The topic of methane emission mitigation from the energy sector and natural gas infrastructure has been a priority in the “Green deal” and “Fit for 55%” frameworks governed by the European Union.

Emissions from the natural gas infrastructure have been identified as targets to reduce EU’s Carbon Footprint by 2030, hence new regulations for the European utilities to quantify and reduce fugitive methane emissions are on the horizon.

Several studies (e.g., A. Brandt et al. 2016) have shown the heavy-tail distribution of methane emissions from natural gas infrastructure, resulting in a small fraction of the total number of emitters constituting the majority of the system’s fugitive emissions.

Recent emission data collected by Picarro from many natural gas distribution systems have confirmed the presence of large emitters (“Super Emitters”) which contribute disproportionately to the overall methane emissions from mid- and downstream infrastructures.

In this paper, we’ll describe how Picarro’s P-Cubed® cloud-based analytics and data visualization platform enables gas operators to quickly identify and localize the largest methane emitters on the entire gas infrastructure, allowing them to remediate these Super Emitters first as part of an informed and cost-effective emission reduction strategy.

Additional benefits of identifying and removing high-emitting leaks include a reduction in odour calls as well as a reduction in risk since these leaks are more likely to migrate than smaller leaks, especially in winter months.

The Picarro P-Cubed Solution is a hardware-enabled software and data analytics platform that combines mobile methane emissions measurements with powerful geospatial analytics and visualization modules. By driving a data collection vehicle within a gas distribution infrastructure, Picarro quickly and efficiently captures signatures of leaks in the target area. By combining wind measurements and characterization of the methane plumes, the Picarro solution accurately determines the potential emission sources characteristics, including flow rate, risk, and origin.