Variations and Sources of Atmospheric CO2 Measured at East Trout Lake, Canada
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Reducing uncertainties in projections of surface emissions of major greenhouse gases (GHGs) including CO2 relies on continuously improving our scientific understanding of the exchange processes between the atmosphere and land at regional scales. In order to enhance our understanding in emission processes and atmospheric transports, an integrated framework that addresses individual natural and anthropogenic factors in a complementary way proves to be invaluable. This study presents an example of top-down inverse modeling that utilizes high precision measurement data collected at a Canadian greenhouse gas monitoring site. The measurements include multiple tracers encompassing standard greenhouse gas species, stable isotopes of CO2, and combustion-related species. The potential for the proposed analysis framework is demonstrated using Stochastic Time- Inverted Lagrangian Transport (STILT) model runs to yield a unique regional-scale constraint that can be used to relate the observed changes of tracer concentrations to the processes in their upwind source regions. The uncertainties in emission estimates are assessed using different transport fields and background concentrations coupled with the STILT model. Also, methods to further reduce uncertainties in the retrieved emissions by incorporating additional constraints including tracer-to- tracer correlations and satellite measurements are briefly discussed. The inversion approach both reproduces source areas in a spatially explicit way through sophisticated Lagrangian transport modeling and infers emission processes that leave imprints on atmospheric tracers. The results indicate that the changes in greenhouse gas concentration are strongly influenced by regional sources, including significant contributions from fossil fuel emissions, and that the integrated approach can be used for regulatory regimes to verify reported emissions of the greenhouse gas from oilsands developments.