101 citations as recorded by crossref.

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2. Development of four-dimensional variational assimilation system based on the GRAPES–CUACE adjoint model (GRAPES–CUACE-4D-Var V1.0) and its application in emission inversion C. Wang et al. 10.5194/gmd-14-337-2021
3. Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0 J. Jin et al. 10.5194/gmd-14-5607-2021
4. Study of Methodology for Estimating PM10Concentration of Asian Dust Using Visibility Data H. Lee et al. 10.14191/Atmos.2012.22.1.013
5. Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in China's Jing-Jin-Ji area T. Liu et al. 10.5194/acp-17-2971-2017
6. Inverse modeling of black carbon emissions over China using ensemble data assimilation P. Wang et al. 10.5194/acp-16-989-2016
7. Incorporation and improvement of a heterogeneous chemistry mechanism in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on secondary inorganic aerosol and PM2.5 simulations in Middle-Eastern China Z. Liu et al. 10.1016/j.scitotenv.2022.157530
8. Description and evaluation of a newly developed emission inventory processing system (EMIPS) W. Chen et al. 10.1016/j.scitotenv.2023.161909
9. Assessment of the impacts of cloud chemistry on surface SO2 and sulfate levels in typical regions of China J. Lu et al. 10.5194/acp-23-8021-2023
10. The variability of spring sand-dust storm frequency in Northeast Asia from 1980 to 2011 Y. Yang et al. 10.1007/s13351-013-0112-0
11. Modeling study of PM2.5 pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013 C. Jiang et al. 10.5194/acp-15-5803-2015
12. Dust events in Beijing, China (2004–2006): comparison of ground-based measurements with columnar integrated observations Z. Wu et al. 10.5194/acp-9-6915-2009
13. Numerical Simulation of the Direct Radiative Effects of Dust Aerosol on the East Asian Winter Monsoon H. Sun & X. Liu 10.1155/2015/142617
14. Saltation transport rate in unsteady wind variations P. Wang & X. Zheng 10.1140/epje/i2014-14040-3
15. National Environmental Meteorological Services in China Z. Kang et al. 10.1155/2016/1985207
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24. 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
25. Application of a Neural Network to Store and Compute the Optical Properties of Non-Spherical Particles J. Yu et al. 10.1007/s00376-021-1375-5
26. The transport and deposition of dust and its impact on phytoplankton growth in the Yellow Sea S. Tan & H. Wang 10.1016/j.atmosenv.2014.10.016
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28. Assessment of meteorology vs. control measures in the China fine particular matter trend from 2013 to 2019 by an environmental meteorology index S. Gong et al. 10.5194/acp-21-2999-2021
29. Numerical Modeling of Topography-Modulated Dust Aerosol Distribution and Its Influence on the Onset of East Asian Summer Monsoon H. Sun & X. Liu 10.1155/2016/6951942
30. Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar J. Jin et al. 10.1016/j.atmosenv.2018.05.060
31. High-resolution anthropogenic emission inventory for China (2015–2024): Spatiotemporal changes and environmental application D. Li et al. 10.1016/j.atmosenv.2025.121495
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37. Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al. 10.5194/gmd-17-8223-2024
38. An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008 Q. Zhang et al. 10.1016/S1001-0742(11)60733-X
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42. Superimposed effects of typical local circulations driven by mountainous topography and aerosol–radiation interaction on heavy haze in the Beijing–Tianjin–Hebei central and southern plains in winter Y. Peng et al. 10.5194/acp-23-8325-2023
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45. A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013 H. Wang et al. 10.1016/j.atmosenv.2014.03.004
46. Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction W. Zhang et al. 10.5194/acp-25-9005-2025
47. New Directions: The need to develop process-based emission forecasting models D. Tong et al. 10.1016/j.atmosenv.2011.10.070
48. Prediction of Asian Dust Days over Northern China Using the KMA-ADAM2 Model S. Hong et al. 10.1175/WAF-D-19-0008.1
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50. Source apportionment of SPM by positive matrix factorization and PM2.5 analysis in an urban industrial area P. Khobragade & A. Ahirwar 10.1108/WJE-11-2020-0550
51. Investigation of the influence of mineral dust on airborne particulate matter during the COVID-19 epidemic in spring 2020 over China L. Liang et al. 10.1016/j.apr.2022.101424
52. Numerical Studies on a Severe Dust Storm in East Asia Using WRF-Chem X. Yu et al. 10.4236/acs.2017.71008
53. Sensitivity analysis of atmospheric oxidation capacity in Beijing based on the GRAPES-CUACE adjoint model C. Wang et al. 10.1016/j.atmosenv.2023.119641
54. Overview of current limitations and challenges in data and methods for assessing the health effects of sand and dust storms under the climate change scenario A. Tobias et al. 10.1016/j.coesh.2025.100651
55. Variability in the correlation between satellite-derived liquid cloud droplet effective radius and aerosol index over the northern Pacific Ocean S. Tan et al. 10.1080/16000889.2017.1391656
56. The application study of the revised IMPROVE atmospheric extinction algorithm in atmospheric chemistry model focusing on improving low visibility prediction in eastern China C. Han et al. 10.1016/j.atmosres.2023.107135
57. The influence of Asian dust outflow on particle microphysical and optical properties at Mt. Tai in central east China X. Shen et al. 10.1016/j.atmosenv.2016.08.014
58. The Role of Aerosol‐Radiation Interaction in the Meteorology Prediction at the Weather Scale in the Numerical Weather Prediction Model W. Zhang et al. 10.1029/2021GL097026
59. Chemistry‐Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/Fog Prediction in China H. Wang et al. 10.1029/2022MS003222
60. Numerical modeling of a strong dust event over the south China region in March 2010 K. Chow et al. 10.1007/s00703-014-0338-0
61. Tracking sensitive source areas of different weather pollution types using GRAPES-CUACE adjoint model C. Wang et al. 10.1016/j.atmosenv.2017.11.041
62. Simulating Performance of CHIMERE on a Late Autumnal Dust Storm over Northern China S. Ma et al. 10.3390/su11041074
63. Quantifying Mechanisms of Aeolian Dust Emission: Field Measurements at Etosha Pan, Namibia G. Wiggs et al. 10.1029/2022JF006675
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65. Study on the contribution of the major desert groups on SDS weather in East Asia combining the model simulation and multiple observations H. Ning et al. 10.1016/j.atmosres.2025.107967
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74. Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China J. Jin et al. 10.5194/acp-20-15207-2020
75. Single‐Scattering Properties of Encapsulated Fractal Black Carbon Particles Computed Using the Invariant Imbedding T‐Matrix Method and Deep Learning Approaches X. Wang et al. 10.1029/2023JD039568
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77. Relationships between soil moisture and dust emissions in a bare sandy soil of Mongolia E. Munkhtsetseg et al. 10.1016/j.partic.2016.03.001
78. An improved four-dimensional variation source term inversion model with observation error regularization C. Han et al. 10.1016/j.dt.2022.03.012
79. Status and Perspectives of the Validation and Evaluation of Wind-Blown Dust Models Using Three-Dimensional Air Quality Models H. Lee & S. Park 10.5572/KOSAE.2025.41.2.199
80. 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
81. Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter M. Pang et al. 10.1016/j.atmosenv.2023.119831
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86. Improving short-term forecasting of surface dust concentration in Northern China: Integrating machine learning with multi-numerical models Z. Yi et al. 10.1016/j.apr.2025.102480
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