Constraining Carbon Emission Estimates from the Los Angeles Megacity through use of Remote-sensing Techniques and a Time-reversed Lagrangian Particle Dispersion Model

Much of the global increase in carbon dioxide (CO₂) is related to urban activity. Accurate greenhouse gas (GHG) inventories in urban environments are important to inform responsible policy decisions toward GHG reduction, such as California Assembly Bill #32, and more recently, the Obama Administration proposed rule changes to reduce GHG emissions from power plants.

As a megacity (metropolitan area with a population >10 million people), the Los Angeles metropolitan area has been the locus of a number of studies seeking to constrain CO₂ emissions. In this work, we adopt an approach toward the atmospheric transport modeling of urban emissions that examines co-emitted pollutants (CO, CO₂, CH₄) in the LA megacity environment. This approach leverages observations from the ground-based Total Carbon Column Observing Network (TCCON) and space-borne GHG observations through use of the Stochastic Time-Inverted Lagrangian Transport (STILT) model to produce an atmospheric inversion of GHGs in the LA megacity environment. This work seeks to develop accurate GHG emission estimates within a framework that leverages TCCON, along with high-resolution satellite observations (<3 km² footprint) from the recently launched OCO-2 satellite mission to resolve spatial variability on scales that presently challenge Eulerian models.