Inference of Global Methane Emissions from Oil and Gas Production

Citation

Tribby, Ariana Linnae (2023) Inference of Global Methane Emissions from Oil and Gas Production. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/pjn3-az83. https://resolver.caltech.edu/CaltechTHESIS:06022023-045855497

Abstract

Atmospheric methane plays a significant role in warming the climate. Characterizing its sources and sinks is important for future climate and air quality impacts. Global methane background trends suggest a sustained increase in emissions since 2007. There is no debate that reducing anthropogenic (human-driven) emissions can lead to short-term decreases in atmospheric methane, posing an attractive avenue towards mitigating climate change. Yet, effective policy to limit emissions from energy-related activities relies on accurate emission estimates, and historically, it has been challenging to diagnose both the magnitude and origin of methane leaks from a wide range of facilities and components across production, transmission, storage, and distribution systems. We present a novel Bayesian hierarchical model to improve methane emission estimates on global and regional scales from oil and gas processes. We also present methods to optimize time and cost of model simulations of certain trace gases, including several of which have important climate implications. Finally, we present our efforts in characterizing fossil methane from burgeoning oil production in Oklahoma and Texas using long term ground-based remote-sensing observations combined with Stochastic Time-Inverted Larangian Transport modeling.

Thesis Files