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31. Investigations of MODIS AOD and cloud properties with CERES sensor based net cloud radiative effect and a NOAA HYSPLIT Model over Bangladesh for the period 2001–2016 M. Ali et al. 10.1016/j.atmosres.2018.09.001
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38. Large Air Quality and Public Health Impacts due to Amazonian Deforestation Fires in 2019 E. Butt et al. 10.1029/2021GH000429
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42. Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET M. Singh et al. 10.1109/JSTARS.2017.2734331
43. Aerosol Characteristics during the COVID-19 Lockdown in China: Optical Properties, Vertical Distribution, and Potential Source Y. Jin et al. 10.3390/rs14143336
44. Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm C. Chen et al. 10.5194/acp-18-12551-2018
45. City-level variations in aerosol optical properties and aerosol type identification derived from long-term MODIS/Aqua observations in the Sichuan Basin, China H. Cai et al. 10.1016/j.uclim.2021.100886
46. Dust Impacts of Rapid Agricultural Expansion on the Great Plains A. Lambert et al. 10.1029/2020GL090347
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48. Simulation of a Dust‐And‐Rain Event Across the Red Sea Using WRF‐Chem S. Parajuli et al. 10.1029/2022JD038384
49. Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds D. Rosenfeld et al. 10.1126/science.aav0566
50. Spatial and Temporal Distribution of PM2.5 Pollution over Northeastern Mexico: Application of MERRA-2 Reanalysis Datasets J. Carmona et al. 10.3390/rs12142286
51. Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations R. Fan et al. 10.1016/j.scitotenv.2022.159117
52. Source profiling of air pollution and its association with acute respiratory infections in the Himalayan-bound region of India M. Wani et al. 10.1007/s11356-021-15413-0
53. Variation of Aerosol Optical Properties over Cluj-Napoca, Romania, Based on 10 Years of AERONET Data and MODIS MAIAC AOD Product H. Ștefănie et al. 10.3390/rs15123072
54. Validation of MODIS 3 km Resolution Aerosol Optical Depth Retrievals Over Asia J. Nichol & M. Bilal 10.3390/rs8040328
55. Characterization of temporal and spatial variability of aerosols from ground-based climatology: towards evaluation of satellite mission requirements C. Chen et al. 10.1016/j.jqsrt.2021.107627
56. Variability of surface solar radiation under clear skies over Qinghai-Tibet Plateau: Role of aerosols and water vapor L. Yu et al. 10.1016/j.atmosenv.2022.119286
57. Lidar Profiling of Aerosol Vertical Distribution in the Urbanized French Alpine Valley of Annecy and Impact of a Saharan Dust Transport Event P. Chazette & J. Totems 10.3390/rs15041070
58. Evaluation of MODIS Deep Blue Aerosol Algorithm in Desert Region of East Asia: Ground Validation and Intercomparison M. Tao et al. 10.1002/2017JD026976
59. Pre-seismic anomalies from optical satellite observations: a review Z. Jiao et al. 10.5194/nhess-18-1013-2018
60. Status update: is smoke on your mind? Using social media to assess smoke exposure B. Ford et al. 10.5194/acp-17-7541-2017
61. Satellite observations of smoke–cloud–radiation interactions over the Amazon rainforest R. Herbert & P. Stier 10.5194/acp-23-4595-2023
62. Aerosol Distributions and Transport over Southern Morocco from Ground-Based and Satellite Observations (2004–2020) T. Millet et al. 10.3390/atmos13060923
63. Historical footprints and future projections of global dust burden from bias-corrected CMIP6 models J. Liu et al. 10.1038/s41612-023-00550-9
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65. Cold-season atmospheric conditions associated with sudden changes in PM10 concentration over Seoul, Korea M. Cho et al. 10.1016/j.apr.2021.03.004
66. Ocean flux of salt, sulfate, and organic components to atmospheric aerosol L. Russell et al. 10.1016/j.earscirev.2023.104364
67. Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster 10.1016/j.rse.2020.111971
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69. Generation of typical meteorological years for 33 locations in Greece: adaptation to the needs of various applications H. Kambezidis et al. 10.1007/s00704-020-03264-7
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75. Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP) P. Xian et al. 10.1002/qj.3497
76. Impact of atmospheric anthropogenic nitrogen on new production in the northern Indian Ocean: constrained based on satellite aerosol optical depth and particulate nitrogen levels V. Sarma et al. 10.1039/D2EM00234E
77. Temporal coherence in particulate matter in East Asian outflow regions: fingerprints of ENSO and Asian dust M. Kueh et al. 10.1038/s41612-023-00530-z
78. The Lake Urmia environmental disaster in Iran: A look at aerosol pollution A. Hossein Mardi et al. 10.1016/j.scitotenv.2018.03.148
79. Using Satellite‐Derived Fire Arrival Times for Coupled Wildfire‐Air Quality Simulations at Regional Scales of the 2020 California Wildfire Season W. Lassman et al. 10.1029/2022JD037062
80. Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models S. Park et al. 10.1016/j.scitotenv.2020.136516
81. Review of surface particulate monitoring of dust events using geostationary satellite remote sensing M. Sowden et al. 10.1016/j.atmosenv.2018.04.020
82. Modeling atmospheric brown carbon in the GISS ModelE Earth system model M. DeLessio et al. 10.5194/acp-24-6275-2024
83. Investigation of CATS aerosol products and application toward global diurnal variation of aerosols L. Lee et al. 10.5194/acp-19-12687-2019
84. Earth-Observation-Based Estimation and Forecasting of Particulate Matter Impact on Solar Energy in Egypt P. Kosmopoulos et al. 10.3390/rs10121870
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87. Bias induced by the AOD representation time scale in long-term solar radiation calculations. Part 2: Impact on long-term solar irradiance predictions J. Ruiz-Arias et al. 10.1016/j.solener.2016.06.017
88. Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites A. Dadashi-Roudbari & M. Ahmadi 10.1007/s12517-020-5232-0
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118. Residential energy use emissions dominate health impacts from exposure to ambient particulate matter in India L. Conibear et al. 10.1038/s41467-018-02986-7
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126. Studying the Impact on Urban Health over the Greater Delta Region in Egypt Due to Aerosol Variability Using Optical Characteristics from Satellite Observations and Ground-Based AERONET Measurements W. Li et al. 10.3390/rs11171998
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135. Long-term validation of MODIS C6 and C6.1 Dark Target aerosol products over China using CARSNET and AERONET H. Che et al. 10.1016/j.chemosphere.2019.06.238
136. Estimation of hourly full-coverage PM2.5 concentrations at 1-km resolution in China using a two-stage random forest model T. Jiang et al. 10.1016/j.atmosres.2020.105146
137. A novel method of identifying and analysing oil smoke plumes based on MODIS and CALIPSO satellite data A. Mereuţă et al. 10.5194/acp-22-5071-2022
138. Retrieval of Atmospheric Aerosol Optical Depth From AVHRR Over Land With Global Coverage Using Machine Learning Method X. Tian et al. 10.1109/TGRS.2021.3129853
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150. Comparisons of aerosol types and optical characters over Shouxian Area China observed from ground- and space-based systems X. Deng et al. 10.1364/OE.524152
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685. Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model S. Dong et al. 10.3390/rs15215221
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689. Dust induced radiative perturbations during an episode of long-range dust transport over Delhi, India: a high-resolution regional NWP model study T. Francis et al. 10.1007/s00703-020-00760-3
690. Impacts of climate and synoptic fluctuations on dust storm activity over the Middle East S. Namdari et al. 10.1016/j.atmosenv.2017.11.016
691. Can Forest Fires Be an Important Factor in the Reduction in Solar Power Production in India? U. Dumka et al. 10.3390/rs14030549
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693. Assessment and Improvement of MISR Angstrom Exponent and Single-Scattering Albedo Products Using AERONET Data in China Y. Si et al. 10.3390/rs9070693
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699. Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage G. Gamal et al. 10.3390/su15129362
700. Surface and Atmospheric Driven Variability of the Single‐Layer Urban Canopy Model Under Clear‐Sky Conditions Over London A. Tsiringakis et al. 10.1029/2019JD032167
701. Nonlinearity of the cloud response postpones climate penalty of mitigating air pollution in polluted regions H. Jia & J. Quaas 10.1038/s41558-023-01775-5
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703. Examining Intrinsic Aerosol‐Cloud Interactions in South Asia Through Multiple Satellite Observations Z. Pan et al. 10.1029/2017JD028232
704. High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite I F. Bao et al. 10.1109/TGRS.2016.2568246
705. Comparison of MODIS- and CALIPSO-Derived Temporal Aerosol Optical Depth over Yellow River Basin (China) from 2007 to 2015 Z. Zhang et al. 10.1007/s41748-020-00181-7
706. Aerosol optical properties over Europe: an evaluation of the AQMEII Phase 3 simulations against satellite observations L. Palacios-Peña et al. 10.5194/acp-19-2965-2019
707. Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results L. Mei et al. 10.1016/j.rse.2016.11.015
708. In situ identification of aerosol types in Athens, Greece, based on long-term optical and on online chemical characterization D. Kaskaoutis et al. 10.1016/j.atmosenv.2020.118070
709. New global aerosol fine-mode fraction data over land derived from MODIS satellite retrievals X. Yan et al. 10.1016/j.envpol.2021.116707
710. Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter A. van Donkelaar et al. 10.1289/ehp.1408646
711. Evaluation of MODIS Aerosol Optical Depth and Surface Data Using an Ensemble Modeling Approach to Assess PM2.5 Temporal and Spatial Distributions J. Carmona et al. 10.3390/rs13163102
712. Temporal evolution of aerosols and their extreme events in polluted Asian regions during Terra's 20-year observations Z. Hu et al. 10.1016/j.rse.2021.112541
713. Effects of COVID-19 lockdowns on fine particulate matter concentrations M. Hammer et al. 10.1126/sciadv.abg7670
714. Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data W. Zhang et al. 10.3390/rs10010137
715. Opportunistic experiments to constrain aerosol effective radiative forcing M. Christensen et al. 10.5194/acp-22-641-2022
716. Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci) T. Popp et al. 10.3390/rs8050421
717. The Canadian Optimized Statistical Smoke Exposure Model (Canossem): A Machine Learning Approach to Estimate National Daily Fine Particulate Matter (Pm2.5) Exposure N. Paul et al. 10.2139/ssrn.4098551
718. The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluation S. Callewaert et al. 10.5194/amt-12-3673-2019
719. Recent reductions in aerosol emissions have increased Earth’s energy imbalance Ø. Hodnebrog et al. 10.1038/s43247-024-01324-8
720. Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes A. Sayer et al. 10.5194/amt-10-1425-2017
721. Changes in the shape of cloud ice water content vertical structure due to aerosol variations S. Massie et al. 10.5194/acp-16-6091-2016
722. A comparative time series analysis and modeling of aerosols in the contiguous United States and China X. Li et al. 10.1016/j.scitotenv.2019.07.072
723. Arctic amplification–induced decline in West and South Asia dust warrants stronger antidesertification toward carbon neutrality F. Wang et al. 10.1073/pnas.2317444121
724. The impact of three recent coal-fired power plant closings on Pittsburgh air quality: A natural experiment M. Russell et al. 10.1080/10962247.2016.1170738
725. Comparison of V4 and V3 CALIOP (L3) aerosol products: A global perspective V. Sreekanth & P. Kulkarni 10.1016/j.rsase.2020.100412
726. Comparison of hourly aerosol retrievals from JAXA Himawari/AHI in version 3.0 and a simple customized method W. Xu et al. 10.1038/s41598-020-77948-5
727. Observation and modeling of the historic “Godzilla” African dust intrusion into the Caribbean Basin and the southern US in June 2020 H. Yu et al. 10.5194/acp-21-12359-2021
728. Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak C. Tang et al. 10.1016/j.scitotenv.2023.164456
729. Validation of ESA Sentinel-2 L2A Aerosol Optical Thickness and Columnar Water Vapour during 2017–2018 M. Obregón et al. 10.3390/rs11141649
730. Adapting the Dark Target Algorithm to Advanced MERSI Sensor on the FengYun-3-D Satellite: Retrieval and Validation of Aerosol Optical Depth Over Land S. Jin et al. 10.1109/TGRS.2020.3021021
731. Highly anomalous fire emissions from the 2019–2020 Australian bushfires F. Li et al. 10.1088/2515-7620/ac2e6f
732. Aerosol optical depth retrieval over land from OCEANSAT-2/ OCM- 2 data – A simple physics based approach M. Mehta et al. 10.1016/j.apr.2022.101339
733. Spatial variability of aerosols over Greek archaeological sites using Space-Borne Remote Sensing A. Sakka et al. 10.1016/j.culher.2020.07.001
734. Retrieval and validation of aerosol optical depth using GF-1 WFV cameras data X. Wang et al. 10.1016/j.asr.2019.10.023
735. Retrieval of the Fine-Mode Aerosol Optical Depth over East China Using a Grouped Residual Error Sorting (GRES) Method from Multi-Angle and Polarized Satellite Data Y. Zhang et al. 10.3390/rs10111838
736. Is the Awareness of the Aerosol State Useful in Predicting Enhanced Lightning for Lightning-Producing Storms over Northern Alabama? T. Ren et al. 10.1175/JAMC-D-17-0182.1
737. Enhancing the Applicability of Satellite Remote Sensing for PM2.5 Estimation Using MODIS Deep Blue AOD and Land Use Regression in California, United States H. Lee et al. 10.1021/acs.est.6b01438
738. Infusing satellite data into aerosol forecast for near real-time episode detection and diagnosis in East Asia S. Chen et al. 10.1016/j.scitotenv.2022.158797
739. Radiometric calibration and reflectivity inversion of spaceborne LiDAR X. Huang et al. 10.1364/AO.558017
740. A key study on spatial source distribution of PM2.5 based on the airflow trajectory model C. Wang et al. 10.1080/01431161.2016.1251628
741. Separating emission and meteorological contributions to long-term PM2.5 trends over eastern China during 2000–2018 Q. Xiao et al. 10.5194/acp-21-9475-2021
742. Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future Climate R. Séférian et al. 10.1029/2019MS001791
743. Increased aerosol content in the atmosphere over Ukraine during summer 2010 E. Galytska et al. 10.5194/amt-11-2101-2018
744. On the Use of CALIPSO Land Surface Returns to Retrieve Aerosol and Cloud Optical Depths D. Josset et al. 10.1109/TGRS.2018.2796850
745. Estimating the effective spatial resolution of the operational BRDF, albedo, and nadir reflectance products from MODIS and VIIRS M. Campagnolo et al. 10.1016/j.rse.2015.12.033
746. Estimation of ultrahigh resolution PM2.5 concentrations in urban areas using 160 m Gaofen-1 AOD retrievals T. Zhang et al. 10.1016/j.rse.2018.06.030
747. Model-enforced post-process correction of satellite aerosol retrievals A. Lipponen et al. 10.5194/amt-14-2981-2021
748. Satellite Aerosol Optical Depth Retrieval Based on Fully Connected Neural Network (FCNN) and a Combine Algorithm of Simplified Aerosol Retrieval Algorithm and Simplified and Robust Surface Reflectance Estimation (SREMARA) Y. Fan & L. Sun 10.1109/JSTARS.2023.3281777
749. Evaluation of the AVHRR DeepBlue aerosol optical depth dataset over mainland China Y. Che et al. 10.1016/j.isprsjprs.2018.09.004
750. Two decades of aerosol observations by AATSR, MISR, MODIS and MERRA-2 over India and Indian Ocean J. Kuttippurath & S. Raj 10.1016/j.rse.2021.112363
751. Estimation of particulate matter concentrations in Türkiye using a random forest model based on satellite AOD retrievals G. Tuna Tuygun & T. Elbir 10.1007/s00477-023-02459-4
752. The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition J. Belle et al. 10.3390/ijerph14101244
753. A Decade of Aerosol Optical Properties Measurements over Athens, Greece I. Raptis et al. 10.3390/atmos11020154
754. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. 10.1029/2018JD028989
755. A review of biomass burning: Emissions and impacts on air quality, health and climate in China J. Chen et al. 10.1016/j.scitotenv.2016.11.025
756. Forecasting dust impact on solar energy using remote sensing and modeling techniques A. Masoom et al. 10.1016/j.solener.2021.09.033
757. Retrieval of Aerosol Optical Depth over Arid Areas from MODIS Data X. Tian & L. Sun 10.3390/atmos7100134
758. Spatiotemporal aerosol prediction model based on fusion of machine learning and spatial analysis K. Lee et al. 10.1007/s44273-024-00031-2
759. Global maps of aerosol single scattering albedo using combined CERES-MODIS retrieval A. Devi & S. Satheesh 10.5194/acp-22-5365-2022
760. Long-term trends in air quality in major cities in the UK and India: a view from space K. Vohra et al. 10.5194/acp-21-6275-2021
761. 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
762. Assessment of the Coupled Model Intercomparison Project phase 6 (CMIP6) Model performance in simulating the spatial-temporal variation of aerosol optical depth over Eastern Central China X. Li et al. 10.1016/j.atmosres.2021.105747
763. Interdecadal variation in aerosol optical properties and their relationships to meteorological parameters over northeast China from 1980 to 2017 H. Zhao et al. 10.1016/j.chemosphere.2019.125737
764. Long-term three-dimensional distribution and transport of Saharan dust: Observation from CALIPSO, MODIS, and reanalysis data A. Merdji et al. 10.1016/j.atmosres.2023.106658
765. Remote sensing and model analysis of biomass burning smoke transported across the Atlantic during the 2020 Western US wildfire season X. Ceamanos et al. 10.1038/s41598-023-39312-1
766. The interactive global fire module pyrE (v1.0) K. Mezuman et al. 10.5194/gmd-13-3091-2020
767. Characterizing Weekly Cycles of Particulate Matter in a Coastal Megacity: The Importance of a Seasonal, Size‐Resolved, and Chemically Speciated Analysis M. Hilario et al. 10.1029/2020JD032614
768. Spatiotemporal Distribution of Major Aerosol Types over China Based on MODIS Products between 2008 and 2017 Q. Chen et al. 10.3390/atmos11070703
769. GOCI-II geostationary satellite hourly aerosol optical depth obtained by data-driven methods: Validation and comparison Y. Fan et al. 10.1016/j.atmosenv.2023.119965
770. Estimating ground-level PM2.5 concentrations over three megalopolises in China using satellite-derived aerosol optical depth measurements Y. Zheng et al. 10.1016/j.atmosenv.2015.06.046
771. Chemically specific sampling bias: the ratio of PM2.5 to surface AOD on average and peak days in the U.S. S. Rosanka et al. 10.1039/D3EA00163F
772. Estimating ground-level particulate matter concentrations using satellite-based data: a review M. Shin et al. 10.1080/15481603.2019.1703288
773. Importance of Bias Correction in Data Assimilation of Multiple Observations Over Eastern China Using WRF‐Chem/DART C. Ma et al. 10.1029/2019JD031465
774. A global perspective on CO2 satellite observations in high AOD conditions T. Virtanen et al. 10.5194/amt-18-929-2025
775. Improving the understanding between climate variability and observed extremes of global NO2 over the past 15 years W. Deng et al. 10.1088/1748-9326/abd502
776. Decadal evaluation of regional climate, air quality, and their interactions over the continental US and their interactions using WRF/Chem version 3.6.1 K. Yahya et al. 10.5194/gmd-9-671-2016
777. Can MODIS detect trends in aerosol optical depth over land? X. Fan et al. 10.1007/s00376-017-7017-2
778. 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
779. Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China L. Yang et al. 10.3390/rs14081935
780. Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties F. Bender et al. 10.16993/tellusb.1868
781. Evaluation of Terra-MODIS C6 and C6.1 Aerosol Products against Beijing, XiangHe, and Xinglong AERONET Sites in China during 2004-2014 M. Bilal et al. 10.3390/rs11050486
782. Investigation of Aerosol Climatology, Optical Characteristics and Variability over Egypt Based on Satellite Observations and In-Situ Measurements I. Abou El-Magd et al. 10.3390/atmos11070714
783. Identification of dust aerosols, their sources, and the effect of soil moisture in Central Asia J. Liu et al. 10.1016/j.scitotenv.2023.161575
784. A generalized land surface reflectance reconstruction method for aerosol retrieval: Application to the Particulate Observing Scanning Polarimeter (POSP) onboard GaoFen-5 (02) satellite Z. Shi et al. 10.1016/j.rse.2023.113683
785. Satellite-Based Optimization and Planning of Urban Ventilation Corridors for a Healthy Microclimate Environment D. Gong et al. 10.3390/su152115653
786. Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017) L. Sogacheva et al. 10.5194/acp-18-11389-2018
787. Preliminary Retrieval and Validation of Aerosol Optical Depths from FY-4B Advanced Geostationary Radiation Imager Images D. Zhou et al. 10.3390/rs16020372
788. Aerosol retrieval algorithm based on adaptive land–atmospheric decoupling for polarized remote sensing over land surfaces H. Wang et al. 10.1016/j.jqsrt.2018.08.011
789. National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD W. You et al. 10.3390/rs8030184
790. Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua M. Filonchyk et al. 10.1016/j.gsf.2020.03.014
791. Potential responses of vegetation to atmospheric aerosols in arid and semi-arid regions of Asia L. Jiao et al. 10.1007/s40333-021-0005-5
792. Evaluation of biomass burning aerosols in the HadGEM3 climate model with observations from the SAMBBA field campaign B. Johnson et al. 10.5194/acp-16-14657-2016
793. Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM2.5 Using a Random Forest Approach J. Handschuh et al. 10.3390/rs15082064
794. Estimation and Validation of Collection 6 Moderate Resolution Imaging Spectroradiometer Aerosol Products for East Asia K. Lee 10.5572/ajae.2018.12.3.193
795. Spatial-Temporal Variation of AOD Based on MAIAC AOD in East Asia from 2011 to 2020 P. Wang et al. 10.3390/atmos13121983
796. Evaluation of the NDVI-Based Pixel Selection Criteria of the MODIS C6 Dark Target and Deep Blue Combined Aerosol Product M. Bilal & J. Nichol 10.1109/JSTARS.2017.2693289
797. Variability in the correlation between satellite-derived liquid cloud droplet effective radius and aerosol index over the northern Pacific Ocean S. Tan et al. 10.1080/16000889.2017.1391656
798. The impact of resolution on meteorological, chemical and aerosol properties in regional simulations with WRF-Chem P. Crippa et al. 10.5194/acp-17-1511-2017
799. Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions D. Pérez-Ramírez et al. 10.1016/j.atmosres.2018.09.007
800. Radiative Impacts of Aerosols During COVID-19 Lockdown Period Over the Indian Region R. Bhawar et al. 10.3389/fenvs.2021.746090
801. Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation X. Li et al. 10.1016/j.jclepro.2019.03.121
802. 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
803. Improving XCO2 retrieval under high aerosol loads with fused satellite aerosol Data: Advancing understanding of anthropogenic emissions H. Zhu et al. 10.1016/j.isprsjprs.2025.03.009
804. Investigating the Spatial and Temporal Limitations for Remote Sensing of Wildfire Smoke Using Satellite and Airborne Imagers During FIREX‐AQ Y. Shi et al. 10.1029/2023JD039085
805. A Comprehensive Machine and Deep Learning Approach for Aerosol Optical Depth Forecasting: New Evidence from the Arabian Peninsula A. Alban et al. 10.1007/s41748-024-00398-w
806. A satellite-measured view of aerosol component content and optical property in a haze-polluted case over North China Plain L. Li et al. 10.1016/j.atmosres.2021.105958
807. Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign P. Gupta et al. 10.5194/amt-12-6557-2019
808. A hybrid method for reconstructing the historical evolution of aerosol optical depth from sunshine duration measurements W. Wandji Nyamsi et al. 10.5194/amt-13-3061-2020
809. Variability of mineral dust deposition in the western Mediterranean basin and south-east of France J. Vincent et al. 10.5194/acp-16-8749-2016
810. Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach T. Li et al. 10.1002/2017GL075710
811. Evaluation of WRF-Chem-RTFDDA dust forecasts over the MENA region using in-situ and remote-sensing observations D. Rostkier-Edelstein et al. 10.3389/fenvs.2022.981852
812. Study of optical scattering properties and direct radiative effects of high-altitude cirrus clouds in Barcelona, Spain, with 4 years of lidar measurements C. Gil-Díaz et al. 10.5194/acp-25-3445-2025
813. Statistics and Meteorology of Air Pollution Episodes over the South African Highveld Based on Satellite–Model Datasets M. Jury 10.1175/JAMC-D-16-0354.1
814. Long-term Changes in Solar Radiation in Northern Eurasia during the Warm Season According to Measurements and Reconstruction Model E. Volpert & N. Chubarova 10.3103/S1068373921080021
815. ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set A. Gkikas et al. 10.5194/amt-14-309-2021
816. Spaceborne observations of aerosol vertical distribution over Indian mainland (2009–2018) M. Mehta et al. 10.1016/j.atmosenv.2020.117902
817. Effects of COVID-19 pandemic lockdown: A satellite data-based appraisal of air quality in Guwahati, Assam J. Biswas & B. Pathak 10.1016/j.matpr.2022.06.218
818. Landscape determinants of spatio-temporal patterns of aerosol optical depth in the two most polluted metropolitans in the United States C. Wang et al. 10.1016/j.scitotenv.2017.07.273
819. Technical note: Constraining the hydroxyl (OH) radical in the tropics with satellite observations of its drivers – first steps toward assessing the feasibility of a global observation strategy D. Anderson et al. 10.5194/acp-23-6319-2023
820. Spatiotemporal variability of aerosol-cloud interactions in Northwestern Pacific and impact on NPP X. Qiu et al. 10.1016/j.atmosenv.2025.121151
821. Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models J. Yeom et al. 10.1109/TGRS.2021.3107542
822. An exploratory study on the aerosol height retrieval from OMI measurements of the 477  nm O2 − O2 spectral band using a neural network approach J. Chimot et al. 10.5194/amt-10-783-2017
823. CALIOP-Based Quantification of Central Asian Dust Transport Y. Han et al. 10.3390/rs14061416
824. Spatial and seasonal variations in atmospheric aerosols over Nigeria: Assessment of influence of intertropical discontinuity movement A. Ayanlade et al. 10.1177/1759313118820306
825. 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
826. Continental aerosol properties and absorption retrieval using random forest machine learning method specific to geostationary remote sensing F. Bao et al. 10.1016/j.rse.2024.114275
827. Spatio-temporal variations in fine particulate matter and evaluation of associated health risk over Pakistan A. Mariam et al. 10.1002/ieam.4446
828. Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS G. Wind et al. 10.5194/gmd-15-1-2022
829. Evaluation and utilization of MODIS and CALIPSO aerosol retrievals over a complex terrain in Himalaya A. Kumar et al. 10.1016/j.rse.2017.12.019
830. Impact of atmospheric circulation types on southwest Asian dust and Indian summer monsoon rainfall D. Kaskaoutis et al. 10.1016/j.atmosres.2017.11.002
831. Impacts of Sun Glint Off Ice Clouds on DSCOVR EPIC Cloud Products T. Várnai et al. 10.1109/TGRS.2024.3400253
832. Implications of MODIS bow-tie distortion on aerosol optical depth retrievals, and techniques for mitigation A. Sayer et al. 10.5194/amt-8-5277-2015
833. The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data Y. Wu et al. 10.3390/rs8090765
834. SI-traceable solar irradiance measurements for aerosol optical depth retrieval N. Kouremeti et al. 10.1088/1681-7575/ac6cbb
835. The regime of aerosol asymmetry parameter over Europe, the Mediterranean and the Middle East based on MODIS satellite data: evaluation against surface AERONET measurements M. Korras-Carraca et al. 10.5194/acp-15-13113-2015
836. Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh A. Gupta et al. 10.1007/s42452-020-03829-1
837. Long-term aerosol optical depth trend over Iran and identification of dominant aerosol types R. Yousefi et al. 10.1016/j.scitotenv.2020.137906
838. High-Resolution Satellite-Based PM2.5 Concentration Data Acquired During the COVID-19 Outbreak Throughout China: Model, Variations, and Reasons H. Guo et al. 10.1109/JSTARS.2021.3119383
839. SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
840. Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China Y. Che et al. 10.5194/acp-16-9655-2016
841. Global validation and comparison of MODIS DT and POLDER-3 GRASP aerosol products over ocean X. Pei et al. 10.1016/j.atmosres.2022.106480
842. Global and regional evaluation of a global model simulated AODs with AERONET and MODIS observations V. Sheel et al. 10.1002/joc.5367
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844. A critical view of long-term AVHRR aerosol data record in China: Retrieval frequency and heavy pollution M. Tao et al. 10.1016/j.atmosenv.2019.117246
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878. Climatology of the aerosol optical depth by components from the Multi-angle Imaging SpectroRadiometer (MISR) and chemistry transport models H. Lee et al. 10.5194/acp-16-6627-2016
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948. The impact of using assimilated Aeolus wind data on regional WRF-Chem dust simulations P. Kiriakidis et al. 10.5194/acp-23-4391-2023
949. The Tibetan Plateau as dust aerosol transit station in middle troposphere over northern East Asia: A case study J. Cao & S. Chen 10.1016/j.atmosres.2022.106416
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952. California wildfire smoke contributes to a positive atmospheric temperature anomaly over the western United States J. Gomez et al. 10.5194/acp-24-6937-2024
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969. Characteristics of Ethiopia Air Chemistry and Its Meteorological Context M. Jury 10.1175/EI-D-17-0009.1
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987. Dust impact on surface solar irradiance assessed with model simulations, satellite observations and ground-based measurements P. Kosmopoulos et al. 10.5194/amt-10-2435-2017
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989. Dust Activities Induced by Nocturnal Low‐Level Jet Over the Taklimakan Desert From WRF‐Chem Simulation Z. Han et al. 10.1029/2021JD036114
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999. Forest-fire aerosol–weather feedbacks over western North America using a high-resolution, online coupled air-quality model P. Makar et al. 10.5194/acp-21-10557-2021
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1351. Comprehensive Evaluation of Spatial Distribution and Temporal Trend of NO2, SO2 and AOD Using Satellite Observations over South and East Asia from 2011 to 2021 M. Rahman et al. 10.3390/rs15205069
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1353. Satellite Remote Sensing for Estimating PM2.5 and Its Components Y. Li et al. 10.1007/s40726-020-00170-4
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1365. Exploring the effect of waterbodies coupled with other environmental parameters to model PM2.5 over Delhi-NCT in northwest India B. Gayen et al. 10.1016/j.apr.2022.101614
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1368. Multi-dimensional satellite observations of aerosol properties and aerosol types over three major urban clusters in eastern China Y. Liu et al. 10.5194/acp-21-12331-2021
1369. Characterisation of dust aerosols and their absorbing efficiency over South Asia using infrared observations from INSAT-3D Imager C. Lima et al. 10.1080/01431161.2024.2431176
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1376. Multi-Sensor Retrieval of Aerosol Optical Properties for Near-Real-Time Applications Using the Metop Series of Satellites: Concept, Detailed Description, and First Validation M. Grzegorski et al. 10.3390/rs14010085
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1388. Dust emission and transport in Northwest China: WRF-Chem simulation and comparisons with multi-sensor observations J. Zhao et al. 10.1016/j.atmosres.2020.104978
1389. Surface Reflectance and Aerosol Retrieval from SPOT-VGT and PROBA-V in the Mission Exploitation Platform Environment M. Luffarelli et al. 10.3390/rs15215109
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1393. Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China X. Tian et al. 10.3390/rs10020197
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1401. Satellite-derived spatiotemporal PM2.5 concentrations and variations from 2006 to 2017 in China W. Xue et al. 10.1016/j.scitotenv.2019.134577
1402. A review of statistical methods used for developing large-scale and long-term PM2.5 models from satellite data Z. Ma et al. 10.1016/j.rse.2021.112827
1403. Development of an Ozone Monitoring Instrument (OMI) aerosol index (AI) data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum J. Zhang et al. 10.5194/gmd-14-27-2021
1404. Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances R. Houborg & M. McCabe 10.1016/j.rse.2017.03.013
1405. Accuracy assessment of MODIS land aerosol optical thickness algorithms using AERONET measurements over North America H. Jethva et al. 10.5194/amt-12-4291-2019
1406. Towards long-term, high-accuracy, and continuous satellite total and fine-mode aerosol records: Enhanced Land General Aerosol (e-LaGA) retrieval algorithm for VIIRS L. Wang et al. 10.1016/j.isprsjprs.2024.06.022
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1409. Lower tropospheric ozone over the North China Plain: variability and trends revealed by IASI satellite observations for 2008–2016 G. Dufour et al. 10.5194/acp-18-16439-2018
1410. Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion G. Geng et al. 10.1021/acs.est.1c01863
1411. Analysis of Atmospheric Aerosol Optical Properties in the Northeast Brazilian Atmosphere with Remote Sensing Data from MODIS and CALIOP/CALIPSO Satellites, AERONET Photometers and a Ground-Based Lidar A. de Oliveira et al. 10.3390/atmos10100594
1412. Decreased dust particles amplify the cloud cooling effect by regulating cloud ice formation over the Tibetan Plateau J. Chen et al. 10.1126/sciadv.ado0885
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1414. Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. 10.5194/essd-16-443-2024
1415. Analysis and Validation of the Aerosol Optical Depth of MODIS Products in Gansu Province, Northwest China F. Huang et al. 10.3390/rs15122972
1416. Impact of California Fires on Local and Regional Air Quality: The Role of a Low‐Cost Sensor Network and Satellite Observations P. Gupta et al. 10.1029/2018GH000136
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1420. Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al. 10.1016/j.atmosenv.2023.119916
1421. Spatial downscaling of surface ozone concentration calculation from remotely sensed data based on mutual information X. Wang et al. 10.3389/fenvs.2022.925979
1422. A Decadal Data Set of Global Atmospheric Dust Retrieved From IASI Satellite Measurements L. Clarisse et al. 10.1029/2018JD029701
1423. The Sub-Daily Variability of Aerosol Loading and Associated Radiative Forcing Over the Indian Region T. Mukherjee & V. Vinoj 10.3389/feart.2021.727169
1424. PM2.5 mapping using integrated geographically temporally weighted regression (GTWR) and random sample consensus (RANSAC) models H. Chu & M. Bilal 10.1007/s11356-018-3763-7
1425. Long-term study of desert dust deposition effects on phytoplankton biomass in the Persian Gulf using Google Earth Engine H. Asgari & A. Soleimany 10.1016/j.marpolbul.2023.115564
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1427. An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data Q. Xiao et al. 10.1021/acs.est.8b02917
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1429. High resolution aerosol optical depth retrieval over urban areas from Landsat-8 OLI images H. Lin et al. 10.1016/j.atmosenv.2021.118591
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1431. A study of 15-year aerosol optical thickness and direct shortwave aerosol radiative effect trends using MODIS, MISR, CALIOP and CERES R. Alfaro-Contreras et al. 10.5194/acp-17-13849-2017
1432. Large contrast in the vertical distribution of aerosol optical properties and radiative effects across the Indo-Gangetic Plain during the SWAAMI–RAWEX campaign A. Vaishya et al. 10.5194/acp-18-17669-2018
1433. Can We Detect the Brownness or Greenness of the Congo Rainforest Using Satellite-Derived Surface Albedo? A Study on the Role of Aerosol Uncertainties S. Moparthy et al. 10.3390/su11051410
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1435. Top-of-atmosphere hyper and multispectral signatures of submerged plastic litter with changing water clarity and depth S. Garaba & T. Harmel 10.1364/OE.451415
1436. A New Chemistry-Climate Model GRIMs-CCM: Model Evaluation of Interactive Chemistry-Meteorology Simulations S. Lee et al. 10.1007/s13143-022-00281-6
1437. Impact of mineral dust photocatalytic heterogeneous chemistry on the formation of the sulfate and nitrate: A modelling study over East Asia X. Li et al. 10.1016/j.atmosenv.2023.120166
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1448. Satellites See the World’s Atmosphere S. Ackerman et al. 10.1175/AMSMONOGRAPHS-D-18-0009.1
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1452. Multiconstituent Data Assimilation With WRF‐Chem/DART: Potential for Adjusting Anthropogenic Emissions and Improving Air Quality Forecasts Over Eastern China C. Ma et al. 10.1029/2019JD030421
1453. Transport of aerosols over the French Riviera – link between ground-based lidar and spaceborne observations P. Chazette et al. 10.5194/acp-19-3885-2019
1454. Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends P. Colarco et al. 10.5194/amt-7-2313-2014
1455. The Evaluation of the North Atlantic Climate System in UKESM1 Historical Simulations for CMIP6 J. Robson et al. 10.1029/2020MS002126
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1457. April 2008 Saharan dust event: Its contribution to PM10 concentrations over the Anatolian Peninsula and relation with synoptic conditions B. Kabatas et al. 10.1016/j.scitotenv.2018.03.150
1458. Description and evaluation of the tropospheric aerosol scheme in the Integrated Forecasting System (IFS-AER, cycle 47R1) of ECMWF S. Rémy et al. 10.5194/gmd-15-4881-2022
1459. Evaluating Aerosol Optical Depth From Himawari‐8 With Sun Photometer Network W. Wang et al. 10.1029/2018JD028599
1460. Assimilation and Forecasting Experiment for Heavy Siberian Wildfire Smoke in May 2016 with Himawari-8 Aerosol Optical Thickness K. YUMIMOTO et al. 10.2151/jmsj.2018-035
1461. Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea W. Li et al. 10.3390/rs9080778
1462. Improved estimation of fire particulate emissions using a combination of VIIRS and AHI data for Indonesia during 2015–2020 X. Lu et al. 10.1016/j.rse.2022.113238
1463. Decadal variations in natural and anthropogenic aerosol optical depth over the Bay of Bengal: the influence of pollutants from Indo-GangeticPlain K. Yadav et al. 10.1007/s11356-021-14703-x
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1465. Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites A. Naeger et al. 10.5194/amt-9-2463-2016
1466. Aerosol Optical Depth over the Andhra Pradesh State in South India from Reanalysis Data: Spatiotemporal Variabilities and Machine Learning Approach P. Althaf et al. 10.1007/s41748-024-00465-2
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1468. Screening for snow/snowmelt in SNPP VIIRS aerosol optical depth algorithm J. Huang et al. 10.5194/amt-11-5813-2018
1469. Leveraging spatial textures, through machine learning, to identify aerosols and distinct cloud types from multispectral observations W. Marais et al. 10.5194/amt-13-5459-2020
1470. Evaluation of MODIS and two reanalysis aerosol optical depth products over AERONET sites H. Shi et al. 10.1016/j.atmosres.2019.01.009
1471. Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons T. Zhao et al. 10.1021/acsestair.4c00120
1472. Validation and Accuracy Assessment of MODIS C6.1 Aerosol Products over the Heavy Aerosol Loading Area X. Tian & Z. Gao 10.3390/atmos10090548
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1474. Simulating and Evaluating Global Aerosol Distributions With the Online Aerosol‐Coupled CAS‐FGOALS Model H. Wang et al. 10.1029/2019JD032097
1475. AOD Derivation from SDGSAT-1/GLI Dataset in Mega-City Area N. Wang et al. 10.3390/rs15051343
1476. Recent Increase in Winter Hazy Days over Central India and the Arabian Sea A. Thomas et al. 10.1038/s41598-019-53630-3
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1478. Impact of satellite AOD data on top-down estimation of biomass burning particulate matter emission X. Ye et al. 10.1016/j.scitotenv.2022.161055
1479. Using Multi-Platform Satellite Observations to Study the Atmospheric Evolution of Brown Carbon in Siberian Biomass Burning Plumes I. Konovalov et al. 10.3390/rs14112625
1480. Use of A Neural Network-Based Ocean Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle Polarimetric Measurements C. Fan et al. 10.3390/rs11232877
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1482. Differences between the MODIS Collection 6 and 5.1 aerosol datasets over the greater Mediterranean region A. Georgoulias et al. 10.1016/j.atmosenv.2016.10.014
1483. Research agenda for the Russian Far East and utilization of multi-platform comprehensive environmental observations T. Petäjä et al. 10.1080/17538947.2020.1826589
1484. Impact of vegetation greening on TOA clear-sky shortwave radiation in Northwest India M. Mishra et al. 10.1007/s00382-024-07321-z
1485. Regional sulfate drives long-term rise in AOD over megacity Kolkata, India P. Rawat et al. 10.1016/j.atmosenv.2019.04.031
1486. Pollution Trends in China from 2000 to 2017: A Multi-Sensor View from Space J. Li 10.3390/rs12020208
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1488. Investigating the applicability of a simple iterative approach for aerosol optical depth (AOD) retrieval over diverse land surface types from Landsat 8 and Sentinel 2 using visible and near-infrared (VNIR) spectral bands A. Kumar & M. Mehta 10.1016/j.atmosenv.2023.120082
1489. MODIS high-resolution MAIAC aerosol product: Global validation and analysis W. Qin et al. 10.1016/j.atmosenv.2021.118684
1490. An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India J. Singh et al. 10.1007/s10661-022-10573-z
1491. Which dual-band infrared indices are optimum for identifying aerosol compositional change using Himawari-8 data? M. Sowden & D. Blake 10.1016/j.atmosenv.2020.117620
1492. Validation of POLDER-3/GRASP aerosol products using AERONET measurements over China Y. Tan et al. 10.1016/j.atmosenv.2019.116893
1493. An Evaluation of MODIS-Retrieved Aerosol Optical Depth over AERONET Sites in Alaska A. McPhetres & S. Aggarwal 10.3390/rs10091384
1494. Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product M. Garay et al. 10.5194/amt-13-593-2020
1495. Numerical study of aerosol radiative forcing over East Asia and the impacts of cloud coverage and relative humidity J. Guo et al. 10.1016/j.atmosres.2022.106168
1496. Anthropogenic aerosol emissions mapping and characterization by imaging spectroscopy – application to a metallurgical industry and a petrochemical complex Y. Philippets et al. 10.1080/01431161.2018.1513665
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