Articles | Volume 22, issue 2
https://doi.org/10.5194/acp-22-1333-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-1333-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2022
Research article |
| 26 Jan 2022
| 26 Jan 2022
A new method for inferring city emissions and lifetimes of nitrogen oxides from high-resolution nitrogen dioxide observations: a model study
Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD 21046, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
now at: Morgan State University, Goddard Earth Sciences Technology and Research (GESTAR) II, Baltimore, MD 21251, USA
Zhining Tao
Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD 21046, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
now at: Morgan State University, Goddard Earth Sciences Technology and Research (GESTAR) II, Baltimore, MD 21251, USA
Steffen Beirle
Max-Planck-Institut für Chemie, 55128 Mainz, Germany
Joanna Joiner
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Yasuko Yoshida
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Science Systems and Applications Inc., Lanham, MD 20706, USA
Steven J. Smith
Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740, USA
K. Emma Knowland
Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD 21046, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
now at: Morgan State University, Goddard Earth Sciences Technology and Research (GESTAR) II, Baltimore, MD 21251, USA
Thomas Wagner
Max-Planck-Institut für Chemie, 55128 Mainz, Germany
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Cited
20 citations as recorded by crossref.
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Quantifying Urban Daily Nitrogen Oxide Emissions from Satellite Observations T. Tang et al. 10.3390/atmos15040508
- NH3 Emissions and Lifetime Estimated by Satellite Observations with Differential Evolution Algorithm Y. Xie et al. 10.3390/atmos15030251
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting J. Joiner et al. 10.5194/amt-16-481-2023
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- Estimating the variability in NOx emissions from Wuhan with TROPOMI NO2 data during 2018 to 2023 Q. Zhang et al. 10.5194/acp-25-3313-2025
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al. 10.1016/j.scitotenv.2024.172779
- Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset J. Hakkarainen et al. 10.3389/frsen.2022.878731
- S‐5P/TROPOMI‐Derived NOxEmissions From Copper/Cobalt Mining and Other Industrial Activities in the Copperbelt (Democratic Republic of Congo and Zambia) S. Martínez‐Alonso et al. 10.1029/2023GL104109
- Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021 X. Liu et al. 10.1016/j.scitotenv.2023.169693
- Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes F. Cifuentes et al. 10.5194/gmd-18-621-2025
- A new method for estimating megacity NOx emissions and lifetimes from satellite observations S. Beirle & T. Wagner 10.5194/amt-17-3439-2024
- The attempt to estimate annual variability of NOx emission in Poland using Sentinel-5P/TROPOMI data J. Godłowska et al. 10.1016/j.atmosenv.2022.119482
- Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2 D. Goldberg et al. 10.1016/j.rse.2023.113917
- Impact of Hurricane Ida on Nitrogen Oxide Emissions in Southwestern Louisiana Detected from Space T. Lee et al. 10.1021/acs.estlett.2c00414
- Evaluation of the WRF-Chem performance for the air pollutants over the United Arab Emirates Y. Yarragunta et al. 10.5194/acp-25-1685-2025
- High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns F. Liu et al. 10.5194/acp-24-3717-2024
- Estimations of NOxemissions, NO2lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2observations M. Pommier 10.1039/D2EA00086E
- UNCERTAINTY QUANTIFICATION BY GAUSSIAN RANDOM FIELDS FOR POINT-LIKE EMISSIONS FROM SATELLITE OBSERVATIONS T. Härkönen et al. 10.1615/Int.J.UncertaintyQuantification.2023044906
19 citations as recorded by crossref.
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Quantifying Urban Daily Nitrogen Oxide Emissions from Satellite Observations T. Tang et al. 10.3390/atmos15040508
- NH3 Emissions and Lifetime Estimated by Satellite Observations with Differential Evolution Algorithm Y. Xie et al. 10.3390/atmos15030251
- Estimating global 0.1° scale gridded anthropogenic CO2 emissions using TROPOMI NO2 and a data-driven method Y. Zhang et al. 10.1016/j.scitotenv.2024.175177
- Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting J. Joiner et al. 10.5194/amt-16-481-2023
- A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx D. Wu et al. 10.5194/gmd-16-6161-2023
- Estimating the variability in NOx emissions from Wuhan with TROPOMI NO2 data during 2018 to 2023 Q. Zhang et al. 10.5194/acp-25-3313-2025
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al. 10.1016/j.scitotenv.2024.172779
- Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset J. Hakkarainen et al. 10.3389/frsen.2022.878731
- S‐5P/TROPOMI‐Derived NOxEmissions From Copper/Cobalt Mining and Other Industrial Activities in the Copperbelt (Democratic Republic of Congo and Zambia) S. Martínez‐Alonso et al. 10.1029/2023GL104109
- Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021 X. Liu et al. 10.1016/j.scitotenv.2023.169693
- Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes F. Cifuentes et al. 10.5194/gmd-18-621-2025
- A new method for estimating megacity NOx emissions and lifetimes from satellite observations S. Beirle & T. Wagner 10.5194/amt-17-3439-2024
- The attempt to estimate annual variability of NOx emission in Poland using Sentinel-5P/TROPOMI data J. Godłowska et al. 10.1016/j.atmosenv.2022.119482
- Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2 D. Goldberg et al. 10.1016/j.rse.2023.113917
- Impact of Hurricane Ida on Nitrogen Oxide Emissions in Southwestern Louisiana Detected from Space T. Lee et al. 10.1021/acs.estlett.2c00414
- Evaluation of the WRF-Chem performance for the air pollutants over the United Arab Emirates Y. Yarragunta et al. 10.5194/acp-25-1685-2025
- High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns F. Liu et al. 10.5194/acp-24-3717-2024
- Estimations of NOxemissions, NO2lifetime and their temporal variation over three British urbanised regions in 2019 using TROPOMI NO2observations M. Pommier 10.1039/D2EA00086E
Latest update: 03 Jul 2025
Short summary
In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
In this work, we present a novel method to infer NOx emissions and lifetimes based on...
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