111 citations as recorded by crossref.

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25. Tracking Long-Term Ozone Pollution Dynamics in Chinese Cities with Meteorological and Emission Attribution H. Li et al. 10.3390/atmos16070768
26. Analysis of the Trend Characteristics of Air Pollutants in the Fenwei Plain Based on the KZ Filter X. Xia et al. 10.3390/atmos14121785
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28. Spatial Correlation Analysis of Carbonaceous Aerosols and Air Pollutants Obserevd in Anmyeondo Global Atmosphere Watch (GAW) Regional Station E. Lee et al. 10.5572/KOSAE.2025.41.2.372
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30. Synoptic circulation factors associated with wintertime high-PM2.5 concentrations in seoul, Republic of Korea: Their interpretations and applications H. Oh et al. 10.1016/j.atmosenv.2024.120444
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36. Determination of Input variables for Artificial Intelligence Models to predict the High PM2.5 concentration events in Seoul, Korea S. Kim & M. Park 10.1007/s13143-023-00333-5
37. Pm10 Aerosol Enhancement in the Anticyclonic Anomalies Caused by the East Asian Spring Warming of 2021 J. Cho & H. Kim 10.2139/ssrn.4149621
38. Long-term Trend of PM2.5 Concentration in Seoul M. Yeo et al. 10.5572/KOSAE.2019.35.4.438
39. Tropical Cyclone as a Possible Remote Controller of Air Quality over South Korea through Poleward-Propagating Rossby Waves D. Park et al. 10.1175/JAMC-D-19-0058.1
40. Impact Comparison of Synoptic Meteorology and Nationwide/local Emissions on the Seoul Metropolitan Area during High PM Multi-event and Non-event Days I. Park et al. 10.5572/ajae.2020.14.3.263
41. Spatio-temporal changes of PM10 trends in South Korea caused by East Asian atmospheric variability J. Cho et al. 10.1007/s11869-021-00995-y
42. An evaluation approach to PM2.5 policy effectiveness over South Korea based on a newly proposed scalable spatial decomposition method J. Seo et al. 10.1088/1748-9326/ada2b2
43. Air quality trends and regimes in South Korea inferred from 2015–2023 surface and satellite observations Y. Oak et al. 10.5194/acp-25-3233-2025
44. Impact of Meteorological Changes on Particulate Matter and Aerosol Optical Depth in Seoul during the Months of June over Recent Decades S. Yang et al. 10.3390/atmos11121282
45. Regulatory measures significantly reduced air-pollutant concentrations in Seoul, Korea C. Ho et al. 10.1016/j.apr.2021.101098
46. Exposure Risk of Global Surface O3 During the Boreal Spring Season Y. Zhou et al. 10.1007/s12403-022-00463-7
47. Trends in urban air pollution over the last two decades: A global perspective P. Sicard et al. 10.1016/j.scitotenv.2022.160064
48. Examining the spatially varying effects of factors on PM2.5 concentrations in Chinese cities using geographically weighted regression modeling J. Wang et al. 10.1016/j.envpol.2019.02.081
49. Multi-Model Evaluation of Meteorological Drivers, Air Pollutants and Quantification of Emission Sources over the Upper Brahmaputra Basin A. Saikia et al. 10.3390/atmos10110703
50. Airborne formaldehyde and volatile organic compound measurements over the Daesan petrochemical complex on Korea’s northwest coast during the Korea-United States Air Quality study A. Fried et al. 10.1525/elementa.2020.121
51. Terrain Effect on Provincial PM2.5 Concentrations in South Korea S. Jeong et al. 10.5572/KOSAE.2024.40.6.628
52. Climate Change Penalty to Ozone Air Quality: Review of Current Understandings and Knowledge Gaps T. Fu & H. Tian 10.1007/s40726-019-00115-6
53. Multi-scale characteristics and statistically associated factors of ozone pollution in Hangzhou based on machine learning Y. He et al. 10.1016/j.apr.2025.102522
54. Were traffic restrictions in Madrid effective at reducing NO2 levels? R. Salas et al. 10.1016/j.trd.2020.102689
55. Quantifying changes in ambient NOx, O3 and PM10 concentrations in Austria during the COVID-19 related lockdown in spring 2020 C. Staehle et al. 10.1007/s11869-022-01232-w
56. Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022 H. Zheng et al. 10.1016/j.envint.2023.108361
57. A 5.5-year observations of black carbon aerosol at a megacity in Central China: Levels, sources, and variation trends H. Zheng et al. 10.1016/j.atmosenv.2020.117581
58. Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta (YRD), China from 2015 to 2022 L. Wu & J. An 10.1016/j.jes.2024.01.038
59. The influence of atmospheric blocking on regional PM10 aerosol transport to South Korea during February–March of 2019 J. Cho et al. 10.1016/j.atmosenv.2022.119056
60. Evidence of haze-driven secondary production of supermicrometer aerosol nitrate and sulfate in size distribution data in South Korea J. Schlosser et al. 10.5194/acp-22-7505-2022
61. Statistical Characteristics of Air Quality Index DAQx*-Specific Air Pollutants Differentiated by Types of Air Quality Monitoring Stations: A Case Study of Seoul, Republic of Korea H. Lee et al. 10.3390/su15118599
62. Urban meteorology and air quality in a rapidly growing city: Inter-parameter associations and intra-urban heterogeneity G. Ulpiani et al. 10.1016/j.scs.2021.103553
63. Using observed urban NOx sinks to constrain VOC reactivity and the ozone and radical budget in the Seoul Metropolitan Area B. Nault et al. 10.5194/acp-24-9573-2024
64. Impact assessment of Beirut explosion on local and regional air quality P. Broomandi et al. 10.1007/s11869-021-01066-y
65. Observation-based modeling of ozone chemistry in the Seoul metropolitan area during the Korea-United States Air Quality Study (KORUS-AQ) J. Schroeder et al. 10.1525/elementa.400
66. End-to-end deep learning for pollutant prediction using street view images L. Wu et al. 10.1016/j.uclim.2025.102368
67. Variations in major aerosol components from long-term measurement of columnar aerosol optical properties at a SKYNET site downwind of Seoul, Korea Y. Choi & Y. Ghim 10.1016/j.atmosenv.2020.117991
68. Role of emissions and meteorology in the recent PM2.5 changes in China and South Korea from 2015 to 2018 M. Bae et al. 10.1016/j.envpol.2020.116233
69. Box Model Applications for Atmospheric Chemistry Research: Photochemical Reactions and Ozone Formation S. Park 10.5572/KOSAE.2023.39.5.627
70. Ground-level ozone over time: An observation-based global overview P. Sicard 10.1016/j.coesh.2020.100226
71. An intercomparison of weather normalization of PM2.5 concentration using traditional statistical methods, machine learning, and chemistry transport models H. Zheng et al. 10.1038/s41612-023-00536-7
72. Characterizing the emission trends and pollution evolution patterns during the transition period following COVID-19 at an industrial megacity of central China Y. Li et al. 10.1016/j.ecoenv.2024.116354
73. Impact of North Atlantic-East Asian teleconnections on extremely high January PM10 cases in Korea J. Kim et al. 10.1016/j.envpol.2021.118051
74. Using machine learning to quantify drivers of aerosol pollution trend in China from 2015 to 2022 Y. Ji et al. 10.1016/j.apgeochem.2023.105614
75. Identification of Pollution Characteristics of PM2.5 Using a Geographic Information System and Statistical Tools: A Case Study of the Southeastern and Southern Regions of South Korea J. Ju et al. 10.5572/KOSAE.2023.39.4.478
76. Long-Term Variations and Relationships between Urban Heat Island and Air Pollutants in Seoul over the Past 20 Years J. Kim et al. 10.5572/KOSAE.2024.40.2.209
77. Quantifying the Impact of Synoptic Weather Systems on High PM2.5 Episodes in the Seoul Metropolitan Area, Korea L. Chang et al. 10.1029/2020JD034085
78. Ozone weekend effect in cities: Deep insights for urban air pollution control P. Sicard et al. 10.1016/j.envres.2020.110193
79. Meteorological Characteristics and Assessment of the Effect of Local Emissions during High PM10 Concentration in the Seoul Metropolitan Area I. Park et al. 10.5572/ajae.2019.13.2.117
80. The analysis of ozone pollution in urban agglomerations of the Sichuan basin based on the scale decomposition-synthesis method F. Liu et al. 10.1016/j.envres.2025.121121
81. The State of the Air Quality and Measures for Improving it in North Korea M. Yeo & Y. Kim 10.5572/kosae.2019.35.3.318
82. Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model S. Gao et al. 10.1016/j.atmosenv.2021.118599
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88. Seasonal analysis of meteorological parameters and air pollutant concentrations in Kolkata: An evaluation of their relationship N. Maltare et al. 10.1016/j.jclepro.2023.140514
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