98 citations as recorded by crossref.

1. Taehwa Research Forest: a receptor site for severe domestic pollution events in Korea during 2016 J. Sullivan et al. 10.5194/acp-19-5051-2019
2. Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study C. Whaley et al. 10.5194/acp-22-5775-2022
3. Anthropogenic emissions estimated using surface observations and their impacts on PM2.5 source apportionment over the Yangtze River Delta, China S. Feng et al. 10.1016/j.scitotenv.2022.154522
4. Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
5. A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data K. Miyazaki et al. 10.5194/acp-15-8315-2015
6. CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model D. Pendergrass et al. 10.5194/gmd-16-4793-2023
7. Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis K. Miyazaki & K. Bowman 10.5194/acp-17-8285-2017
8. A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity S. Naus et al. 10.5194/acp-21-4809-2021
9. Changes in US background ozone associated with the 2011 turnaround in Chinese NOx emissions K. Miyazaki et al. 10.1088/2515-7620/ac619b
10. Forecasting of Asian dust storm that occurred on May 10–13, 2011, using an ensemble-based data assimilation system K. Yumimoto et al. 10.1016/j.partic.2015.09.001
11. Multiconstituent Data Assimilation With WRF‐Chem/DART: Potential for Adjusting Anthropogenic Emissions and Improving Air Quality Forecasts Over Eastern China C. Ma et al. 10.1029/2019JD030421
12. Toward a multivariate formulation of the parametric Kalman filter assimilation: application to a simplified chemical transport model A. Perrot et al. 10.5194/npg-30-139-2023
13. Improving PM<sub>2. 5</sub> forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter Z. Peng et al. 10.5194/acp-17-4837-2017
14. Inverse modeling of SO<sub>2</sub> and NO<sub><i>x</i></sub> emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts Y. Wang et al. 10.5194/acp-20-6651-2020
15. A modeling study of effective radiative forcing and climate response due to tropospheric ozone B. Xie et al. 10.1007/s00376-016-5193-0
16. Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model B. Gaubert et al. 10.5194/gmd-7-283-2014
17. Improvement of PM2.5 Forecast in China by Ground-Based Multi-Pollutant Emission Source Inversion in 2022 L. Zhu et al. 10.3390/atmos15020181
18. Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China Q. Zhao et al. 10.1155/2021/9933466
19. Impacts of Horizontal Resolution on Global Data Assimilation of Satellite Measurements for Tropospheric Chemistry Analysis T. Sekiya et al. 10.1029/2020MS002180
20. Assimilating compact phase space retrievals (CPSRs): comparison with independent observations (MOZAIC in situ and IASI retrievals) and extension to assimilation of truncated retrieval profiles A. Mizzi et al. 10.5194/gmd-11-3727-2018
21. A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application S. Feng et al. 10.5194/gmd-16-5949-2023
22. Retrievals of tropospheric ozone profiles from the synergism of AIRS and OMI: methodology and validation D. Fu et al. 10.5194/amt-11-5587-2018
23. Inferring and evaluating satellite-based constraints on NOx emissions estimates in air quality simulations J. East et al. 10.5194/acp-22-15981-2022
24. Evaluating Carbon Monoxide and Aerosol Optical Depth Simulations from CAM-Chem Using Satellite Observations D. Alvim et al. 10.3390/rs13112231
25. Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
26. Implications of carbon monoxide bias for methane lifetime and atmospheric composition in chemistry climate models S. Strode et al. 10.5194/acp-15-11789-2015
27. Accounting for model error in air quality forecasts: an application of 4DEnVar to the assimilation of atmospheric composition using QG-Chem 1.0 E. Emili et al. 10.5194/gmd-9-3933-2016
28. Decadal changes in global surface NO<sub><i>x</i></sub> emissions from multi-constituent satellite data assimilation K. Miyazaki et al. 10.5194/acp-17-807-2017
29. Evaluation and uncertainty investigation of the NO<sub>2</sub>, CO and NH<sub>3</sub> modeling over China under the framework of MICS-Asia III L. Kong et al. 10.5194/acp-20-181-2020
30. Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018 K. Miyazaki et al. 10.5194/essd-12-2223-2020
31. First Top‐Down Estimates of Anthropogenic NOx Emissions Using High‐Resolution Airborne Remote Sensing Observations A. Souri et al. 10.1002/2017JD028009
32. Quantifying impacts of crop residue burning in the North China Plain on summertime tropospheric ozone over East Asia M. Ma et al. 10.1016/j.atmosenv.2018.09.018
33. Comparison between the assimilation of IASI Level 2 ozone retrievals and Level 1 radiances in a chemical transport model E. Emili et al. 10.5194/amt-12-3963-2019
34. Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS A. Inness et al. 10.5194/acp-15-5275-2015
35. Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
36. Sensitivity of top-down CO source estimates to the modeled vertical structure in atmospheric CO Z. Jiang et al. 10.5194/acp-15-1521-2015
37. The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework K. Yumimoto & T. Takemura 10.5194/gmd-6-2005-2013
38. Vertical Profile of Ozone Derived from Combined MLS and TES Satellite Observations J. Liu et al. 10.3390/rs14071588
39. Intercomparison of Remote Sensing Retrievals: An Examination of Prior-Induced Biases in Averaging Kernel Corrections H. Nguyen & J. Hobbs 10.3390/rs12193239
40. Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ B. Gaubert et al. 10.5194/acp-20-14617-2020
41. Impact of model resolution and its representativeness consistency with observations on operational prediction of PM2.5 with 3D-VAR data assimilation Y. Wei et al. 10.1016/j.apr.2024.102141
42. Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations W. Ma et al. 10.1029/2023JD038937
43. Estimating daily full-coverage near surface O3, CO, and NO2 concentrations at a high spatial resolution over China based on S5P-TROPOMI and GEOS-FP Y. Wang et al. 10.1016/j.isprsjprs.2021.03.018
44. The impact of observing characteristics on the ability to predict ozone under varying polluted photochemical regimes P. Hamer et al. 10.5194/acp-15-10645-2015
45. Regional CO<sub>2</sub> fluxes from 2010 to 2015 inferred from GOSAT XCO<sub>2</sub> retrievals using a new version of the Global Carbon Assimilation System F. Jiang et al. 10.5194/acp-21-1963-2021
46. The assessment of potential observability for joint chemical states and emissions in atmospheric modelings X. Wu et al. 10.1007/s00477-021-02113-x
47. Improved ozone simulation in East Asia via assimilating observations from the first geostationary air-quality monitoring satellite: Insights from an Observing System Simulation Experiment L. Shu et al. 10.1016/j.atmosenv.2022.119003
48. Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model S. Skachko et al. 10.5194/gmd-7-1451-2014
49. An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2 V. Huijnen et al. 10.5194/gmd-13-1513-2020
50. Transboundary ozone pollution across East Asia: daily evolution and photochemical production analysed by IASI + GOME2 multispectral satellite observations and models J. Cuesta et al. 10.5194/acp-18-9499-2018
51. Detection and emission estimates of NOx sources over China North Plain using OMI observations J. Zhang et al. 10.1080/01431161.2018.1430402
52. Significant contribution of carbonyls to atmospheric oxidation capacity (AOC) during the winter haze pollution over North China Plain X. Yang et al. 10.1016/j.jes.2023.06.004
53. Quantifying Emissions of CO and NOx Using Observations From MOPITT, OMI, TES, and OSIRIS X. Zhang et al. 10.1029/2018JD028670
54. On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations O. Stein et al. 10.5194/acp-14-9295-2014
55. Fall of oxidized while rise of reduced reactive nitrogen deposition in China L. Liu et al. 10.1016/j.jclepro.2020.122875
56. Ensemble Dispersion Simulation of a Point-Source Radioactive Aerosol Using Perturbed Meteorological Fields over Eastern Japan T. Sekiyama et al. 10.3390/atmos12060662
57. Assessment of the Meteorological Impact on Improved PM2.5 Air Quality Over North China During 2016–2019 Based on a Regional Joint Atmospheric Composition Reanalysis Data‐Set X. Kou et al. 10.1029/2020JD034382
58. Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study M. Huang et al. 10.5194/acp-17-5721-2017
59. NO<sub><i>x</i></sub> emission estimates during the 2014 Youth Olympic Games in Nanjing J. Ding et al. 10.5194/acp-15-9399-2015
60. Deriving tropospheric ozone from assimilated profiles J. van Peet & R. van der A 10.5194/acp-19-8297-2019
61. The status of carbon neutrality of the world's top 5 CO2 emitters as seen by carbon satellites F. Jiang et al. 10.1016/j.fmre.2022.02.001
62. Structural uncertainty in air mass factor calculation for NO<sub>2</sub> and HCHO satellite retrievals A. Lorente et al. 10.5194/amt-10-759-2017
63. Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis K. Miyazaki et al. 10.5194/acp-20-931-2020
64. CO Emissions Inferred From Surface CO Observations Over China in December 2013 and 2017 S. Feng et al. 10.1029/2019JD031808
65. Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification J. Silver et al. 10.1007/s10874-015-9326-0
66. Toward a chemical reanalysis in a coupled chemistry‐climate model: An evaluation of MOPITT CO assimilation and its impact on tropospheric composition B. Gaubert et al. 10.1002/2016JD024863
67. Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM‐CAM‐chem and DART J. Barré et al. 10.1002/2015JD023467
68. Evaluating the Impact of Emissions Regulations on the Emissions Reduction During the 2015 China Victory Day Parade With an Ensemble Square Root Filter K. Chu et al. 10.1002/2017JD027631
69. Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models M. Bocquet et al. 10.5194/acp-15-5325-2015
70. H 2 in Antarctic firn air: Atmospheric reconstructions and implications for anthropogenic emissions J. Patterson et al. 10.1073/pnas.2103335118
71. Emissions estimation from satellite retrievals: A review of current capability D. Streets et al. 10.1016/j.atmosenv.2013.05.051
72. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
73. Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs X. Liu et al. 10.5194/acp-17-7067-2017
74. Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation L. Kong et al. 10.5194/acp-23-6217-2023
75. Improved western U.S. background ozone estimates via constraining nonlocal and local source contributions using Aura TES and OMI observations M. Huang et al. 10.1002/2014JD022993
76. Changes in nitrogen oxides emissions in California during 2005–2010 indicated from top‐down and bottom‐up emission estimates M. Huang et al. 10.1002/2014JD022268
77. A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC L. Kong et al. 10.5194/essd-13-529-2021
78. Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide E. Ryan & O. Wild 10.5194/gmd-14-5373-2021
79. Toward the next generation of air quality monitoring: Ozone K. Bowman 10.1016/j.atmosenv.2013.07.007
80. Balance of Emission and Dynamical Controls on Ozone During the Korea‐United States Air Quality Campaign From Multiconstituent Satellite Data Assimilation K. Miyazaki et al. 10.1029/2018JD028912
81. Global lightning NO<sub>x</sub> production estimated by an assimilation of multiple satellite data sets K. Miyazaki et al. 10.5194/acp-14-3277-2014
82. Improving ozone simulations in Asia via multisource data assimilation: results from an observing system simulation experiment with GEMS geostationary satellite observations L. Shu et al. 10.5194/acp-23-3731-2023
83. Long-term evaluation of atmospheric composition reanalyses from CAMS, TCR-2, and MERRA-2 over South Korea: Insights into applications, implications, and limitations Y. Ryu & S. Min 10.1016/j.atmosenv.2020.118062
84. An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
85. Horizontal Resolution Dependence of Atmospheric Simulations of the Fukushima Nuclear Accident Using 15-km, 3-km, and 500-m Grid Models T. SEKIYAMA et al. 10.2151/jmsj.2015-002
86. Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite K. Yumimoto et al. 10.1002/2016GL069298
87. CO variability and its association with household cooking fuels consumption over the Indo-Gangetic Plains A. Pandey et al. 10.1016/j.envpol.2016.12.080
88. Combined assimilation of IASI and MLS observations to constrain tropospheric and stratospheric ozone in a global chemical transport model E. Emili et al. 10.5194/acp-14-177-2014
89. EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06) S. Skachko et al. 10.5194/gmd-9-2893-2016
90. Impacts of geostationary satellite measurements on CO forecasting: An observing system simulation experiment with GEOS-Chem/LETKF data assimilation system K. Yumimoto 10.1016/j.atmosenv.2013.03.032
91. Key chemical NO<sub>x</sub> sink uncertainties and how they influence top-down emissions of nitrogen oxides T. Stavrakou et al. 10.5194/acp-13-9057-2013
92. A comparison of the impact of TROPOMI and OMI tropospheric NO<sub>2</sub> on global chemical data assimilation T. Sekiya et al. 10.5194/amt-15-1703-2022
93. A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 over North America: Part II. Evaluation of column variable predictions using satellite data K. Wang et al. 10.1016/j.atmosenv.2014.07.044
94. Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments J. van Peet et al. 10.5194/acp-18-1685-2018
95. The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. 10.5194/acp-18-17387-2018
96. Improvement of PM2.5 forecast over China by the joint adjustment of initial conditions and emissions with the NLS-4DVar method S. Zhang et al. 10.1016/j.atmosenv.2021.118896
97. The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations V. Khade et al. 10.5194/gmd-14-2525-2021
98. Improvement of air quality forecasts with satellite and ground based particulate matter observations M. Hirtl et al. 10.1016/j.atmosenv.2013.11.027