192 citations as recorded by crossref.

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2. A Measurement‐Model Fusion Approach for Improved Wet Deposition Maps and Trends Y. Zhang et al. https://doi.org/10.1029/2018JD029051
3. Ozone Pollution in the North China Plain during the 2016 Air Chemistry Research in Asia (ARIAs) Campaign: Observations and a Modeling Study H. He et al. https://doi.org/10.3390/air2020011
4. Halogen Production from Playa Dust Emitted from the Great Salt Lake: Implications of the Shrinking Great Salt Lake on Regional Air Quality J. Christie et al. https://doi.org/10.1021/acsearthspacechem.4c00258
5. Insights into seasonal variation of wet deposition over southeast Asia via precipitation adjustment from the findings of MICS-Asia III S. Itahashi et al. https://doi.org/10.5194/acp-21-8709-2021
6. Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3 U. Im et al. https://doi.org/10.5194/acp-18-8929-2018
7. Development of Korean Air Quality Prediction System version 1 (KAQPS v1) with focuses on practical issues K. Lee et al. https://doi.org/10.5194/gmd-13-1055-2020
8. Impacts of future climate and emission changes on U.S. air quality A. Penrod et al. https://doi.org/10.1016/j.atmosenv.2014.01.001
9. A Global‐Scale Mineral Dust Equation X. Liu et al. https://doi.org/10.1029/2022JD036937
10. Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depth X. Jin et al. https://doi.org/10.5194/acp-19-295-2019
11. Observation and modeling of black soil wind-blown erosion from cropland in Northeastern China X. Zhang et al. https://doi.org/10.1016/j.aeolia.2015.07.009
12. Impacts of aerosol direct effects on tropospheric ozone through changes in atmospheric dynamics and photolysis rates J. Xing et al. https://doi.org/10.5194/acp-17-9869-2017
13. Health and economic cost estimates of short-term total and wildfire PM2.5 exposure on work loss: using the consecutive California Health Interview Survey (CHIS) data 2015–2018 Y. Meng et al. https://doi.org/10.1136/bmjph-2023-000491
14. Expanding the simulation of East Asian super dust storms: physical transport mechanisms impacting the western Pacific S. Kong et al. https://doi.org/10.5194/acp-24-1041-2024
15. Exploring deep learning for air pollutant emission estimation L. Huang et al. https://doi.org/10.5194/gmd-14-4641-2021
16. Shipborne nutrient dynamics and impact on the eutrophication in the Baltic Sea U. Raudsepp et al. https://doi.org/10.1016/j.scitotenv.2019.03.264
17. A Review of the Representation of Aerosol Mixing State in Atmospheric Models R. Stevens & A. Dastoor https://doi.org/10.3390/atmos10040168
18. The potential effects of climate change on air quality across the conterminous US at 2030 under three Representative Concentration Pathways C. Nolte et al. https://doi.org/10.5194/acp-18-15471-2018
19. Enhancing 72-Hour air quality forecasting with an observation-driven deep learning chemistry transport model S. Li & J. Xing https://doi.org/10.1016/j.envint.2025.109689
20. Estimation of Aromatic Secondary Organic Aerosol Using a Molecular Tracer—A Chemical Transport Model Assessment J. Zhang et al. https://doi.org/10.1021/acs.est.1c03670
21. Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments J. He & Y. Zhang https://doi.org/10.5194/acp-14-9171-2014
22. The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012 J. Wilkins et al. https://doi.org/10.1071/WF18053
23. Modeling Reactive Ammonia Uptake by Secondary Organic Aerosol in a Changing Climate: A WRF-CMAQ Evaluation S. Zhu et al. https://doi.org/10.3389/fenvs.2022.867908
24. Drought Impacts on Secondary Organic Aerosol: A Case Study in the Southeast United States Z. Zhao et al. https://doi.org/10.1021/acs.est.8b04842
25. Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model X. Li et al. https://doi.org/10.5194/acp-19-2327-2019
26. A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality K. Wang et al. https://doi.org/10.5194/gmd-14-7189-2021
27. A Holistic Clean Air Strategy Considering Integrated Health and Ecological Impacts Z. Dong et al. https://doi.org/10.1021/acs.est.5c08854
28. Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach Y. Hu et al. https://doi.org/10.5194/acp-14-5415-2014
29. Health-Oriented Emission Control Strategy of Energy Utilization and Its Co-CO2 Benefits: A Case Study of the Yangtze River Delta, China Z. Dong et al. https://doi.org/10.1021/acs.est.3c10693
30. Short-Term total and wildfire fine particulate matter exposure and work loss in California Y. Meng et al. https://doi.org/10.1016/j.envint.2023.108045
31. 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. https://doi.org/10.5194/gmd-15-2773-2022
32. Refinement of Modeled Aqueous-Phase Sulfate Production via the Fe- and Mn-Catalyzed Oxidation Pathway S. Itahashi et al. https://doi.org/10.3390/atmos9040132
33. Climate-driven trends of biogenic volatile organic compound emissions and their impacts on summertime ozone and secondary organic aerosol in China in the 2050s S. Liu et al. https://doi.org/10.1016/j.atmosenv.2019.117020
34. Current State of Atmospheric Aerosol Thermodynamics and Mass Transfer Modeling: A Review K. Semeniuk & A. Dastoor https://doi.org/10.3390/atmos11020156
35. Source apportionment of Pb-containing particles in Beijing during January 2013 J. Cai et al. https://doi.org/10.1016/j.envpol.2017.04.004
36. Analysis of the emission inventories and model-ready emission datasets of Europe and North America for phase 2 of the AQMEII project G. Pouliot et al. https://doi.org/10.1016/j.atmosenv.2014.10.061
37. Assessment of the effects of horizontal grid resolution on long-term air quality trends using coupled WRF-CMAQ simulations C. Gan et al. https://doi.org/10.1016/j.atmosenv.2016.02.036
38. Effects of ship emissions on air quality in the Baltic Sea region simulated with three different chemistry transport models M. Karl et al. https://doi.org/10.5194/acp-19-7019-2019
39. MICS-Asia III: multi-model comparison and evaluation of aerosol over East Asia L. Chen et al. https://doi.org/10.5194/acp-19-11911-2019
40. The acidity of atmospheric particles and clouds H. Pye et al. https://doi.org/10.5194/acp-20-4809-2020
41. Investigation of aerosol direct effects on meteorology and air quality in East Asia by using an online coupled modeling system G. Nguyen et al. https://doi.org/10.1016/j.atmosenv.2019.03.017
42. Why do models perform differently on particulate matter over East Asia? A multi-model intercomparison study for MICS-Asia III J. Tan et al. https://doi.org/10.5194/acp-20-7393-2020
43. A database and tool for boundary conditions for regional air quality modeling: description and evaluation B. Henderson et al. https://doi.org/10.5194/gmd-7-339-2014
44. Modeling intercontinental transport of ozone in North America with CAMx for the Air Quality Model Evaluation International Initiative (AQMEII) Phase 3 U. Nopmongcol et al. https://doi.org/10.5194/acp-17-9931-2017
45. A Physically Constrained Deep-Learning Fusion Method for Estimating Surface NO2 Concentration from Satellite and Ground Monitors J. Xing et al. https://doi.org/10.1021/acs.est.4c07341
46. Enhanced CAMx source apportionment analysis at an urban receptor in Milan based on source categories and emission regions N. Pepe et al. https://doi.org/10.1016/j.aeaoa.2019.100020
47. Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown E. Solazzo et al. https://doi.org/10.5194/acp-17-3001-2017
48. Two-way coupled meteorology and air quality models in Asia: a systematic review and meta-analysis of impacts of aerosol feedbacks on meteorology and air quality C. Gao et al. https://doi.org/10.5194/acp-22-5265-2022
49. Quantification of the enhanced effectiveness of NOx control from simultaneous reductions of VOC and NH3 for reducing air pollution in the Beijing–Tianjin–Hebei region, China J. Xing et al. https://doi.org/10.5194/acp-18-7799-2018
50. Present Knowledge and Future Perspectives of Atmospheric Emission Inventories of Toxic Trace Elements: A Critical Review X. Bai et al. https://doi.org/10.1021/acs.est.2c07147
51. Formation mechanisms of a severe springtime ozone episode in the Beibu Gulf, China: The role of the marine “ozone pool” and regional transport R. Pan et al. https://doi.org/10.1016/j.apr.2026.103122
52. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1 K. Appel et al. https://doi.org/10.5194/gmd-10-1703-2017
53. Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States X. Chen et al. https://doi.org/10.5194/gmd-14-3969-2021
54. The Effect of Lockdown Period during the COVID-19 Pandemic on Air Quality in Sydney Region, Australia H. Duc et al. https://doi.org/10.3390/ijerph18073528
55. Size-segregated aerosol chemical composition from an agro-industrial region of São Paulo state, Brazil C. Gonçalves et al. https://doi.org/10.1007/s11869-016-0441-0
56. Aerosol Absorption: Progress Towards Global and Regional Constraints B. Samset et al. https://doi.org/10.1007/s40641-018-0091-4
57. A review of the CAMx, CMAQ, WRF-Chem and NAQPMS models: Application, evaluation and uncertainty factors Z. Gao & X. Zhou https://doi.org/10.1016/j.envpol.2023.123183
58. The spatiotemporal influence of atmospheric nitrogen deposition on basin nitrogen exports based on CMAQ-SWAT model Q. Hu et al. https://doi.org/10.1016/j.wroa.2025.100465
59. Cross-comparison and evaluation of air pollution field estimation methods H. Yu et al. https://doi.org/10.1016/j.atmosenv.2018.01.045
60. Current and Future Responses of Aerosol pH and Composition in the U.S. to Declining SO2 Emissions and Increasing NH3 Emissions Y. Chen et al. https://doi.org/10.1021/acs.est.9b02005
61. Ambient air pollution and depressed mood in the National Longitudinal Study of Adolescent to Adult Health (Add Health) wave 4 W. Yu et al. https://doi.org/10.1093/aje/kwae314
62. Simulating the phase partitioning of NH3, HNO3, and HCl with size-resolved particles over northern Colorado in winter J. Kelly et al. https://doi.org/10.1016/j.atmosenv.2016.01.049
63. Role of emission controls in reducing the 2050 climate change penalty for PM2.5 in China S. Liu et al. https://doi.org/10.1016/j.scitotenv.2020.144338
64. Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models S. Philip et al. https://doi.org/10.1088/1748-9326/aa65a4
65. Crop Residue Burning Emissions and the Impact on Ambient Particulate Matters over South Korea K. Han et al. https://doi.org/10.3390/atmos13040559
66. Modeling the impacts of open biomass burning on regional O3 and PM2.5 in Southeast Asia considering light absorption and photochemical bleaching of Brown carbon M. Choi & Q. Ying https://doi.org/10.1016/j.atmosenv.2024.120942
67. Evaluation of Regional Atmospheric Models for Air Quality Simulations in the Winter Season in China F. Meng et al. https://doi.org/10.3390/atmos17010001
68. Direct and indirect wildland fire exposures and impacts in California’s wildland–urban interface M. Marlier et al. https://doi.org/10.1071/WF25070
69. Characteristics of Northwest Atlantic Cloud Water: PMF Applied to ACTIVATE’s Cloud Water Data Set T. Ajayi et al. https://doi.org/10.1021/acsearthspacechem.6c00028
70. Predicting wildfire particulate matter and hypothetical re-emission of radiological Cs-137 contamination incidents K. Baker et al. https://doi.org/10.1016/j.scitotenv.2021.148872
71. Coordinated Reduction of Reactive Nitrogen and Volatile Organic Compounds Enables Greater and More Equitable Integrated Health and Ecological Benefits Z. Dong et al. https://doi.org/10.1021/acs.est.5c12151
72. Revealing the impacts of transboundary pollution on PM2.5-related deaths in China S. Liu et al. https://doi.org/10.1016/j.envint.2019.105323
73. A preliminary study of turbulent coherent structures and ozone air quality in Seoul using the WRF-CMAQ model at a 50 m grid spacing B. Han et al. https://doi.org/10.1016/j.atmosenv.2019.117012
74. Simulating the Weekly Cycle of NOx‐VOC‐HOx‐O3 Photochemical System in the South Coast of California During CalNex‐2010 Campaign C. Cai et al. https://doi.org/10.1029/2018JD029859
75. Constrained Estimates of Anthropogenic NOx Emissions in China (2014–2021) from Surface Observations Y. Shen et al. https://doi.org/10.3390/atmos17010051
76. Impact of halogen chemistry on summertime air quality in coastal and continental Europe: application of the CMAQ model and implications for regulation Q. Li et al. https://doi.org/10.5194/acp-19-15321-2019
77. Mimicking atmospheric photochemical modeling with a deep neural network J. Xing et al. https://doi.org/10.1016/j.atmosres.2021.105919
78. Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 2: Multi-year prospective and retrospective performance evaluation M. Moran et al. https://doi.org/10.5194/gmd-19-4205-2026
79. Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed P. Campbell et al. https://doi.org/10.1029/2019JG005203
80. The Role of Vegetation on Urban Atmosphere of Three European Cities. Part 2: Evaluation of Vegetation Impact on Air Pollutant Concentrations and Depositions M. Mircea et al. https://doi.org/10.3390/f14061255
81. Impacts of Atmospheric Nitrogen Deposition on Surface Waters of the Western North Atlantic Mitigated by Multiple Feedbacks P. St‐Laurent et al. https://doi.org/10.1002/2017JC013072
82. Emission-driven changes in anthropogenic aerosol concentrations in China during 1970–2010 and its implications for PM2.5 control policy W. Chang et al. https://doi.org/10.1016/j.atmosres.2018.05.008
83. An uncertainty for clean air: Air quality modeling implications of underestimating VOC emissions in urban inventories S. Zhu et al. https://doi.org/10.1016/j.atmosenv.2019.05.019
84. Impact of inherent meteorology uncertainty on air quality model predictions R. Gilliam et al. https://doi.org/10.1002/2015JD023674
85. Multisource Observation-Constrained Tuning for Air Quality Forecasting in a Machine Learning-Enhanced NOAA Unified Forecast System J. Xing et al. https://doi.org/10.1021/acs.est.6c04600
86. Aerosol Uptake Coefficients of Isoprene Epoxides: Determination and Parameter Estimation from Online Field Measurements of Organic Molecular Markers S. Zhu et al. https://doi.org/10.1021/acs.est.5c09046
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89. Toward Improving Short‐Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals R. Kumar et al. https://doi.org/10.1029/2018JD029009
90. Simulation of chemical transport model estimates by means of a neural network using meteorological data A. Vlasenko et al. https://doi.org/10.1016/j.atmosenv.2021.118236
91. Ozone source apportionment during peak summer events over southwestern Europe M. Pay et al. https://doi.org/10.5194/acp-19-5467-2019
92. Role of black carbon in modulating aerosol direct effects driven by air pollution controls during 2013–2017 in China F. Zhang et al. https://doi.org/10.1016/j.scitotenv.2022.154928
93. The Eulerian urban dispersion model EPISODE – Part 2: Extensions to the source dispersion and photochemistry for EPISODE–CityChem v1.2 and its application to the city of Hamburg M. Karl et al. https://doi.org/10.5194/gmd-12-3357-2019
94. Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222 S. Chambers et al. https://doi.org/10.3390/atmos10010025
95. Simulation of airborne trace metals in fine particulate matter over North America J. Xu et al. https://doi.org/10.1016/j.atmosenv.2019.116883
96. Evaluation of the Community Multiscale Air Quality (CMAQ) model v5.0 against size-resolved measurements of inorganic particle composition across sites in North America C. Nolte et al. https://doi.org/10.5194/gmd-8-2877-2015
97. Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia X. Dong et al. https://doi.org/10.5194/acp-16-8157-2016
98. DeepSAT4D: Deep learning empowers four-dimensional atmospheric chemical concentration and emission retrieval from satellite S. Li & J. Xing https://doi.org/10.59717/j.xinn-geo.2024.100061
99. Sensitivity analysis of the dust emission treatment in CMAQv5.2.1 and its application to long-range transport over East Asia S. Kong et al. https://doi.org/10.1016/j.atmosenv.2021.118441
100. Summertime tropospheric ozone source apportionment study in the Madrid region (Spain) D. de la Paz et al. https://doi.org/10.5194/acp-24-4949-2024
101. Effect of Meteorological Variability on Fine Particulate Matter Simulations Over the Contiguous United States R. Kumar et al. https://doi.org/10.1029/2018JD029637
102. Coupling of organic and inorganic aerosol systems and the effect on gas–particle partitioning in the southeastern US H. Pye et al. https://doi.org/10.5194/acp-18-357-2018
103. The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2 Z. Luo et al. https://doi.org/10.5194/gmd-16-6757-2023
104. Dynamic evaluation of CMAQ part II: Evaluation of relative response factor metrics for ozone attainment demonstrations K. Foley et al. https://doi.org/10.1016/j.atmosenv.2014.12.039
105. Assessing ozone abatement scenarios in the framework of the Spanish ozone mitigation plan H. Petetin et al. https://doi.org/10.1016/j.scitotenv.2023.165380
106. Wind-blown dust and its impacts on particulate matter pollution in Northern China: current and future scenarios S. Liu et al. https://doi.org/10.1088/1748-9326/ac31ec
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108. Developing nitrate-nitrogen transport models using remotely-sensed geospatial data of soil moisture profiles and wet depositions P. Preetha & A. Al-Hamdan https://doi.org/10.1080/10934529.2020.1724503
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110. Assessing the Uncertainties in Ozone and SOA Predictions due to Different Branching Ratios of the Cresol Pathway in the Toluene-OH Oxidation Mechanism J. Zhang et al. https://doi.org/10.1021/acsearthspacechem.1c00092
111. Impact of a nitrogen emission control area (NECA) on the future air quality and nitrogen deposition to seawater in the Baltic Sea region M. Karl et al. https://doi.org/10.5194/acp-19-1721-2019
112. Bias corrections for species- and source-resolved PM2.5 chemical transport model simulations using a geographically weighted regression K. Skyllakou et al. https://doi.org/10.1016/j.atmosenv.2025.121637
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119. A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application S. Feng et al. https://doi.org/10.5194/gmd-16-5949-2023
120. Data Assimilation of Ambient Concentrations of Multiple Air Pollutants Using an Emission-Concentration Response Modeling Framework J. Xing et al. https://doi.org/10.3390/atmos11121289
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