Articles | Volume 15, issue 4
https://doi.org/10.5194/acp-15-1601-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-1601-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Feb 2015
Research article |
| 16 Feb 2015
Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling
W. Tang
Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA
now at: Chinese Research Academy of Environmental Sciences, Beijing, China
D. S. Cohan
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA
A. Pour-Biazar
Earth System Science Center, University of Alabama, Huntsville, AL, USA
L. N. Lamsal
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Goddard Earth Sciences Technology & Research, Universities Space Research Association, Columbia, MD, USA
A. T. White
Department of Atmospheric Science, University of Alabama, Huntsville, AL, USA
X. Xiao
Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA
W. Zhou
Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA
B. H. Henderson
Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL, USA
B. F. Lash
Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA
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Cited
9 citations as recorded by crossref.
- Improved modeling of cloudy‐sky actinic flux using satellite cloud retrievals Y. Ryu et al. 10.1002/2016GL071892
- Validation of GOES-Based Surface Insolation Retrievals and Its Utility for Model Evaluation P. Cheng et al. 10.1175/JTECH-D-19-0058.1
- Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals Y. Ryu et al. 10.5194/acp-18-7509-2018
- Reflecting on progress since the 2005 NARSTO emissions inventory report M. Day et al. 10.1080/10962247.2019.1629363
- Short history of NASA applied science teams for air quality and health T. Holloway et al. 10.1117/1.JRS.12.042611
- Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations P. Cheng et al. 10.1016/j.atmosenv.2021.118751
- Meteorological modeling relevant to mesoscale and regional air quality applications: a review R. McNider & A. Pour-Biazar 10.1080/10962247.2019.1694602
- Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments L. Lamsal et al. 10.5194/amt-14-455-2021
- Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data S. Kemball-Cook et al. 10.1016/j.atmosenv.2015.07.002
8 citations as recorded by crossref.
- Improved modeling of cloudy‐sky actinic flux using satellite cloud retrievals Y. Ryu et al. 10.1002/2016GL071892
- Validation of GOES-Based Surface Insolation Retrievals and Its Utility for Model Evaluation P. Cheng et al. 10.1175/JTECH-D-19-0058.1
- Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals Y. Ryu et al. 10.5194/acp-18-7509-2018
- Reflecting on progress since the 2005 NARSTO emissions inventory report M. Day et al. 10.1080/10962247.2019.1629363
- Short history of NASA applied science teams for air quality and health T. Holloway et al. 10.1117/1.JRS.12.042611
- Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations P. Cheng et al. 10.1016/j.atmosenv.2021.118751
- Meteorological modeling relevant to mesoscale and regional air quality applications: a review R. McNider & A. Pour-Biazar 10.1080/10962247.2019.1694602
- Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments L. Lamsal et al. 10.5194/amt-14-455-2021
Saved (final revised paper)
Latest update: 21 Nov 2024
Short summary
A joint application of multiple satellite-derived model inputs to improve Texas O3 SIP modeling is demonstrated in this study. The GOES-retrieved clouds are applied to correct the modeled photolysis rates, and the DKF inversion approach is incorporated into the CAMx-DDM model to adjust NOx emissions using OMI NO2. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together improves O3 simulations and makes O3 more sensitive to NOx emissions in the O3 non-attainment areas.
A joint application of multiple satellite-derived model inputs to improve Texas O3 SIP modeling...
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