This project developed and validated a field method to collect and analyze measurements of fugitive methane emissions — accidental emissions of gases from a pressurized apparatus due to faulty equipment, leakage, or other unforeseen mishaps — from commercial buildings in California. The field method measured post-meter methane leakage from gas-fired appliances and post-meter gas piping components. Researchers took measurements at 20 commercial foodservice sites and 2 hospitals.
Field data paired with statistical and probabalisitc analyses indicates fugitive methane emissions from commercial buildings were higher than those shown in current inventories. The data also shows that for both gas appliances and piping components, the top 3 percent of leakers accounted for more than 50 percent of total fugitive methane emissions. This suggests that identifying and repairing a relatively small number of problem areas could greatly reduce fugitive emissions from the commercial foodservice subsector.
After collecting field data, the project team used a Monte Carlo method to analyze the data on exhaust and fugitive emissions from appliances and pipe system components, respectively. The researchers created seven simulations of cities and regions of different sizes to demonstrate the analysis that could estimate methane emissions from commercial cooking appliances and associated piping in various commercial building types.
A key element of this project was developing the necessary tools for field-based data collection and statistical and probabilistic analyses to construct a statewide emissions estimate. These tools could collect and use field data to estimate emissions from other commercial building types such as schools or lodging. Collecting datasets for all appropriate commercial building types will allow for a robust and detailed estimate of California-wide fugitive methane emissions. By quantifying emissions from all sources in the natural gas system, including natural gas customers like the commercial building sector, researchers can characterize emission profiles and focus on sources with the largest potential for emissions reduction to meet the state’s statutory targets.
Author(s)
Meredith Sweeney, Daniel Ersoy, Kristine Wiley, Erin Case, Eric Stubee, Marc L. Fischer