title: Equivalent leak definitions for Smart LDAR (leak detection and repair) when using optical imaging technology.
abstract: Controlling fugitive emissions from leaks in petrochemical industry process equipment now requires periodic monitoring of valves, flanges, pumps etc., typically on a quarterly basis. Previous studies have shown that over 90% of the reducible emissions come from approximately 0.1% of the components, i.e. the large leakers. A new, and more cost-effective approach for controlling these large leakers would entail more frequent monitoring of process equipment, allowing for the detection and repair of the highly leaking components that contribute the most to emissions. This approach has been called "Smart LDAR." New optical imaging instruments, which significantly reduce monitoring costs, are now available to implement such an alternative work practice. This work describes the determination of the leak detection sensitivity (equivalency threshold) that an optical imaging instrument must achieve to ensure that it will provide at least the equivalent emission control of the current leak detection and repair practice. Equivalency thresholds were developed for various monitoring intervals. The U.S. Environment Protection Agency's Monte Carlo simulation approach was used to perform the analysis and to demonstrate that optical imaging, which is capable of identifying all of the largest leakers, can provide better control of fugitive emissions.
authors.affiliation: The LEVON Group, LLC, Thousand Oaks, CA 91320, USA.
authors.forename: David
authors.initials: D
authors.lastname: Epperson
authors.forename: Miriam
authors.initials: M
authors.lastname: Lev-On
authors.forename: Hal
authors.initials: H
authors.lastname: Taback
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Siegell
authors.forename: Karin
authors.initials: K
authors.lastname: Ritter
mesh_terms: D002617:Chemical Industry / Q000295:instrumentation; D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods*; D004785:Environmental Pollutants / Q000032:analysis*; D019544:Equipment Failure Analysis; D008962:Models, Theoretical; D009010:Monte Carlo Method; D010578:Petroleum; D012984:Software
chemical_list: D004785:Environmental Pollutants; D010578:Petroleum