| Summary: | The aim of this thesis is to explore the use of atmospheric inversions to quantify emissions of fossil fuel CO2 (ffCO2) for the U.S. state of California and assess its implications for the monitoring and verification of emissions. California is of particular interest to atmospheric inversion studies of ffCO2 due to a combination of its ambitious emissions reduction legislation and high density greenhouse gas measurement network. First I examine uncertainties associated with inventories of ffCO2 emissions that inform prior uncertainty in the inversion. Next I investigate potential errors and uncertainties related to the spatial and temporal representation of ffCO2 emissions, and modelled atmospheric transport. To do this I perform simulation experiments based on a network of groundbased observations of CO2 concentration and radiocarbon in CO2, a tracer of ffCO2, by combining prior emissions and transport models, currently used in many atmospheric studies. Finally, as nearly all national and sub national climate change mitigation policies target economic sector specific emissions reductions, I investigate the development of a novel inversion approach that optimizes emissions by sector. My results show that although an atmospheric inversion of ffCO2 in California can reduce a hypothetical bias in the magnitude of prior emissions estimates, uncertainties in ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15% or less of state-total emissions for the ground-based network in California we consider. The need for temporal variations to be included in prior emissions is highlighted along with continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions. I conclude that further work on establishing relationships between emissions sectors and trace gases is required for the successful monitoring of sector specific ffCO2 emissions.
|
|---|
