provide a three-dimensional characterization of emission plumes. These tests would be run under a wide variety of meteorological conditions and detailed, local three-dimensional meteorological data will be collected. The output would be a community data set that could be used to evaluate the performance of and tune dispersion models.