299 citations as recorded by crossref.

1. Assessment of aerosol burden over Ghana K. Fosu-Amankwah et al. 10.1016/j.sciaf.2021.e00971
2. Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China C. Zhang et al. 10.3390/atmos10020046
3. Estimating the daily PM2.5 concentration in the Beijing-Tianjin-Hebei region using a random forest model with a 0.01° × 0.01° spatial resolution C. Zhao et al. 10.1016/j.envint.2019.105297
4. Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research J. le Roux et al. 10.3390/rs13152981
5. Improving the accuracy of AOD by using multi-sensors data over the Red Sea and the Persian Gulf M. Pashayi et al. 10.1016/j.apr.2023.101948
6. Evaluation of MODIS aerosol retrieval algorithms over the Beijing‐Tianjin‐Hebei region during low to very high pollution events M. Bilal & J. Nichol 10.1002/2015JD023082
7. Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. 10.3390/rs13061096
8. Ozone depletion and climate change: impacts on UV radiation A. Bais et al. 10.1039/c4pp90032d
9. MODIS Collection 6.1 3 km resolution aerosol optical depth product: global evaluation and uncertainty analysis J. Wei et al. 10.1016/j.atmosenv.2020.117768
10. Improving Satellite-Driven PM2.5 Models with VIIRS Nighttime Light Data in the Beijing–Tianjin–Hebei Region, China X. Zhang & H. Hu 10.3390/rs9090908
11. Evaluation and Comparison of Long-Term MODIS C5.1 and C6 Products against AERONET Observations over China A. Fan et al. 10.3390/rs9121269
12. Prediction and spatio – Temporal analysis of ozone concentration in a metropolitan area K. Ezimand & A. Kakroodi 10.1016/j.ecolind.2019.04.059
13. Accounting for 3D radiative effects in MODIS aerosol retrievals near clouds using CALIPSO observations G. Wen et al. 10.3389/frsen.2023.1333814
14. 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
15. Trends and classification of aerosol observed from MODIS sensor over Northern Europe and the Arctic K. Han et al. 10.1016/j.apr.2024.102329
16. Spatiotemporal patterns of aerosol optical depth throughout China from 2003 to 2016 Q. He et al. 10.1016/j.scitotenv.2018.10.307
17. Retrievals of aerosol optical depth over the western North Atlantic Ocean during ACTIVATE L. Siu et al. 10.5194/amt-17-2739-2024
18. Variation of the aerosol optical properties and validation of MODIS AOD products over the eastern edge of the Tibetan Plateau based on ground-based remote sensing in 2017 Y. You et al. 10.1016/j.atmosenv.2019.117257
19. A critical assessment of high-resolution aerosol optical depth retrievals for fine particulate matter predictions A. Chudnovsky et al. 10.5194/acp-13-10907-2013
20. Pre-seismic anomalies from optical satellite observations: a review Z. Jiao et al. 10.5194/nhess-18-1013-2018
21. Evaluation of the MODIS Collection 6.1 3 km aerosol optical depth product over China M. Zhang et al. 10.1016/j.atmosenv.2022.118970
22. Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India V. Sharma et al. 10.2478/jlecol-2022-0019
23. Influence of Spatial Resolution and Retrieval Frequency on Applicability of Satellite-Predicted PM2.5 in Northern China R. Li et al. 10.3390/rs12040736
24. The Influence of Underlying Land Cover on the Accuracy of MODIS C6.1 Aerosol Products—A Case Study over the Yangtze River Delta Region of China K. Sun et al. 10.3390/rs14040938
25. Observations of rapid aerosol optical depth enhancements in the vicinity of polluted cumulus clouds T. Eck et al. 10.5194/acp-14-11633-2014
26. Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China M. Ali et al. 10.1016/j.gsf.2021.101325
27. 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
28. Validation of Aerosol Products from AATSR and MERIS/AATSR Synergy Algorithms—Part 1: Global Evaluation Y. Che et al. 10.3390/rs10091414
29. 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
30. Validation of MODIS-Aqua Aerosol Products C051 and C006 over the Beijing-Tianjin-Hebei Region K. Wang et al. 10.3390/atmos8090172
31. Quantifying urban air quality through multispectral satellite imagery and Google earth Engine F. Aghdam et al. 10.1016/j.jastp.2024.106301
32. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing W. Chen et al. 10.3390/rs9050496
33. Validation of MODIS C6 Dark Target Aerosol Products at 3 km and 10 km Spatial Resolutions Over the China Seas and the Eastern Indian Ocean X. Shen et al. 10.3390/rs10040573
34. Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia A. Mhawish et al. 10.1016/j.rse.2019.01.033
35. Retrieval and validation of aerosol optical depth using GF-1 WFV cameras data X. Wang et al. 10.1016/j.asr.2019.10.023
36. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
37. Comparison of MODIS 3 km and 10 km resolution aerosol optical depth retrievals over land with airborne sunphotometer measurements during ARCTAS summer 2008 J. Livingston et al. 10.5194/acp-14-2015-2014
38. Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions P. Gupta et al. 10.5194/amt-11-3145-2018
39. Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin V. Schumacher et al. 10.1016/j.atmosenv.2024.120597
40. MODIS AOD sampling rate and its effect on PM2.5 estimation in North China Z. Song et al. 10.1016/j.atmosenv.2019.04.020
41. Validation of the Atmospheric Boundary Layer Height Estimated from the MODIS Atmospheric Profile Data at an Equatorial Site S. Onyango et al. 10.3390/atmos11090908
42. The influence and contribution of fine mode particles to aerosol optical properties during haze events at the foothills of Himalaya-Karakorum region S. Mohyuddin et al. 10.1016/j.atmosenv.2022.119388
43. Atmospheric Correction of Multispectral VNIR Remote Sensing Data: Algorithm and Inter‐sensor Comparison of Aerosol and Surface Reflectance Products M. Mishra et al. 10.1029/2019EA000710
44. Measurement and Modelling of Particulate Pollution over Kashmir Himalaya, India M. Bhat et al. 10.1007/s11270-021-05062-x
45. Aerosol Optical Depth Over the Nepalese Cryosphere Derived From an Empirical Model B. Bhattarai et al. 10.3389/feart.2019.00178
46. Information et comportement d'évitement: effets de la publication de données relatives à la pollution de l'air sur l'offre de travail en Chine Y. SHEN & W. SUN 10.1111/ilrf.12293
47. Himawari-8/AHI and MODIS Aerosol Optical Depths in China: Evaluation and Comparison T. Jiang et al. 10.3390/rs11091011
48. Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia N. Zaman et al. 10.3390/app11167326
49. Retrieval of High-Resolution Aerosol Optical Depth for Urban Air Pollution Monitoring R. Bai et al. 10.3390/atmos13050756
50. Spatial Variation and Relation of Aerosol Optical Depth with LULC and Spectral Indices V. Sharma et al. 10.3390/atmos13121992
51. Ambient PM 2.5 exposure and premature mortality burden in the holy city Varanasi, India V. Jain et al. 10.1016/j.envpol.2017.04.028
52. Radiative response of biomass-burning aerosols over an urban atmosphere in northern peninsular Southeast Asia S. Pani et al. 10.1016/j.scitotenv.2018.03.204
53. 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
54. Retrieval of Daily PM2.5 Concentrations Using Nonlinear Methods: A Case Study of the Beijing–Tianjin–Hebei Region, China L. Li et al. 10.3390/rs10122006
55. Effects of Monsoon, Shamal and Levar winds on dust accumulation over the Arabian Sea during summer – The July 2016 case A. Rashki et al. 10.1016/j.aeolia.2018.11.002
56. 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
57. Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results L. Mei et al. 10.1016/j.rse.2016.11.015
58. Joint retrieval of the aerosol fine mode fraction and optical depth using MODIS spectral reflectance over northern and eastern China: Artificial neural network method X. Chen et al. 10.1016/j.rse.2020.112006
59. Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21–22 August 2017 A. Ansmann et al. 10.5194/acp-18-11831-2018
60. 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
61. An Improved High‐Spatial‐Resolution Aerosol Retrieval Algorithm for MODIS Images Over Land J. Wei et al. 10.1029/2017JD027795
62. Aerosol optical depth over Northeastern Brazil: A multi-platform intercomparison study G. Münchow et al. 10.1016/j.atmosres.2024.107864
63. Estimating PM 2.5 concentrations in a central region of China using a three-stage model Y. Jing et al. 10.1080/17538947.2023.2175499
64. Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters M. Bilal et al. 10.1016/j.atmosres.2016.11.009
65. Comparison of AOD from CALIPSO, MODIS, and Sun Photometer under Different Conditions over Central China B. Liu et al. 10.1038/s41598-018-28417-7
66. A seasonal analysis of aerosol-cloud-radiation interaction over Indian region during 2000–2017 S. Kant et al. 10.1016/j.atmosenv.2018.12.044
67. Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases M. Bilal et al. 10.1016/j.rse.2021.112617
68. Satellite-based view of the aerosol spatial and temporal variability in the Córdoba region (Argentina) using over ten years of high-resolution data L. Della Ceca et al. 10.1016/j.isprsjprs.2018.08.016
69. Estimating PM1 concentrations from MODIS over Yangtze River Delta of China during 2014–2017 K. Qin et al. 10.1016/j.atmosenv.2018.09.054
70. Improving MODIS Aerosol Estimates Over Land With the Surface BRDF Reflectances Using the 3-D Discrete Cosine Transform and RossThick-LiSparse Models X. Tian et al. 10.1109/TGRS.2020.3048109
71. 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
72. Estimating Regional Ground‐Level PM2.5 Directly From Satellite Top‐Of‐Atmosphere Reflectance Using Deep Belief Networks H. Shen et al. 10.1029/2018JD028759
73. High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS P. Gupta et al. 10.3390/rs12172847
74. Quantifying PM2.5 mass concentration and particle radius using satellite data and an optical-mass conversion algorithm M. Liu et al. 10.1016/j.isprsjprs.2019.10.010
75. Using the Gaofen-4 geostationary satellite to retrieve aerosols with high spatiotemporal resolution X. Chen et al. 10.1117/1.JRS.12.042606
76. Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships S. Christopher & P. Gupta 10.3390/rs12121985
77. Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM2.5 Using a Random Forest Approach J. Handschuh et al. 10.3390/rs15082064
78. 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
79. Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring S. Ahn et al. 10.3390/s24051490
80. Satellite-based mapping of daily high-resolution ground PM2.5 in China via space-time regression modeling Q. He & B. Huang 10.1016/j.rse.2017.12.018
81. A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model L. El Amraoui et al. 10.3390/rs14081949
82. An improved algorithm for retrieving the fine-mode fraction of aerosol optical thickness, part 1: Algorithm development X. Yan et al. 10.1016/j.rse.2017.02.005
83. A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces J. Wei et al. 10.1002/2017JD026922
84. Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-Tianjin-Hebei Region Based on MODIS AOD and Meteorological Data Using the Back Propagation Neural Network X. Ni et al. 10.3390/atmos9030105
85. Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012 S. Loría-Salazar et al. 10.1016/j.atmosenv.2016.08.070
86. Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period L. Cheng et al. 10.3390/ijerph16193522
87. A global perspective on CO2 satellite observations in high AOD conditions T. Virtanen et al. 10.5194/amt-18-929-2025
88. Evaluating MODIS and MISR aerosol optical depth retrievals over environmentally distinct sites in Pakistan G. Ali et al. 10.1016/j.jastp.2018.12.008
89. High-resolution urban air quality monitoring using sentinel satellite images and low-cost ground-based sensor networks J. Gitahi et al. 10.1051/e3sconf/202017102002
90. 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
91. Using MODIS derived aerosol optical depth to estimate ground-level PM2.5 concentrations over Turkey Ö. Zeydan & Y. Wang 10.1016/j.apr.2019.05.005
92. Long-term validation and error analysis of DB and MAIAC aerosol products over bright surface of China W. Ji et al. 10.1016/j.atmosres.2023.107106
93. Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China N. Liu et al. 10.5194/acp-19-8243-2019
94. Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction Y. Wu et al. 10.5194/amt-9-5575-2016
95. Spatiotemporal mixed effects modeling for the estimation of PM2.5from MODIS AOD over the Indian subcontinent S. Unnithan & L. Gnanappazham 10.1080/15481603.2020.1712101
96. Evaluation of MAIAC aerosol retrievals over China Z. Zhang et al. 10.1016/j.atmosenv.2019.01.013
97. Improvement of spatial-temporal resolution of aerosol profile by using multi-source satellite data over the Persian Gulf M. Pashayi et al. 10.1016/j.atmosenv.2022.119410
98. Simulating aerosols over Arabian Peninsula with CHIMERE: Sensitivity to soil, surface parameters and anthropogenic emission inventories S. Beegum et al. 10.1016/j.atmosenv.2016.01.010
99. Enhanced net CO2 exchange of a semideciduous forest in the southern Amazon due to diffuse radiation from biomass burning S. Rodrigues et al. 10.5194/bg-21-843-2024
100. Properties of aerosols and formation mechanisms over southern China during the monsoon season W. Chen et al. 10.5194/acp-16-13271-2016
101. 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
102. Türkiye’de Terra ve Aqua MODIS Uydularından Elde Edilen Aerosol Optik Derinliğinin Zamansal ve Mekansal Değişimi S. KARSLIOĞLU et al. 10.21205/deufmd.2022247027
103. 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
104. Assessment of aerosol optical and physical properties and implications for radiative effects over the semiarid region of Indo‐Gangetic Basin P. Gupta et al. 10.1002/gj.4857
105. Transboundary transport of biomass burning aerosols and photochemical pollution in the Orinoco River Basin A. Hernandez et al. 10.1016/j.atmosenv.2019.01.051
106. A New MODIS C6 Dark Target and Deep Blue Merged Aerosol Product on a 3 km Spatial Grid M. Bilal et al. 10.3390/rs10030463
107. Satellite-based high-resolution mapping of ground-level PM2.5 concentrations over East China using a spatiotemporal regression kriging model H. Hu et al. 10.1016/j.scitotenv.2019.03.480
108. Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China J. Wu et al. 10.3390/rs11192223
109. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm P. Gupta et al. 10.5194/amt-9-3293-2016
110. Urban heat islands in China enhanced by haze pollution C. Cao et al. 10.1038/ncomms12509
111. 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
112. Study on global atmospheric aerosol type identification from combined satellite and ground observations X. Nie et al. 10.1016/j.atmosenv.2025.121100
113. A new method of satellite-based haze aerosol monitoring over the North China Plain and a comparison with MODIS Collection 6 aerosol products X. Yan et al. 10.1016/j.atmosres.2015.12.003
114. 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
115. A Review on Estimation of Particulate Matter from Satellite-Based Aerosol Optical Depth: Data, Methods, and Challenges A. Ranjan et al. 10.1007/s13143-020-00215-0
116. Collocation mismatch uncertainties in satellite aerosol retrieval validation T. Virtanen et al. 10.5194/amt-11-925-2018
117. Transparencia y conducta de evitación. Efectos de la información ambiental sobre la oferta de trabajo en China Y. SHEN & W. SUN 10.1111/ilrs.12294
118. Study on Vertically Distributed Aerosol Optical Characteristics over Saudi Arabia Using CALIPSO Satellite Data Z. Zhang et al. 10.3390/app12020603
119. Comparison and evaluation of multiple satellite aerosol products over China in different scenarios under a unified criterion: Preparation for consistent and high-quality dataset construction H. Zhu et al. 10.1016/j.atmosres.2022.106374
120. Seasonal monitoring and estimation of regional aerosol distribution over Po valley, northern Italy, using a high-resolution MAIAC product B. Arvani et al. 10.1016/j.atmosenv.2016.06.037
121. Validation of MODIS Aerosol Optical Depth Retrieval over Mountains in Central China Based on a Sun-Sky Radiometer Site of SONET Y. Ma et al. 10.3390/rs8020111
122. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency A. Sayer et al. 10.1002/2015JD023878
123. Multi-Sensor Observation of a Saharan Dust Outbreak over Transylvania, Romania in April 2019 N. Ajtai et al. 10.3390/atmos11040364
124. Application of DIAL/HSRL and CATCH algorithm-based methodologies for surface PM2.5 concentrations during the KORUS-AQ campaign B. Sutherland et al. 10.1016/j.atmosenv.2023.119719
125. Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors A. van Donkelaar et al. 10.1021/acs.est.5b05833
126. SAMIRA-SAtellite Based Monitoring Initiative for Regional Air Quality K. Stebel et al. 10.3390/rs13112219
127. National Civil Space Infrastructure Satellite Aerosol Product Validation Network (SIAVNET) measurements: Supporting satellite aerosol product validation for different surface types over China T. Cheng et al. 10.1016/j.atmosres.2022.106508
128. Near‐Cloud Aerosol Retrieval Using Machine Learning Techniques, and Implied Direct Radiative Effects C. Yang et al. 10.1029/2022GL098274
129. Information and avoidance behaviour: The effect of air pollution disclosure on labour supply in China Y. SHEN & W. SUN 10.1111/ilr.12360
130. An Evaluation of Four MODIS Collection 6 Aerosol Products in a Humid Subtropical Region M. Zhang et al. 10.3390/rs9111173
131. Long-term trends of satellite-based fine-mode aerosol optical depth over the Seto Inland Sea, Japan, over two decades (2001–2020) S. Itahashi et al. 10.1088/1748-9326/ac03db
132. Multisensor and Multimodel Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front Over Eastern China X. Hu et al. 10.1029/2020JD033538
133. Discrimination of Biomass-Burning Smoke From Clouds Over the Ocean Using MODIS Measurements Q. Wang et al. 10.1109/TGRS.2021.3084042
134. Decadal-scale relationship between measurements of aerosols, land-use change, and fire over Southeast Asia J. Cohen et al. 10.5194/acp-17-721-2017
135. Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model Y. Guo et al. 10.1016/j.rse.2017.06.001
136. SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
137. Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data A. Beloconi et al. 10.1016/j.rse.2015.10.017
138. Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China X. Tian et al. 10.3390/rs10020197
139. Differences in fine particle chemical composition on clear and cloudy days A. Christiansen et al. 10.5194/acp-20-11607-2020
140. Retrieval of High Spatial Resolution Aerosol Optical Depth from HJ-1 A/B CCD Data X. Fan & Y. Qu 10.3390/rs11070832
141. Satellite-based ground PM2.5 estimation using a gradient boosting decision tree T. Zhang et al. 10.1016/j.chemosphere.2020.128801
142. MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison J. Wei et al. 10.1016/j.atmosenv.2018.12.004
143. A nonparametric approach to filling gaps in satellite-retrieved aerosol optical depth for estimating ambient PM2.5 levels R. Zhang et al. 10.1016/j.envpol.2018.09.052
144. Spatiotemporal variability of optical properties of aerosols over the Indo-Gangetic Plain during 2011–2015 P. Kumar et al. 10.1007/s12648-020-01987-x
145. Structure of tropical cyclones in the southeast Iran using satellite observations E. Ghasemifar et al. 10.1016/j.jastp.2024.106308
146. SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. 10.3390/rs13050844
147. Evaluation of MODIS and two reanalysis aerosol optical depth products over AERONET sites H. Shi et al. 10.1016/j.atmosres.2019.01.009
148. Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption L. Mei et al. 10.1016/j.atmosres.2019.05.023
149. Evaluation of the Aqua-MODIS C6 and C6.1 Aerosol Optical Depth Products in the Yellow River Basin, China M. Zhang et al. 10.3390/atmos10080426
150. Performance of MODIS C6.1 Dark Target and Deep Blue aerosol products in Delhi National Capital Region, India: Application for aerosol studies V. Sharma et al. 10.1016/j.apr.2021.01.023
151. On the build-up of dust aerosols and possible indirect effect during Indian summer monsoon break spells using recent satellite observations of aerosols and cloud properties V. Arya et al. 10.1007/s12040-020-01526-6
152. High-Resolution Satellite-Derived PM2.5 from Optimal Estimation and Geographically Weighted Regression over North America A. van Donkelaar et al. 10.1021/acs.est.5b02076
153. The Collection 6 MODIS aerosol products over land and ocean R. Levy et al. 10.5194/amt-6-2989-2013
154. Long Temporal Analysis of 3-km MODIS Aerosol Product Over East China Q. Ma et al. 10.1109/JSTARS.2017.2650144
155. Incorporating environmental stress improves estimation of photosynthesis from NIRvP in US Great Plains pasturelands and Midwest croplands L. Gao et al. 10.1016/j.rse.2024.114516
156. Intercomparison of Multiple Satellite Aerosol Products against AERONET over the North China Plain X. Fan et al. 10.3390/atmos10090480
157. An algorithm for retrieving aerosol optical depth from Landsat 8 Operational Land Imager in Vietnam V. Tran Tuan et al. 10.1080/10106049.2023.2228748
158. Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan W. Wang et al. 10.3390/rs9050403
159. A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM2.5 Concentration by Integrating Multisource Datasets Y. Shi et al. 10.3390/ijerph19010321
160. Spatiotemporal Evolution and Prediction of AOT in Coal Resource Cities: A Case Study of Shanxi Province, China Y. Tang et al. 10.3390/su14052498
161. Estimating monthly PM2.5 concentrations from satellite remote sensing data, meteorological variables, and land use data using ensemble statistical modeling and a random forest approach C. Chen et al. 10.1016/j.envpol.2021.118159
162. Performance of the NPP-VIIRS and aqua-MODIS Aerosol Optical Depth Products over the Yangtze River Basin L. He et al. 10.3390/rs10010117
163. Gap-filling MODIS daily aerosol optical depth products by developing a spatiotemporal fitting algorithm T. Zhang et al. 10.1080/15481603.2022.2060596
164. Observational evidence of aerosol-warm cloud interaction over two urban locations in eastern India S. Kant et al. 10.1007/s11707-024-1124-z
165. Continuing the MODIS Dark Target Aerosol Time Series with VIIRS V. Sawyer et al. 10.3390/rs12020308
166. 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
167. Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2.5 estimations, a study on Tehran A. Mirzaei et al. 10.1007/s12145-022-00912-6
168. Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: Application to Himawari-8 T. Su et al. 10.1016/j.rse.2020.112093
169. Operational AOD Retrieval at Subkilometer Resolution Using OceanSat‐2 OCM Over Land: SAER Algorithm, Uncertainties, Validation & Inter‐Sensor Comparison M. Mishra et al. 10.1029/2023EA002896
170. Characterization of Subgrid-Scale Variability in Particulate Matter with Respect to Satellite Aerosol Observations M. Franklin et al. 10.3390/rs10040623
171. Spatiotemporal high-resolution imputation modeling of aerosol optical depth for investigating its full-coverage variation in China from 2003 to 2020 Q. He et al. 10.1016/j.atmosres.2022.106481
172. Daily Estimation of Ground-Level PM2.5 Concentrations over Beijing Using 3 km Resolution MODIS AOD Y. Xie et al. 10.1021/acs.est.5b01413
173. Comparison and Evaluation of Different MODIS Aerosol Optical Depth Products Over the Beijing-Tianjin-Hebei Region in China J. Wei & L. Sun 10.1109/JSTARS.2016.2595624
174. Spatio-temporal variability of near-surface air pollutants at four distinct geographical locations in Andhra Pradesh State of India V. Varaprasad et al. 10.1016/j.envpol.2020.115899
175. Validation of MODIS 3 km Resolution Aerosol Optical Depth Retrievals Over Asia J. Nichol & M. Bilal 10.3390/rs8040328
176. Wintertime characteristics of aerosols over middle Indo-Gangetic Plain: Vertical profile, transport and radiative forcing M. Kumar et al. 10.1016/j.atmosres.2016.09.012
177. Extended validation and evaluation of the OLCI–SLSTR SYNERGY aerosol product (SY_2_AOD) on Sentinel-3 L. Sogacheva et al. 10.5194/amt-15-5289-2022
178. 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
179. Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. 10.1016/j.rsase.2022.100716
180. Dramatic improvement of aerosol pollution status over the East Asian ocean: from the establishment of Japanese environmental quality standard for PM2.5 in 2009 to its achievement in 2021 S. Itahashi & I. Uno 10.1088/1748-9326/ad37ce
181. Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing T. Eck et al. 10.1029/2018JD028313
182. Temporal and Spatial Distribution of Aerosol Optical Depth in Sichuan and Its Correlation with Meteorological Factors from 2006 to 2016 天. 刘 10.12677/AG.2019.912133
183. The effect of atmospheric aerosol particles and clouds on net ecosystem exchange in the Amazon G. Cirino et al. 10.5194/acp-14-6523-2014
184. An Improved Aerosol Optical Depth Retrieval Algorithm for Multiangle Directional Polarimetric Camera (DPC) B. Ge et al. 10.3390/rs14164045
185. Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy J. Park et al. 10.5194/amt-16-3039-2023
186. Aerosol Property Retrieval Algorithm over Northeast Asia from TANSO-CAI Measurements Onboard GOSAT S. Lee et al. 10.3390/rs9070687
187. Air pollution and mortality impacts of coal mining: Evidence from coalmine accidents in China Y. Chu et al. 10.1016/j.jeem.2023.102846
188. Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas M. Bilal et al. 10.3390/rs14020373
189. High-resolution daily AOD estimated to full coverage using the random forest model approach in the Beijing-Tianjin-Hebei region C. Zhao et al. 10.1016/j.atmosenv.2019.01.045
190. Analysis of global three-dimensional aerosol structure with spectral radiance matching D. Liu et al. 10.5194/amt-12-6541-2019
191. MAIAC AOD profiling over the Persian Gulf: A seasonal-independent machine learning approach M. Pashayi et al. 10.1016/j.apr.2024.102128
192. Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
193. Application of Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Weather Research Forecasting (WRF) model meteorological data for assessment of fine particulate matter (PM2.5) over India Y. Sathe et al. 10.1016/j.apr.2018.08.016
194. 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
195. 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
196. Estimation of High-Resolution Surface Shortwave Radiative Fluxes Using SARA AOD over the Southern Great Plains E. Javadnia et al. 10.3390/rs9111146
197. Sensitivity of surface downward longwave radiation to aerosol optical depth over the Lake Taihu region, China C. Liu et al. 10.1016/j.atmosres.2024.107444
198. The Influences of Indian Monsoon Phases on Aerosol Distribution and Composition over India P. Khan et al. 10.3390/rs16173171
199. Aerosol Retrieval in the Autumn and Winter From the Red and $2.12~\mu\text{m}$ Bands of MODIS Z. Wang et al. 10.1109/TGRS.2018.2872914
200. Retrieval uncertainty and consistency of Suomi-NPP VIIRS Deep Blue and Dark Target aerosol products under diverse aerosol loading scenarios over South Asia K. Aditi et al. 10.1016/j.envpol.2023.121913
201. Aerosol remote sensing in polar regions C. Tomasi et al. 10.1016/j.earscirev.2014.11.001
202. Retrieval of Horizontal Visibility Using MODIS Data: A Deep Learning Approach B. Hu et al. 10.3390/atmos10120740
203. Evaluation of satellite-based aerosol datasets and the CAMS reanalysis over the ocean utilizing shipborne reference observations J. Witthuhn et al. 10.5194/amt-13-1387-2020
204. Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product E. Zhdanova et al. 10.5194/amt-13-877-2020
205. Preliminary On-Orbit Performance Test of the First Polarimetric Synchronization Monitoring Atmospheric Corrector (SMAC) On-Board High-Spatial Resolution Satellite Gao Fen Duo Mo (GFDM) Z. Li et al. 10.1109/TGRS.2021.3110320
206. Satellite-based high-resolution PM2.5 estimation over the Beijing-Tianjin-Hebei region of China using an improved geographically and temporally weighted regression model Q. He & B. Huang 10.1016/j.envpol.2018.01.053
207. Influence of aerosols on clouds, precipitation and freezing level height over the foothills of the Himalayas during the Indian summer monsoon P. Adhikari & J. Mejia 10.1007/s00382-021-05710-2
208. Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S‐NPP VIIRS as Part of the “Deep Blue” Aerosol Project A. Sayer et al. 10.1002/2017JD027412
209. Overview of atmospheric aerosol studies in Malaysia: Known and unknown K. Kanniah et al. 10.1016/j.atmosres.2016.08.002
210. Temporal and spatial variation of particulate matter and its correlation with other criteria of air pollutants in Lanzhou, China, in spring-summer periods M. Filonchyk et al. 10.1016/j.apr.2018.04.011
211. Terrestrial aerosol retrieval over Beijing from Chinese GF-1 data based on the blue/red correlation. Y. Zhang et al. 10.1080/2150704X.2020.1856959
212. Simulation and analysis of synoptic scale dust storms over the Arabian Peninsula S. Beegum et al. 10.1016/j.atmosres.2017.09.003
213. Fusion of Multisource Satellite AOD Products via Bayesian Maximum Entropy With Explicit A Priori Knowledge H. Zhu et al. 10.1109/TGRS.2023.3285943
214. Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data W. Zhang et al. 10.3390/rs10010137
215. Long-Term (2005–2017) View of Atmospheric Pollutants in Central China Using Multiple Satellite Observations R. Li et al. 10.3390/rs12061041
216. Development of a Practical Atmospheric Correction Algorithm for Inland and Nearshore Coastal Waters D. Zhao et al. 10.1109/TGRS.2021.3092839
217. Evaluation of MODIS Dark Target AOD Product with 3 and 10 km Resolution in Amazonia R. Palácios et al. 10.3390/atmos13111742
218. Evaluating biases in filter-based aerosol absorption measurements using photoacoustic spectroscopy N. Davies et al. 10.5194/amt-12-3417-2019
219. High-Resolution Satellite Mapping of Fine Particulates Based on Geographically Weighted Regression B. Zou et al. 10.1109/LGRS.2016.2520480
220. Spatiotemporal assessment of PM2.5 concentrations and exposure in China from 2013 to 2017 using satellite-derived data Q. He et al. 10.1016/j.jclepro.2020.124965
221. Identification of Aerosol Pollution Hotspots in Jiangsu Province of China Y. Wang et al. 10.3390/rs13142842
222. A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States C. Jiang et al. 10.5194/essd-13-281-2021
223. Estimation of High-Resolution Daily Ground-Level PM2.5 Concentration in Beijing 2013–2017 Using 1 km MAIAC AOT Data W. Han et al. 10.3390/app8122624
224. Improving satellite aerosol optical Depth-PM2.5 correlations using land use regression with microscale geographic predictors in a high-density urban context Y. Shi et al. 10.1016/j.atmosenv.2018.07.021
225. A Two-Stage Machine Learning Algorithm for Retrieving Multiple Aerosol Properties Over Land: Development and Validation M. Cao et al. 10.1109/TGRS.2023.3307934
226. Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
227. Assessment of Remote Sensing Data to Model PM10 Estimation in Cities with a Low Number of Air Quality Stations: A Case of Study in Quito, Ecuador C. Alvarez-Mendoza et al. 10.3390/environments6070085
228. Near-Time Measurement of Aerosol Optical Depth and Black Carbon Concentration at Socheongcho Ocean Research Station: Aerosol Episode Case Analysis S. Ahn et al. 10.3390/rs17030382
229. Development of non-linear models predicting daily fine particle concentrations using aerosol optical depth retrievals and ground-based measurements at a municipality in the Brazilian Amazon region K. Gonçalves et al. 10.1016/j.atmosenv.2018.03.057
230. 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
231. An Improved DDV Algorithm for the Retrieval of Aerosol Optical Depth From NOAA/AVHRR Data R. Li et al. 10.1007/s12524-020-01301-6
232. Aerosol and monsoon climate interactions over Asia Z. Li et al. 10.1002/2015RG000500
233. 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. 10.1016/j.scitotenv.2022.157956
234. Using gap-filled MAIAC AOD and WRF-Chem to estimate daily PM2.5 concentrations at 1 km resolution in the Eastern United States D. Goldberg et al. 10.1016/j.atmosenv.2018.11.049
235. What caused severe air pollution episode of November 2016 in New Delhi? V. Kanawade et al. 10.1016/j.atmosenv.2019.117125
236. Size-resolved particulate matter concentrations derived from 4.4 km-resolution size-fractionated Multi-angle Imaging SpectroRadiometer (MISR) aerosol optical depth over Southern California M. Franklin et al. 10.1016/j.rse.2017.05.002
237. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. 10.1029/2018JD028989
238. 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
239. Predicting Daily Urban Fine Particulate Matter Concentrations Using a Random Forest Model C. Brokamp et al. 10.1021/acs.est.7b05381
240. Radiative impact of Etna volcanic aerosols over south eastern Italy on 3 December 2015 S. Romano et al. 10.1016/j.atmosenv.2018.03.038
241. Validation and Accuracy Assessment of MODIS C6.1 Aerosol Products over the Heavy Aerosol Loading Area X. Tian & Z. Gao 10.3390/atmos10090548
242. Improved estimation of PM2.5 using Lagrangian satellite-measured aerosol optical depth R. Saunders et al. 10.1016/j.atmosenv.2014.03.060
243. Extreme gradient boosting model to estimate PM2.5 concentrations with missing-filled satellite data in China Z. Chen et al. 10.1016/j.atmosenv.2019.01.027
244. Interaction between urban heat island and urban pollution island during summer in Berlin H. Li et al. 10.1016/j.scitotenv.2018.04.254
245. “Traffic intervention” policy fails to mitigate air pollution in megacity Delhi S. Chowdhury et al. 10.1016/j.envsci.2017.04.018
246. A Global Climatology of Dust Aerosols Based on Satellite Data: Spatial, Seasonal and Inter-Annual Patterns over the Period 2005–2019 M. Gavrouzou et al. 10.3390/rs13030359
247. Investigation of air quality over the largest city in central China using high resolution satellite derived aerosol optical depth data K. Sun et al. 10.1016/j.apr.2017.12.011
248. Exploring systematic offsets between aerosol products from the two MODIS sensors R. Levy et al. 10.5194/amt-11-4073-2018
249. Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia Q. Xiao et al. 10.5194/acp-16-1255-2016
250. Validation, inter-comparison, and usage recommendation of six latest VIIRS and MODIS aerosol products over the ocean and land on the global and regional scales X. Su et al. 10.1016/j.scitotenv.2023.163794
251. Evaluation of MODIS Collection 6 aerosol retrieval algorithms over Indo-Gangetic Plain: Implications of aerosols types and mass loading A. Mhawish et al. 10.1016/j.rse.2017.09.016
252. Transport of Po Valley aerosol pollution to the northwestern Alps – Part 1: Phenomenology H. Diémoz et al. 10.5194/acp-19-3065-2019
253. Spectrally Enhanced Cloud Objects—A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 1. Multispectral analysis M. Pavolonis et al. 10.1002/2014JD022968
254. Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
255. Intercomparison of CALIOP, MODIS, and AERONET aerosol optical depth over China during the past decade C. Liu et al. 10.1080/01431161.2018.1466070
256. The characteristics of air pollutants during different seasons in the urban area of Lanzhou, Northwest China M. Filonchyk & H. Yan 10.1007/s12665-018-7925-1
257. First Retrieval of AOD at Fine Resolution Over Shallow and Turbid Coastal Waters From MODIS Y. Wang et al. 10.1029/2021GL094344
258. 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
259. 基于国产碳卫星的在轨光谱性能评估及大气二氧化碳的高精度反演（特邀） 洪. Hong Xinhua et al. 10.3788/AOS241153
260. PM2.5 concentration assessment based on geographical and temporal weighted regression model and MCD19A2 from 2015 to 2020 in Xinjiang, China W. Quan et al. 10.1371/journal.pone.0285610
261. Retrieval of Aerosol Optical Depth over Arid Areas from MODIS Data X. Tian & L. Sun 10.3390/atmos7100134
262. Long term analysis of the columnar and surface aerosol relationship at an urban European coastal site S. Segura et al. 10.1016/j.atmosenv.2017.08.012
263. Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia E. Kang et al. 10.1016/j.atmosenv.2023.119951
264. Observed aerosol-induced radiative effect on plant productivity in the eastern United States S. Strada et al. 10.1016/j.atmosenv.2015.09.051
265. Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. 10.5194/amt-14-4575-2021
266. Performance of MODIS high-resolution MAIAC aerosol algorithm in China: Characterization and limitation M. Tao et al. 10.1016/j.atmosenv.2019.06.004
267. Synchronous Atmospheric Correction of High Spatial Resolution Images from Gao Fen Duo Mo Satellite L. Xu et al. 10.3390/rs14174427
268. A multidimensional comparison between MODIS and VIIRS AOD in estimating ground-level PM2.5 concentrations over a heavily polluted region in China F. Yao et al. 10.1016/j.scitotenv.2017.08.209
269. 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
270. Development and assessment of a higher-spatial-resolution (4.4 km) MISR aerosol optical depth product using AERONET-DRAGON data M. Garay et al. 10.5194/acp-17-5095-2017
271. Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China Z. Sun et al. 10.3390/rs13183752
272. Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6  ×  6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data D. Pendergrass et al. 10.5194/amt-15-1075-2022
273. Trend relationship between mountain normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) across two decades: implication for water quality within the Lesotho Highlands, Drakensberg, South Africa A. Chukwuka et al. 10.1007/s10661-023-11110-2
274. Evaluation and comparison of MODIS and VIIRS aerosol optical depth (AOD) products over regions in the Eastern Mediterranean and the Black Sea P. Ettehadi Osgouei et al. 10.1016/j.atmosenv.2021.118784
275. Does the prohibition on open burning of straw mitigate air pollution? An empirical study in Jilin Province of China in the post-harvest season X. Wen et al. 10.1016/j.jenvman.2020.110451
276. Summarizing multiple aspects of triple collocation analysis in a single diagram L. Siu et al. 10.3389/frsen.2024.1395442
277. Future inhibition of ecosystem productivity by increasing wildfire pollution over boreal North America X. Yue et al. 10.5194/acp-17-13699-2017
278. The Role of Aerosol‐Radiation Interaction in the Meteorology Prediction at the Weather Scale in the Numerical Weather Prediction Model W. Zhang et al. 10.1029/2021GL097026
279. Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals A. Chudnovsky et al. 10.1016/j.atmosenv.2014.02.019
280. Evaluation and Comparison of MODIS Collection 6.1 and Collection 6 Dark Target Aerosol Optical Depth over Mainland China Under Various Conditions Including Spatiotemporal Distribution, Haze Effects, and Underlying Surface Y. Huang et al. 10.1029/2019EA000809
281. Validation of MODIS C6 AOD products retrieved by the Dark Target method in the Beijing–Tianjin–Hebei urban agglomeration, China J. Zhang et al. 10.1007/s00376-016-6217-5
282. Validation of high‐resolution MAIAC aerosol product over South America V. Martins et al. 10.1002/2016JD026301
283. Satellite-based identification of aerosol particle species using a 2D-space aerosol classification model Q. Mao et al. 10.1016/j.atmosenv.2019.117057
284. Aerosol optical depth retrieval over snow using AATSR data L. Mei et al. 10.1080/01431161.2013.786197
285. Characteristics and formation mechanism of a serious haze event in autumn 2017 in Harbin, China D. Zhu & L. Wan 10.1007/s11869-019-00726-4
286. Spatio-temporal variation and impact factors analysis of satellite-based aerosol optical depth over China from 2002 to 2015 Q. He et al. 10.1016/j.atmosenv.2016.01.002
287. Accuracy assessment and climatology of MODIS aerosol optical properties over North Africa A. Merdji et al. 10.1007/s11356-022-22997-8
288. Optimal estimation for global ground‐level fine particulate matter concentrations A. van Donkelaar et al. 10.1002/jgrd.50479
289. Toward the next generation of air quality monitoring: Particulate Matter J. Engel-Cox et al. 10.1016/j.atmosenv.2013.08.016
290. Evaluation and improvement of MODIS aerosol optical depth products over China Y. Li et al. 10.1016/j.atmosenv.2019.117251
291. Correlation between Urban Forest and Satellite-borne Imagery-based Ambient Particulate Matter across Seoul, South Korea S. Lee & J. Park 10.14397/jals.2019.53.6.1
292. Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model S. Ghotbi et al. 10.1016/j.atmosenv.2016.06.057
293. Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS J. Wei et al. 10.1016/j.atmosenv.2017.11.048
294. Ambient air particulate matter (PM10) satellite monitoring and respiratory health effects assessment M. Mohebbichamkhorami et al. 10.1007/s40201-020-00542-4
295. MODIS 3 km aerosol product: applications over land in an urban/suburban region L. Munchak et al. 10.5194/amt-6-1747-2013
296. 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
297. MODIS 3 km and 10 km aerosol optical depth for China: Evaluation and comparison Q. He et al. 10.1016/j.atmosenv.2017.01.023
298. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements Y. Tong et al. 10.3390/rs12142330
299. A sparse representation-based fusion model for improving daily MODIS C6.1 aerosol products on a 3 km grid Y. Zhao et al. 10.1080/01431161.2020.1823040