Space-Based Evaluations of Urban Carbon Dioxide Emissions: Applications, Methods, and Policy Implications

Abstract

Humans are perturbing the carbon cycle, primarily through the emission of carbon dioxide (CO2) from the combustion of fossil fuels, resulting in a warming climate and uncertainties in how the carbon cycle will respond to these changes. Cities play an outsized role in contributing to climate change, as they are the source of the majority of fossil CO2 emissions. Cities are also emerging as leaders in the fight against climate change, through the implementation of urban climate action programs, with ambitious emissions reductions targets, policy plans to achieve these targets, and self-calculated estimates of emissions tracked in self-reported inventories (SRIs). As space-based technology for observing CO2 and co-located proxy species such as nitrogen dioxide (NO2) improve, satellites are opening up many pathways for the estimation of urban CO2 emissions. This dissertation interrogates the utility of space-based assessments of urban CO2 emissions and their implications, using observations of CO2 from the Orbiting Carbon Observatory-2 (OCO-2) and the Orbiting Carbon Observatory-3 (OCO-3) in its urban-focused Snapshot Area Map (SAM) mode, as well as observations of NO2 from the TROPOspheric Monitoring Instrument (TROPOMI).

Applications, methods, and policy implications of assessments of urban CO2 emissions with the use of satellite observations are explored in this work. First, global emissions inventory representations of five Middle Eastern cities’ fossil CO2 emissions are evaluated using comparisons between OCO-2 observations and simulations using the global emissions inventories in combination with the column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model. These comparisons provide optimum inventory scaling factors that suggest that the inventory representations are underestimating the Middle Eastern cities’ emissions. These results are found to be insensitive to the spatial distribution of the inventories. Next, empirical relationships between SAM CO2 and TROPOMI NO2 observations for three cities around the world are derived and applied to observed NO2 fields to generate NO2-derived CO2 fields (NDCFs). Leveraging the greater availability and quality of the TROPOMI NO2 observations, the NDCF method demonstrates relatively small methodological uncertainties when taken in aggregate, and shows a capacity to estimate emissions at a subannual timescale. The last study in this dissertation evaluates the ability of satellite observation-based estimates of CO2 to assess urban climate action programs in the U.S. Application of results from previous studies using OCO-2 observations as well as extrapolating these results to the use of OCO-3 SAMs suggest that these satellite-based estimates have some policy relevance. They are shown to be able to evaluate the accuracy of SRIs and assess progress toward long-term emissions reduction targets, but more improvements in methods need to be made to track emissions year-to-year and to estimate sectoral emissions. A lack of compatibility between the design of the climate action plans and what observations can feasibly be used to estimate is found, which limits the ability of satellite-based emissions estimates to achieve policy-relevant urban CO2 assessments.