What is so super about super-emitters? Characterizing methane high emitters from natural gas infrastructure

Abstract:

Methane emissions across the natural gas supply chain are dominated at any one time by a few high-emitters (super-emitters or fat-tail of the distribution), often underrepresented in published datasets used to construct emission inventories. Characterization of high-emitters is essential for improving emission estimates based on atmospheric data (top-down) and emission inventories (bottom-up).

The population of high-emitters (e.g. 10-20% of sites that account for 80-90% of the emissions) is temporally and spatially dynamic. As a consequence, it is challenging to design sampling methods and construct estimates that accurately represent their frequency and magnitude of emissions.

We present new methods to derive facility-specific emission distribution functions that explicitly integrate the influence of the relatively rare super-emitters. These methods were applied in the Barnett Shale region to construct a custom emission inventory that is then compared to top-down emission estimates for the region. We offer a methodological framework relevant to the design of future sampling campaigns, in which these high-emitters are seamlessly incorporated to representative emissions distributions. This framework can be applied to heterogeneous oil and gas production regions across geographies to obtain accurate regional emission estimates.

Additionally, we characterize emissions relative to the fraction of a facility’s total methane throughput; an effective metric to identify sites with excess emissions resulting from avoidable operating conditions, such as malfunctioning equipment (defined here as functional super-emitters). This work suggests that identifying functional super-emitters and correcting their avoidable operating conditions would result in significant emission reductions. However, due to their spatiotemporal dynamic behavior, achieving and maintaining uniformly low emissions across the entire population of sites will require mitigation steps (e.g. leak detection and repair) at a large fraction of sites.