Work Description

Title: Data in support of the study "Using space-based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East" Open Access Deposited
Attribute Value
  • Column-averaged dry-air mole fraction of CO2 (XCO2) data from the OCO-2 satellite, for days and cities of interest, were binned by latitude at a resolution of 0.1 degrees. Using the X-STILT model, we simulated corresponding data points. Simulated enhancements due to near-field emissions were found by convolving X-STILT footprints with global CO2 emissions inventory data. The background contributions to total XCO2 were estimated using CarbonTracker data, with biases corrected through comparison to observed OCO-2 background values. Overpass-level scaling factors for each inventory were estimated by dividing the sum of OCO-2 enhancements for each overpass by the sum of the modeled enhancements. These overpass-level scaling factors were combined using a bootstrap method to find city-level mean scaling factors. The city-level mean scaling factors were used to estimate scaled emissions for each city. 90% confidence intervals were also evaluated using the bootstrap method. City-level estimates were summed.
  • This data set supports a study that seeks to evaluate global fossil fuel CO2 emissions inventory representations of CO2 emissions of five cities in the Middle East, and assess the ability of satellite observations to inform this evaluation. 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. In this study 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/y (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/y). 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.

  • There are three files included in this data set, and all data are in tab-delimited form. The first file,, contains 26 separate text files, each named by the city and date of the corresponding OCO-2 overpass. Each of these 26 files includes overpass-specific data, with modeled and observed XCO2 values binned by 0.1 degree of latitude. The file overpass_scaling_factors.txt provides the scaling factors for each overpass used in this study. The file city_estimates.txt provides the scaled emissions estimates for each city (or sum of cities) as well as the lower and upper bounds of the 90% confidence intervals, for each inventory.
Contact information
Funding agency
  • National Science Foundation (NSF)
  • National Aeronautics and Space Administration (NASA)
ORSP grant number
  • F039072, F052836
Citations to related material
  • Yang, E. G., Kort, E. A., Wu, D., Lin, J. C., Oda, T., Ye, X., & Lauvaux, T. (2020). Using space‐based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East. Journal of Geophysical Research: Atmospheres, 125, e2019JD031922.
Resource type
Curation notes
  • Updated the citation to the article in the "citation to related material" field on March 27, 2020
Last modified
  • 03/27/2020
  • 03/20/2020
To Cite this Work:
Yang, E., Kort, E., Wu, D., Lin, J., Oda, T., Ye, X., Lauvaux, T. (2020). Data in support of the study "Using space-based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East" [Data set]. University of Michigan - Deep Blue.


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