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- Creator:
- Kort, Eric A, Plant, Genevieve, and Dacic, Natasha
- Description:
- Ensemble of optimized posterior N2O (nitrous oxide) fluxes derived from a Bayesian Inversion framework and in-situ aircraft observations of Iowa in 2021 (May 26, 2021 – June 4, 2021) and 2022 (May 18, 2022 – May 31, 2022) from “Airborne measurements reveal high spatiotemporal variation and the heavy-tail characteristic of nitrous oxide emissions in Iowa,” citation below. For each flight day there (12 in total), there are three separate files that represent fluxes derived for three distinct spatial resolutions. Further details about the ensemble members are provided in Dacic, Plant, & Kort (2024). Citation: Dacic N, Plant G, Kort EA, “Airborne measurements reveal high spatiotemporal variation and the heavy-tail characteristic of nitrous oxide emissions in Iowa,” in revisions for JGR: Atmospheres.
- Keyword:
- nitrous oxide, N2O, agriculture, soil, Iowa
- Citation to related publication:
- Dacic N, Plant G, Kort EA, “Airborne measurements reveal high spatiotemporal variation and the heavy-tail characteristic of nitrous oxide emissions in Iowa,” in revisions for JGR: Atmospheres
- Discipline:
- Science
2. Aircraft Data (2022) for Measurement of Agriculture Illuminating farm-Zone Emissions of N2O (MAIZE)
- Creator:
- Kort, Eric A, Plant, Genevieve, and Dacic, Natasha
- Description:
- As part of the Measurement of Agriculture Illuminating farm-Zone Emissions of N2O (MAIZE) project, in 2022 an aircraft platform sampled atmospheric concentrations of nitrous oxide (N2O) in the agriculture regions of Iowa. Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data files contain the merged data for each individual flight day.
- Keyword:
- Greenhouse Gases, Nitrous Oxide, and Agricultural soils
- Citation to related publication:
- Airborne measurements reveal high spatiotemporal variation and the heavy-tail characteristic of nitrous oxide emissions in Iowa" by Natasha Dacic, Genevieve Plant, and Eric A Kort. Journal of Geophysical Research: Atmospheres. Submitted. and 2021 dataset: Kort, E. A., Plant, G., Dacic, N. (2022). Aircraft Data (2021) for Measurement of Agriculture Illuminating farm-Zone Emissions of N2O (MAIZE) [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/0jvh-0c91
- Discipline:
- Science
- Creator:
- Yang, Emily G, Kort, Eric A, Wu, Dien, Lin, John C, Oda, Tomohiro, Ye, Xinxin, and Lauvaux, Thomas
- Description:
- 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. and There are three files included in this data set, and all data are in tab-delimited form. The first file, xco2_lat.zip, 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.
- Keyword:
- greenhouse gases, carbon dioxide, urban, cities, satellite, remote sensing, Lagrangian modeling, emissions inventories, carbon cycle, and climate
- Citation to related publication:
- 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. https://doi.org/10.1029/2019JD031922
- Discipline:
- Science