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Open Data Commons Attribution (ODC-By) V1.0, Open Access
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Dataset
High spatial resolution top-down SO2 and NOx emissions over China
University of Iowa
10/19/2020
DOI: 10.25820/data.006134
Abstract
Accurate air quality simulation and forecast require timely-updated emission inventory. Compared with the bottom-up approach that has at least one-year time lag, the top-down approach that uses satellite observations of atmospheric composition to estimate emissions can provide timely emission inventory. We integrate SO2 and NO2 observations from the Ozone Monitoring Instrument (OMI) Ozone Mapping and Profiler Suite (OMPS) satellite sensors with the GEOS-Chem adjoin model to estimate SO2 and NOx emissions over China (2005-12-01 to 2012-01-20 and 2013-10-01 to 2013-10-31) (Qu et al., 2019; Wang et al., 2016; Wang et al., 2020a). These emission estimate are conducted at coarse resolution to save time computational time, and they are further downscaled (Wang et al., 2020b) to fine resolution (0.25 deg x 0.25 deg or 0.05 deg x 0.05 deg) using Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light or emission distribution proxy data. The fine-resolution emission inventory is summarized in the dataset, and it is useful for improve simulation and forecast of SO2 and NO2 concentrations. References: Qu, Z., Henze, D. K., Theys, N., Wang, J., and Wang, W.: Hybrid Mass Balance/4D-Var Joint Inversion of NOx and SO2 Emissions in East Asia, J. Geophys. Res., 124, 8203-8224, 10.1029/2018JD030240, 2019. Wang, Y., Wang, J., Xu, X., Henze, D. K., Wang, Y., and Qu, Z.: A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts, Geophys. Res. Lett., 43, 9931-9938, 10.1002/2016GL070204, 2016. Wang, Y., Wang, J., Xu, X., Henze, D. K., Qu, Z., and Yang, K.: Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data Ð Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, 10.5194/acp-20-6631-2020, 2020a. Wang, Y., Wang, J., Xu, X., Henze, D. K., Qu, Z., and Yang, K.: Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data Ð Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, 10.5194/acp-20-6631-2020, 2020b
Details
- Title: Subtitle
- High spatial resolution top-down SO2 and NOx emissions over China
- Creators
- Yi Wang - University of Iowa, Iowa Technology InstituteJun Wang - University of Iowa, Chemical and Biochemical EngineeringDaven K Henze - University of Colorado BoulderZhen Qu - Harvard University
- Resource Type
- Dataset
- Publisher
- University of Iowa
- DOI
- 10.25820/data.006134
- Size
- 90 files in one zipped archive
- Grants
- 80NSSC19K0950, National Aeronautics and Space Administration (United States, Washington) - NASANNX17AF77G, National Aeronautics and Space Administration (United States, Washington) - NASASV7-87011, National Aeronautics and Space Administration (United States, Washington) - NASA
- Language
- English
- Date published
- 10/19/2020
- Description methods
- Satellite data (OMI and OMPS SO2 and NO2) are used to constrain SO2 and NOx emissions at coarse spatial resolution to constrain SO2 and NOx emissions over China (Qu et al., 2019; Wang et al., 2016; Wang et al., 2020a), which are further downscaled to fine spatial resolution using the downscaling approaches (Wang et al., 2020b).
- Academic Unit
- Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering; Civil and Environmental Engineering
- Record Identifier
- 9983995497102771
Metrics
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