59 citations as recorded by crossref.

1. Development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: aiming to improve air quality forecasting and diagnose model deficiencies W. Sun et al. 10.5194/acp-20-9311-2020
2. A temporally and spatially resolved validation of emission inventories by measurements of ambient volatile organic compounds in Beijing, China M. Wang et al. 10.5194/acp-14-5871-2014
3. Improved Inversion of Monthly Ammonia Emissions in China Based on the Chinese Ammonia Monitoring Network and Ensemble Kalman Filter L. Kong et al. 10.1021/acs.est.9b02701
4. Future tropospheric ozone budget and distribution over east Asia under a net-zero scenario X. Hou et al. 10.5194/acp-23-15395-2023
5. Trends of non-methane hydrocarbons (NMHC) emissions in Beijing during 2002–2013 M. Wang et al. 10.5194/acp-15-1489-2015
6. Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method X. Zhang et al. 10.1029/2020JD033599
7. 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
8. 3DVAR meteorological data assimilation and aerosol impact on the simulation of heat wave 2022 over Haryana using WRF-Chem P. Deb et al. 10.1016/j.apr.2025.102440
9. Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions S. Li et al. 10.5194/gmd-16-4171-2023
10. Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 1. Bias Correction With Surface Observations in Nonrural Areas H. Zhang et al. 10.1029/2019JD032293
11. 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
12. Limitations of ozone data assimilation with adjustment of NOx emissions: mixed effects on NO2 forecasts over Beijing and surrounding areas X. Tang et al. 10.5194/acp-16-6395-2016
13. High-spatiotemporal-resolution inverse estimation of CO and NOx emission reductions during emission control periods with a modified ensemble Kalman filter H. Wu et al. 10.1016/j.atmosenv.2020.117631
14. Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods U. Dash et al. 10.1016/j.envpol.2023.121099
15. Improving PM2. 5 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
16. 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
17. Dataset for atmospheric transport of nutrients during a harmful algal bloom R. Tian et al. 10.1016/j.dib.2020.105839
18. 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
19. A new inverse modeling approach for emission sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei region X. Cheng et al. 10.5194/acp-21-13747-2021
20. 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
21. 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
22. An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. 10.5194/gmd-15-3555-2022
23. 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
24. Inversion of CO emissions over Beijing and its surrounding areas with ensemble Kalman filter X. Tang et al. 10.1016/j.atmosenv.2013.08.051
25. Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts C. Ma et al. 10.1007/s00376-017-7179-y
26. Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5 S. Park et al. 10.5194/gmd-15-2773-2022
27. Improvement of AI forecast of gridded PM2.5 forecast in China through ConvLSTM and Attention P. Liu et al. 10.1007/s42514-021-00087-4
28. Evaluation and uncertainty investigation of the NO2, CO and NH3 modeling over China under the framework of MICS-Asia III L. Kong et al. 10.5194/acp-20-181-2020
29. Constraining non-methane VOC emissions with TROPOMI HCHO observations: impact on summertime ozone simulation in August 2022 in China S. Feng et al. 10.5194/acp-24-7481-2024
30. Fusing Observational, Satellite Remote Sensing and Air Quality Model Simulated Data to Estimate Spatiotemporal Variations of PM2.5 Exposure in China T. Xue et al. 10.3390/rs9030221
31. Development of an integrated machine learning model to improve the secondary inorganic aerosol simulation over the Beijing–Tianjin–Hebei region N. Ding et al. 10.1016/j.atmosenv.2024.120483
32. Impacts of using an ensemble Kalman filter on air quality simulations along the California–Mexico border region during Cal–Mex 2010 Field Campaign N. Bei et al. 10.1016/j.scitotenv.2014.07.121
33. 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
34. 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
35. Relative effects of open biomass burning and open crop straw burning on haze formation over central and eastern China: modeling study driven by constrained emissions K. Mehmood et al. 10.5194/acp-20-2419-2020
36. 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
37. Ozone pollution characteristics and sensitivity analysis using an observation-based model in Nanjing, Yangtze River Delta Region of China M. Wang et al. 10.1016/j.jes.2020.02.027
38. Forecasting O3 and NO2 concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach Z. Li et al. 10.1016/j.envint.2024.109249
39. 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
40. 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
41. Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau M. Zhao et al. 10.5194/acp-24-235-2024
42. Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation J. Wu et al. 10.1016/j.partic.2014.10.008
43. EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06) S. Skachko et al. 10.5194/gmd-9-2893-2016
44. The Technologies for Global Four-Dimensional Variational Data Assimilation of Ozone Observations 小. 曹 10.12677/AG.2017.76088
45. Ozone source apportionment over the Yangtze River Delta region, China: Investigation of regional transport, sectoral contributions and seasonal differences L. Li et al. 10.1016/j.atmosenv.2019.01.028
46. 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
47. Ozone formation sensitivity study using machine learning coupled with the reactivity of volatile organic compound species J. Zhan et al. 10.5194/amt-15-1511-2022
48. Ensemble-based simultaneous emission estimates and improved forecast of radioactive pollution from nuclear power plant accidents: application to ETEX tracer experiment X. Zhang et al. 10.1016/j.jenvrad.2015.01.013
49. Transition in air pollution, disease burden and health cost in China: A comparative study of long-term and short-term exposure J. Liu et al. 10.1016/j.envpol.2021.116770
50. A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China G. Jia et al. 10.1016/j.jes.2021.08.048
51. 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
52. The Impact of the Numbers of Monitoring Stations on the National and Regional Air Quality Assessment in China During 2013–18 H. Luo et al. 10.1007/s00376-022-1346-5
53. 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
54. The 2015 and 2016 wintertime air pollution in China: SO2 emission changes derived from a WRF-Chem/EnKF coupled data assimilation system D. Chen et al. 10.5194/acp-19-8619-2019
55. 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
56. Estimating adult mortality attributable to PM2.5 exposure in China with assimilated PM2.5 concentrations based on a ground monitoring network J. Liu et al. 10.1016/j.scitotenv.2016.05.165
57. Kalman filter-based air quality forecast adjustment K. De Ridder et al. 10.1016/j.atmosenv.2012.01.032
58. PM2.5 analog forecast and Kalman filter post-processing for the Community Multiscale Air Quality (CMAQ) model I. Djalalova et al. 10.1016/j.atmosenv.2015.02.021
59. Atmospheric transport of nutrients during a harmful algal bloom event R. Tian et al. 10.1016/j.rsma.2019.101007