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Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban...

Yang, E. G., E. Kort, D. Wu, J. C. Lin, T. Oda, X. Ye, and T. Lauvaux (2020), Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East, J. Geophys. Res., 125, e2019JD031922, doi:10.1029/2019JD031922.

Improved observational understanding of urban CO2 emissions, a large and dynamic global source of fossil CO2, can provide essential insights for both carbon cycle science and mitigation decision making. Here we compare three distinct global CO2 emissions inventory representations of urban CO2 emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory‐2 (OCO‐2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO2 simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC year−1 (50–151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC year−1). We find our results to be insensitive to the prior spatial distributions in inventories of the cities' emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high‐resolution gridded inventories. Plain Language Summary Carbon dioxide (CO2) emitted from burning fossil fuels is the most important contributor to climate change and is changing the Earth's carbon cycle. Most of these emissions can be linked to cities. Since cities around the world are quickly changing and growing, especially in developing countries, it is important to better understand the extent of urban CO2 emissions to understand how the climate and carbon cycle will change. In this study, we evaluate three global emissions inventories —modeled estimates of CO2 emissions on a grid spanning the globe—and their ability to capture the afternoon emissions of five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad). This assessment relies on comparing simulations using the inventories with observations from the Orbiting Carbon Observatory‐2 (OCO‐2) satellite. Based on these comparisons, we see that the inventory representations have underestimated afternoon emissions of the five studied cities and that the level of underestimation is a substantial portion of total Middle Eastern emissions. Our results are unaffected by the differing spatial patterns of emissions from different inventories. This work demonstrates the ability to use satellites to evaluate subnational emissions, a valuable advance for both science and policy issues relating to climate change and the carbon cycle.

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Orbiting Carbon Observatory-2 (OCO-2)