Articles | Volume 9, issue 10
https://doi.org/10.5194/amt-9-5193-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-5193-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Oct 2016
Research article |
| 24 Oct 2016
Inverse modelling of NOx emissions over eastern China: uncertainties due to chemical non-linearity
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA, USA
now at: Department of Earth System Science, University of California,
Irvine, USA
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA, USA
Ran Yin
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA, USA
Yuzhong Zhang
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA, USA
Charles Smeltzer
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA, USA
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Cited
18 citations as recorded by crossref.
- Inferring the anthropogenic NO<sub><i>x</i></sub> emission trend over the United States during 2003–2017 from satellite observations: was there a flattening of the emission trend after the Great Recession? J. Li & Y. Wang 10.5194/acp-19-15339-2019
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- Inversing NOx emissions based on an optimization model that combines a source-receptor relationship correction matrix and monitoring data: A case study in Linyi, China M. Li et al. 10.1016/j.atmosenv.2024.120848
- The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia J. Jung et al. 10.1029/2021JD035251
- Development of an integrated machine-learning and data assimilation framework for NOx emission inversion Y. Chen et al. 10.1016/j.scitotenv.2023.161951
- Improve observation-based ground-level ozone spatial distribution by compositing satellite and surface observations: A simulation experiment Y. Zhang et al. 10.1016/j.atmosenv.2018.02.044
- High-resolution (0.05° × 0.05°) NOx emissions in the Yangtze River Delta inferred from OMI H. Kong et al. 10.5194/acp-19-12835-2019
- Development and Assessment of a Fast NO2 Detection System with Luminol Chemiluminescence Reaction J. Kim et al. 10.5572/KOSAE.2022.38.5.734
- Enhanced trans-Himalaya pollution transport to the Tibetan Plateau by cut-off low systems R. Zhang et al. 10.5194/acp-17-3083-2017
- Estimator of Surface Ozone Using Formaldehyde and Carbon Monoxide Concentrations Over the Eastern United States in Summer Y. Cheng et al. 10.1029/2018JD028452
- Comparing OMI-based and EPA AQS in situ NO<sub>2</sub> trends: towards understanding surface NO<sub><i>x</i></sub> emission changes R. Zhang et al. 10.5194/amt-11-3955-2018
- Comparison and evaluation of anthropogenic emissions of SO<sub>2</sub> and NO<sub><i>x</i></sub> over China M. Li et al. 10.5194/acp-18-3433-2018
- Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea J. Mun et al. 10.1016/j.atmosenv.2022.119429
- Monthly top‐down NOx emissions for China (2005–2012): A hybrid inversion method and trend analysis Z. Qu et al. 10.1002/2016JD025852
- Evaluating the methods and influencing factors of satellite-derived estimates of NOX emissions at regional scale: A case study for Yangtze River Delta, China Y. Yang et al. 10.1016/j.atmosenv.2019.117051
- Effect of changing NO<sub><i>x</i></sub> lifetime on the seasonality and long-term trends of satellite-observed tropospheric NO<sub>2</sub> columns over China V. Shah et al. 10.5194/acp-20-1483-2020
- NOx Emission Reduction and Recovery during COVID-19 in East China R. Zhang et al. 10.3390/atmos11040433
- Summertime Clean-Background Ozone Concentrations Derived from Ozone Precursor Relationships are Lower than Previous Estimates in the Southeast United States Q. Yan et al. 10.1021/acs.est.1c03035
18 citations as recorded by crossref.
- Inferring the anthropogenic NO<sub><i>x</i></sub> emission trend over the United States during 2003–2017 from satellite observations: was there a flattening of the emission trend after the Great Recession? J. Li & Y. Wang 10.5194/acp-19-15339-2019
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- Inversing NOx emissions based on an optimization model that combines a source-receptor relationship correction matrix and monitoring data: A case study in Linyi, China M. Li et al. 10.1016/j.atmosenv.2024.120848
- The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia J. Jung et al. 10.1029/2021JD035251
- Development of an integrated machine-learning and data assimilation framework for NOx emission inversion Y. Chen et al. 10.1016/j.scitotenv.2023.161951
- Improve observation-based ground-level ozone spatial distribution by compositing satellite and surface observations: A simulation experiment Y. Zhang et al. 10.1016/j.atmosenv.2018.02.044
- High-resolution (0.05° × 0.05°) NOx emissions in the Yangtze River Delta inferred from OMI H. Kong et al. 10.5194/acp-19-12835-2019
- Development and Assessment of a Fast NO2 Detection System with Luminol Chemiluminescence Reaction J. Kim et al. 10.5572/KOSAE.2022.38.5.734
- Enhanced trans-Himalaya pollution transport to the Tibetan Plateau by cut-off low systems R. Zhang et al. 10.5194/acp-17-3083-2017
- Estimator of Surface Ozone Using Formaldehyde and Carbon Monoxide Concentrations Over the Eastern United States in Summer Y. Cheng et al. 10.1029/2018JD028452
- Comparing OMI-based and EPA AQS in situ NO<sub>2</sub> trends: towards understanding surface NO<sub><i>x</i></sub> emission changes R. Zhang et al. 10.5194/amt-11-3955-2018
- Comparison and evaluation of anthropogenic emissions of SO<sub>2</sub> and NO<sub><i>x</i></sub> over China M. Li et al. 10.5194/acp-18-3433-2018
- Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea J. Mun et al. 10.1016/j.atmosenv.2022.119429
- Monthly top‐down NOx emissions for China (2005–2012): A hybrid inversion method and trend analysis Z. Qu et al. 10.1002/2016JD025852
- Evaluating the methods and influencing factors of satellite-derived estimates of NOX emissions at regional scale: A case study for Yangtze River Delta, China Y. Yang et al. 10.1016/j.atmosenv.2019.117051
- Effect of changing NO<sub><i>x</i></sub> lifetime on the seasonality and long-term trends of satellite-observed tropospheric NO<sub>2</sub> columns over China V. Shah et al. 10.5194/acp-20-1483-2020
- NOx Emission Reduction and Recovery during COVID-19 in East China R. Zhang et al. 10.3390/atmos11040433
- Summertime Clean-Background Ozone Concentrations Derived from Ozone Precursor Relationships are Lower than Previous Estimates in the Southeast United States Q. Yan et al. 10.1021/acs.est.1c03035
Latest update: 20 Nov 2024
Short summary
We show in this study that the non-linearity of NOx chemistry implies that the local derivative (of a first-order Taylor expansion) is better suited in the inverse modelling of NOx emissions over eastern China. We used single-grid-cell-based perturbation sensitivity calculation. The method leads to smaller NOx emission over highly polluted regions and higher NOx emission over rural regions. There are also more consistent results from using two different satellite instruments.
We show in this study that the non-linearity of NOx chemistry implies that the local derivative...
