87 citations as recorded by crossref.

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5. Characteristics of Turbulence and Aerosol Optical and Radiative Properties during Haze–Fog Episodes in Shenyang, Northeast China X. Li et al. 10.3390/atmos12121658
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14. Visibility Prediction over South Korea Based on Random Forest B. Kim et al. 10.3390/atmos12050552
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27. Diagnosing atmospheric stability effects on the modeling accuracy of PM2.5 /AOD relationship in eastern China using radiosonde data K. Bai et al. 10.1016/j.envpol.2019.04.104
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29. Decreasing Dust Over the Middle East Partly Caused by Irrigation Expansion W. Xia et al. 10.1029/2021EF002252
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31. Mixing layer height estimated from AMDAR and its relationship with PMs and meteorological parameters in two cities in North China during 2014–2017 Z. Lv et al. 10.1016/j.apr.2019.11.017
32. Assessment of PM2.5 using satellite lidar observations: Effect of bio-mass burning emissions over India N. Lakshmi et al. 10.1016/j.scitotenv.2022.155215
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36. Indoor particulate matter exposure and correlation of PM2.5 with lung efficacy and SpO2 level of Dhaka City Dwellers S. Nahian et al. 10.1007/s11869-024-01586-3
37. Changes in wintertime visibility across China over 2013–2019 and the drivers: A comprehensive assessment using machine learning method L. Chen et al. 10.1016/j.scitotenv.2023.169516
38. Improving the estimating accuracy of extinction coefficient of surface aerosol with a new layer-resolved model in China L. Wang et al. 10.1016/j.scitotenv.2019.136443
39. A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China K. Bai et al. 10.5194/essd-12-3067-2020
40. Performance evaluation of photographic measurement in the machine-learning prediction of ground PM2.5 concentration L. Feng et al. 10.1016/j.atmosenv.2021.118623
41. Long-term temporal analysis of the columnar and surface aerosol relationship with planetary boundary layer height at a southern coastal site of Turkey G. Tuna Tuygun & T. Elbir 10.1016/j.apr.2020.09.008
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44. Simulated impacts of vertical distributions of black carbon aerosol on meteorology and PM<sub>2.5</sub> concentrations in Beijing during severe haze events D. Chen et al. 10.5194/acp-22-1825-2022
45. Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM2.5 data K. Bai et al. 10.1016/j.jenvman.2018.12.071
46. Aerosol Physical‐Optical Properties and PBLH Under Different Air Pollution Levels From Ground Lidar and Satellite Observations Over Shouxian Area, China Y. Zhang et al. 10.1029/2021JD035236
47. Severe haze events in the Indo-Gangetic Plain during post-monsoon: Synergetic effect of synoptic meteorology and crop residue burning emission S. Kumari et al. 10.1016/j.scitotenv.2021.145479
48. A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading Y. Shi et al. 10.5194/amt-14-3449-2021
49. Long-term meteorology-adjusted and unadjusted trends of PM2.5 using the AirGAM model over Delhi, 2007–2022 . Chetna et al. 10.1016/j.aeaoa.2024.100255
50. Predictability of PM2.5 in Seoul based on atmospheric blocking forecasts using the NCEP global forecast system U. Shin et al. 10.1016/j.atmosenv.2020.118141
51. Analyzing the influence of the planetary boundary layer height, ventilation coefficient, thermal inversions, and aerosol optical Depth on the concentration of PM2.5 in the city of São Paulo: A long-term study G. Moreira et al. 10.1016/j.apr.2024.102179
52. Long-term variation characteristics and influencing factors of low-visibility events on the coast of China R. Lyu et al. 10.1016/j.atmosres.2021.105583
53. Quantifying the impact of terrain–wind–governed close-effect on atmospheric polluted concentrations L. Wu et al. 10.1016/j.jclepro.2022.132995
54. A Comprehensive Study on Winter PM2.5 Variation in the Yangtze River Delta: Unveiling Causes and Pollution Transport Pathways Y. Pan et al. 10.3390/atmos15091037
55. Roadside atmospheric pollution: still a serious environmental problem in Beijing, China W. Chen et al. 10.1007/s11869-018-0620-2
56. Different characteristics of individual particles from light-duty diesel vehicle at the launching and idling state by AAC-SPAMS B. Su et al. 10.1016/j.jhazmat.2021.126304
57. Analysis of Changes and Statistical Characteristics in PM-2.5 based on the Seasonal Management Data H. Ahn et al. 10.4491/KSEE.2022.44.8.276
58. Vertical Distribution of Water Vapor During Haze Processes in Northeast China Based on Raman Lidar Measurements T. Zhang et al. 10.3390/rs16193713
59. The major chemical constituents of PM2.5 and airborne bacterial community phyla in Beijing, Seoul, and Nagasaki E. Park et al. 10.1016/j.chemosphere.2020.126870
60. Aerosol vertical profile variations with seasons, air mass movements and local PM2.5 levels in three large China cities L. Wang et al. 10.1016/j.atmosenv.2020.117329
61. Two pathways of how remote SST anomalies drive the interannual variability of autumnal haze days in the Beijing–Tianjin–Hebei region, China J. Wang et al. 10.5194/acp-19-1521-2019
62. The spatially heterogeneous response of aerosol properties to anthropogenic activities and meteorology changes in China during 1980–2018 based on the singular value decomposition method S. Ding et al. 10.1016/j.scitotenv.2020.138135
63. Radiative effects of clouds and fog on long-lasting heavy fog events in northern China L. Guo et al. 10.1016/j.atmosres.2020.105444
64. Comparison of ambient air pollution levels of Amritsar during foggy conditions with that of five major north Indian cities: multivariate analysis and air mass back trajectories R. Yadav et al. 10.1007/s42452-020-03569-2
65. Effects of anthropogenic precursor emissions and meteorological conditions on PM2.5 concentrations over the “2+26” cities of northern China J. Dong et al. 10.1016/j.envpol.2022.120392
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71. Distribution of Fine Particulate Matter Pollution in Winter over Eastern China Affected by Synoptic Conditions X. Liu et al. 10.3390/atmos15070821
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75. Meteorological characteristics within boundary layer and its influence on PM2.5 pollution in six cities of North China based on WRF-Chem Z. Lv et al. 10.1016/j.atmosenv.2020.117417
76. FogNet: A multiscale 3D CNN with double-branch dense block and attention mechanism for fog prediction H. Kamangir et al. 10.1016/j.mlwa.2021.100038
77. AirMLP: A Multilayer Perceptron Neural Network for Temporal Correction of PM2.5 Values in Turin M. Casari et al. 10.3390/s23239446
78. Impacts of the near-surface urban boundary layer structure on PM2.5 concentrations in Beijing during winter L. Wang et al. 10.1016/j.scitotenv.2019.03.097
79. Size-Segregated Particulate Mass and Carbonaceous Components in Roadside and Riverside Environments M. Amin et al. 10.3390/app112110214
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81. Carbonaceous component of Total Suspended Particulate (TSP) in Makassar City, Sulawesi Island, Indonesia M. Amin et al. 10.1088/1755-1315/1199/1/012021
82. The spatial and temporal variation of fine particulate matter pollution in Ethiopia: Data from the Atmospheric Composition Analysis Group (1998–2019) A. Shiferaw et al. 10.1371/journal.pone.0283457
83. Exploring the Sensitivity of Visibility to PM2.5 Mass Concentration and Relative Humidity for Different Aerosol Types J. Wang et al. 10.3390/atmos13030471
84. Estimating PM2.5 Concentrations Using Spatially Local Xgboost Based on Full-Covered SARA AOD at the Urban Scale Z. Fan et al. 10.3390/rs12203368
85. Observational study of the vertical aerosol and meteorological factor distributions with respect to particulate pollution in Xi'an D. Huige et al. 10.1016/j.atmosenv.2021.118215
86. Concentrations of Four Major Air Pollutants among Ecological Functional Zones in Shenyang, Northeast China L. Li et al. 10.3390/atmos11101070
87. Regional source apportionment of trace metals in fine particulate matter using an observation-constrained hybrid model K. Liao et al. 10.1038/s41612-023-00393-4