142 citations as recorded by crossref.

1. Toward Understanding the Differences of PM2.5 Characteristics Among Five China Urban Cities K. Zhang et al. 10.1007/s13143-019-00125-w
2. Study of the aerosol optical characteristics over the Romanian Black Sea Coast using AERONET data S. Stefan et al. 10.1016/j.apr.2020.04.007
3. Exploring the relationship between high-resolution aerosol optical depth values and ground-level particulate matter concentrations in the Metropolitan Area of São Paulo A. Damascena et al. 10.1016/j.atmosenv.2020.117949
4. Satellite Remote Sensing for Estimating PM2.5 and Its Components Y. Li et al. 10.1007/s40726-020-00170-4
5. Trends in the types and absorption characteristics of ambient aerosols over the Indo-Gangetic Plain and North China Plain in last two decades S. Ramachandran & M. Rupakheti 10.1016/j.scitotenv.2022.154867
6. Investigation of the relationship between dust storm index, climatic parameters, and normalized difference vegetation index using the ridge regression method in arid regions of Central Iran Z. Ebrahimi Khusfi et al. 10.1080/15324982.2019.1694087
7. Improved Aerosol Retrievals Over Complex Regions Using NPP Visible Infrared Imaging Radiometer Suite Observations Y. Yang et al. 10.1029/2019EA000574
8. Estimation of high-resolution PM2.5 concentrations based on gap-filling aerosol optical depth using gradient boosting model M. Han et al. 10.1007/s11869-021-01149-w
9. Spatial characteristics and temporal evolution of the relationship between PM2.5 and aerosol optical depth over the eastern USA during 2003–2017 Q. Jin et al. 10.1016/j.atmosenv.2020.117718
10. Estimation of PM<sub>2.5</sub> concentration in China using linear hybrid machine learning model Z. Song et al. 10.5194/amt-14-5333-2021
11. Baseline of Surface and Column-Integrated Aerosol Loadings in the Pearl River Delta Region, China X. Fan et al. 10.3389/fenvs.2022.893408
12. Evaluation of the MISR fine resolution aerosol product using MODIS, MISR, and ground observations over China Y. Si et al. 10.1016/j.atmosenv.2019.117229
13. PM2.5 Estimation and Spatial-Temporal Pattern Analysis Based on the Modified Support Vector Regression Model and the 1 km Resolution MAIAC AOD in Hubei, China N. Chen et al. 10.3390/ijgi10010031
14. Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables A. Mhawish et al. 10.1021/acs.est.0c01769
15. Long-term analysis of AOD separated by aerosol type in East Asia J. Shin et al. 10.1016/j.atmosenv.2023.119957
16. Variabilities in PM2.5 and Black Carbon Surface Concentrations Reproduced by Aerosol Optical Properties Estimated by In-Situ Data, Ground Based Remote Sensing and Modeling A. Damiani et al. 10.3390/rs13163163
17. Evaluation and Comparison of Spatio-Temporal Relationship between Multiple Satellite Aerosol Optical Depth (AOD) and Near-Surface PM2.5 Concentration over China Q. Xu et al. 10.3390/rs14225841
18. The impact threshold of the aerosol radiative forcing on the boundary layer structure in the pollution region D. Zhao et al. 10.5194/acp-21-5739-2021
19. Potential Impacts of Aerosol on Diurnal Variation of Precipitation in Autumn Over the Sichuan Basin, China J. Liu et al. 10.1029/2022JD036674
20. Observational evidence of elevated smoke layers during crop residue burning season over Delhi: Potential implications on associated heterogeneous PM2.5 enhancements A. Mhawish et al. 10.1016/j.rse.2022.113167
21. Statistical aerosol properties associated with fire events from 2002 to 2019 and a case analysis in 2019 over Australia X. Yang et al. 10.5194/acp-21-3833-2021
22. Monitoring air quality of Sharkia Governorate using remote sensing A. Nagy et al. 10.1007/s11600-023-01283-2
23. Seasonal and Daily Variability of Aerosol Particle Concentrations near St. Petersburg K. Volkova et al. 10.1134/S102485602005019X
24. A spatially structured adaptive two-stage model for retrieving ground-level PM2.5 concentrations from VIIRS AOD in China F. Yao et al. 10.1016/j.isprsjprs.2019.03.011
25. PM2.5 Modeling and Historical Reconstruction over the Continental USA Utilizing GOES-16 AOD X. Yu et al. 10.3390/rs13234788
26. High Spatial-Temporal PM2.5 Modeling Utilizing Next Generation Weather Radar (NEXRAD) as a Supplementary Weather Source X. Yu et al. 10.3390/rs14030495
27. Mapping daily PM2.5 at 500 m resolution over Beijing with improved hazy day performance Y. Xie et al. 10.1016/j.scitotenv.2018.12.365
28. Estimation of PM2.5 Mass Concentration from Visibility D. Ji et al. 10.1007/s00376-020-0009-7
29. Estimation of PM2.5 Concentration across China Based on Multi-Source Remote Sensing Data and Machine Learning Methods Y. Yang et al. 10.3390/rs16030467
30. Trends in atmospheric particles and their light extinction performance between 1980 and 2015 in Beijing, China L. Guo et al. 10.1016/j.chemosphere.2018.04.071
31. Impact of weather and emission changes on NO2 concentrations in China during 2014–2019 Y. Shen et al. 10.1016/j.envpol.2020.116163
32. Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem A. Raman et al. 10.1016/j.atmosenv.2020.118134
33. 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
34. Exploring the drivers of the increased ozone production in Beijing in summertime during 2005–2016 W. Wang et al. 10.5194/acp-20-15617-2020
35. Characteristics of urban boundary layer in heavy haze process based on Beijing 325m tower data Y. SHI et al. 10.1080/16742834.2019.1547084
36. A Spatial-Temporal Interpretable Deep Learning Model for improving interpretability and predictive accuracy of satellite-based PM2.5 X. Yan et al. 10.1016/j.envpol.2021.116459
37. Seasonal Tropospheric Aerosol Classification Using AERONET Spectral Absorption Properties in African Locations S. Aladodo et al. 10.1007/s41810-022-00140-x
38. Analysis of Long-Term Aerosol Optical Properties Combining AERONET Sunphotometer and Satellite-Based Observations in Hong Kong X. Yu et al. 10.3390/rs14205220
39. 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
40. The optimization of XGBoost model and its application in PM2.5concentrations estimation based on MODIS data in the Guanzhong region, China H. Ma et al. 10.1080/01431161.2023.2184217
41. Observed decrease of summer sea-land breeze in Shanghai from 1994 to 2014 and its association with urbanization L. Shen et al. 10.1016/j.atmosres.2019.05.007
42. Columnar aerosol optical depth, water vapor and ozone over a semi-arid urban location of western India: Potential sources and direct radiative effects N. Godhani et al. 10.1016/j.asr.2022.07.046
43. Embedded information of aerosol type, hygroscopicity and scattering enhancement factor revealed by the relationship between PM2.5 and aerosol optical depth K. Chang et al. 10.1016/j.scitotenv.2023.161471
44. Temporal and Spatial Matching in Human‐Earth System Model Coupling J. Chou et al. 10.1002/2018EA000371
45. Aerosol classification in Europe, Middle East, North Africa and Arabian Peninsula based on AERONET Version 3 S. Logothetis et al. 10.1016/j.atmosres.2020.104893
46. A MAIA-like modeling framework to estimate PM2.5 mass and speciation concentrations with uncertainty Z. Jin et al. 10.1016/j.rse.2024.113995
47. Uncertainties of Simulated Aerosol Direct Radiative Effect Induced by Aerosol Chemical Components: A Measurement‐Based Perspective From Urban‐Forest Transition Region in East China Y. Ma et al. 10.1029/2020JD033688
48. Effects of soiling on photovoltaic (PV) modules in the Atacama Desert R. Cordero et al. 10.1038/s41598-018-32291-8
49. Relationships between cloudiness, aerosol optical thickness, and sunshine duration in Poland K. Bartoszek et al. 10.1016/j.atmosres.2020.105097
50. Characteristics of Chemical Speciation in PM1 in Six Representative Regions in China K. Bai et al. 10.1007/s00376-020-0224-2
51. Improving machine-learned surface NO2 concentration mapping models with domain knowledge from data science perspective M. Hu et al. 10.1016/j.atmosenv.2024.120372
52. PM<sub>2.5</sub> surface concentrations in southern West African urban areas based on sun photometer and satellite observations J. Léon et al. 10.5194/acp-21-1815-2021
53. A comparative study of EOF and NMF analysis on downward trend of AOD over China from 2011 to 2019 Q. Ma et al. 10.1016/j.envpol.2021.117713
54. A Validation Approach Considering the Uneven Distribution of Ground Stations for Satellite-Based PM2.5 Estimation T. Li et al. 10.1109/JSTARS.2020.2977668
55. Comparison of Two Air Pollution Episodes over Northeast China in Winter 2016/17 Using Ground-Based Lidar Y. Ma et al. 10.1007/s13351-018-7047-4
56. Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data W. Zhang et al. 10.3390/rs16081410
57. 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
58. Particulate air pollution in Durban: Characteristics and its relationship with 1 km resolution satellite aerosol optical depth B. Mahesh et al. 10.1016/j.asr.2022.04.053
59. Global and Geographically and Temporally Weighted Regression Models for Modeling PM2.5 in Heilongjiang, China from 2015 to 2018 Q. Wei et al. 10.3390/ijerph16245107
60. Spatio-temporal characteristics of air pollutants over Xinjiang, northwestern China D. Rupakheti et al. 10.1016/j.envpol.2020.115907
61. 15-year variability of desert dust optical depth on global and regional scales S. Logothetis et al. 10.5194/acp-21-16499-2021
62. The comparison of AOD-based and non-AOD prediction models for daily PM2.5 estimation in Guangdong province, China with poor AOD coverage G. Chen et al. 10.1016/j.envres.2021.110735
63. Satellite-based estimation of the impacts of summertime wildfires on PM<sub>2.5</sub> concentration in the United States Z. Xue et al. 10.5194/acp-21-11243-2021
64. 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
65. Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations X. Shi et al. 10.1002/2017JD027913
66. Time series modeling of PM2.5 concentrations with residual variance constraint in eastern mainland China during 2013–2017 S. Li et al. 10.1016/j.scitotenv.2019.135755
67. Classification of aerosol types using AERONET version 3 data over Kuwait City F. Khademi & A. Bayat 10.1016/j.atmosenv.2021.118716
68. The impact of aerosols on photolysis frequencies and ozone production in Beijing during the 4-year period 2012–2015 W. Wang et al. 10.5194/acp-19-9413-2019
69. Black-carbon-induced regime transition of boundary layer development strongly amplifies severe haze J. Wang et al. 10.1016/j.oneear.2023.05.010
70. Stubborn aerosol: why particulate mass concentrations do not drop during the wet season in Metro Manila, Philippines M. Hilario et al. 10.1039/D2EA00073C
71. Satellite-Based Aerosol Classification for Capital Cities in Asia Using a Random Forest Model W. Choi et al. 10.3390/rs13132464
72. Composition and source based aerosol classification using machine learning algorithms S. Annapurna et al. 10.1016/j.asr.2023.09.068
73. Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak A. Rudke et al. 10.1016/j.rse.2023.113514
74. The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations Q. Yang et al. 10.1016/j.envpol.2019.02.071
75. Determining the fluctuation of PM2.5 mass concentration and its applicability to Monin–Obukhov similarity Y. Ren et al. 10.1016/j.scitotenv.2019.136398
76. Geographical and temporal encoding for improving the estimation of PM2.5 concentrations in China using end-to-end gradient boosting N. Yang et al. 10.1016/j.rse.2021.112828
77. Mechanism of the effect of vertically propagating internal gravity waves on turbulence barrier and pollutant diffusion during heavy haze episodes Z. Wei et al. 10.1016/j.scitotenv.2022.157349
78. 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
79. Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al. 10.1029/2019JD031380
80. Exploring the relationships between ground-measured particulate matter and satellite-retrieved aerosol parameters in China S. Yin 10.1007/s11356-022-19049-6
81. Integration of air pollution data collected by mobile sensors and ground-based stations to derive a spatiotemporal air pollution profile of a city Y. Leung et al. 10.1080/13658816.2019.1633468
82. Dynamics of Mixing Layer Height and Homogeneity from Ceilometer-Measured Aerosol Profiles and Correlation to Ground Level PM2.5 in New York City D. Li et al. 10.3390/rs14246370
83. Estimation of Hourly Ground-Level PM2.5 Concentration Based on Himawari-8 Apparent Reflectance W. Fan et al. 10.1109/TGRS.2020.2990791
84. Satellite-based estimation of the aerosol forcing contribution to the global land surface temperature in the recent decade H. Feng & B. Zou 10.1016/j.rse.2019.111299
85. Spatial distribution of aerosol microphysical and optical properties and direct radiative effect from the China Aerosol Remote Sensing Network H. Che et al. 10.5194/acp-19-11843-2019
86. Spatiotemporal relationship between Himawari-8 hourly columnar aerosol optical depth (AOD) and ground-level PM2.5 mass concentration in mainland China Q. Xu et al. 10.1016/j.scitotenv.2020.144241
87. Changes in apparent temperature and PM2.5 around the Beijing–Tianjin megalopolis under greenhouse gas and stratospheric aerosol intervention scenarios J. Wang et al. 10.5194/esd-14-989-2023
88. Response of fine particulate matter and ozone concentrations to meteorology and anthropogenic precursors over the “2+26” cities of northern China P. Liu et al. 10.1016/j.chemosphere.2024.141439
89. Himawari-8/AHI and MODIS Aerosol Optical Depths in China: Evaluation and Comparison T. Jiang et al. 10.3390/rs11091011
90. Effects of Anthropogenic Emissions from Different Sectors on PM2.5 Concentrations in Chinese Cities J. Yang et al. 10.3390/ijerph182010869
91. Linkages between aerosol pollution and planetary boundary layer structure in China Y. Miao & S. Liu 10.1016/j.scitotenv.2018.09.032
92. Effect of model errors in ambient air humidity on the aerosol optical depth obtained via aerosol hygroscopicity in eastern China in the Atmospheric Chemistry and Climate Model Intercomparison Project datasets W. CHANG 10.1080/16742834.2019.1588063
93. Estimating Regional PM2.5 Concentrations in China Using a Global-Local Regression Model Considering Global Spatial Autocorrelation and Local Spatial Heterogeneity H. Su et al. 10.3390/rs14184545
94. Influence of Human Activities on Wintertime Haze-Related Meteorological Conditions over the Jing–Jin–Ji Region Y. Xu et al. 10.1016/j.eng.2020.03.015
95. Estimating Regional Ground‐Level PM2.5 Directly From Satellite Top‐Of‐Atmosphere Reflectance Using Deep Belief Networks H. Shen et al. 10.1029/2018JD028759
96. Global synthesis of two decades of research on improving PM2.5 estimation models from remote sensing and data science perspectives K. Bai et al. 10.1016/j.earscirev.2023.104461
97. Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China H. Che et al. 10.5194/acp-18-405-2018
98. Investigating size-segregated sources of elemental composition of particulate matter in the South China Sea during the 2011 <i>Vasco</i> cruise M. Hilario et al. 10.5194/acp-20-1255-2020
99. Turbulence barrier effect during heavy haze pollution events Y. Ren et al. 10.1016/j.scitotenv.2020.142286
100. Influence of AOD remotely sensed products, meteorological parameters, and AOD–PM2.5 models on the PM2.5 estimation Y. Xu et al. 10.1007/s00477-020-01941-7
101. Improved method of visibility parameterization focusing on high humidity and aerosol concentrations during fog–haze events: Application in the GRAPES_CAUCE model in Jing-Jin-Ji, China Y. Peng et al. 10.1016/j.atmosenv.2019.117139
102. Visibility, aerosol optical depth, and low-visibility events in Bangkok during the dry season and associated local weather and synoptic patterns N. Aman et al. 10.1007/s10661-022-09880-2
103. Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments Z. Chen et al. 10.1016/j.scitotenv.2024.170593
104. Obtaining vertical distribution of PM2.5 from CALIOP data and machine learning algorithms B. Chen et al. 10.1016/j.scitotenv.2021.150338
105. Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China: Intercomparison of a plain site and a mountainous site in Beijing Y. Zheng et al. 10.1016/j.scitotenv.2019.03.418
106. Mapping the seamless hourly surface visibility in China: a real-time retrieval framework using a machine-learning-based stacked ensemble model X. Zhang et al. 10.1038/s41612-024-00617-1
107. Accounting for the aerosol type and additional satellite-borne aerosol products improves the prediction of PM2.5 concentrations S. Falah et al. 10.1016/j.envpol.2023.121119
108. The Impact of COVID-19 Lockdowns on Satellite-Observed Aerosol Optical Thickness over the Surrounding Coastal Oceanic Areas of Megacities in the Coastal Zone K. Wang & X. Zhao 10.3390/geographies1030021
109. Machine learning-based estimation of ground-level NO2 concentrations over China Y. Chi et al. 10.1016/j.scitotenv.2021.150721
110. Mathematical Estimation of Particulate Air Pollution Levels by Aerosols Tomography O. Vernik et al. 10.1109/JSEN.2022.3158890
111. Seasonal distribution and vertical structure of different types of aerosols in southwest China observed from CALIOP T. Liao et al. 10.1016/j.atmosenv.2020.118145
112. Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 2001–2018 G. Khamala et al. 10.1016/j.scitotenv.2022.161041
113. Spatio-temporal air pollution modelling using a compositional approach J. Sánchez-Balseca & A. Pérez-Foguet 10.1016/j.heliyon.2020.e04794
114. Superior PM2.5 Estimation by Integrating Aerosol Fine Mode Data from the Himawari-8 Satellite in Deep and Classical Machine Learning Models Z. Zang et al. 10.3390/rs13142779
115. Estimation of ground-level particulate matter concentrations based on synergistic use of MODIS, MERRA-2 and AERONET AODs over a coastal site in the Eastern Mediterranean G. Tuna Tuygun et al. 10.1016/j.atmosenv.2021.118562
116. Does green infrastructure affect housing prices via extreme heat and air pollution mitigation? A focus on green and climate gentrification in Los Angeles County, 2000-2021 J. Kim et al. 10.1016/j.scs.2024.105225
117. Distribution and Meteorological Control of PM2.5 and Its Effect on Visibility in Northern Thailand T. Amnuaylojaroen et al. 10.3390/atmos14030538
118. Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning M. Wang et al. 10.3390/atmos13020255
119. A Comprehensive Review of a Decade of Field PV Soiling Assessment in QEERI’s Outdoor Test Facility in Qatar: Learned Lessons and Recommendations B. Aïssa et al. 10.3390/en16135224
120. Effects of Anthropogenic Emission Control and Meteorology Changes on the Inter-Annual Variations of PM2.5–AOD Relationship in China L. Qi et al. 10.3390/rs14184683
121. Impact of aerosol concentration changes on carbon sequestration potential of rice in a temperate monsoon climate zone during the COVID-19: a case study on the Sanjiang Plain, China X. Zuo & H. Wang 10.1007/s11356-024-33149-5
122. Spatiotemporal Heterogeneity and the Key Influencing Factors of PM2.5 and PM10 in Heilongjiang, China from 2014 to 2018 L. Fu et al. 10.3390/ijerph191811627
123. Variations in aerosol optical characteristics from SKYNET measurements in Beijing X. Dong et al. 10.1016/j.atmosenv.2023.119747
124. Joint features random forest (JFRF) model for mapping hourly surface PM2.5 over China L. Dong et al. 10.1016/j.atmosenv.2022.118969
125. Modeling and spatial characterization of aerosols at Middle East AERONET stations C. Anoruo et al. 10.1007/s00704-023-04384-6
126. Self-supervised multi-task learning framework for safety and health-oriented road environment surveillance based on connected vehicle visual perception S. Jia & W. Yao 10.1016/j.jag.2024.103753
127. A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM₂.₅ T. Li et al. 10.1109/TGRS.2021.3074569
128. Exploring the Drivers and Photochemical Impact of the Positive Correlation between Single Scattering Albedo and Aerosol Optical Depth in the Troposphere W. Wang et al. 10.1021/acs.estlett.1c00300
129. 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
130. Ground-level NO2 concentration estimation based on OMI tropospheric NO2 and its spatiotemporal characteristics in typical regions of China Y. Chi et al. 10.1016/j.atmosres.2021.105821
131. Synoptic pattern and planetary boundary layer structure associated with aerosol pollution during winter in Beijing, China Y. Miao et al. 10.1016/j.scitotenv.2019.05.199
132. Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism Z. Chen et al. 10.1016/j.envint.2020.105558
133. Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives Y. Zhang et al. 10.1016/j.fmre.2021.04.007
134. Impacts of relative humidity on fine aerosol properties via environmental wind tunnel experiments J. Xu et al. 10.1016/j.atmosenv.2019.03.002
135. Sub-seasonal aerosol characterization at the Middle East regions of AERONET site C. Anoruo 10.1016/j.uclim.2021.100827
136. Multiyear Ground‐Based Measurements of Aerosol Optical Properties and Direct Radiative Effect Over Different Surface Types in Northeastern China H. Zhao et al. 10.1029/2018JD029141
137. Changes in the frequency and temperature of air masses over east‐central Europe K. Bartoszek & B. Kaszewski 10.1002/joc.7704
138. Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets B. Zhao et al. 10.5194/acp-18-11247-2018
139. Multiple Regression Analysis of Low Visibility Focusing on Severe Haze-Fog Pollution in Various Regions of China Z. Liu et al. 10.3390/atmos13020203
140. Monsoon-seasonal validation of MODIS aerosol optical depth and characterization using AERONET observation retrieve over Italy C. Anoruo 10.1016/j.envres.2021.111985
141. Vertical Structure of Dust Aerosols Observed by a Ground-Based Raman Lidar with Polarization Capabilities in the Center of the Taklimakan Desert S. Zhang et al. 10.3390/rs14102461
142. Aerosol Optical Depth Over the Nepalese Cryosphere Derived From an Empirical Model B. Bhattarai et al. 10.3389/feart.2019.00178