An Observing System Simulation Experiment Analysis of How Well Geostationary Satellite Trace‐Gas Observations Constrain NOx Emissions in the US

Author:

Hsu Chia‐Hua123ORCID,Henze Daven K.1ORCID,Mizzi Arthur P.1345,González Abad Gonzalo6ORCID,He Jian23,Harkins Colin23ORCID,Naeger Aaron R.7,Lyu Congmeng23,Liu Xiong6ORCID,Chan Miller Christopher68,Pierce R. Bradley9,Johnson Matthew S.10ORCID,McDonald Brian C.3

Affiliation:

1. Department of Mechanical Engineering University of Colorado Boulder Boulder CO USA

2. Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USA

3. NOAA Chemical Sciences Laboratory Boulder CO USA

4. NASA Earth Exchange NASA Ames Research Center Moffett Field CA USA

5. Bay Area Environmental Research Institute Moffett Field CA USA

6. Center for Astrophysics Harvard & Smithsonian Cambridge MA USA

7. Earth System Science Center University of Alabama in Huntsville Huntsville AL USA

8. Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA

9. Space Science and Engineering Center University of Wisconsin‐Madison Madison WI USA

10. Earth Science Division NASA Ames Research Center Moffett Field CA USA

Abstract

AbstractWe investigate the benefit of assimilating high spatial‐temporal resolution nitrogen dioxide (NO2) measurements from a geostationary (GEO) instrument such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) versus a low‐earth orbit (LEO) platform like TROPOspheric Monitoring Instrument (TROPOMI) on the inverse modeling of nitrogen oxides (NOx) emissions. We generated synthetic TEMPO and TROPOMI NO2 measurements based on emissions from the COVID‐19 lockdown period. Starting with emissions levels prior to the lockdown, we use the Weather Research and Forecasting Model coupled with Chemistry/Data Assimilation Research Testbed (WRF‐Chem/DART) to assimilate these pseudo‐observations in Observing System Simulation Experiments to adjust NOx emissions and quantify how well the assimilation of TEMPO versus TROPOMI measurements recovers the lockdown‐induced emissions changes. We find that NOx emission biases can be ameliorated using half as many simulation days when assimilating GEO observations, and the estimated NOx emissions in 23 out of 29 major urban regions in the US are more accurate. The root mean square error and coefficient of determination of posterior NOx emissions are reduced by 12.5%–41.5% and 1.5%–17.1%, respectively, across different regions. We conduct sensitivity experiments that use different data assimilation (DA) configurations to assimilate synthetic GEO observations. Results demonstrate that the temporal width of the DA window introduces −10% to −20% biases in the emissions inversion and constraining both NOx concentrations and emissions simultaneously yields the most accurate NOx emissions estimates. Our work serves as a valuable reference on how to appropriately assimilate GEO observations for constraining NOx emissions in future studies.

Publisher

American Geophysical Union (AGU)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. GeoXO: NOAA’s Future Geostationary Satellite System;Bulletin of the American Meteorological Society;2024-03

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