Project Canary’s Analysis of Continuous Methane Monitoring Data Finds Short-Lived Events Drive an Outsized Share of Total Emissions

Based on one of the largest site-level continuous methane monitoring datasets — 24.7 million 15-minute measurements across 940 upstream facilities in seven U.S. basins — analyzed using a consistent event-detection approach.

DENVER, Feb. 24, 2026 /PRNewswire/ — Project Canary, the leading provider of emissions management solutions for the energy industry, today released findings from a temporal analysis of methane emissions at upstream production facilities in the United States. The study draws on one of the largest site-level continuous methane monitoring datasets, evaluated with a consistent event-detection approach and comprising 24.7 million 15-minute rate estimates from 940 upstream facilities across seven U.S. basins.

Key Findings from the Analysis

The analysis applies a consistent event-detection approach across the entire dataset. An event is defined as a period during which estimated emissions exceed a site’s baseline. The method time-bounds each event’s start and end, enabling duration-based analysis. The findings are:

• Super emitters are not the key problem. Super emitters, defined as those emitting above 100 kilograms per hour, account for 10% to 20% of total emissions. Emissions below 100 kilograms per hour account for 80% to 90% of the total.
• Short events add up. About 75% of event-related emissions come from events lasting three days or less.
• Emissions are concentrated. About 11% of monitored facilities account for 50% of total estimated methane mass.
• Emissions are intermittent. Only about 4% of 15-minute periods are in an event state, yet those periods account for about 41% of total estimated emissions.
• Duration matters. Many emissions events last hours to days, not months. Programs that assume emissions persist until the next survey can overstate impact and misdirect fieldwork.

Why this Matters for Leak Detection and Repair Programs (LDAR)

These findings have direct implications for LDAR programs that rely on snapshot measurements. When emissions start and stop over hours or days, a single flyover can miss events entirely or detect an event that ends soon after, leading teams to deploy crews to issues that are no longer active. Time-resolved monitoring provides duration context, enabling operators to identify when emissions begin and end, prioritize active problems, and verify that mitigation held.

“Operators need methane data that reflects how emissions behave in the real world,” said Will Foiles, Chief Executive Officer of Project Canary. “This analysis shows that intermittency is a defining feature of methane emissions at many sites. When programs measure an emissions rate and assume emissions persist until the next survey, savings estimates can be inflated, and field effort misdirected. Combining all forms of data, including operational SCADA data, provides the time context needed to respond to active events faster, avoid unnecessary dispatch, and support more defensible reporting.”

Project Canary plans to publish additional technical details through a peer-reviewed journal, including methods, definitions, and limitations. All publicly shared results are aggregated and anonymized, and do not identify operators or individual facilities.

Operators interested in applying these findings to LDAR design and field triage can contact Project Canary to review the results and operational implications.

About Project Canary

Project Canary provides a unified operational intelligence platform for methane. Operational intelligence brings methane signals and operational data into one place, enabling energy operators to significantly improve day-to-day system performance, streamline leak detection & repair (LDAR), and simplify reporting.

View original content to download multimedia:https://www.prnewswire.com/news-releases/project-canarys-analysis-of-continuous-methane-monitoring-data-finds-short-lived-events-drive-an-outsized-share-of-total-emissions-302695026.html

SOURCE Project Canary