300 citations as recorded by crossref.

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2. Aerosol models from the AERONET database: application to surface reflectance validation J. Roger et al. https://doi.org/10.5194/amt-15-1123-2022
3. Scattering and absorbing aerosols in the climate system J. Li et al. https://doi.org/10.1038/s43017-022-00296-7
4. Atmospheric Correction of DSCOVR EPIC: Version 2 MAIAC Algorithm A. Lyapustin et al. https://doi.org/10.3389/frsen.2021.748362
5. Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations M. Zhou et al. https://doi.org/10.1016/j.rse.2021.112717
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7. Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and central Africa M. Choi et al. https://doi.org/10.5194/acp-24-10543-2024
8. Ground-based ultraviolet polarimetry for imaging the Babinet polarization neutral point C. DeLeon & M. Kupinski https://doi.org/10.1007/s10043-025-00958-z
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10. Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring C. Chen et al. https://doi.org/10.5194/essd-12-3573-2020
11. Aerosol variability over oceans using micro-pulse lidar and photometer: insights from TRANSAMA ship-based campaign M. Sanchez-Barrero et al. https://doi.org/10.5194/amt-19-507-2026
12. Reflectance Consistency Between MERSI-II and MODIS in Northeast China Under Varying Conditions R. Xie et al. https://doi.org/10.1109/JSTARS.2026.3673349
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14. Effects of Aerosols and Clouds on the Levels of Surface Solar Radiation and Solar Energy in Cyprus I. Fountoulakis et al. https://doi.org/10.3390/rs13122319
15. Comparison of Scanning LiDAR with Other Remote Sensing Measurements and Transport Model Predictions for a Saharan Dust Case H. Zhang et al. https://doi.org/10.3390/rs14071693
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19. Implementation of the MOSAIC aerosol module (v1.0) in the Canadian air quality model GEM-MACH (v3.1) K. Semeniuk et al. https://doi.org/10.5194/gmd-18-6479-2025
20. Spring 2020 Atmospheric Aerosol Contamination over Kyiv City C. Zhang et al. https://doi.org/10.3390/atmos13050687
21. Development of Level 2 aerosol and surface products from cross-track scanning polarimeter POSP on board the GF-5(02) satellite C. Chen et al. https://doi.org/10.5194/essd-17-3497-2025
22. Improved simulations of biomass burning aerosol optical properties and lifetimes in the NASA GEOS Model during the ORACLES-I campaign S. Das et al. https://doi.org/10.5194/acp-24-4421-2024
23. The SMART-P Algorithm for Aerosol and Ocean Properties Part 1: Algorithm Theoretical Basis and Expected Accuracy of PolCube Aerosol Products S. Lee et al. https://doi.org/10.3390/rs18040560
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26. Retrieval of global aerosol and surface properties from the Gaofen-5 Directional Polarimetric Camera measurements Z. Zhang et al. https://doi.org/10.5194/amt-19-2555-2026
27. Long range transport of Canadian wildfire smoke to Europe in 2023: aerosol properties and spectral features of smoke particles A. Masoom et al. https://doi.org/10.5194/acp-26-10801-2026
28. Global evaluation and uncertainty analysis of MODIS Deep Blue and MAIAC aerosol products over bright surfaces P. Zhang et al. https://doi.org/10.1016/j.atmosenv.2026.121991
29. First triple-wavelength lidar observations of depolarization and extinction-to-backscatter ratios of Saharan dust M. Haarig et al. https://doi.org/10.5194/acp-22-355-2022
30. The Ground-Based Absolute Radiometric Calibration of the Landsat 9 Operational Land Imager J. Czapla-Myers et al. https://doi.org/10.3390/rs16061101
31. Aerosol Optical Properties of Extreme Global Wildfires and Estimated Radiative Forcing With GCOM‐C SGLI K. Tanada et al. https://doi.org/10.1029/2022JD037914
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34. Retrieval of aerosol properties from zenith sky radiance measurements S. Herrero-Anta et al. https://doi.org/10.5194/amt-16-4423-2023
35. Anomalous Selective Absorption of Smoke Aerosol during Forest Fires in Alaska in July–August 2019 G. Gorchakov et al. https://doi.org/10.1134/S000143382306004X
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37. The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation S. Wei et al. https://doi.org/10.5194/gmd-17-795-2024
38. Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region U. Dumka et al. https://doi.org/10.3390/rs13163248
39. Retrieval of microphysical properties of dust aerosols from extinction, backscattering and depolarization lidar measurements using various particle scattering models Y. Chang et al. https://doi.org/10.5194/acp-25-6787-2025
40. Global Accuracy, Stability, and Consistency Assessment and Usage Recommendations of POLDER/PARASOL GRASP Aerosol Products X. Ma et al. https://doi.org/10.3390/rs18101633
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44. Lognormal mode dissociation method based on intrinsic characteristics of aerosol size distribution S. Chen et al. https://doi.org/10.1364/OE.531268
45. What caused record-breaking aerosol loading over the South China Sea in April 2023 S. Ravindra Babu & N. Lin https://doi.org/10.5194/acp-26-8961-2026
46. Unveiling the effects of post-monsoon agricultural biomass burning on aerosols, clouds, and radiation in Northwest India P. Khatri et al. https://doi.org/10.1186/s40645-025-00685-8
47. Spectral Aerosol Radiative Forcing and Efficiency of the La Palma Volcanic Plume over the Izaña Observatory R. García et al. https://doi.org/10.3390/rs15010173
48. Spectral calibration method of the field spectrometer using combined solar Fraunhofer lines and atmospheric absorption characteristics: case study at the Baotou RadCalNet site and implications for reflectance measurement Y. Zhao et al. https://doi.org/10.1364/AO.544936
49. Optical and physical characteristics of aerosols over Asia: AERONET, MERRA-2 and CAMS K. Ansari & S. Ramachandran https://doi.org/10.1016/j.atmosenv.2024.120470
50. Fallowed agricultural lands dominate anthropogenic dust sources in California A. Adebiyi et al. https://doi.org/10.1038/s43247-025-02306-0
51. Observationally constrained regional variations of shortwave absorption by iron oxides emphasize the cooling effect of dust V. Obiso et al. https://doi.org/10.5194/acp-24-5337-2024
52. Spatiotemporal patterns of aerosol optical depth and PM2.5 concentrations derived from multi-source remote sensing Q. Mao & S. Liu https://doi.org/10.1016/j.jastp.2025.106689
53. A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method M. Tao et al. https://doi.org/10.1016/j.rse.2023.113763
54. Deep neural networks reveal organic pollutants’ dominance in global inflammatory bowel disease I. Khan et al. https://doi.org/10.1016/j.jes.2025.04.058
55. Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties? D. Carrer et al. https://doi.org/10.3390/rs13163072
56. An ensemble machine learning method to retrieve aerosol parameters from ground-based Sun-sky photometer measurements Q. Li et al. https://doi.org/10.5194/amt-19-2507-2026
57. Comparison of the Performance of the GRASP and MERRA2 Models in Reproducing Tropospheric Aerosol Layers A. Fernandes et al. https://doi.org/10.3390/atmos14091409
58. Black Carbon and Brown Carbon and Selective Smoke Aerosol Absorption during Massive Wildfires in Alaska in 2019 and Canada in 2023 G. Gorchakov et al. https://doi.org/10.1134/S1024856025700058
59. Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm A. Sinyuk et al. https://doi.org/10.5194/amt-15-4135-2022
60. Inversion of Aerosol Particle Size Distribution Using an Improved Stochastic Particle Swarm Optimization Algorithm X. Nie & Q. Mao https://doi.org/10.3390/rs14164085
61. Increased aerosols can reverse Twomey effect in water clouds through radiative pathway P. Khatri et al. https://doi.org/10.1038/s41598-022-25241-y
62. Atmospheric aerosol size distribution impacts radiative effects over the Himalayas via modulating aerosol single-scattering albedo P. Tian et al. https://doi.org/10.1038/s41612-023-00368-5
63. Impact of Chemical Composition on Aerosol Scattering: Insights from the Surface Particulate Matter Network and Aerosol Robotic Network S. Eom et al. https://doi.org/10.1021/acs.est.5c09325
64. Remote sensing of aerosols over drylands: Challenges, uncertainties, and paths forward C. Chen et al. https://doi.org/10.1126/sciadv.aec4247
65. Global evaluation of sentinel 2 level 2A Sen2Cor aerosol optical thickness retrievals A. Kumar & M. Mehta https://doi.org/10.1080/01431161.2024.2421947
66. Investigating the role of aerosol wet scavenging on global horizontal irradiance simulation in the WRF-Chem-solar model S. Wang et al. https://doi.org/10.1016/j.apenergy.2025.126062
67. Adaptation of the CIMEL-318T to shipborne use: 3 years of automated AERONET-compatible aerosol measurements on board the research vessel Marion Dufresne B. Torres et al. https://doi.org/10.5194/amt-18-4809-2025
68. Simultaneous retrieval of aerosol optical depth, spectral absorption and layer height from DSCOVR EPIC using MAIAC algorithm A. Lyapustin et al. https://doi.org/10.3389/frsen.2025.1677438
69. Aerosol retrieval over snow using the RemoTAP algorithm Z. Zhang et al. https://doi.org/10.5194/amt-16-6051-2023
70. Implications of dust minerals on radiative transfer at regional scale, using the METAL-WRF model C. Spyrou et al. https://doi.org/10.5194/amt-18-7717-2025
71. A Regional Aerosol Model for the Oceanic Area around Eastern China Based on Aerosol Robotic Network (AERONET) S. Chen et al. https://doi.org/10.3390/rs16061106
72. Optical and chemical properties of long-range transported aerosols using satellite and ground-based observations over seoul, South Korea G. Choo et al. https://doi.org/10.1016/j.atmosenv.2020.118024
73. Simulation and evaluation study of atmospheric aerosol nonsphericity as a function of particle size Q. Mao & X. Nie https://doi.org/10.1016/j.partic.2023.12.013
74. Influence of changes in anthropogenic and natural sources on global aerosol optical depth during COVID-19 lockdown: Ground-based observations, satellites, models S. Ramachandran & K. Ansari https://doi.org/10.1016/j.atmosenv.2024.120948
75. Rapid, accurate computation of narrow-band sky radiance in the 940 nm gas absorption region using the correlated k-distribution method for sun-photometer observations M. Momoi et al. https://doi.org/10.1186/s40645-022-00467-6
76. EPISODES OF VARIABILITY OF THE AEROSOL PARTICLES CONTENT AND PROPERTIES IN THE ATMOSPHERE OVER KYIV IN 2022 V. DANYLEVSKY https://doi.org/10.17721/BTSNUA.2025.71.5-14
77. Estimates of remote sensing retrieval errors by the GRASP algorithm: application to ground-based observations, concept and validation M. Herrera et al. https://doi.org/10.5194/amt-15-6075-2022
78. Modeling atmospheric brown carbon in the GISS ModelE Earth system model M. DeLessio et al. https://doi.org/10.5194/acp-24-6275-2024
79. ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set A. Gkikas et al. https://doi.org/10.5194/amt-14-309-2021
80. AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. https://doi.org/10.5194/acp-21-6895-2021
81. Aerosol optical depth climatology from the high-resolution MAIAC product over Europe: differences between major European cities and their surrounding environments L. Di Antonio et al. https://doi.org/10.5194/acp-23-12455-2023
82. Intensity-resolved classification of forest fire smoke via fused satellite and ground-based optical climatology Y. Ma et al. https://doi.org/10.1016/j.envres.2026.124710
83. Retrieval of aerosol properties using relative radiance measurements from an all-sky camera R. Román et al. https://doi.org/10.5194/amt-15-407-2022
84. A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode J. Reid et al. https://doi.org/10.3390/rs14132978
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88. Temperature correction method and verification of the CW193 sun–sky photometer J. Zhu et al. https://doi.org/10.1364/OE.535213
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100. Synergetic retrieval from multi-mission spaceborne measurements for enhanced aerosol and surface characterization P. Litvinov et al. https://doi.org/10.5194/amt-18-7679-2025
101. Seasonal comparisons of GEOS-Chem-TOMAS (GCT) simulations with AERONET-inversion retrievals over sites in the North American and European Arctic Y. AboEl-Fetouh et al. https://doi.org/10.1016/j.atmosenv.2021.118852
102. A deep learning-based imputation method for missing gaps in satellite aerosol products by fusing numerical model data N. Liu et al. https://doi.org/10.1016/j.atmosenv.2024.120440
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107. Estimation of the Mass Concentration of Volcanic Ash Using Ceilometers: Study of Fresh and Transported Plumes from La Palma Volcano A. Bedoya-Velásquez et al. https://doi.org/10.3390/rs14225680
108. Weather specific evaluation of satellite retrieved aerosol optical depth over drylands of the Southwest United States H. Dhaliwal & S. Pal https://doi.org/10.1016/j.atmosres.2026.108932
109. MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation C. Roychoudhury et al. https://doi.org/10.5194/essd-18-5209-2026
110. Emission-Intensity-Driven Evolution of Black Carbon Microphysics in Wildfire Smoke Revealed by Multiwavelength Remote Sensing J. Luo et al. https://doi.org/10.1109/TGRS.2026.3697773
111. Error characterization and analysis of aerosol products from the geostationary environment monitoring spectrometer (GEMS) G. Du et al. https://doi.org/10.1016/j.atmosres.2025.108682
112. Extended POLIPHON dust conversion factor dataset for lidar-derived cloud condensation nuclei and ice-nucleating particle concentration profiles Y. He et al. https://doi.org/10.5194/amt-18-5669-2025
113. Compact dual-wavelength depolarization lidar for aerosol characterization over the subtropical North Atlantic Y. González et al. https://doi.org/10.5194/amt-18-1885-2025
114. The impact of using assimilated Aeolus wind data on regional WRF-Chem dust simulations P. Kiriakidis et al. https://doi.org/10.5194/acp-23-4391-2023
115. Anomalous Selective Absorption of Smoke Aerosol during Forest Fires in Alaska in July–August 2019 G. Gorchakov et al. https://doi.org/10.31857/S0002351523060044
116. Long-term trends in aerosol properties derived from AERONET measurements Z. Zhang et al. https://doi.org/10.5194/acp-25-4617-2025
117. Aerosol characterisation in the subtropical eastern North Atlantic region using long-term AERONET measurements Á. Barreto et al. https://doi.org/10.5194/acp-22-11105-2022
118. A Sequence-to-Sequence Transformer Model for Satellite Retrieval of Aerosol Optical and Microphysical Parameters from Space L. Zhang et al. https://doi.org/10.3390/rs16244659
119. Validation of the aerosol optical property products derived by the GRASP/Component approach from multi-angular polarimetric observations X. Zhang et al. https://doi.org/10.1016/j.atmosres.2021.105802
120. Aerosol Loading and Radiation Budget Perturbations in Densely Populated and Highly Polluted Indo‐Gangetic Plain by COVID‐19: Influences on Cloud Properties and Air Temperature P. Khatri et al. https://doi.org/10.1029/2021GL093796
121. Aerosol single-scattering albedo derived by merging OMI/POLDER satellite products and AERONET ground observations Y. Dong et al. https://doi.org/10.5194/essd-17-3873-2025
122. Retrieval of aerosol properties from aerosol optical depth measurements with high temporal resolution and spectral range A. Karanikolas et al. https://doi.org/10.5194/amt-18-7651-2025
123. Characterization of Stratospheric Smoke Particles over the Antarctica by Remote Sensing Instruments R. González et al. https://doi.org/10.3390/rs12223769
124. Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods M. Kim et al. https://doi.org/10.5194/amt-17-4317-2024
125. Type-based assessment of aerosol direct radiative effects: A proof-of-concept using GEOS-Chem and CATCH B. Sutherland & N. Meskhidze https://doi.org/10.1016/j.atmosres.2025.108036
126. Global aerosol models considering their spatial heterogeneities based on AERONET measurements S. Wang et al. https://doi.org/10.1016/j.atmosres.2024.107521
127. Augmenting Heritage Ocean-Color Aerosol Models for Enhanced Remote Sensing of Inland and Nearshore Coastal Waters M. Montes et al. https://doi.org/10.3389/frsen.2022.860816
128. Retrieving BRDFs from UAV-based radiometers for fiducial reference measurements: caveats and recommendations S. Schunke et al. https://doi.org/10.3389/frsen.2023.1285800
129. Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX‐AQ Field Campaign P. Brodrick et al. https://doi.org/10.1029/2021JD034905
130. Absorbing Aerosol Optical Depth From OMI/TROPOMI Based on the GBRT Algorithm and AERONET Data in Asia D. Li et al. https://doi.org/10.1109/TGRS.2022.3231699
131. Feasibility analysis of AERONET lunar AOD for nighttime particulate matter estimation K. Kim et al. https://doi.org/10.1088/2515-7620/accfe9
132. A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust E. Proestakis et al. https://doi.org/10.5194/amt-17-3625-2024
133. Exceptional high AOD over Svalbard in summer 2019: a multi-instrumental approach S. Herrero-Anta et al. https://doi.org/10.5194/acp-26-1435-2026
134. New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests H. Hashimoto et al. https://doi.org/10.1038/s41467-021-20994-y
135. A Contrast Minimization Approach to Remove Sun Glint in Landsat 8 Imagery F. Fell https://doi.org/10.3390/rs14184643
136. Aerosol characteristics over Indo-Gangetic Plain from ground-based AERONET and MERRA-2/CAMS model simulations K. Ansari & S. Ramachandran https://doi.org/10.1016/j.atmosenv.2022.119434
137. Difference between global and regional aerosol model classifications and associated implications for spaceborne aerosol optical depth retrieval P. Zhou et al. https://doi.org/10.1016/j.atmosenv.2023.119674
138. Atmospheric dust and air quality over large-cities and megacities of the world E. Proestakis et al. https://doi.org/10.5194/acp-25-14777-2025
139. Simultaneous retrievals of biomass burning aerosols and trace gases from the ultraviolet to near-infrared over northern Thailand during the 2019 pre-monsoon season U. Jeong et al. https://doi.org/10.5194/acp-22-11957-2022
140. Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001–2018) S. Liu et al. https://doi.org/10.1021/acs.est.3c02111
141. The mineral aerosol profiling from infrared radiances version 5.1 algorithm and its evaluation S. Vandenbussche et al. https://doi.org/10.5194/amt-19-4889-2026
142. Aerosol properties and aerosol–radiation interactions in clear-sky conditions over Germany J. Witthuhn et al. https://doi.org/10.5194/acp-21-14591-2021
143. On the retrieval of cloud optical thickness from spectral radiances - An intercomparison of ground-based measurements in the Arctic F. Calì Quaglia et al. https://doi.org/10.1016/j.jqsrt.2026.109898
144. Global hourly seamless AOD through measurement-adjusted machine learning fusion of multi-satellite and reanalysis data Y. Ding et al. https://doi.org/10.1080/15481603.2025.2586203
145. Ground-based validation of aerosol optical depth from CAMS reanalysis project: An uncertainty input on direct normal irradiance under cloud-free conditions V. Salamalikis et al. https://doi.org/10.1016/j.renene.2021.02.025
146. A Modular Framework for All-Sky Radiance: Physically Based Simulation for Complex Cloud Conditions M. Yang et al. https://doi.org/10.1109/TGRS.2026.3687091
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148. Impact of military activity on atmospheric aerosol characteristics in Ukraine and Kyiv city X. Wei et al. https://doi.org/10.1016/j.apr.2025.102496
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151. Spectral transformer with physics-informed regularization for high-resolution Landsat-8 AOD retrieval X. Xu et al. https://doi.org/10.1016/j.jqsrt.2026.110084
152. Prediction of Circumsolar Irradiance and Its Impact on CSP Systems under Clear Skies E. Abreu et al. https://doi.org/10.3390/en16247950
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161. Inferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observations I. Konovalov et al. https://doi.org/10.5194/amt-14-6647-2021
162. The evolution of aerosol types and direct radiative forcing in Beijing-Tianjin-Hebei, China: A long-term analysis with a modified Gaussian mixture model J. Wang et al. https://doi.org/10.1016/j.atmosres.2026.109072
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166. Ground-based MFRSR UV-Vis spectral retrievals of Saharan dust absorption at Izaña Observatory H. Jethva et al. https://doi.org/10.5194/amt-19-4335-2026
167. 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. https://doi.org/10.5194/amt-14-3449-2021
168. Advancing operational global aerosol forecasting with machine learning K. Gui et al. https://doi.org/10.1038/s41586-026-10234-y
169. Two decades of fire activity over the PEEX domain: a look from space, with contribution from models and ground-based measurements L. Sogacheva et al. https://doi.org/10.1080/20964471.2024.2316730
170. The influence of scattering correction effect based on optical path distribution on CO2 retrieval Y. Jiang et al. https://doi.org/10.1515/phys-2025-0245
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172. Detection and analysis of Lhù'ààn Mân' (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements S. Sayedain et al. https://doi.org/10.5194/amt-16-4115-2023
173. Capabilities of an Automatic Lidar Ceilometer to Retrieve Aerosol Characteristics within the Planetary Boundary Layer D. Li et al. https://doi.org/10.3390/rs13183626
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175. First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia Y. Cho et al. https://doi.org/10.5194/amt-17-4369-2024
176. Microstructure and Absorption Capacity of Aerosol in Nonphotochemical Smog G. Gorchakov et al. https://doi.org/10.1134/S1028334X25609861
177. Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires D. Robbins et al. https://doi.org/10.5194/amt-17-3279-2024
178. First Ever Observations of Mineral Dust in Wintertime over Warsaw, Poland D. Szczepanik et al. https://doi.org/10.3390/rs14153788
179. Estimation of Aerosol Columnar Size Distribution from Spectral Extinction Data in Coastal and Maritime Environment E. Kassianov et al. https://doi.org/10.3390/atmos12111412
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182. Efficient calculation of radiative intensity including the polarization effect in moderately thick atmospheres using a truncation approximation M. Momoi et al. https://doi.org/10.1016/j.jqsrt.2021.107976
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184. Radiative effects of absorbing aerosol types over South Asia K. Ansari & S. Ramachandran https://doi.org/10.1016/j.scitotenv.2022.159969
185. Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe J. Vaquero-Martínez et al. https://doi.org/10.1016/j.atmosres.2023.106698
186. Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim et al. https://doi.org/10.5194/amt-17-1913-2024
187. 基于AERONET的东沙海域气溶胶光学模型 陈. Chen Shunping et al. https://doi.org/10.3788/AOS230587
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189. The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water J. Limbacher et al. https://doi.org/10.5194/amt-15-6865-2022
190. Impact of synoptic meteorological conditions on air quality in three different case studies in Rome, Italy A. Di Bernardino et al. https://doi.org/10.1016/j.apr.2021.02.019
191. Seasonal aerosol variations at the Land-Ocean boundary: Insights from a global AERONET network analysis J. Zhao et al. https://doi.org/10.1016/j.envint.2026.110158
192. An emerging aerosol climatology via remote sensing over Metro Manila, the Philippines G. Lorenzo et al. https://doi.org/10.5194/acp-23-10579-2023
193. Regional validation of the solar irradiance tool SolaRes in clear-sky conditions, with a focus on the aerosol module T. Elias et al. https://doi.org/10.5194/amt-17-4041-2024
194. Feasibility of Ceilometers Data to Estimate Radiative Forcing Values: Application to Different Conditions around the COVID-19 Lockdown Period R. Barragan et al. https://doi.org/10.3390/rs12223699
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196. Overview of the SLOPE I and II campaigns: aerosol properties retrieved with lidar and sun–sky photometer measurements J. Benavent-Oltra et al. https://doi.org/10.5194/acp-21-9269-2021
197. Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka P. Tiwari et al. https://doi.org/10.1038/s43247-025-02012-x
198. Small but Notable Influence of Numerical Diffusion on Super Coarse Dust Sedimentation: Insights from UNO3 vs. Upwind Schemes E. Drakaki et al. https://doi.org/10.3390/atmos16091086
199. Water vapour characteristics and radiative effects at high-altitude Himalayan sites U. Dumka et al. https://doi.org/10.1016/j.apr.2021.101303
200. The polarimetric characteristics of dust with irregular shapes: evaluation of the spheroid model for single particles J. Luo et al. https://doi.org/10.5194/amt-15-2767-2022
201. Properties of aerosol and surface derived from OLCI/Sentinel-3A using GRASP approach: Retrieval development and preliminary validation C. Chen et al. https://doi.org/10.1016/j.rse.2022.113142
202. Columnar optical-radiative properties and components of aerosols in the Arctic summer from long-term AERONET measurements Y. Liang et al. https://doi.org/10.1016/j.scitotenv.2023.169052
203. A large reduction of direct aerosol cooling over Poland in the last decades K. Markowicz et al. https://doi.org/10.1002/joc.7488
204. Measurement report: Combined use of MAX-DOAS and AERONET ground-based measurements in Montevideo, Uruguay, for the detection of distant biomass burning M. Osorio et al. https://doi.org/10.5194/acp-24-7447-2024
205. Advanced Time series Multi-wavelength AOD Transformer (TMAT) model: joint retrieval of aerosol optical and microphysical properties using Himawari-8 AHI data L. She et al. https://doi.org/10.1016/j.jag.2026.105252
206. A regional case study of aerosol-induced radiative and precipitation responses in Mainland Southeast Asia S. Bran et al. https://doi.org/10.1016/j.atmosenv.2026.122184
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208. The Aerosol Optical Depth Retrieval from Wide-Swath Imaging of DaQi-1 over Beijing Z. Wang et al. https://doi.org/10.3390/atmos15121476
209. Characterization of aerosol size properties from measurements of spectral optical depth: a global validation of the GRASP-AOD code using long-term AERONET data B. Torres & D. Fuertes https://doi.org/10.5194/amt-14-4471-2021
210. CAECENET: An automatic system processing photometer and ceilometer data from different networks to provide columnar and vertically-resolved aerosol properties C. Herrero del Barrio et al. https://doi.org/10.1371/journal.pone.0311990
211. Intercomparison of Aerosol Types Reported as Part of Aerosol Product Retrieval over Diverse Geographic Regions S. Falah et al. https://doi.org/10.3390/rs14153667
212. Polarimetric coordinate validation for merging GRASP and AirMSPI FIREX-AQ observations C. DeLeon et al. https://doi.org/10.1016/j.jqsrt.2024.108910
213. Extreme wildfires over northern Greece during summer 2023 – Part A: Effects on aerosol optical properties and solar UV radiation K. Michailidis et al. https://doi.org/10.1016/j.atmosres.2024.107700
214. 20 years of columnar aerosol properties at Valencia area (Eastern Spain) by ground-based sun-photometry M. Garcia-Suñer et al. https://doi.org/10.1016/j.atmosres.2023.107198
215. Long-Term Trends in Aerosol Single Scattering Albedo Cause Bias in MODIS Aerosol Optical Depth Trends Z. Zhang et al. https://doi.org/10.1109/TGRS.2024.3424981
216. Impact of cloud presence on sky radiances and the retrieval of aerosol properties S. Herrero-Anta et al. https://doi.org/10.1016/j.atmosres.2025.107938
217. POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. https://doi.org/10.5194/amt-16-1951-2023
218. Atmospheric Aerosol Outbreak over Nicosia, Cyprus, in April 2019: Case Study Y. Yukhymchuk et al. https://doi.org/10.3390/atmos13121997
219. Remote sensing of local-dust across the Canadian Arctic S. Sayedain et al. https://doi.org/10.5194/amt-19-4553-2026
220. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison C. Chen et al. https://doi.org/10.1016/j.rse.2024.114374
221. Radiative and climate effects of aerosol scattering in long-wave radiation based on global climate modelling T. Drugé et al. https://doi.org/10.5194/acp-25-11651-2025
222. A global black carbon dataset of column concentration and microphysical information derived from MISR multi-band observations and Mie scattering simulations Z. Liu et al. https://doi.org/10.5194/essd-18-507-2026
223. Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing C. Chen et al. https://doi.org/10.1038/s41467-022-35147-y
224. The retrieval of cloud properties based on spectral solar light diffuse transmittance measurements under optically thick cloud cover conditions A. Kokhanovsky et al. https://doi.org/10.1016/j.jqsrt.2020.107008
225. Aerosols optical and radiative properties in Indonesia based on AERONET version 3 S. Kusumaningtyas et al. https://doi.org/10.1016/j.atmosenv.2022.119174
226. Satellite remote sensing of aerosol single scattering albedo: Instruments, algorithms, and challenges Y. Dong et al. https://doi.org/10.1016/j.jqsrt.2025.109802
227. Global assessment of aerosol radiative effects: New insights from observations, reanalysis, and climate models K. Ansari et al. https://doi.org/10.1016/j.scitotenv.2025.180871
228. TROPOMI aerosol products: evaluation and observations of synoptic-scale carbonaceous aerosol plumes during 2018–2020 O. Torres et al. https://doi.org/10.5194/amt-13-6789-2020
229. Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations R. Kudo et al. https://doi.org/10.5194/amt-16-3835-2023
230. On the retrieval of cloud optical thickness from spectral radiances - A sensitivity study with high albedo surfaces F. Calì Quaglia et al. https://doi.org/10.1016/j.jqsrt.2024.109108
231. Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network M. Kim et al. https://doi.org/10.3390/rs15143621
232. Introduction of Ground-based Remote Sensing and Applications for Air Quality Monitoring S. Park et al. https://doi.org/10.5572/KOSAE.2025.41.2.254
233. Retrieving Nocturnal Aerosol Optical Depth Using Lunar Photometry: Algorithm Improvements and Evaluation J. Zhu et al. https://doi.org/10.1109/TGRS.2025.3642839
234. Sensitivity analysis of Look-up table for satellite-based aerosol optical depth retrieval S. Amini et al. https://doi.org/10.1016/j.jaerosci.2021.105842
235. A multilevel downscaling model for enhancing nocturnal aerosol optical depth reanalysis from CAMS over the Beijing-Tianjin-Hebei region, China S. Wang et al. https://doi.org/10.1016/j.eti.2025.104238
236. Intelligent Atmospheric Correction Algorithm for Polarization Ocean Color Satellite Measurements Over the Open Ocean X. He et al. https://doi.org/10.1109/TGRS.2023.3348159
237. Increased aerosol scattering contributes to the recent monsoon rainfall decrease over the Gangetic Plain T. Ying et al. https://doi.org/10.1016/j.scib.2023.08.052
238. Aerosol properties in the atmosphere of Natal/Brazil measured by an AERONET Sun-photometer D. Fortunato dos Santos Oliveira et al. https://doi.org/10.1007/s11356-020-11373-z
239. A comprehensive analysis of blue-to-red atmospheric signatures from all-sky imagery: CLARIS, an adaptive cloud-cover framework P. Valdelomar et al. https://doi.org/10.1016/j.atmosres.2026.109131
240. Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S. X. Ye et al. https://doi.org/10.3390/rs14236113
241. Extended aerosol optical depth (AOD) time series analysis in an Alpine valley: a comparative study from 2007 to 2023 J. Wagner et al. https://doi.org/10.5194/ar-2-153-2024
242. Feasibility of satellite vicarious calibration using HYPERNETS surface reflectances from Gobabeb and Princess Elisabeth Antarctica sites P. De Vis et al. https://doi.org/10.3389/frsen.2024.1323998
243. Effect of Shape and Sizes of Crystal Particles on Angular Distributions of Transmitted Solar Radiation in Two Sensing Geometries: Results of Numerical Simulation T. Zhuravleva https://doi.org/10.1134/S1024856021010127
244. Downscaling aerosol optical depth by fusing satellite retrieval and model simulation using artificial intelligence technology L. Sun et al. https://doi.org/10.1016/j.atmosres.2025.108411
245. Exploring biases in the GISS ModelE Earth system model brown carbon representation with in-situ flight observations M. DeLessio et al. https://doi.org/10.5194/acp-26-7325-2026
246. First assessment of Aeolus Standard Correct Algorithm particle backscatter coefficient retrievals in the eastern Mediterranean A. Gkikas et al. https://doi.org/10.5194/amt-16-1017-2023
247. Growth and Global Persistence of Stratospheric Sulfate Aerosols From the 2022 Hunga Tonga–Hunga Ha'apai Volcanic Eruption M. Boichu et al. https://doi.org/10.1029/2023JD039010
248. A global perspective on CO2 satellite observations in high AOD conditions T. Virtanen et al. https://doi.org/10.5194/amt-18-929-2025
249. Study on global atmospheric aerosol type identification from combined satellite and ground observations X. Nie et al. https://doi.org/10.1016/j.atmosenv.2025.121100
250. Selective Absorption of a Dust Haze in the Visible Spectrum over the Middle East in Spring 2022 G. Gorchakov et al. https://doi.org/10.1134/S1028334X2460525X
251. Modeling radiative and climatic effects of brown carbon aerosols with the ARPEGE-Climat global climate model T. Drugé et al. https://doi.org/10.5194/acp-22-12167-2022
252. Modeling coarse and giant desert dust particles E. Drakaki et al. https://doi.org/10.5194/acp-22-12727-2022
253. Atmospheric Correction of Coastal Waters Based on Satellite–AERONET-OC Matchups X. Li et al. https://doi.org/10.34133/remotesensing.0886
254. A decadal, hourly high-resolution satellite dataset of aerosol optical properties over East Asia J. Lee et al. https://doi.org/10.5194/essd-17-5761-2025
255. A Generalized Aerosol Algorithm for Multi‐Spectral Satellite Measurement With Physics‐Informed Deep Learning Method J. Jiang et al. https://doi.org/10.1029/2023GL106806
256. Sensitivity of global direct aerosol shortwave radiative forcing to uncertainties in aerosol optical properties J. Elsey et al. https://doi.org/10.5194/acp-24-4065-2024
257. Detection of potential structural deficiencies in a global aerosol model using a perturbed parameter ensemble L. Prévost et al. https://doi.org/10.5194/acp-26-2487-2026
258. Retrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environments V. Kayetha et al. https://doi.org/10.5194/amt-15-845-2022
259. The extreme forest fires in California/Oregon in 2020: Aerosol optical and physical properties and comparisons of aged versus fresh smoke T. Eck et al. https://doi.org/10.1016/j.atmosenv.2023.119798
260. Investigating the Presence of Biomass Burning Events at Ny-Ålesund: Optical and Chemical Insights from Summer-Fall 2019 S. Pulimeno et al. https://doi.org/10.1016/j.atmosenv.2024.120336
261. Combined Characterization of Airborne Saharan Dust above Sofia, Bulgaria, during Blocking-Pattern Conditioned Dust Episode in February 2021 Z. Peshev et al. https://doi.org/10.3390/rs15153833
262. Interpretable machine learning quantifies composition and size influences on aerosol spectral absorption W. Wang et al. https://doi.org/10.5194/acp-26-6471-2026
263. Preliminary Retrieval and Validation of Aerosol Optical Depths from FY-4B Advanced Geostationary Radiation Imager Images D. Zhou et al. https://doi.org/10.3390/rs16020372
264. Enhanced net CO2 exchange of a semideciduous forest in the southern Amazon due to diffuse radiation from biomass burning S. Rodrigues et al. https://doi.org/10.5194/bg-21-843-2024
265. Intercomparison of aerosol optical depth retrievals from GAW-PFR and SKYNET sun photometer networks and the effect of calibration A. Karanikolas et al. https://doi.org/10.5194/amt-17-6085-2024
266. A Comprehensive Description of Multi-Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Applications O. Dubovik et al. https://doi.org/10.3389/frsen.2021.706851
267. Statistical Approach to the Synergy of Data from Caliop and Ground-Based Radiometric Stations for Studying Altitude Profiles of Aerosol Parameters A. Chaikovsky et al. https://doi.org/10.1007/s10812-024-01729-5
268. Numerical neural network approach to simultaneous material classification and sizing of aerosolized particles M. Geisler et al. https://doi.org/10.1016/j.jqsrt.2021.107982
269. Addressing observational gaps in aerosol parameters using machine learning: Implications to aerosol radiative forcing M. Parmar et al. https://doi.org/10.1016/j.atmosenv.2024.120661
270. Continental aerosol properties and absorption retrieval using random forest machine learning method specific to geostationary remote sensing F. Bao et al. https://doi.org/10.1016/j.rse.2024.114275
271. Pretrained Deep Learning Framework for Assessing Aerosol Pollution and Radiative Forcing from Satellite Polarization Measurements Z. Ji et al. https://doi.org/10.1021/acsestair.5c00445
272. Aerosol optical depth retrieval from Geostationary Environment Monitoring Spectrometer (GEMS): Advancing the first hyperspectral geostationary air quality mission using deep learning H. Choi et al. https://doi.org/10.1016/j.scitotenv.2025.180535
273. Characterization of aerosol optical depth (AOD) anomalies in September and October 2022 over Skukuza in South Africa M. Ranaivombola et al. https://doi.org/10.5194/acp-25-3519-2025
274. Retrieval of Aged Biomass-Burning Aerosol Properties by Using GRASP Code in Synergy with Polarized Micro-Pulse Lidar and Sun/Sky Photometer M. López-Cayuela et al. https://doi.org/10.3390/rs14153619
275. Inferring iron-oxide species content in atmospheric mineral dust from DSCOVR EPIC observations S. Go et al. https://doi.org/10.5194/acp-22-1395-2022
276. Enhancing mobile aerosol monitoring with CE376 dual-wavelength depolarization lidar M. Sanchez Barrero et al. https://doi.org/10.5194/amt-17-3121-2024
277. Diurnal and nocturnal aerosol properties by AERONET sun-sky-lunar photometer measurements along four years M. Perrone et al. https://doi.org/10.1016/j.atmosres.2021.105889
278. Air Pollution and Health Burden in India Quantified Using the AEIM-India Emission Inventory M. Lund et al. https://doi.org/10.1021/acsestair.5c00171
279. Twilight Near-Infrared Radiometry for Stratospheric Aerosol Layer Height L. Mukherjee et al. https://doi.org/10.3390/rs17122071
280. Atmospheric processing and aerosol aging responsible for observed increase in absorptivity of long-range-transported smoke over the southeast Atlantic A. Fakoya et al. https://doi.org/10.5194/acp-25-7879-2025
281. Version 2 of hourly aerosol optical centroid height (AOCH) data product from EPIC/DSCOVR in deep space Z. Lu et al. https://doi.org/10.1016/j.rse.2026.115623
282. A review of coarse mineral dust in the Earth system A. Adebiyi et al. https://doi.org/10.1016/j.aeolia.2022.100849
283. Joint Diagnostics of Circumsolar Sky Brightness Using Coronagraphic Measurements and Aerosol Optical Inversions at Maunaloa T. Schad et al. https://doi.org/10.3847/1538-4357/ae4ec2
284. Impact of Brown Carbon on the Simulation of Optical Properties over East Asia in a Chemistry–climate Model S. Yang et al. https://doi.org/10.1007/s13143-026-00438-7
285. Assessing Lidar Ratio Impact on CALIPSO Retrievals Utilized for the Estimation of Aerosol SW Radiative Effects across North Africa, the Middle East, and Europe A. Moustaka et al. https://doi.org/10.3390/rs16101689
286. Interpolation uncertainty of atmospheric temperature profiles A. Fassò et al. https://doi.org/10.5194/amt-13-6445-2020
287. Retrieval of Long-Term (1980–2024) Time Series of PM10 Concentration by an Empirical Method: The Paris, Cairo, and New Delhi Case Studies A. Khaled et al. https://doi.org/10.3390/atmos16111272
288. Quantitative analysis of the Martian atmospheric dust cycle: Transported mass, surface dust lifting and sedimentation rates M. López-Cayuela et al. https://doi.org/10.1016/j.icarus.2023.115854
289. Canadian Wildfire Smoke Episode over Europe in October 2023: Lidar, Sun-Photometer, and Model Characterization of Smoke Layers Observed Above Sofia, Bulgaria T. Evgenieva et al. https://doi.org/10.3390/rs17162899
290. Aerosol absorption using in situ filter-based photometers and ground-based sun photometry in the Po Valley urban atmosphere A. Bigi et al. https://doi.org/10.5194/acp-23-14841-2023
291. Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region Y. Xie et al. https://doi.org/10.3390/rs14020406
292. A methodology for realistic estimation of the aerosol impact on the solar potential R. Blaga et al. https://doi.org/10.1016/j.solener.2024.112425
293. Validation of aerosol chemical composition and optical properties provided by Copernicus Atmosphere Monitoring Service (CAMS) using ground-based global data A. Amarillo et al. https://doi.org/10.1016/j.atmosenv.2024.120683
294. Relative sky radiance from multi-exposure all-sky camera images J. Antuña-Sánchez et al. https://doi.org/10.5194/amt-14-2201-2021
295. Accuracy of SeaHawk-HawkEye Ocean color CubeSat remote sensing reflectance products in globally distributed aquatic sites S. Kolluru et al. https://doi.org/10.1016/j.rse.2025.115111
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